2026-05-20T18:45:30 - INFO: Slick 0.0.8a13

🟢 Starting Calibration Pipeline

=== Processing MCDP3D-SL-012_W039(6)_2026-03-04 ===
2026-05-20T18:45:30 - INFO: Camera ID: 06PFN
2026-05-20T18:45:30 - INFO: Wand ID: 00001f0c5182

-------------------------------------------------------------------
                        Step 1: Digitization                       
-------------------------------------------------------------------

[🔄] Full PTD mode: Processing ALL images then creating calibration subset
[📸] Digitizing ALL images...
2026-05-20T18:45:30 - INFO: Recorded At: 2026-03-04T18:34:23Z
[📸] Full dataset mode: Processing ALL images (no debug visualizations)
[INFO] Found 4 las0.zip files to process

Processing Rigs:   0%|          | 0/4 [00:00<?, ?it/s][INFO] Filtered 544 stationary frames, 455 remain


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                                                                           [PASS2] Frame 0000457: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000458: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000459: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000460: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000549: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000550: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000551: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000553: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000555: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000557: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000558: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000559: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000560: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000561: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000562: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000563: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000564: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000565: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000566: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000567: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000569: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000574: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000575: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000576: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000577: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000578: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000579: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000580: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000581: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000582: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000589: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000856: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000935: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001036: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001196: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001198: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001199: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001200: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001201: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001265: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001266: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001267: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001268: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001269: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000459: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000551: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000552: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000553: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000554: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000563: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000564: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000566: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000575: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001198: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001267: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001268: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001198: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Summary: 31 frames fixed, 25 untrusted, 454 total


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→ 1500 Phase 3: finalize:  96%|█████████▋| 437/454 [00:08<00:00, 53.17it/s]

→ 1500 Phase 3: finalize:  98%|█████████▊| 443/454 [00:08<00:00, 53.27it/s]

→ 1500 Phase 3: finalize:  99%|█████████▉| 449/454 [00:08<00:00, 53.31it/s]

                                                                           
[TIMING] 1500 — 455 frames
  Phase 1  radial detect   (parallel)  :   8.58s  (18.9 ms/frame)
  Phase 2a corner detect   (parallel)  :   3.17s  (7.0 ms/frame)
  Phase 2b corner fix      (sequential):   1.14s
  Phase 3  finalize        (sequential):   8.53s  (18.7 ms/frame)
    decode + undistort                 :   4.55s  (10.0 ms/frame)
    corner apply + refinement          :   1.74s  (3.8 ms/frame)
    segment                            :   1.83s  (4.0 ms/frame)
    smooth                             :   0.26s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  21.42s


Processing Rigs:  25%|██▌       | 1/4 [00:26<01:19, 26.50s/it][INFO] Filtered 449 stationary frames, 421 remain


→ 2000L (421 images) Phase 1:   0%|          | 0/421 [00:00<?, ?it/s]

→ 2000L (421 images) Phase 1:   0%|          | 1/421 [00:00<03:27,  2.03it/s]

→ 2000L (421 images) Phase 1:   0%|          | 2/421 [00:00<02:06,  3.31it/s]

→ 2000L (421 images) Phase 1:   8%|▊         | 33/421 [00:00<00:08, 48.03it/s]

→ 2000L (421 images) Phase 1:   9%|▉         | 38/421 [00:01<00:09, 42.24it/s]

→ 2000L (421 images) Phase 1:  15%|█▌        | 65/421 [00:01<00:05, 62.58it/s]

→ 2000L (421 images) Phase 1:  17%|█▋        | 71/421 [00:01<00:06, 53.52it/s]

→ 2000L (421 images) Phase 1:  23%|██▎       | 97/421 [00:01<00:04, 68.33it/s]

→ 2000L (421 images) Phase 1:  25%|██▍       | 104/421 [00:02<00:05, 58.94it/s]

→ 2000L (421 images) Phase 1:  31%|███       | 129/421 [00:02<00:04, 70.10it/s]

→ 2000L (421 images) Phase 1:  32%|███▏      | 136/421 [00:02<00:04, 60.03it/s]

→ 2000L (421 images) Phase 1:  38%|███▊      | 161/421 [00:02<00:03, 71.63it/s]

→ 2000L (421 images) Phase 1:  40%|███▉      | 168/421 [00:03<00:04, 61.64it/s]

→ 2000L (421 images) Phase 1:  46%|████▌     | 193/421 [00:03<00:03, 72.75it/s]

→ 2000L (421 images) Phase 1:  48%|████▊     | 200/421 [00:03<00:03, 63.53it/s]

→ 2000L (421 images) Phase 1:  53%|█████▎    | 225/421 [00:03<00:02, 72.91it/s]

→ 2000L (421 images) Phase 1:  55%|█████▌    | 232/421 [00:03<00:02, 63.30it/s]

→ 2000L (421 images) Phase 1:  61%|██████    | 257/421 [00:04<00:02, 72.93it/s]

→ 2000L (421 images) Phase 1:  63%|██████▎   | 264/421 [00:04<00:02, 63.19it/s]

→ 2000L (421 images) Phase 1:  69%|██████▊   | 289/421 [00:04<00:01, 73.18it/s]

→ 2000L (421 images) Phase 1:  70%|███████   | 296/421 [00:04<00:01, 63.73it/s]

→ 2000L (421 images) Phase 1:  76%|███████▌  | 321/421 [00:05<00:01, 73.22it/s]

→ 2000L (421 images) Phase 1:  78%|███████▊  | 328/421 [00:05<00:01, 63.20it/s]

→ 2000L (421 images) Phase 1:  84%|████████▍ | 353/421 [00:05<00:00, 75.18it/s]

→ 2000L (421 images) Phase 1:  86%|████████▌ | 361/421 [00:05<00:00, 63.96it/s]

→ 2000L (421 images) Phase 1:  91%|█████████▏| 385/421 [00:06<00:00, 75.10it/s]

→ 2000L (421 images) Phase 1:  93%|█████████▎| 393/421 [00:06<00:00, 56.63it/s]

→ 2000L (421 images) Phase 1:  99%|█████████▉| 417/421 [00:06<00:00, 78.25it/s]

                                                                               

→ 2000L Phase 2: corners:   0%|          | 0/420 [00:00<?, ?it/s]

→ 2000L Phase 2: corners:   0%|          | 1/420 [00:00<01:49,  3.81it/s]

→ 2000L Phase 2: corners:   3%|▎         | 14/420 [00:00<00:08, 47.95it/s]

→ 2000L Phase 2: corners:   6%|▌         | 26/420 [00:00<00:05, 71.25it/s]

→ 2000L Phase 2: corners:   9%|▉         | 38/420 [00:00<00:04, 83.35it/s]

→ 2000L Phase 2: corners:  13%|█▎        | 53/420 [00:00<00:03, 101.65it/s]

→ 2000L Phase 2: corners:  16%|█▌        | 67/420 [00:00<00:03, 110.14it/s]

→ 2000L Phase 2: corners:  19%|█▉        | 80/420 [00:00<00:02, 115.48it/s]

→ 2000L Phase 2: corners:  22%|██▏       | 94/420 [00:01<00:02, 119.38it/s]

→ 2000L Phase 2: corners:  25%|██▌       | 107/420 [00:01<00:02, 120.78it/s]

→ 2000L Phase 2: corners:  29%|██▊       | 120/420 [00:01<00:02, 122.40it/s]

→ 2000L Phase 2: corners:  33%|███▎      | 140/420 [00:01<00:01, 141.64it/s]

→ 2000L Phase 2: corners:  37%|███▋      | 155/420 [00:01<00:01, 139.55it/s]

→ 2000L Phase 2: corners:  41%|████      | 172/420 [00:01<00:01, 147.98it/s]

→ 2000L Phase 2: corners:  45%|████▍     | 187/420 [00:01<00:01, 147.81it/s]

→ 2000L Phase 2: corners:  48%|████▊     | 202/420 [00:01<00:01, 131.93it/s]

→ 2000L Phase 2: corners:  51%|█████▏    | 216/420 [00:01<00:01, 133.73it/s]

→ 2000L Phase 2: corners:  55%|█████▍    | 230/420 [00:01<00:01, 135.37it/s]

→ 2000L Phase 2: corners:  58%|█████▊    | 244/420 [00:02<00:01, 136.60it/s]

→ 2000L Phase 2: corners:  61%|██████▏   | 258/420 [00:02<00:01, 125.82it/s]

→ 2000L Phase 2: corners:  65%|██████▌   | 275/420 [00:02<00:01, 136.58it/s]

→ 2000L Phase 2: corners:  69%|██████▉   | 289/420 [00:02<00:01, 91.36it/s] 

→ 2000L Phase 2: corners:  72%|███████▏  | 304/420 [00:02<00:01, 103.19it/s]

→ 2000L Phase 2: corners:  75%|███████▌  | 317/420 [00:02<00:00, 107.95it/s]

→ 2000L Phase 2: corners:  79%|███████▉  | 331/420 [00:02<00:00, 115.79it/s]

→ 2000L Phase 2: corners:  82%|████████▏ | 344/420 [00:03<00:00, 118.44it/s]

→ 2000L Phase 2: corners:  86%|████████▋ | 363/420 [00:03<00:00, 134.34it/s]

→ 2000L Phase 2: corners:  90%|█████████ | 378/420 [00:03<00:00, 130.75it/s]

→ 2000L Phase 2: corners:  93%|█████████▎| 392/420 [00:03<00:00, 127.24it/s]

                                                                            [PASS2] Frame 0000519: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000547: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000548: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000549: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000550: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000551: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000552: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000553: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000554: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000556: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000557: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000560: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000561: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000562: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000563: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000567: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000568: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000569: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000570: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000596: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000597: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000598: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000599: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000615: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000548: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000552: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000555: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000556: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000555: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 12 frames fixed, 16 untrusted, 420 total


→ 2000L Phase 3: finalize:   0%|          | 0/420 [00:00<?, ?it/s]

→ 2000L Phase 3: finalize:   1%|▏         | 6/420 [00:00<00:08, 51.53it/s]

→ 2000L Phase 3: finalize:   3%|▎         | 12/420 [00:00<00:07, 51.37it/s]

→ 2000L Phase 3: finalize:   4%|▍         | 18/420 [00:00<00:07, 51.56it/s]

→ 2000L Phase 3: finalize:   6%|▌         | 24/420 [00:00<00:07, 52.05it/s]

→ 2000L Phase 3: finalize:   7%|▋         | 30/420 [00:00<00:07, 52.04it/s]

→ 2000L Phase 3: finalize:   9%|▊         | 36/420 [00:00<00:07, 52.54it/s]

→ 2000L Phase 3: finalize:  10%|█         | 42/420 [00:00<00:07, 53.08it/s]

→ 2000L Phase 3: finalize:  11%|█▏        | 48/420 [00:00<00:06, 53.31it/s]

→ 2000L Phase 3: finalize:  13%|█▎        | 54/420 [00:01<00:06, 53.51it/s]

→ 2000L Phase 3: finalize:  14%|█▍        | 60/420 [00:01<00:06, 53.85it/s]

→ 2000L Phase 3: finalize:  16%|█▌        | 66/420 [00:01<00:06, 54.06it/s]

→ 2000L Phase 3: finalize:  17%|█▋        | 72/420 [00:01<00:06, 53.89it/s]

→ 2000L Phase 3: finalize:  19%|█▊        | 78/420 [00:01<00:06, 53.94it/s]

→ 2000L Phase 3: finalize:  20%|██        | 84/420 [00:01<00:06, 53.86it/s]

→ 2000L Phase 3: finalize:  21%|██▏       | 90/420 [00:01<00:06, 53.95it/s]

→ 2000L Phase 3: finalize:  23%|██▎       | 96/420 [00:01<00:06, 53.90it/s]

→ 2000L Phase 3: finalize:  24%|██▍       | 102/420 [00:01<00:05, 53.74it/s]

→ 2000L Phase 3: finalize:  26%|██▌       | 108/420 [00:02<00:05, 53.61it/s]

→ 2000L Phase 3: finalize:  27%|██▋       | 114/420 [00:02<00:05, 53.65it/s]

→ 2000L Phase 3: finalize:  29%|██▊       | 120/420 [00:02<00:05, 53.78it/s]

→ 2000L Phase 3: finalize:  30%|███       | 126/420 [00:02<00:05, 53.97it/s]

→ 2000L Phase 3: finalize:  31%|███▏      | 132/420 [00:02<00:05, 54.00it/s]

→ 2000L Phase 3: finalize:  33%|███▎      | 138/420 [00:02<00:05, 53.95it/s]

→ 2000L Phase 3: finalize:  34%|███▍      | 144/420 [00:02<00:05, 53.94it/s]

→ 2000L Phase 3: finalize:  36%|███▌      | 150/420 [00:02<00:05, 53.94it/s]

→ 2000L Phase 3: finalize:  37%|███▋      | 156/420 [00:02<00:04, 53.82it/s]

→ 2000L Phase 3: finalize:  39%|███▊      | 162/420 [00:03<00:04, 53.71it/s]

→ 2000L Phase 3: finalize:  40%|████      | 168/420 [00:03<00:04, 53.75it/s]

→ 2000L Phase 3: finalize:  41%|████▏     | 174/420 [00:03<00:04, 53.67it/s]

→ 2000L Phase 3: finalize:  43%|████▎     | 180/420 [00:03<00:04, 53.68it/s]

→ 2000L Phase 3: finalize:  44%|████▍     | 186/420 [00:03<00:04, 53.76it/s]

→ 2000L Phase 3: finalize:  46%|████▌     | 192/420 [00:03<00:04, 53.63it/s]

→ 2000L Phase 3: finalize:  47%|████▋     | 198/420 [00:03<00:04, 53.57it/s]

→ 2000L Phase 3: finalize:  49%|████▊     | 204/420 [00:03<00:04, 53.55it/s]

→ 2000L Phase 3: finalize:  50%|█████     | 210/420 [00:03<00:03, 53.32it/s]

→ 2000L Phase 3: finalize:  51%|█████▏    | 216/420 [00:04<00:03, 53.24it/s]

→ 2000L Phase 3: finalize:  53%|█████▎    | 222/420 [00:04<00:03, 53.11it/s]

→ 2000L Phase 3: finalize:  54%|█████▍    | 228/420 [00:04<00:03, 53.14it/s]

→ 2000L Phase 3: finalize:  56%|█████▌    | 234/420 [00:04<00:03, 53.05it/s]

→ 2000L Phase 3: finalize:  57%|█████▋    | 240/420 [00:04<00:03, 52.90it/s]

→ 2000L Phase 3: finalize:  59%|█████▊    | 246/420 [00:04<00:03, 52.67it/s]

→ 2000L Phase 3: finalize:  60%|██████    | 252/420 [00:04<00:03, 52.66it/s]

→ 2000L Phase 3: finalize:  61%|██████▏   | 258/420 [00:04<00:03, 52.58it/s]

→ 2000L Phase 3: finalize:  63%|██████▎   | 264/420 [00:04<00:02, 52.24it/s]

→ 2000L Phase 3: finalize:  64%|██████▍   | 270/420 [00:05<00:02, 52.23it/s]

→ 2000L Phase 3: finalize:  66%|██████▌   | 276/420 [00:05<00:02, 52.13it/s]

→ 2000L Phase 3: finalize:  67%|██████▋   | 282/420 [00:05<00:02, 51.96it/s]

→ 2000L Phase 3: finalize:  69%|██████▊   | 288/420 [00:05<00:02, 51.97it/s]

→ 2000L Phase 3: finalize:  70%|███████   | 294/420 [00:05<00:02, 52.04it/s]

→ 2000L Phase 3: finalize:  71%|███████▏  | 300/420 [00:05<00:02, 52.01it/s]

→ 2000L Phase 3: finalize:  73%|███████▎  | 306/420 [00:05<00:02, 52.03it/s]

→ 2000L Phase 3: finalize:  74%|███████▍  | 312/420 [00:05<00:02, 51.71it/s]

→ 2000L Phase 3: finalize:  76%|███████▌  | 318/420 [00:05<00:01, 51.44it/s]

→ 2000L Phase 3: finalize:  77%|███████▋  | 324/420 [00:06<00:01, 51.40it/s]

→ 2000L Phase 3: finalize:  79%|███████▊  | 330/420 [00:06<00:01, 51.43it/s]

→ 2000L Phase 3: finalize:  80%|████████  | 336/420 [00:06<00:01, 51.39it/s]

→ 2000L Phase 3: finalize:  81%|████████▏ | 342/420 [00:06<00:01, 51.44it/s]

→ 2000L Phase 3: finalize:  83%|████████▎ | 348/420 [00:06<00:01, 51.34it/s]

→ 2000L Phase 3: finalize:  84%|████████▍ | 354/420 [00:06<00:01, 51.44it/s]

→ 2000L Phase 3: finalize:  86%|████████▌ | 360/420 [00:06<00:01, 51.54it/s]

→ 2000L Phase 3: finalize:  87%|████████▋ | 366/420 [00:06<00:01, 51.41it/s]

→ 2000L Phase 3: finalize:  89%|████████▊ | 372/420 [00:07<00:00, 51.26it/s]

→ 2000L Phase 3: finalize:  90%|█████████ | 378/420 [00:07<00:00, 51.31it/s]

→ 2000L Phase 3: finalize:  91%|█████████▏| 384/420 [00:07<00:00, 51.38it/s]

→ 2000L Phase 3: finalize:  93%|█████████▎| 390/420 [00:07<00:00, 51.57it/s]

→ 2000L Phase 3: finalize:  94%|█████████▍| 396/420 [00:07<00:00, 51.61it/s]

→ 2000L Phase 3: finalize:  96%|█████████▌| 402/420 [00:07<00:00, 51.77it/s]

→ 2000L Phase 3: finalize:  97%|█████████▋| 408/420 [00:07<00:00, 52.04it/s]

→ 2000L Phase 3: finalize:  99%|█████████▊| 414/420 [00:07<00:00, 52.09it/s]

→ 2000L Phase 3: finalize: 100%|██████████| 420/420 [00:07<00:00, 51.98it/s]

                                                                            
[TIMING] 2000L — 421 frames
  Phase 1  radial detect   (parallel)  :   6.84s  (16.3 ms/frame)
  Phase 2a corner detect   (parallel)  :   3.54s  (8.4 ms/frame)
  Phase 2b corner fix      (sequential):   0.68s
  Phase 3  finalize        (sequential):   7.97s  (18.9 ms/frame)
    decode + undistort                 :   4.17s  (9.9 ms/frame)
    corner apply + refinement          :   1.70s  (4.0 ms/frame)
    segment                            :   1.72s  (4.1 ms/frame)
    smooth                             :   0.24s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  19.03s


Processing Rigs:  50%|█████     | 2/4 [00:48<00:47, 23.92s/it][INFO] Filtered 633 stationary frames, 377 remain


→ 2000R (377 images) Phase 1:   0%|          | 0/377 [00:00<?, ?it/s]

→ 2000R (377 images) Phase 1:   0%|          | 1/377 [00:00<03:13,  1.95it/s]

→ 2000R (377 images) Phase 1:   1%|          | 2/377 [00:00<02:28,  2.53it/s]

→ 2000R (377 images) Phase 1:   9%|▉         | 33/377 [00:01<00:07, 46.39it/s]

→ 2000R (377 images) Phase 1:  11%|█         | 40/377 [00:01<00:08, 37.57it/s]

→ 2000R (377 images) Phase 1:  17%|█▋        | 65/377 [00:01<00:04, 64.01it/s]

→ 2000R (377 images) Phase 1:  20%|█▉        | 74/377 [00:01<00:06, 50.26it/s]

→ 2000R (377 images) Phase 1:  26%|██▌       | 97/377 [00:01<00:03, 75.01it/s]

→ 2000R (377 images) Phase 1:  29%|██▊       | 108/377 [00:02<00:04, 56.85it/s]

→ 2000R (377 images) Phase 1:  34%|███▍      | 129/377 [00:02<00:03, 77.54it/s]

→ 2000R (377 images) Phase 1:  37%|███▋      | 141/377 [00:02<00:04, 58.96it/s]

→ 2000R (377 images) Phase 1:  43%|████▎     | 161/377 [00:02<00:02, 77.34it/s]

→ 2000R (377 images) Phase 1:  46%|████▌     | 173/377 [00:03<00:03, 59.52it/s]

→ 2000R (377 images) Phase 1:  51%|█████     | 193/377 [00:03<00:02, 78.36it/s]

→ 2000R (377 images) Phase 1:  54%|█████▍    | 205/377 [00:03<00:02, 59.93it/s]

→ 2000R (377 images) Phase 1:  60%|█████▉    | 225/377 [00:03<00:01, 79.36it/s]

→ 2000R (377 images) Phase 1:  63%|██████▎   | 238/377 [00:04<00:02, 61.37it/s]

→ 2000R (377 images) Phase 1:  68%|██████▊   | 257/377 [00:04<00:01, 79.13it/s]

→ 2000R (377 images) Phase 1:  71%|███████▏  | 269/377 [00:04<00:01, 60.11it/s]

→ 2000R (377 images) Phase 1:  77%|███████▋  | 289/377 [00:04<00:01, 78.09it/s]

→ 2000R (377 images) Phase 1:  80%|███████▉  | 301/377 [00:05<00:01, 59.56it/s]

→ 2000R (377 images) Phase 1:  85%|████████▌ | 322/377 [00:05<00:00, 62.63it/s]

→ 2000R (377 images) Phase 1:  88%|████████▊ | 331/377 [00:05<00:00, 62.35it/s]

→ 2000R (377 images) Phase 1:  94%|█████████▎| 353/377 [00:05<00:00, 86.12it/s]

→ 2000R (377 images) Phase 1:  97%|█████████▋| 365/377 [00:05<00:00, 68.99it/s]

                                                                               

→ 2000R Phase 2: corners:   0%|          | 0/376 [00:00<?, ?it/s]

→ 2000R Phase 2: corners:   0%|          | 1/376 [00:00<01:55,  3.25it/s]

→ 2000R Phase 2: corners:   5%|▍         | 18/376 [00:00<00:06, 54.85it/s]

→ 2000R Phase 2: corners:   9%|▉         | 33/376 [00:00<00:04, 83.63it/s]

→ 2000R Phase 2: corners:  13%|█▎        | 48/376 [00:00<00:03, 102.37it/s]

→ 2000R Phase 2: corners:  16%|█▌        | 61/376 [00:00<00:02, 108.91it/s]

→ 2000R Phase 2: corners:  20%|█▉        | 74/376 [00:00<00:02, 108.20it/s]

→ 2000R Phase 2: corners:  23%|██▎       | 88/376 [00:00<00:02, 115.99it/s]

→ 2000R Phase 2: corners:  27%|██▋       | 101/376 [00:01<00:02, 115.42it/s]

→ 2000R Phase 2: corners:  31%|███       | 116/376 [00:01<00:02, 122.11it/s]

→ 2000R Phase 2: corners:  34%|███▍      | 129/376 [00:01<00:02, 112.55it/s]

→ 2000R Phase 2: corners:  38%|███▊      | 141/376 [00:01<00:02, 109.90it/s]

→ 2000R Phase 2: corners:  41%|████      | 154/376 [00:01<00:01, 114.99it/s]

→ 2000R Phase 2: corners:  45%|████▌     | 171/376 [00:01<00:01, 126.20it/s]

→ 2000R Phase 2: corners:  49%|████▉     | 186/376 [00:01<00:01, 130.94it/s]

→ 2000R Phase 2: corners:  54%|█████▎    | 202/376 [00:01<00:01, 135.70it/s]

→ 2000R Phase 2: corners:  58%|█████▊    | 217/376 [00:01<00:01, 137.44it/s]

→ 2000R Phase 2: corners:  62%|██████▏   | 233/376 [00:02<00:01, 141.50it/s]

→ 2000R Phase 2: corners:  66%|██████▌   | 249/376 [00:02<00:00, 144.45it/s]

→ 2000R Phase 2: corners:  70%|███████   | 264/376 [00:02<00:00, 143.06it/s]

→ 2000R Phase 2: corners:  74%|███████▍  | 279/376 [00:02<00:00, 144.11it/s]

→ 2000R Phase 2: corners:  78%|███████▊  | 294/376 [00:02<00:00, 136.41it/s]

→ 2000R Phase 2: corners:  83%|████████▎ | 312/376 [00:02<00:00, 147.57it/s]

→ 2000R Phase 2: corners:  88%|████████▊ | 329/376 [00:02<00:00, 150.31it/s]

→ 2000R Phase 2: corners:  92%|█████████▏| 345/376 [00:02<00:00, 141.89it/s]

→ 2000R Phase 2: corners:  96%|█████████▌| 360/376 [00:02<00:00, 137.29it/s]

                                                                            [PASS2] Frame 0001200: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001223: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001467: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001468: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001469: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001470: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001481: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001482: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001483: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001484: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001200: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001469: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001483: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001200: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Summary: 6 frames fixed, 6 untrusted, 376 total


→ 2000R Phase 3: finalize:   0%|          | 0/376 [00:00<?, ?it/s]

→ 2000R Phase 3: finalize:   1%|▏         | 5/376 [00:00<00:07, 49.91it/s]

→ 2000R Phase 3: finalize:   3%|▎         | 10/376 [00:00<00:07, 49.44it/s]

→ 2000R Phase 3: finalize:   4%|▍         | 15/376 [00:00<00:07, 49.59it/s]

→ 2000R Phase 3: finalize:   6%|▌         | 21/376 [00:00<00:07, 50.22it/s]

→ 2000R Phase 3: finalize:   7%|▋         | 27/376 [00:00<00:06, 50.65it/s]

→ 2000R Phase 3: finalize:   9%|▉         | 33/376 [00:00<00:06, 50.81it/s]

→ 2000R Phase 3: finalize:  10%|█         | 39/376 [00:00<00:06, 50.77it/s]

→ 2000R Phase 3: finalize:  12%|█▏        | 45/376 [00:00<00:06, 50.87it/s]

→ 2000R Phase 3: finalize:  14%|█▎        | 51/376 [00:01<00:06, 50.95it/s]

→ 2000R Phase 3: finalize:  15%|█▌        | 57/376 [00:01<00:06, 51.13it/s]

→ 2000R Phase 3: finalize:  17%|█▋        | 63/376 [00:01<00:06, 51.24it/s]

→ 2000R Phase 3: finalize:  18%|█▊        | 69/376 [00:01<00:05, 51.23it/s]

→ 2000R Phase 3: finalize:  20%|█▉        | 75/376 [00:01<00:05, 51.17it/s]

→ 2000R Phase 3: finalize:  22%|██▏       | 81/376 [00:01<00:05, 51.18it/s]

→ 2000R Phase 3: finalize:  23%|██▎       | 87/376 [00:01<00:05, 51.05it/s]

→ 2000R Phase 3: finalize:  25%|██▍       | 93/376 [00:01<00:05, 51.01it/s]

→ 2000R Phase 3: finalize:  26%|██▋       | 99/376 [00:01<00:05, 51.05it/s]

→ 2000R Phase 3: finalize:  28%|██▊       | 105/376 [00:02<00:05, 51.09it/s]

→ 2000R Phase 3: finalize:  30%|██▉       | 111/376 [00:02<00:05, 51.16it/s]

→ 2000R Phase 3: finalize:  31%|███       | 117/376 [00:02<00:05, 51.00it/s]

→ 2000R Phase 3: finalize:  33%|███▎      | 123/376 [00:02<00:04, 50.99it/s]

→ 2000R Phase 3: finalize:  34%|███▍      | 129/376 [00:02<00:04, 50.76it/s]

→ 2000R Phase 3: finalize:  36%|███▌      | 135/376 [00:02<00:04, 50.94it/s]

→ 2000R Phase 3: finalize:  38%|███▊      | 141/376 [00:02<00:04, 51.11it/s]

→ 2000R Phase 3: finalize:  39%|███▉      | 147/376 [00:02<00:04, 51.37it/s]

→ 2000R Phase 3: finalize:  41%|████      | 153/376 [00:03<00:04, 51.43it/s]

→ 2000R Phase 3: finalize:  42%|████▏     | 159/376 [00:03<00:04, 51.54it/s]

→ 2000R Phase 3: finalize:  44%|████▍     | 165/376 [00:03<00:04, 51.69it/s]

→ 2000R Phase 3: finalize:  45%|████▌     | 171/376 [00:03<00:03, 51.68it/s]

→ 2000R Phase 3: finalize:  47%|████▋     | 177/376 [00:03<00:03, 51.66it/s]

→ 2000R Phase 3: finalize:  49%|████▊     | 183/376 [00:03<00:03, 51.73it/s]

→ 2000R Phase 3: finalize:  50%|█████     | 189/376 [00:03<00:03, 51.45it/s]

→ 2000R Phase 3: finalize:  52%|█████▏    | 195/376 [00:03<00:03, 51.10it/s]

→ 2000R Phase 3: finalize:  53%|█████▎    | 201/376 [00:03<00:03, 51.52it/s]

→ 2000R Phase 3: finalize:  55%|█████▌    | 207/376 [00:04<00:03, 51.86it/s]

→ 2000R Phase 3: finalize:  57%|█████▋    | 213/376 [00:04<00:03, 52.31it/s]

→ 2000R Phase 3: finalize:  58%|█████▊    | 219/376 [00:04<00:02, 52.64it/s]

→ 2000R Phase 3: finalize:  60%|█████▉    | 225/376 [00:04<00:02, 53.07it/s]

→ 2000R Phase 3: finalize:  61%|██████▏   | 231/376 [00:04<00:02, 53.35it/s]

→ 2000R Phase 3: finalize:  63%|██████▎   | 237/376 [00:04<00:02, 53.54it/s]

→ 2000R Phase 3: finalize:  65%|██████▍   | 243/376 [00:04<00:02, 53.66it/s]

→ 2000R Phase 3: finalize:  66%|██████▌   | 249/376 [00:04<00:02, 53.70it/s]

→ 2000R Phase 3: finalize:  68%|██████▊   | 255/376 [00:04<00:02, 53.60it/s]

→ 2000R Phase 3: finalize:  69%|██████▉   | 261/376 [00:05<00:02, 53.30it/s]

→ 2000R Phase 3: finalize:  71%|███████   | 267/376 [00:05<00:02, 53.25it/s]

→ 2000R Phase 3: finalize:  73%|███████▎  | 273/376 [00:05<00:01, 53.50it/s]

→ 2000R Phase 3: finalize:  74%|███████▍  | 279/376 [00:05<00:01, 53.18it/s]

→ 2000R Phase 3: finalize:  76%|███████▌  | 285/376 [00:05<00:01, 53.93it/s]

→ 2000R Phase 3: finalize:  77%|███████▋  | 291/376 [00:05<00:01, 53.97it/s]

→ 2000R Phase 3: finalize:  79%|███████▉  | 297/376 [00:05<00:01, 54.13it/s]

→ 2000R Phase 3: finalize:  81%|████████  | 303/376 [00:05<00:01, 54.26it/s]

→ 2000R Phase 3: finalize:  82%|████████▏ | 309/376 [00:05<00:01, 54.48it/s]

→ 2000R Phase 3: finalize:  84%|████████▍ | 315/376 [00:06<00:01, 54.52it/s]

→ 2000R Phase 3: finalize:  85%|████████▌ | 321/376 [00:06<00:01, 54.56it/s]

→ 2000R Phase 3: finalize:  87%|████████▋ | 327/376 [00:06<00:00, 54.45it/s]

→ 2000R Phase 3: finalize:  89%|████████▊ | 333/376 [00:06<00:00, 54.41it/s]

→ 2000R Phase 3: finalize:  90%|█████████ | 339/376 [00:06<00:00, 54.34it/s]

→ 2000R Phase 3: finalize:  92%|█████████▏| 345/376 [00:06<00:00, 54.17it/s]

→ 2000R Phase 3: finalize:  93%|█████████▎| 351/376 [00:06<00:00, 53.94it/s]

→ 2000R Phase 3: finalize:  95%|█████████▍| 357/376 [00:06<00:00, 53.44it/s]

→ 2000R Phase 3: finalize:  97%|█████████▋| 363/376 [00:06<00:00, 53.13it/s]

→ 2000R Phase 3: finalize:  98%|█████████▊| 369/376 [00:07<00:00, 52.91it/s]

→ 2000R Phase 3: finalize: 100%|█████████▉| 375/376 [00:07<00:00, 52.81it/s]

                                                                            
[TIMING] 2000R — 377 frames
  Phase 1  radial detect   (parallel)  :   6.14s  (16.3 ms/frame)
  Phase 2a corner detect   (parallel)  :   3.13s  (8.3 ms/frame)
  Phase 2b corner fix      (sequential):   0.43s
  Phase 3  finalize        (sequential):   7.19s  (19.1 ms/frame)
    decode + undistort                 :   3.75s  (9.9 ms/frame)
    corner apply + refinement          :   1.56s  (4.1 ms/frame)
    segment                            :   1.53s  (4.1 ms/frame)
    smooth                             :   0.21s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  16.90s


Processing Rigs:  75%|███████▌  | 3/4 [01:09<00:22, 22.32s/it][INFO] Filtered 617 stationary frames, 331 remain


→ 1000 (331 images) Phase 1:   0%|          | 0/331 [00:00<?, ?it/s]

→ 1000 (331 images) Phase 1:   0%|          | 1/331 [00:00<03:02,  1.81it/s]

→ 1000 (331 images) Phase 1:   1%|          | 2/331 [00:00<01:48,  3.03it/s]

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→ 1000 (331 images) Phase 1:  19%|█▊        | 62/331 [00:01<00:03, 75.36it/s]

→ 1000 (331 images) Phase 1:  22%|██▏       | 73/331 [00:01<00:04, 54.00it/s]

→ 1000 (331 images) Phase 1:  28%|██▊       | 94/331 [00:01<00:03, 77.89it/s]

→ 1000 (331 images) Phase 1:  32%|███▏      | 106/331 [00:02<00:03, 56.96it/s]

→ 1000 (331 images) Phase 1:  38%|███▊      | 127/331 [00:02<00:02, 79.49it/s]

→ 1000 (331 images) Phase 1:  42%|████▏     | 140/331 [00:02<00:03, 59.75it/s]

→ 1000 (331 images) Phase 1:  48%|████▊     | 160/331 [00:02<00:02, 76.78it/s]

→ 1000 (331 images) Phase 1:  52%|█████▏    | 172/331 [00:03<00:02, 60.01it/s]

→ 1000 (331 images) Phase 1:  58%|█████▊    | 192/331 [00:03<00:01, 78.23it/s]

→ 1000 (331 images) Phase 1:  62%|██████▏   | 204/331 [00:03<00:02, 59.48it/s]

→ 1000 (331 images) Phase 1:  68%|██████▊   | 224/331 [00:03<00:01, 78.98it/s]

→ 1000 (331 images) Phase 1:  72%|███████▏  | 237/331 [00:04<00:01, 60.42it/s]

→ 1000 (331 images) Phase 1:  77%|███████▋  | 256/331 [00:04<00:00, 78.30it/s]

→ 1000 (331 images) Phase 1:  81%|████████▏ | 269/331 [00:04<00:01, 60.68it/s]

→ 1000 (331 images) Phase 1:  87%|████████▋ | 287/331 [00:04<00:00, 77.27it/s]

→ 1000 (331 images) Phase 1:  90%|█████████ | 299/331 [00:04<00:00, 59.56it/s]

→ 1000 (331 images) Phase 1:  96%|█████████▋| 319/331 [00:05<00:00, 78.74it/s]

→ 1000 (331 images) Phase 1: 100%|██████████| 331/331 [00:05<00:00, 72.65it/s]

                                                                              

→ 1000 Phase 2: corners:   0%|          | 0/330 [00:00<?, ?it/s]

→ 1000 Phase 2: corners:   0%|          | 1/330 [00:00<01:41,  3.25it/s]

→ 1000 Phase 2: corners:   4%|▍         | 13/330 [00:00<00:07, 39.71it/s]

→ 1000 Phase 2: corners:   8%|▊         | 26/330 [00:00<00:04, 67.27it/s]

→ 1000 Phase 2: corners:  12%|█▏        | 39/330 [00:00<00:03, 84.80it/s]

→ 1000 Phase 2: corners:  16%|█▌        | 52/330 [00:00<00:02, 92.83it/s]

→ 1000 Phase 2: corners:  20%|██        | 66/330 [00:00<00:02, 103.69it/s]

→ 1000 Phase 2: corners:  24%|██▎       | 78/330 [00:00<00:02, 103.24it/s]

→ 1000 Phase 2: corners:  27%|██▋       | 90/330 [00:01<00:02, 100.99it/s]

→ 1000 Phase 2: corners:  33%|███▎      | 108/330 [00:01<00:01, 119.85it/s]

→ 1000 Phase 2: corners:  38%|███▊      | 125/330 [00:01<00:01, 131.97it/s]

→ 1000 Phase 2: corners:  42%|████▏     | 139/330 [00:01<00:01, 131.37it/s]

→ 1000 Phase 2: corners:  47%|████▋     | 156/330 [00:01<00:01, 138.77it/s]

→ 1000 Phase 2: corners:  53%|█████▎    | 174/330 [00:01<00:01, 146.96it/s]

→ 1000 Phase 2: corners:  59%|█████▉    | 194/330 [00:01<00:00, 161.57it/s]

→ 1000 Phase 2: corners:  64%|██████▍   | 211/330 [00:01<00:00, 157.66it/s]

→ 1000 Phase 2: corners:  69%|██████▉   | 227/330 [00:01<00:00, 147.25it/s]

→ 1000 Phase 2: corners:  73%|███████▎  | 242/330 [00:02<00:00, 142.46it/s]

→ 1000 Phase 2: corners:  79%|███████▉  | 262/330 [00:02<00:00, 157.96it/s]

→ 1000 Phase 2: corners:  85%|████████▍ | 279/330 [00:02<00:00, 157.79it/s]

→ 1000 Phase 2: corners:  89%|████████▉ | 295/330 [00:02<00:00, 148.43it/s]

→ 1000 Phase 2: corners:  94%|█████████▍| 311/330 [00:02<00:00, 151.39it/s]

                                                                           [PASS2] Frame 0000283: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000290: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000366: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000368: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000369: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000377: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000378: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000379: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000380: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000636: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000637: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000638: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000652: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000717: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000790: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000794: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000795: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000796: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000797: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000798: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000799: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000800: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000801: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000894: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000895: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000896: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000897: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001161: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001162: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001163: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001164: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001165: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000290: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000368: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000379: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000635: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000636: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000651: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000652: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000800: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000895: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000896: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001163: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001164: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000635: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000636: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000651: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000652: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Summary: 21 frames fixed, 17 untrusted, 330 total


→ 1000 Phase 3: finalize:   0%|          | 0/330 [00:00<?, ?it/s]

→ 1000 Phase 3: finalize:   2%|▏         | 6/330 [00:00<00:05, 56.61it/s]

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→ 1000 Phase 3: finalize:   7%|▋         | 24/330 [00:00<00:05, 54.43it/s]

→ 1000 Phase 3: finalize:   9%|▉         | 30/330 [00:00<00:05, 54.51it/s]

→ 1000 Phase 3: finalize:  11%|█         | 36/330 [00:00<00:05, 54.75it/s]

→ 1000 Phase 3: finalize:  13%|█▎        | 42/330 [00:00<00:05, 55.00it/s]

→ 1000 Phase 3: finalize:  15%|█▍        | 48/330 [00:00<00:05, 55.18it/s]

→ 1000 Phase 3: finalize:  16%|█▋        | 54/330 [00:00<00:04, 55.29it/s]

→ 1000 Phase 3: finalize:  18%|█▊        | 60/330 [00:01<00:04, 55.34it/s]

→ 1000 Phase 3: finalize:  20%|██        | 66/330 [00:01<00:04, 55.30it/s]

→ 1000 Phase 3: finalize:  22%|██▏       | 72/330 [00:01<00:04, 55.31it/s]

→ 1000 Phase 3: finalize:  24%|██▎       | 78/330 [00:01<00:04, 54.78it/s]

→ 1000 Phase 3: finalize:  25%|██▌       | 84/330 [00:01<00:04, 54.48it/s]

→ 1000 Phase 3: finalize:  27%|██▋       | 90/330 [00:01<00:04, 54.59it/s]

→ 1000 Phase 3: finalize:  29%|██▉       | 96/330 [00:01<00:04, 54.75it/s]

→ 1000 Phase 3: finalize:  31%|███       | 102/330 [00:01<00:04, 54.82it/s]

→ 1000 Phase 3: finalize:  33%|███▎      | 108/330 [00:01<00:04, 54.88it/s]

→ 1000 Phase 3: finalize:  35%|███▍      | 114/330 [00:02<00:03, 54.87it/s]

→ 1000 Phase 3: finalize:  36%|███▋      | 120/330 [00:02<00:03, 54.80it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 126/330 [00:02<00:03, 54.64it/s]

→ 1000 Phase 3: finalize:  40%|████      | 132/330 [00:02<00:03, 54.48it/s]

→ 1000 Phase 3: finalize:  42%|████▏     | 138/330 [00:02<00:03, 54.38it/s]

→ 1000 Phase 3: finalize:  44%|████▎     | 144/330 [00:02<00:03, 54.37it/s]

→ 1000 Phase 3: finalize:  45%|████▌     | 150/330 [00:02<00:03, 54.45it/s]

→ 1000 Phase 3: finalize:  47%|████▋     | 156/330 [00:02<00:03, 54.44it/s]

→ 1000 Phase 3: finalize:  49%|████▉     | 162/330 [00:02<00:03, 54.42it/s]

→ 1000 Phase 3: finalize:  51%|█████     | 168/330 [00:03<00:02, 54.57it/s]

→ 1000 Phase 3: finalize:  53%|█████▎    | 174/330 [00:03<00:02, 54.84it/s]

→ 1000 Phase 3: finalize:  55%|█████▍    | 180/330 [00:03<00:02, 54.86it/s]

→ 1000 Phase 3: finalize:  56%|█████▋    | 186/330 [00:03<00:02, 54.80it/s]

→ 1000 Phase 3: finalize:  58%|█████▊    | 192/330 [00:03<00:02, 54.67it/s]

→ 1000 Phase 3: finalize:  60%|██████    | 198/330 [00:03<00:02, 54.51it/s]

→ 1000 Phase 3: finalize:  62%|██████▏   | 204/330 [00:03<00:02, 54.48it/s]

→ 1000 Phase 3: finalize:  64%|██████▎   | 210/330 [00:03<00:02, 54.19it/s]

→ 1000 Phase 3: finalize:  65%|██████▌   | 216/330 [00:03<00:02, 53.81it/s]

→ 1000 Phase 3: finalize:  67%|██████▋   | 222/330 [00:04<00:02, 53.39it/s]

→ 1000 Phase 3: finalize:  69%|██████▉   | 228/330 [00:04<00:01, 53.17it/s]

→ 1000 Phase 3: finalize:  71%|███████   | 234/330 [00:04<00:01, 53.15it/s]

→ 1000 Phase 3: finalize:  73%|███████▎  | 240/330 [00:04<00:01, 53.42it/s]

→ 1000 Phase 3: finalize:  75%|███████▍  | 246/330 [00:04<00:01, 53.61it/s]

→ 1000 Phase 3: finalize:  76%|███████▋  | 252/330 [00:04<00:01, 53.87it/s]

→ 1000 Phase 3: finalize:  78%|███████▊  | 258/330 [00:04<00:01, 53.95it/s]

→ 1000 Phase 3: finalize:  80%|████████  | 264/330 [00:04<00:01, 54.15it/s]

→ 1000 Phase 3: finalize:  82%|████████▏ | 270/330 [00:04<00:01, 54.46it/s]

→ 1000 Phase 3: finalize:  84%|████████▎ | 276/330 [00:05<00:00, 54.77it/s]

→ 1000 Phase 3: finalize:  85%|████████▌ | 282/330 [00:05<00:00, 54.93it/s]

→ 1000 Phase 3: finalize:  87%|████████▋ | 288/330 [00:05<00:00, 55.06it/s]

→ 1000 Phase 3: finalize:  89%|████████▉ | 294/330 [00:05<00:00, 55.06it/s]

→ 1000 Phase 3: finalize:  91%|█████████ | 300/330 [00:05<00:00, 54.27it/s]

→ 1000 Phase 3: finalize:  93%|█████████▎| 306/330 [00:05<00:00, 54.69it/s]

→ 1000 Phase 3: finalize:  95%|█████████▍| 312/330 [00:05<00:00, 54.98it/s]

→ 1000 Phase 3: finalize:  96%|█████████▋| 318/330 [00:05<00:00, 54.93it/s]

→ 1000 Phase 3: finalize:  98%|█████████▊| 324/330 [00:05<00:00, 54.68it/s]

→ 1000 Phase 3: finalize: 100%|██████████| 330/330 [00:06<00:00, 54.46it/s]

                                                                           
[TIMING] 1000 — 331 frames
  Phase 1  radial detect   (parallel)  :   5.36s  (16.2 ms/frame)
  Phase 2a corner detect   (parallel)  :   2.69s  (8.1 ms/frame)
  Phase 2b corner fix      (sequential):   0.82s
  Phase 3  finalize        (sequential):   6.05s  (18.3 ms/frame)
    decode + undistort                 :   3.29s  (9.9 ms/frame)
    corner apply + refinement          :   1.16s  (3.5 ms/frame)
    segment                            :   1.31s  (3.9 ms/frame)
    smooth                             :   0.19s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  14.92s


Processing Rigs: 100%|██████████| 4/4 [01:27<00:00, 20.73s/it]
Processing Rigs: 100%|██████████| 4/4 [01:27<00:00, 21.83s/it]
[💾] Saved RigFrameDataset to /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 1580 frames from 4 rigs to /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 1500: 100 frames selected from 454
[📋] 2000L: 100 frames selected from 420
[📋] 2000R: 100 frames selected from 376
[📋] 1000: 100 frames selected from 330
[💾] Saved RigFrameDataset to /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/1_digitized/rig_frames.json

-------------------------------------------------------------------
                      Step 2: Casing Detection                     
-------------------------------------------------------------------

-> Calculating the casing center ...
[INFO] Using 80 total sampled bright frames

Computing max image from bright frames:   0%|          | 0/80 [00:00<?, ?it/s]
Computing max image from bright frames:   1%|▏         | 1/80 [00:02<02:43,  2.08s/it]
Computing max image from bright frames:   2%|▎         | 2/80 [00:05<03:32,  2.73s/it]
Computing max image from bright frames:   4%|▍         | 3/80 [00:05<02:04,  1.61s/it]
Computing max image from bright frames:   5%|▌         | 4/80 [00:05<01:23,  1.10s/it]
Computing max image from bright frames:   8%|▊         | 6/80 [00:06<00:44,  1.68it/s]
Computing max image from bright frames:   9%|▉         | 7/80 [00:06<00:33,  2.16it/s]
Computing max image from bright frames:  10%|█         | 8/80 [00:06<00:26,  2.72it/s]
Computing max image from bright frames:  11%|█▏        | 9/80 [00:06<00:20,  3.40it/s]
Computing max image from bright frames:  12%|█▎        | 10/80 [00:06<00:17,  3.94it/s]
Computing max image from bright frames:  14%|█▍        | 11/80 [00:06<00:14,  4.65it/s]
Computing max image from bright frames:  16%|█▋        | 13/80 [00:06<00:10,  6.41it/s]
Computing max image from bright frames:  19%|█▉        | 15/80 [00:07<00:08,  7.78it/s]
Computing max image from bright frames:  20%|██        | 16/80 [00:07<00:08,  7.85it/s]
Computing max image from bright frames:  21%|██▏       | 17/80 [00:07<00:07,  7.94it/s]
Computing max image from bright frames:  22%|██▎       | 18/80 [00:07<00:07,  8.19it/s]
Computing max image from bright frames:  24%|██▍       | 19/80 [00:07<00:07,  8.18it/s]
Computing max image from bright frames:  25%|██▌       | 20/80 [00:07<00:07,  7.76it/s]
Computing max image from bright frames:  26%|██▋       | 21/80 [00:07<00:07,  8.28it/s]
Computing max image from bright frames:  28%|██▊       | 22/80 [00:07<00:06,  8.32it/s]
Computing max image from bright frames:  29%|██▉       | 23/80 [00:08<00:07,  8.05it/s]
Computing max image from bright frames:  30%|███       | 24/80 [00:08<00:16,  3.50it/s]
Computing max image from bright frames:  31%|███▏      | 25/80 [00:08<00:14,  3.88it/s]
Computing max image from bright frames:  32%|███▎      | 26/80 [00:09<00:17,  3.17it/s]
Computing max image from bright frames:  34%|███▍      | 27/80 [00:09<00:13,  3.89it/s]
Computing max image from bright frames:  36%|███▋      | 29/80 [00:09<00:09,  5.19it/s]
Computing max image from bright frames:  38%|███▊      | 30/80 [00:09<00:08,  5.85it/s]
Computing max image from bright frames:  39%|███▉      | 31/80 [00:09<00:07,  6.54it/s]
Computing max image from bright frames:  40%|████      | 32/80 [00:10<00:07,  6.23it/s]
Computing max image from bright frames:  41%|████▏     | 33/80 [00:10<00:07,  6.18it/s]
Computing max image from bright frames:  42%|████▎     | 34/80 [00:10<00:07,  6.29it/s]
Computing max image from bright frames:  45%|████▌     | 36/80 [00:10<00:05,  7.55it/s]
Computing max image from bright frames:  46%|████▋     | 37/80 [00:11<00:16,  2.61it/s]
Computing max image from bright frames:  48%|████▊     | 38/80 [00:12<00:20,  2.03it/s]
Computing max image from bright frames:  50%|█████     | 40/80 [00:12<00:12,  3.10it/s]
Computing max image from bright frames:  51%|█████▏    | 41/80 [00:12<00:10,  3.57it/s]
Computing max image from bright frames:  52%|█████▎    | 42/80 [00:13<00:09,  4.09it/s]
Computing max image from bright frames:  54%|█████▍    | 43/80 [00:13<00:08,  4.29it/s]
Computing max image from bright frames:  55%|█████▌    | 44/80 [00:13<00:07,  4.73it/s]
Computing max image from bright frames:  56%|█████▋    | 45/80 [00:13<00:06,  5.53it/s]
Computing max image from bright frames:  57%|█████▊    | 46/80 [00:13<00:05,  6.15it/s]
Computing max image from bright frames:  59%|█████▉    | 47/80 [00:13<00:04,  6.63it/s]
Computing max image from bright frames:  60%|██████    | 48/80 [00:13<00:04,  7.28it/s]
Computing max image from bright frames:  62%|██████▎   | 50/80 [00:14<00:03,  9.28it/s]
Computing max image from bright frames:  65%|██████▌   | 52/80 [00:14<00:02, 10.91it/s]
Computing max image from bright frames:  69%|██████▉   | 55/80 [00:14<00:01, 14.20it/s]
Computing max image from bright frames:  71%|███████▏  | 57/80 [00:14<00:01, 11.62it/s]
Computing max image from bright frames:  74%|███████▍  | 59/80 [00:14<00:01, 12.37it/s]
Computing max image from bright frames:  76%|███████▋  | 61/80 [00:15<00:04,  4.61it/s]
Computing max image from bright frames:  79%|███████▉  | 63/80 [00:15<00:02,  5.82it/s]
Computing max image from bright frames:  82%|████████▎ | 66/80 [00:16<00:01,  8.22it/s]
Computing max image from bright frames:  85%|████████▌ | 68/80 [00:16<00:01,  7.66it/s]
Computing max image from bright frames:  88%|████████▊ | 70/80 [00:16<00:01,  6.77it/s]
Computing max image from bright frames:  90%|█████████ | 72/80 [00:17<00:02,  3.86it/s]
Computing max image from bright frames:  91%|█████████▏| 73/80 [00:17<00:01,  4.14it/s]
Computing max image from bright frames:  92%|█████████▎| 74/80 [00:18<00:01,  4.46it/s]
Computing max image from bright frames:  95%|█████████▌| 76/80 [00:18<00:00,  5.50it/s]
Computing max image from bright frames:  99%|█████████▉| 79/80 [00:18<00:00,  7.84it/s]
                                                                                       
[✅] Casing detection complete: cx=909.0, cy=914.0

-------------------------------------------------------------------
                        Step 3: Calibration                        
-------------------------------------------------------------------


  0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:47,  2.10it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:47,  2.10it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   2%|▏         | 2/100 [00:00<00:46,  2.10it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   3%|▎         | 3/100 [00:00<00:15,  6.20it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.000 | Best: {'fx': 321.212} (0.000):   3%|▎         | 3/100 [00:00<00:15,  6.20it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   4%|▍         | 4/100 [00:00<00:15,  6.20it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   5%|▌         | 5/100 [00:00<00:15,  6.20it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   6%|▌         | 6/100 [00:00<00:08, 11.47it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   6%|▌         | 6/100 [00:00<00:08, 11.47it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.000 | Best: {'fx': 349.495} (0.000):   7%|▋         | 7/100 [00:00<00:08, 11.47it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.001 | Best: {'fx': 363.636} (0.001):   8%|▊         | 8/100 [00:00<00:08, 11.47it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.001 | Best: {'fx': 363.636} (0.001):   9%|▉         | 9/100 [00:00<00:06, 14.99it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.001 | Best: {'fx': 363.636} (0.001):   9%|▉         | 9/100 [00:00<00:06, 14.99it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.002 | Best: {'fx': 370.707} (0.002):  10%|█         | 10/100 [00:00<00:06, 14.99it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.003 | Best: {'fx': 377.778} (0.003):  11%|█         | 11/100 [00:00<00:05, 14.99it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.004 | Best: {'fx': 384.848} (0.004):  12%|█▏        | 12/100 [00:00<00:05, 14.99it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.004 | Best: {'fx': 384.848} (0.004):  13%|█▎        | 13/100 [00:00<00:04, 18.13it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  13%|█▎        | 13/100 [00:01<00:04, 18.13it/s] 
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  14%|█▍        | 14/100 [00:01<00:04, 18.13it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.005 | Best: {'fx': 406.061} (0.005):  15%|█▌        | 15/100 [00:01<00:04, 18.13it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  16%|█▌        | 16/100 [00:01<00:04, 18.13it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  17%|█▋        | 17/100 [00:01<00:03, 23.12it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.006 | Best: {'fx': 420.202} (0.006):  17%|█▋        | 17/100 [00:01<00:03, 23.12it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  18%|█▊        | 18/100 [00:01<00:03, 23.12it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.007 | Best: {'fx': 434.343} (0.007):  19%|█▉        | 19/100 [00:01<00:03, 23.12it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.007 | Best: {'fx': 434.343} (0.007):  20%|██        | 20/100 [00:01<00:03, 21.76it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.009 | Best: {'fx': 441.414} (0.009):  20%|██        | 20/100 [00:01<00:03, 21.76it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.011 | Best: {'fx': 448.485} (0.011):  21%|██        | 21/100 [00:01<00:03, 21.76it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.013 | Best: {'fx': 455.556} (0.013):  22%|██▏       | 22/100 [00:01<00:03, 21.76it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.018 | Best: {'fx': 469.697} (0.018):  23%|██▎       | 23/100 [00:01<00:03, 21.76it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.018 | Best: {'fx': 469.697} (0.018):  24%|██▍       | 24/100 [00:01<00:03, 21.86it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.016 | Best: {'fx': 469.697} (0.018):  24%|██▍       | 24/100 [00:01<00:03, 21.86it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.021 | Best: {'fx': 476.768} (0.021):  25%|██▌       | 25/100 [00:01<00:03, 21.86it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.026 | Best: {'fx': 483.838} (0.026):  26%|██▌       | 26/100 [00:01<00:03, 21.86it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.034 | Best: {'fx': 490.909} (0.034):  27%|██▋       | 27/100 [00:01<00:03, 21.86it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.034 | Best: {'fx': 490.909} (0.034):  28%|██▊       | 28/100 [00:01<00:03, 22.07it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.043 | Best: {'fx': 497.98} (0.043):  28%|██▊       | 28/100 [00:01<00:03, 22.07it/s] 
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.051 | Best: {'fx': 505.051} (0.051):  29%|██▉       | 29/100 [00:01<00:03, 22.07it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.062 | Best: {'fx': 512.121} (0.062):  30%|███       | 30/100 [00:01<00:03, 22.07it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.076 | Best: {'fx': 519.192} (0.076):  31%|███       | 31/100 [00:01<00:03, 22.07it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.076 | Best: {'fx': 519.192} (0.076):  32%|███▏      | 32/100 [00:01<00:03, 17.44it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.087 | Best: {'fx': 526.263} (0.087):  32%|███▏      | 32/100 [00:01<00:03, 17.44it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.081 | Best: {'fx': 526.263} (0.087):  33%|███▎      | 33/100 [00:02<00:03, 17.44it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.087 | Best: {'fx': 533.333} (0.087):  34%|███▍      | 34/100 [00:02<00:03, 17.44it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.067 | Best: {'fx': 533.333} (0.087):  35%|███▌      | 35/100 [00:02<00:03, 17.44it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.067 | Best: {'fx': 533.333} (0.087):  36%|███▌      | 36/100 [00:02<00:03, 20.99it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.051 | Best: {'fx': 533.333} (0.087):  36%|███▌      | 36/100 [00:02<00:03, 20.99it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.057 | Best: {'fx': 533.333} (0.087):  37%|███▋      | 37/100 [00:02<00:03, 20.99it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.042 | Best: {'fx': 533.333} (0.087):  38%|███▊      | 38/100 [00:02<00:02, 20.99it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.042 | Best: {'fx': 533.333} (0.087):  39%|███▉      | 39/100 [00:02<00:02, 22.29it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.037 | Best: {'fx': 533.333} (0.087):  39%|███▉      | 39/100 [00:02<00:02, 22.29it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.036 | Best: {'fx': 533.333} (0.087):  40%|████      | 40/100 [00:02<00:02, 22.29it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.032 | Best: {'fx': 533.333} (0.087):  41%|████      | 41/100 [00:02<00:02, 22.29it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.032 | Best: {'fx': 533.333} (0.087):  42%|████▏     | 42/100 [00:02<00:03, 19.21it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.047 | Best: {'fx': 533.333} (0.087):  42%|████▏     | 42/100 [00:02<00:03, 19.21it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.041 | Best: {'fx': 533.333} (0.087):  43%|████▎     | 43/100 [00:02<00:02, 19.21it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.033 | Best: {'fx': 533.333} (0.087):  44%|████▍     | 44/100 [00:02<00:02, 19.21it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.034 | Best: {'fx': 533.333} (0.087):  45%|████▌     | 45/100 [00:02<00:02, 19.21it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.034 | Best: {'fx': 533.333} (0.087):  46%|████▌     | 46/100 [00:02<00:02, 21.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.028 | Best: {'fx': 533.333} (0.087):  46%|████▌     | 46/100 [00:02<00:02, 21.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.029 | Best: {'fx': 533.333} (0.087):  47%|████▋     | 47/100 [00:02<00:02, 21.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.030 | Best: {'fx': 533.333} (0.087):  48%|████▊     | 48/100 [00:02<00:02, 21.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.029 | Best: {'fx': 533.333} (0.087):  49%|████▉     | 49/100 [00:02<00:02, 21.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.026 | Best: {'fx': 533.333} (0.087):  50%|█████     | 50/100 [00:02<00:02, 21.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.026 | Best: {'fx': 533.333} (0.087):  51%|█████     | 51/100 [00:02<00:01, 26.59it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.027 | Best: {'fx': 533.333} (0.087):  51%|█████     | 51/100 [00:02<00:01, 26.59it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.023 | Best: {'fx': 533.333} (0.087):  52%|█████▏    | 52/100 [00:02<00:01, 26.59it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.025 | Best: {'fx': 533.333} (0.087):  53%|█████▎    | 53/100 [00:02<00:01, 26.59it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.025 | Best: {'fx': 533.333} (0.087):  54%|█████▍    | 54/100 [00:02<00:01, 26.47it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.027 | Best: {'fx': 533.333} (0.087):  54%|█████▍    | 54/100 [00:02<00:01, 26.47it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.025 | Best: {'fx': 533.333} (0.087):  55%|█████▌    | 55/100 [00:02<00:01, 26.47it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.025 | Best: {'fx': 533.333} (0.087):  56%|█████▌    | 56/100 [00:02<00:01, 26.47it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.022 | Best: {'fx': 533.333} (0.087):  57%|█████▋    | 57/100 [00:02<00:01, 26.47it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.024 | Best: {'fx': 533.333} (0.087):  58%|█████▊    | 58/100 [00:02<00:01, 26.47it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.024 | Best: {'fx': 533.333} (0.087):  59%|█████▉    | 59/100 [00:02<00:01, 30.95it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.023 | Best: {'fx': 533.333} (0.087):  59%|█████▉    | 59/100 [00:02<00:01, 30.95it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.023 | Best: {'fx': 533.333} (0.087):  60%|██████    | 60/100 [00:02<00:01, 30.95it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.022 | Best: {'fx': 533.333} (0.087):  61%|██████    | 61/100 [00:02<00:01, 30.95it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.024 | Best: {'fx': 533.333} (0.087):  62%|██████▏   | 62/100 [00:02<00:01, 30.95it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.022 | Best: {'fx': 533.333} (0.087):  63%|██████▎   | 63/100 [00:02<00:01, 30.95it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.023 | Best: {'fx': 533.333} (0.087):  64%|██████▍   | 64/100 [00:02<00:01, 30.95it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.021 | Best: {'fx': 533.333} (0.087):  65%|██████▌   | 65/100 [00:02<00:01, 30.95it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.022 | Best: {'fx': 533.333} (0.087):  66%|██████▌   | 66/100 [00:02<00:01, 30.95it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.021 | Best: {'fx': 533.333} (0.087):  67%|██████▋   | 67/100 [00:02<00:01, 30.95it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.021 | Best: {'fx': 533.333} (0.087):  68%|██████▊   | 68/100 [00:03<00:01, 30.95it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.021 | Best: {'fx': 533.333} (0.087):  69%|██████▉   | 69/100 [00:03<00:00, 41.90it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.023 | Best: {'fx': 533.333} (0.087):  69%|██████▉   | 69/100 [00:03<00:00, 41.90it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.021 | Best: {'fx': 533.333} (0.087):  70%|███████   | 70/100 [00:03<00:00, 41.90it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.021 | Best: {'fx': 533.333} (0.087):  71%|███████   | 71/100 [00:03<00:00, 41.90it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.021 | Best: {'fx': 533.333} (0.087):  72%|███████▏  | 72/100 [00:03<00:00, 41.90it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.021 | Best: {'fx': 533.333} (0.087):  73%|███████▎  | 73/100 [00:03<00:00, 41.90it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  74%|███████▍  | 74/100 [00:03<00:00, 41.90it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  75%|███████▌  | 75/100 [00:03<00:00, 41.90it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  76%|███████▌  | 76/100 [00:03<00:00, 41.90it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  77%|███████▋  | 77/100 [00:03<00:00, 47.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  77%|███████▋  | 77/100 [00:03<00:00, 47.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  78%|███████▊  | 78/100 [00:03<00:00, 47.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  79%|███████▉  | 79/100 [00:03<00:00, 47.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  80%|████████  | 80/100 [00:03<00:00, 47.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  81%|████████  | 81/100 [00:03<00:00, 47.93it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  82%|████████▏ | 82/100 [00:03<00:00, 43.49it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  82%|████████▏ | 82/100 [00:03<00:00, 43.49it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  83%|████████▎ | 83/100 [00:03<00:00, 43.49it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  84%|████████▍ | 84/100 [00:03<00:00, 43.49it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  85%|████████▌ | 85/100 [00:03<00:00, 43.49it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  86%|████████▌ | 86/100 [00:03<00:00, 43.49it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  87%|████████▋ | 87/100 [00:03<00:00, 36.45it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  87%|████████▋ | 87/100 [00:03<00:00, 36.45it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.020 | Best: {'fx': 533.333} (0.087):  88%|████████▊ | 88/100 [00:03<00:00, 36.45it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  89%|████████▉ | 89/100 [00:03<00:00, 36.45it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  90%|█████████ | 90/100 [00:03<00:00, 36.45it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  91%|█████████ | 91/100 [00:03<00:00, 35.69it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  91%|█████████ | 91/100 [00:03<00:00, 35.69it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  92%|█████████▏| 92/100 [00:03<00:00, 35.69it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  93%|█████████▎| 93/100 [00:03<00:00, 35.69it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  94%|█████████▍| 94/100 [00:03<00:00, 35.69it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  95%|█████████▌| 95/100 [00:03<00:00, 31.09it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  95%|█████████▌| 95/100 [00:03<00:00, 31.09it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  96%|█████████▌| 96/100 [00:03<00:00, 31.09it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  97%|█████████▋| 97/100 [00:03<00:00, 31.09it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  98%|█████████▊| 98/100 [00:03<00:00, 31.09it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.019 | Best: {'fx': 533.333} (0.087):  99%|█████████▉| 99/100 [00:03<00:00, 28.99it/s]
Brute | Start: {'fx': 500.0} (0.044) | Current: 0.018 | Best: {'fx': 533.333} (0.087):  99%|█████████▉| 99/100 [00:03<00:00, 28.99it/s]
                                                                                                                                       

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.057 | Best: {'fx': 509.354} (0.057):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.057 | Best: {'fx': 509.354} (0.057):   2%|▏         | 1/50 [00:00<00:27,  1.81it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.055 | Best: {'fx': 509.354} (0.057):   2%|▏         | 1/50 [00:00<00:27,  1.81it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.059 | Best: {'fx': 510.374} (0.059):   4%|▍         | 2/50 [00:00<00:26,  1.81it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.063 | Best: {'fx': 512.415} (0.063):   6%|▌         | 3/50 [00:00<00:25,  1.81it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.063 | Best: {'fx': 512.415} (0.063):   8%|▊         | 4/50 [00:00<00:06,  7.20it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.061 | Best: {'fx': 512.415} (0.063):   8%|▊         | 4/50 [00:00<00:06,  7.20it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.067 | Best: {'fx': 514.456} (0.067):  10%|█         | 5/50 [00:00<00:06,  7.20it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.064 | Best: {'fx': 514.456} (0.067):  12%|█▏        | 6/50 [00:00<00:06,  7.20it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.069 | Best: {'fx': 515.476} (0.069):  14%|█▍        | 7/50 [00:00<00:05,  7.20it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.069 | Best: {'fx': 515.476} (0.069):  16%|█▌        | 8/50 [00:00<00:02, 14.11it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.071 | Best: {'fx': 516.497} (0.071):  16%|█▌        | 8/50 [00:00<00:02, 14.11it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.073 | Best: {'fx': 517.517} (0.073):  18%|█▊        | 9/50 [00:00<00:02, 14.11it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.077 | Best: {'fx': 519.558} (0.077):  20%|██        | 10/50 [00:00<00:02, 14.11it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.077 | Best: {'fx': 519.558} (0.077):  22%|██▏       | 11/50 [00:00<00:02, 16.47it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.075 | Best: {'fx': 519.558} (0.077):  22%|██▏       | 11/50 [00:00<00:02, 16.47it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.078 | Best: {'fx': 520.578} (0.078):  24%|██▍       | 12/50 [00:01<00:02, 16.47it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.079 | Best: {'fx': 521.599} (0.079):  26%|██▌       | 13/50 [00:01<00:02, 16.47it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.079 | Best: {'fx': 521.599} (0.079):  28%|██▊       | 14/50 [00:01<00:02, 17.11it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.087 | Best: {'fx': 524.66} (0.087):  28%|██▊       | 14/50 [00:01<00:02, 17.11it/s] 
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.082 | Best: {'fx': 524.66} (0.087):  30%|███       | 15/50 [00:01<00:02, 17.11it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.086 | Best: {'fx': 524.66} (0.087):  32%|███▏      | 16/50 [00:01<00:01, 17.11it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.086 | Best: {'fx': 524.66} (0.087):  34%|███▍      | 17/50 [00:01<00:01, 19.14it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.086 | Best: {'fx': 524.66} (0.087):  34%|███▍      | 17/50 [00:01<00:01, 19.14it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.090 | Best: {'fx': 527.721} (0.090):  36%|███▌      | 18/50 [00:01<00:01, 19.14it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.091 | Best: {'fx': 528.741} (0.091):  38%|███▊      | 19/50 [00:01<00:01, 19.14it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.091 | Best: {'fx': 528.741} (0.091):  40%|████      | 20/50 [00:01<00:01, 21.07it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.086 | Best: {'fx': 528.741} (0.091):  40%|████      | 20/50 [00:01<00:01, 21.07it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.090 | Best: {'fx': 528.741} (0.091):  42%|████▏     | 21/50 [00:01<00:01, 21.07it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.087 | Best: {'fx': 528.741} (0.091):  44%|████▍     | 22/50 [00:01<00:01, 21.07it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.087 | Best: {'fx': 528.741} (0.091):  46%|████▌     | 23/50 [00:01<00:01, 22.42it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.080 | Best: {'fx': 528.741} (0.091):  46%|████▌     | 23/50 [00:01<00:01, 22.42it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.091 | Best: {'fx': 528.741} (0.091):  48%|████▊     | 24/50 [00:01<00:01, 22.42it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.076 | Best: {'fx': 528.741} (0.091):  50%|█████     | 25/50 [00:01<00:01, 22.42it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.077 | Best: {'fx': 528.741} (0.091):  52%|█████▏    | 26/50 [00:01<00:01, 22.42it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.077 | Best: {'fx': 528.741} (0.091):  54%|█████▍    | 27/50 [00:01<00:00, 24.71it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.090 | Best: {'fx': 528.741} (0.091):  54%|█████▍    | 27/50 [00:01<00:00, 24.71it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.072 | Best: {'fx': 528.741} (0.091):  56%|█████▌    | 28/50 [00:01<00:00, 24.71it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.081 | Best: {'fx': 528.741} (0.091):  58%|█████▊    | 29/50 [00:01<00:00, 24.71it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.085 | Best: {'fx': 528.741} (0.091):  60%|██████    | 30/50 [00:01<00:00, 24.71it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.086 | Best: {'fx': 528.741} (0.091):  62%|██████▏   | 31/50 [00:01<00:00, 24.71it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.083 | Best: {'fx': 528.741} (0.091):  64%|██████▍   | 32/50 [00:01<00:00, 24.71it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.083 | Best: {'fx': 528.741} (0.091):  66%|██████▌   | 33/50 [00:01<00:00, 30.08it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.084 | Best: {'fx': 528.741} (0.091):  66%|██████▌   | 33/50 [00:01<00:00, 30.08it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.069 | Best: {'fx': 528.741} (0.091):  68%|██████▊   | 34/50 [00:01<00:00, 30.08it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.070 | Best: {'fx': 528.741} (0.091):  70%|███████   | 35/50 [00:01<00:00, 30.08it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.085 | Best: {'fx': 528.741} (0.091):  72%|███████▏  | 36/50 [00:01<00:00, 30.08it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.065 | Best: {'fx': 528.741} (0.091):  74%|███████▍  | 37/50 [00:01<00:00, 30.08it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.066 | Best: {'fx': 528.741} (0.091):  76%|███████▌  | 38/50 [00:01<00:00, 30.08it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.062 | Best: {'fx': 528.741} (0.091):  78%|███████▊  | 39/50 [00:01<00:00, 30.08it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.068 | Best: {'fx': 528.741} (0.091):  80%|████████  | 40/50 [00:01<00:00, 30.08it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.068 | Best: {'fx': 528.741} (0.091):  82%|████████▏ | 41/50 [00:01<00:00, 40.95it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.064 | Best: {'fx': 528.741} (0.091):  82%|████████▏ | 41/50 [00:01<00:00, 40.95it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.085 | Best: {'fx': 528.741} (0.091):  84%|████████▍ | 42/50 [00:01<00:00, 40.95it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.059 | Best: {'fx': 528.741} (0.091):  86%|████████▌ | 43/50 [00:01<00:00, 40.95it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.060 | Best: {'fx': 528.741} (0.091):  88%|████████▊ | 44/50 [00:01<00:00, 40.95it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.056 | Best: {'fx': 528.741} (0.091):  90%|█████████ | 45/50 [00:01<00:00, 40.95it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.056 | Best: {'fx': 528.741} (0.091):  92%|█████████▏| 46/50 [00:01<00:00, 42.69it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.058 | Best: {'fx': 528.741} (0.091):  92%|█████████▏| 46/50 [00:01<00:00, 42.69it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.057 | Best: {'fx': 528.741} (0.091):  94%|█████████▍| 47/50 [00:01<00:00, 42.69it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.055 | Best: {'fx': 528.741} (0.091):  96%|█████████▌| 48/50 [00:01<00:00, 42.69it/s]
Brute | Start: {'fx': 533.333} (0.087) | Current: 0.054 | Best: {'fx': 528.741} (0.091):  98%|█████████▊| 49/50 [00:02<00:00, 42.69it/s]
                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 528.7414965986395
    px: 909.0
    py: 914.0
    k1: 0.0
    k2: 0.0
    k3: 0.0
    k4: 0.0
    p1: 0.0
    p2: 0.0
    p3: 0.0
    p4: 0.0
    scale: 3.0
    rotation: 0.0


[🔲] Square Reference Optimization
    Including tangential distortion parameters (p1, p2, p3, p4) in joint optimization
  Selecting up to 20 frames per rig (excluded 0 incomplete frames): 80 frames will be used for optimization
  Rigs: 1500(1500mm):20/20, 2000L(2000mm):20/20, 2000R(2000mm):20/20, 1000(1000mm):20/20
  Total: 80/80 frames used for optimization

Initial score: 30.4978: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 30.4978, picklable_objective(x0) = 30.5153

Best score: 30.5153: : 0iter [00:02, ?iter/s] 
Best score: 30.5153: : 1iter [00:02,  2.02s/iter]
Best score: 30.5153: : 1iter [00:02,  2.02s/iter]
Best score: 30.5153: : 2iter [00:02,  2.02s/iter]
Best score: 30.5153: : 3iter [00:02,  1.69iter/s]
Best score: 30.5153: : 3iter [00:02,  1.69iter/s]
Best score: 30.5153: : 4iter [00:02,  1.69iter/s]
Best score: 30.5153: : 5iter [00:02,  3.01iter/s]
Best score: 30.5153: : 5iter [00:02,  3.01iter/s]
Best score: 30.5153: : 6iter [00:02,  3.01iter/s]
Best score: 30.5153: : 7iter [00:02,  4.36iter/s]
Best score: 30.5153: : 7iter [00:02,  4.36iter/s]
Best score: 30.5153: : 8iter [00:02,  4.36iter/s]
Best score: 30.5153: : 9iter [00:02,  5.68iter/s]
Best score: 30.5153: : 9iter [00:02,  5.68iter/s]
Best score: 30.5153: : 10iter [00:02,  5.68iter/s]
Best score: 30.5153: : 11iter [00:02,  6.82iter/s]
Best score: 30.5153: : 11iter [00:03,  6.82iter/s]
Best score: 30.5153: : 12iter [00:03,  6.82iter/s]
Best score: 30.5153: : 13iter [00:03,  7.87iter/s]
Best score: 30.5153: : 13iter [00:03,  7.87iter/s]
Best score: 30.5153: : 14iter [00:03,  7.87iter/s]
Best score: 30.5153: : 15iter [00:03,  8.75iter/s]
Best score: 30.5153: : 15iter [00:03,  8.75iter/s]
Best score: 30.5153: : 16iter [00:03,  8.75iter/s]
Best score: 30.5153: : 17iter [00:03,  9.43iter/s]
Best score: 30.5153: : 17iter [00:03,  9.43iter/s]
Best score: 30.5153: : 18iter [00:03,  9.43iter/s]
Best score: 30.5153: : 19iter [00:03,  9.99iter/s]
Best score: 30.5153: : 19iter [00:03,  9.99iter/s]
Best score: 30.5153: : 20iter [00:03,  9.99iter/s]
Best score: 30.5153: : 21iter [00:03, 10.24iter/s]
Best score: 30.5153: : 21iter [00:03, 10.24iter/s]
Best score: 30.5153: : 22iter [00:03, 10.24iter/s]
Best score: 30.5153: : 23iter [00:03, 10.57iter/s]
Best score: 30.5153: : 23iter [00:04, 10.57iter/s]
Best score: 30.5153: : 24iter [00:04, 10.57iter/s]
Best score: 30.5153: : 25iter [00:04, 10.75iter/s]
Best score: 30.5153: : 25iter [00:04, 10.75iter/s]
Best score: 30.5153: : 26iter [00:04, 10.75iter/s]
Best score: 30.5153: : 27iter [00:04, 10.87iter/s]
Best score: 30.5153: : 27iter [00:04, 10.87iter/s]
Best score: 30.5153: : 28iter [00:04, 10.87iter/s]
Best score: 30.5153: : 29iter [00:04, 10.98iter/s]
Best score: 30.5153: : 29iter [00:04, 10.98iter/s]
Best score: 30.5153: : 30iter [00:04, 10.98iter/s]
Best score: 30.5153: : 31iter [00:04, 10.95iter/s]
Best score: 30.5153: : 31iter [00:04, 10.95iter/s]
Best score: 30.5153: : 32iter [00:04, 10.95iter/s]
Best score: 30.5153: : 33iter [00:04, 11.06iter/s]
Best score: 30.5153: : 33iter [00:04, 11.06iter/s]
Best score: 30.5153: : 34iter [00:05, 11.06iter/s]
Best score: 30.5153: : 35iter [00:05, 11.16iter/s]
Best score: 30.5153: : 35iter [00:05, 11.16iter/s]
Best score: 30.5153: : 36iter [00:05, 11.16iter/s]
Best score: 30.5153: : 37iter [00:05, 11.20iter/s]
Best score: 30.5153: : 37iter [00:05, 11.20iter/s]
Best score: 30.5153: : 38iter [00:05, 11.20iter/s]
Best score: 30.5153: : 39iter [00:05, 11.22iter/s]
Best score: 30.5153: : 39iter [00:05, 11.22iter/s]
Best score: 30.5153: : 40iter [00:05, 11.22iter/s]
Best score: 30.5153: : 41iter [00:05, 11.11iter/s]
Best score: 30.5153: : 41iter [00:05, 11.11iter/s]
Best score: 30.5153: : 42iter [00:05, 11.11iter/s]
Best score: 30.5153: : 43iter [00:05, 11.20iter/s]
Best score: 30.5153: : 43iter [00:05, 11.20iter/s]
Best score: 30.5153: : 44iter [00:05, 11.20iter/s]
Best score: 30.5153: : 45iter [00:05, 11.28iter/s]
Best score: 30.5153: : 45iter [00:06, 11.28iter/s]
Best score: 30.5153: : 46iter [00:06, 11.28iter/s]
Best score: 30.5153: : 47iter [00:06, 11.32iter/s]
Best score: 30.5153: : 47iter [00:06, 11.32iter/s]
Best score: 30.5153: : 48iter [00:06, 11.32iter/s]
Best score: 30.5153: : 49iter [00:06, 11.40iter/s]
Best score: 30.5153: : 49iter [00:06, 11.40iter/s]
[ITER 50] Best: 30.5153
[PARAMS] Current best parameters:
  fx: 528.7415
  fy: 528.7415
  px: 909.0000
  py: 914.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000

Best score: 30.5153: : 50iter [00:06, 11.40iter/s]
Best score: 30.5153: : 51iter [00:06, 11.25iter/s]
Best score: 30.5153: : 51iter [00:06, 11.25iter/s]
Best score: 30.5153: : 52iter [00:06, 11.25iter/s]
Best score: 30.5153: : 53iter [00:06, 11.26iter/s]
Best score: 30.5153: : 53iter [00:06, 11.26iter/s]
Best score: 30.5153: : 54iter [00:06, 11.26iter/s]
Best score: 30.5153: : 55iter [00:06, 11.33iter/s]
Best score: 30.5153: : 55iter [00:06, 11.33iter/s]
Best score: 30.5153: : 56iter [00:06, 11.33iter/s]
Best score: 30.5153: : 57iter [00:06, 11.41iter/s]
Best score: 30.5153: : 57iter [00:07, 11.41iter/s]
Best score: 30.5153: : 58iter [00:07, 11.41iter/s]
Best score: 30.5153: : 59iter [00:07, 11.42iter/s]
Best score: 30.5153: : 59iter [00:07, 11.42iter/s]
Best score: 30.5153: : 60iter [00:07, 11.42iter/s]
Best score: 30.5153: : 61iter [00:07, 11.35iter/s]
Best score: 30.5153: : 61iter [00:07, 11.35iter/s]
Best score: 30.5153: : 62iter [00:07, 11.35iter/s]
Best score: 30.5153: : 63iter [00:07, 11.44iter/s]
Best score: 30.5153: : 63iter [00:07, 11.44iter/s]
Best score: 30.5153: : 64iter [00:07, 11.44iter/s]
Best score: 30.5153: : 65iter [00:07, 11.49iter/s]
Best score: 30.5153: : 65iter [00:07, 11.49iter/s]
Best score: 30.5153: : 66iter [00:07, 11.49iter/s]
Best score: 30.5153: : 67iter [00:07, 11.52iter/s]
Best score: 30.5153: : 67iter [00:07, 11.52iter/s]
Best score: 30.5153: : 68iter [00:08, 11.52iter/s]
Best score: 30.5153: : 69iter [00:08, 11.49iter/s]
Best score: 10.8347: : 69iter [00:08, 11.49iter/s]
Best score: 10.8347: : 70iter [00:08, 11.49iter/s]
Best score: 10.8347: : 71iter [00:08, 11.26iter/s]
Best score: 10.8347: : 71iter [00:08, 11.26iter/s]
Best score: 10.8347: : 72iter [00:08, 11.26iter/s]
Best score: 10.8347: : 73iter [00:08, 11.32iter/s]
Best score: 10.8347: : 73iter [00:08, 11.32iter/s]
Best score: 10.8347: : 74iter [00:08, 11.32iter/s]
Best score: 10.8347: : 75iter [00:08, 11.40iter/s]
Best score: 10.8347: : 75iter [00:08, 11.40iter/s]
Best score: 10.8347: : 76iter [00:08, 11.40iter/s]
Best score: 10.8347: : 77iter [00:08, 11.41iter/s]
Best score: 10.8347: : 77iter [00:08, 11.41iter/s]
Best score: 10.8347: : 78iter [00:08, 11.41iter/s]
Best score: 10.8347: : 79iter [00:08, 11.50iter/s]
Best score: 10.8347: : 79iter [00:09, 11.50iter/s]
Best score: 10.8347: : 80iter [00:09, 11.50iter/s]
Best score: 10.8347: : 81iter [00:09, 11.33iter/s]
Best score: 10.8347: : 81iter [00:09, 11.33iter/s]
Best score: 10.8347: : 82iter [00:09, 11.33iter/s]
Best score: 10.8347: : 83iter [00:09, 11.40iter/s]
Best score: 10.8347: : 83iter [00:09, 11.40iter/s]
Best score: 10.8347: : 84iter [00:09, 11.40iter/s]
Best score: 10.8347: : 85iter [00:09, 11.47iter/s]
Best score: 10.8347: : 85iter [00:09, 11.47iter/s]
Best score: 10.8347: : 86iter [00:09, 11.47iter/s]
Best score: 10.8347: : 87iter [00:09, 11.49iter/s]
Best score: 10.8347: : 87iter [00:09, 11.49iter/s]
Best score: 10.8347: : 88iter [00:09, 11.49iter/s]
Best score: 10.8347: : 89iter [00:09, 11.54iter/s]
Best score: 8.4079: : 89iter [00:09, 11.54iter/s] 
Best score: 8.4079: : 90iter [00:09, 11.54iter/s]
Best score: 8.4079: : 91iter [00:09, 11.34iter/s]
Best score: 8.4079: : 91iter [00:10, 11.34iter/s]
Best score: 8.4079: : 92iter [00:10, 11.34iter/s]
Best score: 8.4079: : 93iter [00:10, 11.33iter/s]
Best score: 8.4079: : 93iter [00:10, 11.33iter/s]
Best score: 8.4079: : 94iter [00:10, 11.33iter/s]
Best score: 8.4079: : 95iter [00:10, 11.36iter/s]
Best score: 8.4079: : 95iter [00:10, 11.36iter/s]
Best score: 8.4079: : 96iter [00:10, 11.36iter/s]
Best score: 8.4079: : 97iter [00:10, 11.42iter/s]
Best score: 8.4079: : 97iter [00:10, 11.42iter/s]
Best score: 8.4079: : 98iter [00:10, 11.42iter/s]
Best score: 8.4079: : 99iter [00:10, 11.50iter/s]
[ITER 100] Best: 8.4079
[PARAMS] Current best parameters:
  fx: 509.3978
  fy: 508.3942
  px: 912.3540
  py: 928.2140
  k1: 0.02218406
  k2: -0.02055052
  k3: 0.02317389
  k4: -0.00714151
  p1: 0.01213651
  p2: 0.00101052
  p3: 0.01283148
  p4: -0.00569622
  s1: 0.0178
  s2: -0.0180
  s3: -0.0125
  s4: -0.0054
  tilt_x: 0.0062
  tilt_y: -0.0344
  scale: 2.9781
  rotation: -0.6108

Best score: 8.4079: : 99iter [00:10, 11.50iter/s]
Best score: 8.4079: : 100iter [00:10, 11.50iter/s]
Best score: 8.4079: : 101iter [00:10,  9.83iter/s]
Best score: 8.4079: : 101iter [00:11,  9.83iter/s]
Best score: 8.4079: : 102iter [00:11,  9.83iter/s]
Best score: 8.4079: : 103iter [00:11, 10.21iter/s]
Best score: 8.4079: : 103iter [00:11, 10.21iter/s]
Best score: 8.4079: : 104iter [00:11, 10.21iter/s]
Best score: 8.4079: : 105iter [00:11, 10.50iter/s]
Best score: 8.4079: : 105iter [00:11, 10.50iter/s]
Best score: 8.4079: : 106iter [00:11, 10.50iter/s]
Best score: 8.4079: : 107iter [00:11, 10.75iter/s]
Best score: 8.4079: : 107iter [00:11, 10.75iter/s]
Best score: 8.4079: : 108iter [00:11, 10.75iter/s]
Best score: 8.4079: : 109iter [00:11, 10.92iter/s]
Best score: 8.4079: : 109iter [00:11, 10.92iter/s]
Best score: 8.4079: : 110iter [00:11, 10.92iter/s]
Best score: 8.4079: : 111iter [00:11, 10.91iter/s]
Best score: 8.4079: : 111iter [00:11, 10.91iter/s]
Best score: 8.4079: : 112iter [00:12, 10.91iter/s]
Best score: 8.4079: : 113iter [00:12, 11.07iter/s]
Best score: 8.4079: : 113iter [00:12, 11.07iter/s]
Best score: 8.4079: : 114iter [00:12, 11.07iter/s]
Best score: 8.4079: : 115iter [00:12, 11.13iter/s]
Best score: 8.4079: : 115iter [00:12, 11.13iter/s]
Best score: 8.4079: : 116iter [00:12, 11.13iter/s]
Best score: 8.4079: : 117iter [00:12, 11.19iter/s]
Best score: 8.4079: : 117iter [00:12, 11.19iter/s]
Best score: 8.4079: : 118iter [00:12, 11.19iter/s]
Best score: 8.4079: : 119iter [00:12, 11.26iter/s]
Best score: 8.4079: : 119iter [00:12, 11.26iter/s]
Best score: 8.4079: : 120iter [00:12, 11.26iter/s]
Best score: 8.4079: : 121iter [00:12, 11.10iter/s]
Best score: 8.4079: : 121iter [00:12, 11.10iter/s]
Best score: 8.4079: : 122iter [00:12, 11.10iter/s]
Best score: 8.4079: : 123iter [00:12, 11.18iter/s]
Best score: 8.4079: : 123iter [00:12, 11.18iter/s]
Best score: 8.4079: : 124iter [00:13, 11.18iter/s]
Best score: 8.4079: : 125iter [00:13, 11.23iter/s]
Best score: 8.4079: : 125iter [00:13, 11.23iter/s]
Best score: 8.4079: : 126iter [00:13, 11.23iter/s]
Best score: 8.4079: : 127iter [00:13, 11.30iter/s]
Best score: 8.4079: : 127iter [00:13, 11.30iter/s]
Best score: 8.4079: : 128iter [00:13, 11.30iter/s]
Best score: 8.4079: : 129iter [00:13, 11.30iter/s]
Best score: 8.4079: : 129iter [00:13, 11.30iter/s]
Best score: 8.4079: : 130iter [00:13, 11.30iter/s]
Best score: 8.4079: : 131iter [00:13, 11.16iter/s]
Best score: 8.4079: : 131iter [00:13, 11.16iter/s]
Best score: 8.4079: : 132iter [00:13, 11.16iter/s]
Best score: 8.4079: : 133iter [00:13, 11.28iter/s]
Best score: 8.4079: : 133iter [00:13, 11.28iter/s]
Best score: 8.4079: : 134iter [00:13, 11.28iter/s]
Best score: 8.4079: : 135iter [00:13, 11.32iter/s]
Best score: 8.4079: : 135iter [00:14, 11.32iter/s]
Best score: 8.4079: : 136iter [00:14, 11.32iter/s]
Best score: 8.4079: : 137iter [00:14, 11.30iter/s]
Best score: 8.4079: : 137iter [00:14, 11.30iter/s]
Best score: 8.4079: : 138iter [00:14, 11.30iter/s]
Best score: 8.4079: : 139iter [00:14,  8.16iter/s]
Best score: 8.4079: : 139iter [00:14,  8.16iter/s]
Best score: 8.4079: : 140iter [00:14,  8.16iter/s]
Best score: 8.4079: : 141iter [00:14,  8.78iter/s]
Best score: 8.4079: : 141iter [00:14,  8.78iter/s]
Best score: 8.4079: : 142iter [00:14,  8.78iter/s]
Best score: 8.4079: : 143iter [00:14,  9.44iter/s]
Best score: 8.4079: : 143iter [00:14,  9.44iter/s]
Best score: 8.4079: : 144iter [00:15,  9.44iter/s]
Best score: 8.4079: : 145iter [00:15,  9.94iter/s]
Best score: 8.4079: : 145iter [00:15,  9.94iter/s]
Best score: 8.4079: : 146iter [00:15,  9.94iter/s]
Best score: 8.4079: : 147iter [00:15, 10.34iter/s]
Best score: 8.4079: : 147iter [00:15, 10.34iter/s]
Best score: 8.4079: : 148iter [00:15, 10.34iter/s]
Best score: 8.4079: : 149iter [00:15, 10.67iter/s]
[ITER 150] Best: 8.4079
[PARAMS] Current best parameters:
  fx: 509.3978
  fy: 508.3942
  px: 912.3540
  py: 928.2140
  k1: 0.02218406
  k2: -0.02055052
  k3: 0.02317389
  k4: -0.00714151
  p1: 0.01213651
  p2: 0.00101052
  p3: 0.01283148
  p4: -0.00569622
  s1: 0.0178
  s2: -0.0180
  s3: -0.0125
  s4: -0.0054
  tilt_x: 0.0062
  tilt_y: -0.0344
  scale: 2.9781
  rotation: -0.6108

Best score: 8.4079: : 149iter [00:15, 10.67iter/s]
Best score: 8.4079: : 150iter [00:15, 10.67iter/s]
Best score: 8.4079: : 151iter [00:15,  7.19iter/s]
Best score: 8.4079: : 151iter [00:16,  7.19iter/s]
Best score: 8.4079: : 152iter [00:16,  7.19iter/s]
Best score: 8.4079: : 153iter [00:16,  8.10iter/s]
Best score: 8.4079: : 153iter [00:16,  8.10iter/s]
Best score: 8.4079: : 154iter [00:16,  8.10iter/s]
Best score: 8.4079: : 155iter [00:16,  8.90iter/s]
Best score: 8.4079: : 155iter [00:16,  8.90iter/s]
Best score: 8.4079: : 156iter [00:16,  8.90iter/s]
Best score: 8.4079: : 157iter [00:16,  9.54iter/s]
Best score: 8.4079: : 157iter [00:16,  9.54iter/s]
Best score: 8.4079: : 158iter [00:16,  9.54iter/s]
Best score: 8.4079: : 159iter [00:16, 10.07iter/s]
Best score: 8.4079: : 159iter [00:16, 10.07iter/s]
Best score: 8.4079: : 160iter [00:16, 10.07iter/s]
Best score: 8.4079: : 161iter [00:16, 10.32iter/s]
Best score: 8.4079: : 161iter [00:16, 10.32iter/s]
Best score: 8.4079: : 162iter [00:16, 10.32iter/s]
Best score: 8.4079: : 163iter [00:16, 10.61iter/s]
Best score: 8.4079: : 163iter [00:17, 10.61iter/s]
Best score: 8.4079: : 164iter [00:17, 10.61iter/s]
Best score: 8.4079: : 165iter [00:17, 10.87iter/s]
Best score: 8.4079: : 165iter [00:17, 10.87iter/s]
Best score: 8.4079: : 166iter [00:17, 10.87iter/s]
Best score: 8.4079: : 167iter [00:17, 11.07iter/s]
Best score: 8.4079: : 167iter [00:17, 11.07iter/s]
Best score: 8.4079: : 168iter [00:17, 11.07iter/s]
Best score: 8.4079: : 169iter [00:17, 11.30iter/s]
Best score: 8.4079: : 169iter [00:17, 11.30iter/s]
Best score: 8.4079: : 170iter [00:17, 11.30iter/s]
Best score: 8.4079: : 171iter [00:17, 11.20iter/s]
Best score: 8.4079: : 171iter [00:17, 11.20iter/s]
Best score: 8.4079: : 172iter [00:17, 11.20iter/s]
Best score: 8.4079: : 173iter [00:17, 11.32iter/s]
Best score: 8.4079: : 173iter [00:17, 11.32iter/s]
Best score: 8.4079: : 174iter [00:18, 11.32iter/s]
Best score: 8.4079: : 175iter [00:18, 11.42iter/s]
Best score: 8.4079: : 175iter [00:18, 11.42iter/s]
Best score: 8.4079: : 176iter [00:18, 11.42iter/s]
Best score: 8.4079: : 177iter [00:18, 11.50iter/s]
Best score: 8.4079: : 177iter [00:18, 11.50iter/s]
Best score: 8.4079: : 178iter [00:18, 11.50iter/s]
Best score: 8.4079: : 179iter [00:18, 11.55iter/s]
Best score: 8.4079: : 179iter [00:18, 11.55iter/s]
Best score: 8.4079: : 180iter [00:18, 11.55iter/s]
Best score: 8.4079: : 181iter [00:18, 11.36iter/s]
Best score: 8.4079: : 181iter [00:18, 11.36iter/s]
Best score: 8.4079: : 182iter [00:18, 11.36iter/s]
Best score: 8.4079: : 183iter [00:18, 11.42iter/s]
Best score: 8.4079: : 183iter [00:18, 11.42iter/s]
Best score: 8.4079: : 184iter [00:18, 11.42iter/s]
Best score: 8.4079: : 185iter [00:18, 11.45iter/s]
Best score: 8.4079: : 185iter [00:18, 11.45iter/s]
Best score: 8.4079: : 186iter [00:19, 11.45iter/s]
Best score: 8.4079: : 187iter [00:19, 11.52iter/s]
Best score: 8.4079: : 187iter [00:19, 11.52iter/s]
Best score: 8.4079: : 188iter [00:19, 11.52iter/s]
Best score: 8.4079: : 189iter [00:19,  8.86iter/s]
Best score: 8.4079: : 189iter [00:19,  8.86iter/s]
Best score: 8.4079: : 190iter [00:19,  8.86iter/s]
Best score: 8.4079: : 191iter [00:19,  9.38iter/s]
Best score: 8.4079: : 191iter [00:19,  9.38iter/s]
Best score: 8.4079: : 192iter [00:19,  9.38iter/s]
Best score: 8.4079: : 193iter [00:19,  9.93iter/s]
Best score: 8.4079: : 193iter [00:19,  9.93iter/s]
Best score: 8.4079: : 194iter [00:19,  9.93iter/s]
Best score: 8.4079: : 195iter [00:19, 10.36iter/s]
Best score: 8.4079: : 195iter [00:20, 10.36iter/s]
Best score: 8.4079: : 196iter [00:20, 10.36iter/s]
Best score: 8.4079: : 197iter [00:20, 10.72iter/s]
Best score: 8.4079: : 197iter [00:20, 10.72iter/s]
Best score: 8.4079: : 198iter [00:20, 10.72iter/s]
Best score: 8.4079: : 199iter [00:20, 10.99iter/s]
[ITER 200] Best: 8.4079
[PARAMS] Current best parameters:
  fx: 509.3978
  fy: 508.3942
  px: 912.3540
  py: 928.2140
  k1: 0.02218406
  k2: -0.02055052
  k3: 0.02317389
  k4: -0.00714151
  p1: 0.01213651
  p2: 0.00101052
  p3: 0.01283148
  p4: -0.00569622
  s1: 0.0178
  s2: -0.0180
  s3: -0.0125
  s4: -0.0054
  tilt_x: 0.0062
  tilt_y: -0.0344
  scale: 2.9781
  rotation: -0.6108

Best score: 8.4079: : 199iter [00:20, 10.99iter/s]
Best score: 8.4079: : 200iter [00:20, 10.99iter/s]
Best score: 8.4079: : 201iter [00:20,  7.25iter/s]
Best score: 8.4079: : 201iter [00:20,  7.25iter/s]
Best score: 8.4079: : 202iter [00:20,  7.25iter/s]
Best score: 8.4079: : 203iter [00:20,  8.17iter/s]
Best score: 8.4079: : 203iter [00:21,  8.17iter/s]
Best score: 8.4079: : 204iter [00:21,  8.17iter/s]
Best score: 8.4079: : 205iter [00:21,  8.95iter/s]
Best score: 8.4079: : 205iter [00:21,  8.95iter/s]
Best score: 8.4079: : 206iter [00:21,  8.95iter/s]
Best score: 8.4079: : 207iter [00:21,  9.60iter/s]
Best score: 8.4079: : 207iter [00:21,  9.60iter/s]
Best score: 8.4079: : 208iter [00:21,  9.60iter/s]
Best score: 8.4079: : 209iter [00:21, 10.16iter/s]
Best score: 8.4079: : 209iter [00:21, 10.16iter/s]
Best score: 8.4079: : 210iter [00:21, 10.16iter/s]
Best score: 8.4079: : 211iter [00:21, 10.39iter/s]
Best score: 8.4079: : 211iter [00:21, 10.39iter/s]
Best score: 8.4079: : 212iter [00:21, 10.39iter/s]
Best score: 8.4079: : 213iter [00:21, 10.72iter/s]
Best score: 8.4079: : 213iter [00:21, 10.72iter/s]
Best score: 8.4079: : 214iter [00:21, 10.72iter/s]
Best score: 8.4079: : 215iter [00:21, 11.00iter/s]
Best score: 8.4079: : 215iter [00:22, 11.00iter/s]
Best score: 8.4079: : 216iter [00:22, 11.00iter/s]
Best score: 8.4079: : 217iter [00:22, 11.19iter/s]
Best score: 8.4079: : 217iter [00:22, 11.19iter/s]
Best score: 8.4079: : 218iter [00:22, 11.19iter/s]
Best score: 8.4079: : 219iter [00:22, 11.32iter/s]
Best score: 7.8794: : 219iter [00:22, 11.32iter/s]
Best score: 7.8794: : 220iter [00:22, 11.32iter/s]
Best score: 7.8794: : 221iter [00:22, 11.25iter/s]
Best score: 7.8794: : 221iter [00:22, 11.25iter/s]
Best score: 7.8794: : 222iter [00:22, 11.25iter/s]
Best score: 7.8794: : 223iter [00:22, 11.37iter/s]
Best score: 7.8794: : 223iter [00:22, 11.37iter/s]
Best score: 7.8794: : 224iter [00:22, 11.37iter/s]
Best score: 7.8794: : 225iter [00:22, 11.44iter/s]
Best score: 7.8794: : 225iter [00:22, 11.44iter/s]
Best score: 7.8794: : 226iter [00:23, 11.44iter/s]
Best score: 7.8794: : 227iter [00:23, 11.51iter/s]
Best score: 7.8794: : 227iter [00:23, 11.51iter/s]
Best score: 7.8794: : 228iter [00:23, 11.51iter/s]
Best score: 7.8794: : 229iter [00:23, 11.59iter/s]
Best score: 7.8794: : 229iter [00:23, 11.59iter/s]
Best score: 7.8794: : 230iter [00:23, 11.59iter/s]
Best score: 7.8794: : 231iter [00:23, 11.43iter/s]
Best score: 7.8794: : 231iter [00:23, 11.43iter/s]
Best score: 7.8794: : 232iter [00:23, 11.43iter/s]
Best score: 7.8794: : 233iter [00:23, 11.52iter/s]
Best score: 7.8794: : 233iter [00:23, 11.52iter/s]
Best score: 7.8794: : 234iter [00:23, 11.52iter/s]
Best score: 7.8794: : 235iter [00:23, 11.58iter/s]
Best score: 7.8794: : 235iter [00:23, 11.58iter/s]
Best score: 7.8794: : 236iter [00:23, 11.58iter/s]
Best score: 7.8794: : 237iter [00:23, 11.60iter/s]
Best score: 7.8794: : 237iter [00:23, 11.60iter/s]
Best score: 7.8794: : 238iter [00:24, 11.60iter/s]
Best score: 7.8794: : 239iter [00:24, 11.63iter/s]
Best score: 6.0786: : 239iter [00:24, 11.63iter/s]
Best score: 6.0786: : 240iter [00:24, 11.63iter/s]
Best score: 6.0786: : 241iter [00:24, 11.42iter/s]
Best score: 6.0786: : 241iter [00:24, 11.42iter/s]
Best score: 6.0786: : 242iter [00:24, 11.42iter/s]
Best score: 6.0786: : 243iter [00:24, 11.46iter/s]
Best score: 6.0786: : 243iter [00:24, 11.46iter/s]
Best score: 6.0786: : 244iter [00:24, 11.46iter/s]
Best score: 6.0786: : 245iter [00:24, 11.54iter/s]
Best score: 6.0786: : 245iter [00:24, 11.54iter/s]
Best score: 6.0786: : 246iter [00:24, 11.54iter/s]
Best score: 6.0786: : 247iter [00:24, 11.60iter/s]
Best score: 6.0786: : 247iter [00:24, 11.60iter/s]
Best score: 6.0786: : 248iter [00:24, 11.60iter/s]
Best score: 6.0786: : 249iter [00:24, 11.62iter/s]
[ITER 250] Best: 3.8601
[PARAMS] Current best parameters:
  fx: 497.2703
  fy: 499.1933
  px: 906.8816
  py: 931.2059
  k1: 0.02206185
  k2: -0.04023842
  k3: 0.05502342
  k4: -0.01799474
  p1: 0.00587010
  p2: -0.01463044
  p3: 0.02159637
  p4: 0.00025781
  s1: 0.0167
  s2: -0.0196
  s3: -0.0111
  s4: -0.0059
  tilt_x: 0.0305
  tilt_y: -0.0244
  scale: 3.0705
  rotation: -0.7051

Best score: 3.8601: : 249iter [00:25, 11.62iter/s]
Best score: 3.8601: : 250iter [00:25, 11.62iter/s]
Best score: 3.8601: : 251iter [00:25,  7.48iter/s]
Best score: 3.8601: : 251iter [00:25,  7.48iter/s]
Best score: 3.8601: : 252iter [00:25,  7.48iter/s]
Best score: 3.8601: : 253iter [00:25,  8.39iter/s]
Best score: 3.8601: : 253iter [00:25,  8.39iter/s]
Best score: 3.8601: : 254iter [00:25,  8.39iter/s]
Best score: 3.8601: : 255iter [00:25,  9.16iter/s]
Best score: 3.8601: : 255iter [00:25,  9.16iter/s]
Best score: 3.8601: : 256iter [00:25,  9.16iter/s]
Best score: 3.8601: : 257iter [00:25,  9.79iter/s]
Best score: 3.8601: : 257iter [00:26,  9.79iter/s]
Best score: 3.8601: : 258iter [00:26,  9.79iter/s]
Best score: 3.8601: : 259iter [00:26, 10.27iter/s]
Best score: 3.8601: : 259iter [00:26, 10.27iter/s]
Best score: 3.8601: : 260iter [00:26, 10.27iter/s]
Best score: 3.8601: : 261iter [00:26, 10.51iter/s]
Best score: 3.8601: : 261iter [00:26, 10.51iter/s]
Best score: 3.8601: : 262iter [00:26, 10.51iter/s]
Best score: 3.8601: : 263iter [00:26, 10.83iter/s]
Best score: 3.8601: : 263iter [00:26, 10.83iter/s]
Best score: 3.8601: : 264iter [00:26, 10.83iter/s]
Best score: 3.8601: : 265iter [00:26, 11.09iter/s]
Best score: 3.8601: : 265iter [00:26, 11.09iter/s]
Best score: 3.8601: : 266iter [00:26, 11.09iter/s]
Best score: 3.8601: : 267iter [00:26, 11.27iter/s]
Best score: 3.8601: : 267iter [00:26, 11.27iter/s]
Best score: 3.8601: : 268iter [00:26, 11.27iter/s]
Best score: 3.8601: : 269iter [00:26, 11.39iter/s]
Best score: 3.1454: : 269iter [00:27, 11.39iter/s]
Best score: 3.1454: : 270iter [00:27, 11.39iter/s]
Best score: 3.1454: : 271iter [00:27, 11.31iter/s]
Best score: 3.1454: : 271iter [00:27, 11.31iter/s]
Best score: 3.1454: : 272iter [00:27, 11.31iter/s]
Best score: 3.1454: : 273iter [00:27, 11.43iter/s]
Best score: 3.1454: : 273iter [00:27, 11.43iter/s]
Best score: 3.1454: : 274iter [00:27, 11.43iter/s]
Best score: 3.1454: : 275iter [00:27, 11.45iter/s]
Best score: 3.1454: : 275iter [00:27, 11.45iter/s]
Best score: 3.1454: : 276iter [00:27, 11.45iter/s]
Best score: 3.1454: : 277iter [00:27, 11.53iter/s]
Best score: 3.1454: : 277iter [00:27, 11.53iter/s]
Best score: 3.1454: : 278iter [00:27, 11.53iter/s]
Best score: 3.1454: : 279iter [00:27, 11.60iter/s]
Best score: 1.8992: : 279iter [00:27, 11.60iter/s]
Best score: 1.8992: : 280iter [00:28, 11.60iter/s]
Best score: 1.8992: : 281iter [00:28, 11.44iter/s]
Best score: 1.8992: : 281iter [00:28, 11.44iter/s]
Best score: 1.8992: : 282iter [00:28, 11.44iter/s]
Best score: 1.8992: : 283iter [00:28, 11.53iter/s]
Best score: 1.8992: : 283iter [00:28, 11.53iter/s]
Best score: 1.8992: : 284iter [00:28, 11.53iter/s]
Best score: 1.8992: : 285iter [00:28, 11.60iter/s]
Best score: 1.8992: : 285iter [00:28, 11.60iter/s]
Best score: 1.8992: : 286iter [00:28, 11.60iter/s]
Best score: 1.8992: : 287iter [00:28, 11.63iter/s]
Best score: 1.8992: : 287iter [00:28, 11.63iter/s]
Best score: 1.8992: : 288iter [00:28, 11.63iter/s]
Best score: 1.8992: : 289iter [00:28, 11.67iter/s]
Best score: 1.8197: : 289iter [00:28, 11.67iter/s]
Best score: 1.8197: : 290iter [00:28, 11.67iter/s]
Best score: 1.8197: : 291iter [00:28, 11.49iter/s]
Best score: 1.8197: : 291iter [00:28, 11.49iter/s]
Best score: 1.8197: : 292iter [00:29, 11.49iter/s]
Best score: 1.8197: : 293iter [00:29, 11.57iter/s]
Best score: 1.8197: : 293iter [00:29, 11.57iter/s]
Best score: 1.8197: : 294iter [00:29, 11.57iter/s]
Best score: 1.8197: : 295iter [00:29, 11.62iter/s]
Best score: 1.8197: : 295iter [00:29, 11.62iter/s]
Best score: 1.8197: : 296iter [00:29, 11.62iter/s]
Best score: 1.8197: : 297iter [00:29, 11.60iter/s]
Best score: 1.8197: : 297iter [00:29, 11.60iter/s]
Best score: 1.8197: : 298iter [00:29, 11.60iter/s]
Best score: 1.8197: : 299iter [00:29, 11.64iter/s]
[ITER 300] Best: 0.9631
[PARAMS] Current best parameters:
  fx: 517.4409
  fy: 516.7600
  px: 914.3938
  py: 932.1313
  k1: 0.04085972
  k2: -0.03152248
  k3: 0.01213093
  k4: -0.00215363
  p1: 0.00979474
  p2: -0.00177119
  p3: 0.01185309
  p4: 0.00453164
  s1: 0.0052
  s2: -0.0151
  s3: -0.0261
  s4: 0.0033
  tilt_x: 0.0260
  tilt_y: -0.0371
  scale: 2.9377
  rotation: -0.5717

Best score: 0.9631: : 299iter [00:29, 11.64iter/s]
Best score: 0.9631: : 300iter [00:30, 11.64iter/s]
Best score: 0.9631: : 301iter [00:30,  7.49iter/s]
Best score: 0.9631: : 301iter [00:30,  7.49iter/s]
Best score: 0.9631: : 302iter [00:30,  7.49iter/s]
Best score: 0.9631: : 303iter [00:30,  8.40iter/s]
Best score: 0.9631: : 303iter [00:30,  8.40iter/s]
Best score: 0.9631: : 304iter [00:30,  8.40iter/s]
Best score: 0.9631: : 305iter [00:30,  9.19iter/s]
Best score: 0.9631: : 305iter [00:30,  9.19iter/s]
Best score: 0.9631: : 306iter [00:30,  9.19iter/s]
Best score: 0.9631: : 307iter [00:30,  9.84iter/s]
Best score: 0.9631: : 307iter [00:30,  9.84iter/s]
Best score: 0.9631: : 308iter [00:30,  9.84iter/s]
Best score: 0.9631: : 309iter [00:30, 10.35iter/s]
Best score: 0.9631: : 309iter [00:30, 10.35iter/s]
Best score: 0.9631: : 310iter [00:30, 10.35iter/s]
Best score: 0.9631: : 311iter [00:30, 10.55iter/s]
Best score: 0.9631: : 311iter [00:30, 10.55iter/s]
Best score: 0.9631: : 312iter [00:31, 10.55iter/s]
Best score: 0.9631: : 313iter [00:31, 10.83iter/s]
Best score: 0.9631: : 313iter [00:31, 10.83iter/s]
Best score: 0.9631: : 314iter [00:31, 10.83iter/s]
Best score: 0.9631: : 315iter [00:31, 11.10iter/s]
Best score: 0.9631: : 315iter [00:31, 11.10iter/s]
Best score: 0.9631: : 316iter [00:31, 11.10iter/s]
Best score: 0.9631: : 317iter [00:31, 11.29iter/s]
Best score: 0.9631: : 317iter [00:31, 11.29iter/s]
Best score: 0.9631: : 318iter [00:31, 11.29iter/s]
Best score: 0.9631: : 319iter [00:31, 11.44iter/s]
Best score: 0.9631: : 319iter [00:31, 11.44iter/s]
Best score: 0.9631: : 320iter [00:31, 11.44iter/s]
Best score: 0.9631: : 321iter [00:31, 11.30iter/s]
Best score: 0.9631: : 321iter [00:31, 11.30iter/s]
Best score: 0.9631: : 322iter [00:31, 11.30iter/s]
Best score: 0.9631: : 323iter [00:31, 11.44iter/s]
Best score: 0.9631: : 323iter [00:32, 11.44iter/s]
Best score: 0.9631: : 324iter [00:32, 11.44iter/s]
Best score: 0.9631: : 325iter [00:32, 11.54iter/s]
Best score: 0.9631: : 325iter [00:32, 11.54iter/s]
Best score: 0.9631: : 326iter [00:32, 11.54iter/s]
Best score: 0.9631: : 327iter [00:32, 11.57iter/s]
Best score: 0.9631: : 327iter [00:32, 11.57iter/s]
Best score: 0.9631: : 328iter [00:32, 11.57iter/s]
Best score: 0.9631: : 329iter [00:32, 11.59iter/s]
Best score: 0.9631: : 329iter [00:32, 11.59iter/s]
Best score: 0.9631: : 330iter [00:32, 11.59iter/s]
Best score: 0.9631: : 331iter [00:32, 11.45iter/s]
Best score: 0.9631: : 331iter [00:32, 11.45iter/s]
Best score: 0.9631: : 332iter [00:32, 11.45iter/s]
Best score: 0.9631: : 333iter [00:32, 11.54iter/s]
Best score: 0.9631: : 333iter [00:32, 11.54iter/s]
Best score: 0.9631: : 334iter [00:32, 11.54iter/s]
Best score: 0.9631: : 335iter [00:32, 11.60iter/s]
Best score: 0.9631: : 335iter [00:33, 11.60iter/s]
Best score: 0.9631: : 336iter [00:33, 11.60iter/s]
Best score: 0.9631: : 337iter [00:33, 11.66iter/s]
Best score: 0.9631: : 337iter [00:33, 11.66iter/s]
Best score: 0.9631: : 338iter [00:33, 11.66iter/s]
Best score: 0.9631: : 339iter [00:33, 11.70iter/s]
Best score: 0.8728: : 339iter [00:33, 11.70iter/s]
Best score: 0.8728: : 340iter [00:33, 11.70iter/s]
Best score: 0.8728: : 341iter [00:33, 11.53iter/s]
Best score: 0.8728: : 341iter [00:33, 11.53iter/s]
Best score: 0.8728: : 342iter [00:33, 11.53iter/s]
Best score: 0.8728: : 343iter [00:33, 11.60iter/s]
Best score: 0.8728: : 343iter [00:33, 11.60iter/s]
Best score: 0.8728: : 344iter [00:33, 11.60iter/s]
Best score: 0.8728: : 345iter [00:33, 11.67iter/s]
Best score: 0.8728: : 345iter [00:33, 11.67iter/s]
Best score: 0.8728: : 346iter [00:33, 11.67iter/s]
Best score: 0.8728: : 347iter [00:33, 11.72iter/s]
Best score: 0.8728: : 347iter [00:34, 11.72iter/s]
Best score: 0.8728: : 348iter [00:34, 11.72iter/s]
Best score: 0.8728: : 349iter [00:34, 11.71iter/s]
[ITER 350] Best: 0.6234
[PARAMS] Current best parameters:
  fx: 522.4795
  fy: 521.7950
  px: 911.7210
  py: 930.0300
  k1: 0.02467547
  k2: -0.03457141
  k3: 0.02334237
  k4: -0.00574650
  p1: 0.01069435
  p2: -0.00764715
  p3: 0.01164846
  p4: 0.00357364
  s1: 0.0060
  s2: -0.0126
  s3: -0.0179
  s4: -0.0060
  tilt_x: 0.0182
  tilt_y: -0.0350
  scale: 2.9832
  rotation: -0.5235

Best score: 0.6234: : 349iter [00:34, 11.71iter/s]
Best score: 0.6234: : 350iter [00:34, 11.71iter/s]
Best score: 0.6234: : 351iter [00:34,  7.48iter/s]
Best score: 0.6234: : 351iter [00:34,  7.48iter/s]
Best score: 0.6234: : 352iter [00:34,  7.48iter/s]
Best score: 0.6234: : 353iter [00:34,  8.40iter/s]
Best score: 0.6234: : 353iter [00:34,  8.40iter/s]
Best score: 0.6234: : 354iter [00:35,  8.40iter/s]
Best score: 0.6234: : 355iter [00:35,  9.19iter/s]
Best score: 0.6234: : 355iter [00:35,  9.19iter/s]
Best score: 0.6234: : 356iter [00:35,  9.19iter/s]
Best score: 0.6234: : 357iter [00:35,  9.84iter/s]
Best score: 0.6234: : 357iter [00:35,  9.84iter/s]
Best score: 0.6234: : 358iter [00:35,  9.84iter/s]
Best score: 0.6234: : 359iter [00:35, 10.36iter/s]
Best score: 0.5428: : 359iter [00:35, 10.36iter/s]
Best score: 0.5428: : 360iter [00:35, 10.36iter/s]
Best score: 0.5428: : 361iter [00:35, 10.57iter/s]
Best score: 0.5428: : 361iter [00:35, 10.57iter/s]
Best score: 0.5428: : 362iter [00:35, 10.57iter/s]
Best score: 0.5428: : 363iter [00:35, 10.92iter/s]
Best score: 0.5428: : 363iter [00:35, 10.92iter/s]
Best score: 0.5428: : 364iter [00:35, 10.92iter/s]
Best score: 0.5428: : 365iter [00:35, 11.16iter/s]
Best score: 0.5428: : 365iter [00:35, 11.16iter/s]
Best score: 0.5428: : 366iter [00:36, 11.16iter/s]
Best score: 0.5428: : 367iter [00:36, 11.26iter/s]
Best score: 0.5428: : 367iter [00:36, 11.26iter/s]
Best score: 0.5428: : 368iter [00:36, 11.26iter/s]
Best score: 0.5428: : 369iter [00:36, 11.41iter/s]
Best score: 0.5410: : 369iter [00:36, 11.41iter/s]
Best score: 0.5410: : 370iter [00:36, 11.41iter/s]
Best score: 0.5410: : 371iter [00:36, 11.32iter/s]
Best score: 0.5410: : 371iter [00:36, 11.32iter/s]
Best score: 0.5410: : 372iter [00:36, 11.32iter/s]
Best score: 0.5410: : 373iter [00:36, 11.46iter/s]
Best score: 0.5410: : 373iter [00:36, 11.46iter/s]
Best score: 0.5410: : 374iter [00:36, 11.46iter/s]
Best score: 0.5410: : 375iter [00:36, 11.53iter/s]
Best score: 0.5410: : 375iter [00:36, 11.53iter/s]
Best score: 0.5410: : 376iter [00:36, 11.53iter/s]
Best score: 0.5410: : 377iter [00:36, 11.62iter/s]
Best score: 0.5410: : 377iter [00:36, 11.62iter/s]
Best score: 0.5410: : 378iter [00:37, 11.62iter/s]
Best score: 0.5410: : 379iter [00:37, 11.67iter/s]
Best score: 0.4855: : 379iter [00:37, 11.67iter/s]
Best score: 0.4855: : 380iter [00:37, 11.67iter/s]
Best score: 0.4855: : 381iter [00:37, 11.50iter/s]
Best score: 0.4855: : 381iter [00:37, 11.50iter/s]
Best score: 0.4855: : 382iter [00:37, 11.50iter/s]
Best score: 0.4855: : 383iter [00:37, 11.57iter/s]
Best score: 0.4855: : 383iter [00:37, 11.57iter/s]
Best score: 0.4855: : 384iter [00:37, 11.57iter/s]
Best score: 0.4855: : 385iter [00:37, 11.61iter/s]
Best score: 0.4855: : 385iter [00:37, 11.61iter/s]
Best score: 0.4855: : 386iter [00:37, 11.61iter/s]
Best score: 0.4855: : 387iter [00:37, 11.69iter/s]
Best score: 0.4855: : 387iter [00:37, 11.69iter/s]
Best score: 0.4855: : 388iter [00:37, 11.69iter/s]
Best score: 0.4855: : 389iter [00:37, 11.74iter/s]
Best score: 0.4855: : 389iter [00:38, 11.74iter/s]
Best score: 0.4855: : 390iter [00:38, 11.74iter/s]
Best score: 0.4855: : 391iter [00:38, 11.56iter/s]
Best score: 0.4855: : 391iter [00:38, 11.56iter/s]
Best score: 0.4855: : 392iter [00:38, 11.56iter/s]
Best score: 0.4855: : 393iter [00:38, 11.65iter/s]
Best score: 0.4855: : 393iter [00:38, 11.65iter/s]
Best score: 0.4855: : 394iter [00:38, 11.65iter/s]
Best score: 0.4855: : 395iter [00:38, 11.71iter/s]
Best score: 0.4855: : 395iter [00:38, 11.71iter/s]
Best score: 0.4855: : 396iter [00:38, 11.71iter/s]
Best score: 0.4855: : 397iter [00:38, 11.73iter/s]
Best score: 0.4855: : 397iter [00:38, 11.73iter/s]
Best score: 0.4855: : 398iter [00:38, 11.73iter/s]
Best score: 0.4855: : 399iter [00:38, 11.74iter/s]
[ITER 400] Best: 0.4298
[PARAMS] Current best parameters:
  fx: 523.5272
  fy: 522.4252
  px: 916.0533
  py: 929.5375
  k1: 0.03168636
  k2: -0.02489351
  k3: 0.00671934
  k4: -0.00067303
  p1: 0.01609167
  p2: -0.00391727
  p3: 0.01227241
  p4: 0.00375320
  s1: -0.0050
  s2: -0.0018
  s3: -0.0303
  s4: -0.0027
  tilt_x: 0.0073
  tilt_y: -0.0465
  scale: 2.9468
  rotation: -0.4577

Best score: 0.4298: : 399iter [00:38, 11.74iter/s]
Best score: 0.4298: : 400iter [00:39, 11.74iter/s]
Best score: 0.4298: : 401iter [00:39,  7.51iter/s]
Best score: 0.4298: : 401iter [00:39,  7.51iter/s]
Best score: 0.4298: : 402iter [00:39,  7.51iter/s]
Best score: 0.4298: : 403iter [00:39,  8.42iter/s]
Best score: 0.4298: : 403iter [00:39,  8.42iter/s]
Best score: 0.4298: : 404iter [00:39,  8.42iter/s]
Best score: 0.4298: : 405iter [00:39,  9.21iter/s]
Best score: 0.4298: : 405iter [00:39,  9.21iter/s]
Best score: 0.4298: : 406iter [00:39,  9.21iter/s]
Best score: 0.4298: : 407iter [00:39,  9.83iter/s]
Best score: 0.4298: : 407iter [00:39,  9.83iter/s]
Best score: 0.4298: : 408iter [00:39,  9.83iter/s]
Best score: 0.4298: : 409iter [00:39, 10.34iter/s]
Best score: 0.4298: : 409iter [00:40, 10.34iter/s]
Best score: 0.4298: : 410iter [00:40, 10.34iter/s]
Best score: 0.4298: : 411iter [00:40, 10.55iter/s]
Best score: 0.4298: : 411iter [00:40, 10.55iter/s]
Best score: 0.4298: : 412iter [00:40, 10.55iter/s]
Best score: 0.4298: : 413iter [00:40, 10.87iter/s]
Best score: 0.4298: : 413iter [00:40, 10.87iter/s]
Best score: 0.4298: : 414iter [00:40, 10.87iter/s]
Best score: 0.4298: : 415iter [00:40, 11.14iter/s]
Best score: 0.4298: : 415iter [00:40, 11.14iter/s]
Best score: 0.4298: : 416iter [00:40, 11.14iter/s]
Best score: 0.4298: : 417iter [00:40, 11.33iter/s]
Best score: 0.4298: : 417iter [00:40, 11.33iter/s]
Best score: 0.4298: : 418iter [00:40, 11.33iter/s]
Best score: 0.4298: : 419iter [00:40, 11.44iter/s]
Best score: 0.3940: : 419iter [00:40, 11.44iter/s]
Best score: 0.3940: : 420iter [00:40, 11.44iter/s]
Best score: 0.3940: : 421iter [00:40, 11.33iter/s]
Best score: 0.3940: : 421iter [00:41, 11.33iter/s]
Best score: 0.3940: : 422iter [00:41, 11.33iter/s]
Best score: 0.3940: : 423iter [00:41, 11.40iter/s]
Best score: 0.3940: : 423iter [00:41, 11.40iter/s]
Best score: 0.3940: : 424iter [00:41, 11.40iter/s]
Best score: 0.3940: : 425iter [00:41, 11.47iter/s]
Best score: 0.3940: : 425iter [00:41, 11.47iter/s]
Best score: 0.3940: : 426iter [00:41, 11.47iter/s]
Best score: 0.3940: : 427iter [00:41, 11.56iter/s]
Best score: 0.3940: : 427iter [00:41, 11.56iter/s]
Best score: 0.3940: : 428iter [00:41, 11.56iter/s]
Best score: 0.3940: : 429iter [00:41, 11.62iter/s]
Best score: 0.3721: : 429iter [00:41, 11.62iter/s]
Best score: 0.3721: : 430iter [00:41, 11.62iter/s]
Best score: 0.3721: : 431iter [00:41, 11.41iter/s]
Best score: 0.3721: : 431iter [00:41, 11.41iter/s]
Best score: 0.3721: : 432iter [00:42, 11.41iter/s]
Best score: 0.3721: : 433iter [00:42, 11.52iter/s]
Best score: 0.3721: : 433iter [00:42, 11.52iter/s]
Best score: 0.3721: : 434iter [00:42, 11.52iter/s]
Best score: 0.3721: : 435iter [00:42, 11.58iter/s]
Best score: 0.3721: : 435iter [00:42, 11.58iter/s]
Best score: 0.3721: : 436iter [00:42, 11.58iter/s]
Best score: 0.3721: : 437iter [00:42, 11.63iter/s]
Best score: 0.3721: : 437iter [00:42, 11.63iter/s]
Best score: 0.3721: : 438iter [00:42, 11.63iter/s]
Best score: 0.3721: : 439iter [00:42, 11.59iter/s]
Best score: 0.3494: : 439iter [00:42, 11.59iter/s]
Best score: 0.3494: : 440iter [00:42, 11.59iter/s]
Best score: 0.3494: : 441iter [00:42, 11.38iter/s]
Best score: 0.3494: : 441iter [00:42, 11.38iter/s]
Best score: 0.3494: : 442iter [00:42, 11.38iter/s]
Best score: 0.3494: : 443iter [00:42, 11.50iter/s]
Best score: 0.3494: : 443iter [00:42, 11.50iter/s]
Best score: 0.3494: : 444iter [00:43, 11.50iter/s]
Best score: 0.3494: : 445iter [00:43, 11.52iter/s]
Best score: 0.3494: : 445iter [00:43, 11.52iter/s]
Best score: 0.3494: : 446iter [00:43, 11.52iter/s]
Best score: 0.3494: : 447iter [00:43, 11.58iter/s]
Best score: 0.3494: : 447iter [00:43, 11.58iter/s]
Best score: 0.3494: : 448iter [00:43, 11.58iter/s]
Best score: 0.3494: : 449iter [00:43, 11.57iter/s]
[ITER 450] Best: 0.3494
[PARAMS] Current best parameters:
  fx: 523.8440
  fy: 523.2207
  px: 915.6105
  py: 927.2657
  k1: 0.02898299
  k2: -0.03374841
  k3: 0.01932097
  k4: -0.00463747
  p1: 0.01195269
  p2: -0.00599743
  p3: 0.00672105
  p4: 0.00268800
  s1: 0.0054
  s2: -0.0035
  s3: -0.0223
  s4: 0.0010
  tilt_x: 0.0025
  tilt_y: -0.0499
  scale: 2.9611
  rotation: -0.4824

Best score: 0.3494: : 449iter [00:43, 11.57iter/s]
Best score: 0.3494: : 450iter [00:43, 11.57iter/s]
Best score: 0.3494: : 451iter [00:43,  7.44iter/s]
Best score: 0.3494: : 451iter [00:43,  7.44iter/s]
Best score: 0.3494: : 452iter [00:44,  7.44iter/s]
Best score: 0.3494: : 453iter [00:44,  8.32iter/s]
Best score: 0.3494: : 453iter [00:44,  8.32iter/s]
Best score: 0.3494: : 454iter [00:44,  8.32iter/s]
Best score: 0.3494: : 455iter [00:44,  9.10iter/s]
Best score: 0.3494: : 455iter [00:44,  9.10iter/s]
Best score: 0.3494: : 456iter [00:44,  9.10iter/s]
Best score: 0.3494: : 457iter [00:44,  9.75iter/s]
Best score: 0.3494: : 457iter [00:44,  9.75iter/s]
Best score: 0.3494: : 458iter [00:44,  9.75iter/s]
Best score: 0.3494: : 459iter [00:44, 10.26iter/s]
Best score: 0.3494: : 459iter [00:44, 10.26iter/s]
Best score: 0.3494: : 460iter [00:44, 10.26iter/s]
Best score: 0.3494: : 461iter [00:44, 10.49iter/s]
Best score: 0.3494: : 461iter [00:44, 10.49iter/s]
Best score: 0.3494: : 462iter [00:44, 10.49iter/s]
Best score: 0.3494: : 463iter [00:44, 10.78iter/s]
Best score: 0.3494: : 463iter [00:45, 10.78iter/s]
Best score: 0.3494: : 464iter [00:45, 10.78iter/s]
Best score: 0.3494: : 465iter [00:45, 11.06iter/s]
Best score: 0.3494: : 465iter [00:45, 11.06iter/s]
Best score: 0.3494: : 466iter [00:45, 11.06iter/s]
Best score: 0.3494: : 467iter [00:45, 11.22iter/s]
Best score: 0.3494: : 467iter [00:45, 11.22iter/s]
Best score: 0.3494: : 468iter [00:45, 11.22iter/s]
Best score: 0.3494: : 469iter [00:45, 11.40iter/s]
Best score: 0.3251: : 469iter [00:45, 11.40iter/s]
Best score: 0.3251: : 470iter [00:45, 11.40iter/s]
Best score: 0.3251: : 471iter [00:45, 11.29iter/s]
Best score: 0.3251: : 471iter [00:45, 11.29iter/s]
Best score: 0.3251: : 472iter [00:45, 11.29iter/s]
Best score: 0.3251: : 473iter [00:45, 11.45iter/s]
Best score: 0.3251: : 473iter [00:45, 11.45iter/s]
Best score: 0.3251: : 474iter [00:45, 11.45iter/s]
Best score: 0.3251: : 475iter [00:45, 11.58iter/s]
Best score: 0.3251: : 475iter [00:46, 11.58iter/s]
Best score: 0.3251: : 476iter [00:46, 11.58iter/s]
Best score: 0.3251: : 477iter [00:46, 11.66iter/s]
Best score: 0.3251: : 477iter [00:46, 11.66iter/s]
Best score: 0.3251: : 478iter [00:46, 11.66iter/s]
Best score: 0.3251: : 479iter [00:46, 11.68iter/s]
Best score: 0.2689: : 479iter [00:46, 11.68iter/s]
Best score: 0.2689: : 480iter [00:46, 11.68iter/s]
Best score: 0.2689: : 481iter [00:46, 11.51iter/s]
Best score: 0.2689: : 481iter [00:46, 11.51iter/s]
Best score: 0.2689: : 482iter [00:46, 11.51iter/s]
Best score: 0.2689: : 483iter [00:46, 11.61iter/s]
Best score: 0.2689: : 483iter [00:46, 11.61iter/s]
Best score: 0.2689: : 484iter [00:46, 11.61iter/s]
Best score: 0.2689: : 485iter [00:46, 11.70iter/s]
Best score: 0.2689: : 485iter [00:46, 11.70iter/s]
Best score: 0.2689: : 486iter [00:47, 11.70iter/s]
Best score: 0.2689: : 487iter [00:47, 11.74iter/s]
Best score: 0.2689: : 487iter [00:47, 11.74iter/s]
Best score: 0.2689: : 488iter [00:47, 11.74iter/s]
Best score: 0.2689: : 489iter [00:47, 11.79iter/s]
Best score: 0.2641: : 489iter [00:47, 11.79iter/s]
Best score: 0.2641: : 490iter [00:47, 11.79iter/s]
Best score: 0.2641: : 491iter [00:47, 11.61iter/s]
Best score: 0.2641: : 491iter [00:47, 11.61iter/s]
Best score: 0.2641: : 492iter [00:47, 11.61iter/s]
Best score: 0.2641: : 493iter [00:47, 11.64iter/s]
Best score: 0.2641: : 493iter [00:47, 11.64iter/s]
Best score: 0.2641: : 494iter [00:47, 11.64iter/s]
Best score: 0.2641: : 495iter [00:47, 11.69iter/s]
Best score: 0.2641: : 495iter [00:47, 11.69iter/s]
Best score: 0.2641: : 496iter [00:47, 11.69iter/s]
Best score: 0.2641: : 497iter [00:47, 11.74iter/s]
Best score: 0.2641: : 497iter [00:47, 11.74iter/s]
Best score: 0.2641: : 498iter [00:48, 11.74iter/s]
Best score: 0.2641: : 499iter [00:48, 11.77iter/s]
[ITER 500] Best: 0.2564
[PARAMS] Current best parameters:
  fx: 525.1717
  fy: 525.0611
  px: 915.3131
  py: 924.1346
  k1: 0.02570185
  k2: -0.03660687
  k3: 0.02387333
  k4: -0.00598145
  p1: 0.00734304
  p2: -0.00187914
  p3: -0.00357139
  p4: 0.00594321
  s1: 0.0067
  s2: -0.0041
  s3: -0.0076
  s4: -0.0063
  tilt_x: -0.0019
  tilt_y: -0.0417
  scale: 2.9653
  rotation: -0.4788

Best score: 0.2564: : 499iter [00:48, 11.77iter/s]
Best score: 0.2564: : 500iter [00:48, 11.77iter/s]
Best score: 0.2564: : 501iter [00:48,  7.54iter/s]
Best score: 0.2564: : 501iter [00:48,  7.54iter/s]
Best score: 0.2564: : 502iter [00:48,  7.54iter/s]
Best score: 0.2564: : 503iter [00:48,  8.46iter/s]
Best score: 0.2564: : 503iter [00:48,  8.46iter/s]
Best score: 0.2564: : 504iter [00:48,  8.46iter/s]
Best score: 0.2564: : 505iter [00:48,  9.23iter/s]
Best score: 0.2564: : 505iter [00:48,  9.23iter/s]
Best score: 0.2564: : 506iter [00:49,  9.23iter/s]
Best score: 0.2564: : 507iter [00:49,  9.87iter/s]
Best score: 0.2564: : 507iter [00:49,  9.87iter/s]
Best score: 0.2564: : 508iter [00:49,  9.87iter/s]
Best score: 0.2564: : 509iter [00:49, 10.38iter/s]
Best score: 0.2519: : 509iter [00:49, 10.38iter/s]
Best score: 0.2519: : 510iter [00:49, 10.38iter/s]
Best score: 0.2519: : 511iter [00:49, 10.58iter/s]
Best score: 0.2519: : 511iter [00:49, 10.58iter/s]
Best score: 0.2519: : 512iter [00:49, 10.58iter/s]
Best score: 0.2519: : 513iter [00:49, 10.90iter/s]
Best score: 0.2519: : 513iter [00:49, 10.90iter/s]
Best score: 0.2519: : 514iter [00:49, 10.90iter/s]
Best score: 0.2519: : 515iter [00:49, 11.11iter/s]
Best score: 0.2519: : 515iter [00:49, 11.11iter/s]
Best score: 0.2519: : 516iter [00:49, 11.11iter/s]
Best score: 0.2519: : 517iter [00:49, 11.33iter/s]
Best score: 0.2519: : 517iter [00:49, 11.33iter/s]
Best score: 0.2519: : 518iter [00:50, 11.33iter/s]
Best score: 0.2519: : 519iter [00:50, 11.51iter/s]
Best score: 0.2425: : 519iter [00:50, 11.51iter/s]
Best score: 0.2425: : 520iter [00:50, 11.51iter/s]
Best score: 0.2425: : 521iter [00:50, 11.41iter/s]
Best score: 0.2425: : 521iter [00:50, 11.41iter/s]
Best score: 0.2425: : 522iter [00:50, 11.41iter/s]
Best score: 0.2425: : 523iter [00:50, 11.52iter/s]
Best score: 0.2425: : 523iter [00:50, 11.52iter/s]
Best score: 0.2425: : 524iter [00:50, 11.52iter/s]
Best score: 0.2425: : 525iter [00:50, 11.54iter/s]
Best score: 0.2425: : 525iter [00:50, 11.54iter/s]
Best score: 0.2425: : 526iter [00:50, 11.54iter/s]
Best score: 0.2425: : 527iter [00:50, 11.61iter/s]
Best score: 0.2425: : 527iter [00:50, 11.61iter/s]
Best score: 0.2425: : 528iter [00:50, 11.61iter/s]
Best score: 0.2425: : 529iter [00:50, 11.68iter/s]
Best score: 0.2359: : 529iter [00:51, 11.68iter/s]
Best score: 0.2359: : 530iter [00:51, 11.68iter/s]
Best score: 0.2359: : 531iter [00:51, 11.53iter/s]
Best score: 0.2359: : 531iter [00:51, 11.53iter/s]
Best score: 0.2359: : 532iter [00:51, 11.53iter/s]
Best score: 0.2359: : 533iter [00:51, 11.61iter/s]
Best score: 0.2359: : 533iter [00:51, 11.61iter/s]
Best score: 0.2359: : 534iter [00:51, 11.61iter/s]
Best score: 0.2359: : 535iter [00:51, 11.64iter/s]
Best score: 0.2359: : 535iter [00:51, 11.64iter/s]
Best score: 0.2359: : 536iter [00:51, 11.64iter/s]
Best score: 0.2359: : 537iter [00:51, 11.69iter/s]
Best score: 0.2359: : 537iter [00:51, 11.69iter/s]
Best score: 0.2359: : 538iter [00:51, 11.69iter/s]
Best score: 0.2359: : 539iter [00:51, 11.68iter/s]
Best score: 0.2323: : 539iter [00:51, 11.68iter/s]
Best score: 0.2323: : 540iter [00:51, 11.68iter/s]
Best score: 0.2323: : 541iter [00:51, 11.44iter/s]
Best score: 0.2323: : 541iter [00:52, 11.44iter/s]
Best score: 0.2323: : 542iter [00:52, 11.44iter/s]
Best score: 0.2323: : 543iter [00:52, 11.56iter/s]
Best score: 0.2323: : 543iter [00:52, 11.56iter/s]
Best score: 0.2323: : 544iter [00:52, 11.56iter/s]
Best score: 0.2323: : 545iter [00:52, 11.66iter/s]
Best score: 0.2323: : 545iter [00:52, 11.66iter/s]
Best score: 0.2323: : 546iter [00:52, 11.66iter/s]
Best score: 0.2323: : 547iter [00:52, 11.72iter/s]
Best score: 0.2323: : 547iter [00:52, 11.72iter/s]
Best score: 0.2323: : 548iter [00:52, 11.72iter/s]
Best score: 0.2323: : 549iter [00:52, 11.77iter/s]
[ITER 550] Best: 0.2195
[PARAMS] Current best parameters:
  fx: 523.2944
  fy: 523.3878
  px: 911.5950
  py: 924.3846
  k1: 0.03030429
  k2: -0.04575728
  k3: 0.03220921
  k4: -0.00834727
  p1: 0.00047614
  p2: -0.00208032
  p3: -0.00402333
  p4: 0.01198149
  s1: 0.0061
  s2: -0.0111
  s3: 0.0026
  s4: -0.0137
  tilt_x: 0.0122
  tilt_y: -0.0233
  scale: 2.9666
  rotation: -0.5060

Best score: 0.2195: : 549iter [00:52, 11.77iter/s]
Best score: 0.2195: : 550iter [00:53, 11.77iter/s]
Best score: 0.2195: : 551iter [00:53,  7.55iter/s]
Best score: 0.2195: : 551iter [00:53,  7.55iter/s]
Best score: 0.2195: : 552iter [00:53,  7.55iter/s]
Best score: 0.2195: : 553iter [00:53,  8.47iter/s]
Best score: 0.2195: : 553iter [00:53,  8.47iter/s]
Best score: 0.2195: : 554iter [00:53,  8.47iter/s]
Best score: 0.2195: : 555iter [00:53,  9.27iter/s]
Best score: 0.2195: : 555iter [00:53,  9.27iter/s]
Best score: 0.2195: : 556iter [00:53,  9.27iter/s]
Best score: 0.2195: : 557iter [00:53,  9.92iter/s]
Best score: 0.2195: : 557iter [00:53,  9.92iter/s]
Best score: 0.2195: : 558iter [00:53,  9.92iter/s]
Best score: 0.2195: : 559iter [00:53, 10.44iter/s]
Best score: 0.2181: : 559iter [00:53, 10.44iter/s]
Best score: 0.2181: : 560iter [00:53, 10.44iter/s]
Best score: 0.2181: : 561iter [00:53, 10.67iter/s]
Best score: 0.2181: : 561iter [00:54, 10.67iter/s]
Best score: 0.2181: : 562iter [00:54, 10.67iter/s]
Best score: 0.2181: : 563iter [00:54, 11.00iter/s]
Best score: 0.2181: : 563iter [00:54, 11.00iter/s]
Best score: 0.2181: : 564iter [00:54, 11.00iter/s]
Best score: 0.2181: : 565iter [00:54, 11.25iter/s]
Best score: 0.2181: : 565iter [00:54, 11.25iter/s]
Best score: 0.2181: : 566iter [00:54, 11.25iter/s]
Best score: 0.2181: : 567iter [00:54, 11.43iter/s]
Best score: 0.2181: : 567iter [00:54, 11.43iter/s]
Best score: 0.2181: : 568iter [00:54, 11.43iter/s]
Best score: 0.2181: : 569iter [00:54, 11.58iter/s]
Best score: 0.2160: : 569iter [00:54, 11.58iter/s]
Best score: 0.2160: : 570iter [00:54, 11.58iter/s]
Best score: 0.2160: : 571iter [00:54, 11.47iter/s]
Best score: 0.2160: : 571iter [00:54, 11.47iter/s]
Best score: 0.2160: : 572iter [00:54, 11.47iter/s]
Best score: 0.2160: : 573iter [00:54, 11.55iter/s]
Best score: 0.2160: : 573iter [00:55, 11.55iter/s]
Best score: 0.2160: : 574iter [00:55, 11.55iter/s]
Best score: 0.2160: : 575iter [00:55, 11.63iter/s]
Best score: 0.2160: : 575iter [00:55, 11.63iter/s]
Best score: 0.2160: : 576iter [00:55, 11.63iter/s]
Best score: 0.2160: : 577iter [00:55, 11.71iter/s]
Best score: 0.2160: : 577iter [00:55, 11.71iter/s]
Best score: 0.2160: : 578iter [00:55, 11.71iter/s]
Best score: 0.2160: : 579iter [00:55, 11.69iter/s]
Best score: 0.2140: : 579iter [00:55, 11.69iter/s]
Best score: 0.2140: : 580iter [00:55, 11.69iter/s]
Best score: 0.2140: : 581iter [00:55, 11.46iter/s]
Best score: 0.2140: : 581iter [00:55, 11.46iter/s]
Best score: 0.2140: : 582iter [00:55, 11.46iter/s]
Best score: 0.2140: : 583iter [00:55, 11.56iter/s]
Best score: 0.2140: : 583iter [00:55, 11.56iter/s]
Best score: 0.2140: : 584iter [00:56, 11.56iter/s]
Best score: 0.2140: : 585iter [00:56, 11.60iter/s]
Best score: 0.2140: : 585iter [00:56, 11.60iter/s]
Best score: 0.2140: : 586iter [00:56, 11.60iter/s]
Best score: 0.2140: : 587iter [00:56, 11.63iter/s]
Best score: 0.2140: : 587iter [00:56, 11.63iter/s]
Best score: 0.2140: : 588iter [00:56, 11.63iter/s]
Best score: 0.2140: : 589iter [00:56, 11.69iter/s]
Best score: 0.2118: : 589iter [00:56, 11.69iter/s]
Best score: 0.2118: : 590iter [00:56, 11.69iter/s]
Best score: 0.2118: : 591iter [00:56, 11.53iter/s]
Best score: 0.2118: : 591iter [00:56, 11.53iter/s]
Best score: 0.2118: : 592iter [00:56, 11.53iter/s]
Best score: 0.2118: : 593iter [00:56, 11.61iter/s]
Best score: 0.2118: : 593iter [00:56, 11.61iter/s]
Best score: 0.2118: : 594iter [00:56, 11.61iter/s]
Best score: 0.2118: : 595iter [00:56, 11.65iter/s]
Best score: 0.2118: : 595iter [00:56, 11.65iter/s]
Best score: 0.2118: : 596iter [00:57, 11.65iter/s]
Best score: 0.2118: : 597iter [00:57, 11.61iter/s]
Best score: 0.2118: : 597iter [00:57, 11.61iter/s]
Best score: 0.2118: : 598iter [00:57, 11.61iter/s]
Best score: 0.2118: : 599iter [00:57, 11.64iter/s]
[ITER 600] Best: 0.2081
[PARAMS] Current best parameters:
  fx: 525.4116
  fy: 525.6384
  px: 907.6601
  py: 924.6849
  k1: 0.03651004
  k2: -0.04954089
  k3: 0.02932647
  k4: -0.00686665
  p1: -0.00114716
  p2: -0.00028332
  p3: -0.00172372
  p4: 0.01317294
  s1: -0.0022
  s2: -0.0118
  s3: 0.0039
  s4: -0.0161
  tilt_x: 0.0165
  tilt_y: -0.0013
  scale: 2.9465
  rotation: -0.5037

Best score: 0.2081: : 599iter [00:57, 11.64iter/s]
Best score: 0.2081: : 600iter [00:57, 11.64iter/s]
Best score: 0.2081: : 601iter [00:57,  7.50iter/s]
Best score: 0.2081: : 601iter [00:57,  7.50iter/s]
Best score: 0.2081: : 602iter [00:57,  7.50iter/s]
Best score: 0.2081: : 603iter [00:57,  8.42iter/s]
Best score: 0.2081: : 603iter [00:57,  8.42iter/s]
Best score: 0.2081: : 604iter [00:58,  8.42iter/s]
Best score: 0.2081: : 605iter [00:58,  9.21iter/s]
Best score: 0.2081: : 605iter [00:58,  9.21iter/s]
Best score: 0.2081: : 606iter [00:58,  9.21iter/s]
Best score: 0.2081: : 607iter [00:58,  9.85iter/s]
Best score: 0.2081: : 607iter [00:58,  9.85iter/s]
Best score: 0.2081: : 608iter [00:58,  9.85iter/s]
Best score: 0.2081: : 609iter [00:58, 10.35iter/s]
Best score: 0.2081: : 609iter [00:58, 10.35iter/s]
Best score: 0.2081: : 610iter [00:58, 10.35iter/s]
Best score: 0.2081: : 611iter [00:58, 10.57iter/s]
Best score: 0.2081: : 611iter [00:58, 10.57iter/s]
Best score: 0.2081: : 612iter [00:58, 10.57iter/s]
Best score: 0.2081: : 613iter [00:58, 10.91iter/s]
Best score: 0.2081: : 613iter [00:58, 10.91iter/s]
Best score: 0.2081: : 614iter [00:58, 10.91iter/s]
Best score: 0.2081: : 615iter [00:58, 11.15iter/s]
Best score: 0.2081: : 615iter [00:58, 11.15iter/s]
Best score: 0.2081: : 616iter [00:59, 11.15iter/s]
Best score: 0.2081: : 617iter [00:59, 11.34iter/s]
Best score: 0.2081: : 617iter [00:59, 11.34iter/s]
Best score: 0.2081: : 618iter [00:59, 11.34iter/s]
Best score: 0.2081: : 619iter [00:59, 11.39iter/s]
Best score: 0.2037: : 619iter [00:59, 11.39iter/s]
Best score: 0.2037: : 620iter [00:59, 11.39iter/s]
Best score: 0.2037: : 621iter [00:59, 11.27iter/s]
Best score: 0.2037: : 621iter [00:59, 11.27iter/s]
Best score: 0.2037: : 622iter [00:59, 11.27iter/s]
Best score: 0.2037: : 623iter [00:59, 11.37iter/s]
Best score: 0.2037: : 623iter [00:59, 11.37iter/s]
Best score: 0.2037: : 624iter [00:59, 11.37iter/s]
Best score: 0.2037: : 625iter [00:59, 11.48iter/s]
Best score: 0.2037: : 625iter [00:59, 11.48iter/s]
Best score: 0.2037: : 626iter [00:59, 11.48iter/s]
Best score: 0.2037: : 627iter [00:59, 11.59iter/s]
Best score: 0.2037: : 627iter [01:00, 11.59iter/s]
Best score: 0.2037: : 628iter [01:00, 11.59iter/s]
Best score: 0.2037: : 629iter [01:00, 11.65iter/s]
Best score: 0.2030: : 629iter [01:00, 11.65iter/s]
Best score: 0.2030: : 630iter [01:00, 11.65iter/s]
Best score: 0.2030: : 631iter [01:00, 11.50iter/s]
Best score: 0.2030: : 631iter [01:00, 11.50iter/s]
Best score: 0.2030: : 632iter [01:00, 11.50iter/s]
Best score: 0.2030: : 633iter [01:00, 11.58iter/s]
Best score: 0.2030: : 633iter [01:00, 11.58iter/s]
Best score: 0.2030: : 634iter [01:00, 11.58iter/s]
Best score: 0.2030: : 635iter [01:00, 11.65iter/s]
Best score: 0.2030: : 635iter [01:00, 11.65iter/s]
Best score: 0.2030: : 636iter [01:00, 11.65iter/s]
Best score: 0.2030: : 637iter [01:00, 11.71iter/s]
Best score: 0.2030: : 637iter [01:00, 11.71iter/s]
Best score: 0.2030: : 638iter [01:00, 11.71iter/s]
Best score: 0.2030: : 639iter [01:00, 11.75iter/s]
Best score: 0.2016: : 639iter [01:01, 11.75iter/s]
Best score: 0.2016: : 640iter [01:01, 11.75iter/s]
Best score: 0.2016: : 641iter [01:01, 11.57iter/s]
Best score: 0.2016: : 641iter [01:01, 11.57iter/s]
Best score: 0.2016: : 642iter [01:01, 11.57iter/s]
Best score: 0.2016: : 643iter [01:01, 11.66iter/s]
Best score: 0.2016: : 643iter [01:01, 11.66iter/s]
Best score: 0.2016: : 644iter [01:01, 11.66iter/s]
Best score: 0.2016: : 645iter [01:01, 11.72iter/s]
Best score: 0.2016: : 645iter [01:01, 11.72iter/s]
Best score: 0.2016: : 646iter [01:01, 11.72iter/s]
Best score: 0.2016: : 647iter [01:01, 11.74iter/s]
Best score: 0.2016: : 647iter [01:01, 11.74iter/s]
Best score: 0.2016: : 648iter [01:01, 11.74iter/s]
Best score: 0.2016: : 649iter [01:01, 11.76iter/s]
[ITER 650] Best: 0.1976
[PARAMS] Current best parameters:
  fx: 527.6068
  fy: 527.6684
  px: 910.1818
  py: 923.2258
  k1: 0.02758177
  k2: -0.04190571
  k3: 0.02687156
  k4: -0.00671080
  p1: -0.00137275
  p2: -0.00209563
  p3: -0.00267838
  p4: 0.01367960
  s1: 0.0020
  s2: -0.0123
  s3: 0.0027
  s4: -0.0159
  tilt_x: 0.0103
  tilt_y: -0.0174
  scale: 2.9554
  rotation: -0.4963

Best score: 0.1976: : 649iter [01:01, 11.76iter/s]
Best score: 0.1976: : 650iter [01:02, 11.76iter/s]
Best score: 0.1976: : 651iter [01:02,  7.50iter/s]
Best score: 0.1976: : 651iter [01:02,  7.50iter/s]
Best score: 0.1976: : 652iter [01:02,  7.50iter/s]
Best score: 0.1976: : 653iter [01:02,  8.41iter/s]
Best score: 0.1976: : 653iter [01:02,  8.41iter/s]
Best score: 0.1976: : 654iter [01:02,  8.41iter/s]
Best score: 0.1976: : 655iter [01:02,  9.21iter/s]
Best score: 0.1976: : 655iter [01:02,  9.21iter/s]
Best score: 0.1976: : 656iter [01:02,  9.21iter/s]
Best score: 0.1976: : 657iter [01:02,  9.87iter/s]
Best score: 0.1976: : 657iter [01:02,  9.87iter/s]
Best score: 0.1976: : 658iter [01:02,  9.87iter/s]
Best score: 0.1976: : 659iter [01:02, 10.39iter/s]
Best score: 0.1964: : 659iter [01:03, 10.39iter/s]
Best score: 0.1964: : 660iter [01:03, 10.39iter/s]
Best score: 0.1964: : 661iter [01:03, 10.63iter/s]
Best score: 0.1964: : 661iter [01:03, 10.63iter/s]
Best score: 0.1964: : 662iter [01:03, 10.63iter/s]
Best score: 0.1964: : 663iter [01:03, 10.96iter/s]
Best score: 0.1964: : 663iter [01:03, 10.96iter/s]
Best score: 0.1964: : 664iter [01:03, 10.96iter/s]
Best score: 0.1964: : 665iter [01:03, 11.20iter/s]
Best score: 0.1964: : 665iter [01:03, 11.20iter/s]
Best score: 0.1964: : 666iter [01:03, 11.20iter/s]
Best score: 0.1964: : 667iter [01:03, 11.34iter/s]
Best score: 0.1964: : 667iter [01:03, 11.34iter/s]
Best score: 0.1964: : 668iter [01:03, 11.34iter/s]
Best score: 0.1964: : 669iter [01:03, 11.47iter/s]
Best score: 0.1940: : 669iter [01:03, 11.47iter/s]
Best score: 0.1940: : 670iter [01:04, 11.47iter/s]
Best score: 0.1940: : 671iter [01:04, 11.37iter/s]
Best score: 0.1940: : 671iter [01:04, 11.37iter/s]
Best score: 0.1940: : 672iter [01:04, 11.37iter/s]
Best score: 0.1940: : 673iter [01:04, 11.50iter/s]
Best score: 0.1940: : 673iter [01:04, 11.50iter/s]
Best score: 0.1940: : 674iter [01:04, 11.50iter/s]
Best score: 0.1940: : 675iter [01:04, 11.60iter/s]
Best score: 0.1940: : 675iter [01:04, 11.60iter/s]
Best score: 0.1940: : 676iter [01:04, 11.60iter/s]
Best score: 0.1940: : 677iter [01:04, 11.68iter/s]
Best score: 0.1940: : 677iter [01:04, 11.68iter/s]
Best score: 0.1940: : 678iter [01:04, 11.68iter/s]
Best score: 0.1940: : 679iter [01:04, 11.68iter/s]
Best score: 0.1908: : 679iter [01:04, 11.68iter/s]
Best score: 0.1908: : 680iter [01:04, 11.68iter/s]
Best score: 0.1908: : 681iter [01:04, 11.53iter/s]
Best score: 0.1908: : 681iter [01:04, 11.53iter/s]
Best score: 0.1908: : 682iter [01:05, 11.53iter/s]
Best score: 0.1908: : 683iter [01:05, 11.52iter/s]
Best score: 0.1908: : 683iter [01:05, 11.52iter/s]
Best score: 0.1908: : 684iter [01:05, 11.52iter/s]
Best score: 0.1908: : 685iter [01:05, 11.55iter/s]
Best score: 0.1908: : 685iter [01:05, 11.55iter/s]
Best score: 0.1908: : 686iter [01:05, 11.55iter/s]
Best score: 0.1908: : 687iter [01:05, 11.63iter/s]
Best score: 0.1908: : 687iter [01:05, 11.63iter/s]
Best score: 0.1908: : 688iter [01:05, 11.63iter/s]
Best score: 0.1908: : 689iter [01:05, 11.69iter/s]
Best score: 0.1884: : 689iter [01:05, 11.69iter/s]
Best score: 0.1884: : 690iter [01:05, 11.69iter/s]
Best score: 0.1884: : 691iter [01:05, 11.52iter/s]
Best score: 0.1884: : 691iter [01:05, 11.52iter/s]
Best score: 0.1884: : 692iter [01:05, 11.52iter/s]
Best score: 0.1884: : 693iter [01:05, 11.61iter/s]
Best score: 0.1884: : 693iter [01:06, 11.61iter/s]
Best score: 0.1884: : 694iter [01:06, 11.61iter/s]
Best score: 0.1884: : 695iter [01:06, 11.66iter/s]
Best score: 0.1884: : 695iter [01:06, 11.66iter/s]
Best score: 0.1884: : 696iter [01:06, 11.66iter/s]
Best score: 0.1884: : 697iter [01:06, 11.70iter/s]
Best score: 0.1884: : 697iter [01:06, 11.70iter/s]
Best score: 0.1884: : 698iter [01:06, 11.70iter/s]
Best score: 0.1884: : 699iter [01:06, 11.74iter/s]
[ITER 700] Best: 0.1878
[PARAMS] Current best parameters:
  fx: 529.9223
  fy: 530.1562
  px: 908.0634
  py: 920.2139
  k1: 0.02457454
  k2: -0.04117299
  k3: 0.02662641
  k4: -0.00666090
  p1: -0.00781792
  p2: -0.00412079
  p3: 0.00285222
  p4: 0.01751517
  s1: -0.0034
  s2: -0.0160
  s3: 0.0001
  s4: -0.0190
  tilt_x: 0.0087
  tilt_y: -0.0115
  scale: 2.9544
  rotation: -0.5295

Best score: 0.1878: : 699iter [01:06, 11.74iter/s]
Best score: 0.1878: : 700iter [01:06, 11.74iter/s]
Best score: 0.1878: : 701iter [01:06,  7.52iter/s]
Best score: 0.1878: : 701iter [01:07,  7.52iter/s]
Best score: 0.1878: : 702iter [01:07,  7.52iter/s]
Best score: 0.1878: : 703iter [01:07,  8.45iter/s]
Best score: 0.1878: : 703iter [01:07,  8.45iter/s]
Best score: 0.1878: : 704iter [01:07,  8.45iter/s]
Best score: 0.1878: : 705iter [01:07,  9.25iter/s]
Best score: 0.1878: : 705iter [01:07,  9.25iter/s]
Best score: 0.1878: : 706iter [01:07,  9.25iter/s]
Best score: 0.1878: : 707iter [01:07,  9.89iter/s]
Best score: 0.1878: : 707iter [01:07,  9.89iter/s]
Best score: 0.1878: : 708iter [01:07,  9.89iter/s]
Best score: 0.1878: : 709iter [01:07, 10.38iter/s]
Best score: 0.1878: : 709iter [01:07, 10.38iter/s]
Best score: 0.1878: : 710iter [01:07, 10.38iter/s]
Best score: 0.1878: : 711iter [01:07, 10.60iter/s]
Best score: 0.1878: : 711iter [01:07, 10.60iter/s]
Best score: 0.1878: : 712iter [01:07, 10.60iter/s]
Best score: 0.1878: : 713iter [01:07, 10.93iter/s]
Best score: 0.1878: : 713iter [01:08, 10.93iter/s]
Best score: 0.1878: : 714iter [01:08, 10.93iter/s]
Best score: 0.1878: : 715iter [01:08, 11.18iter/s]
Best score: 0.1878: : 715iter [01:08, 11.18iter/s]
Best score: 0.1878: : 716iter [01:08, 11.18iter/s]
Best score: 0.1878: : 717iter [01:08, 11.35iter/s]
Best score: 0.1878: : 717iter [01:08, 11.35iter/s]
Best score: 0.1878: : 718iter [01:08, 11.35iter/s]
Best score: 0.1878: : 719iter [01:08, 11.44iter/s]
Best score: 0.1878: : 719iter [01:08, 11.44iter/s]
Best score: 0.1878: : 720iter [01:08, 11.44iter/s]
Best score: 0.1878: : 721iter [01:08, 11.35iter/s]
Best score: 0.1878: : 721iter [01:08, 11.35iter/s]
Best score: 0.1878: : 722iter [01:08, 11.35iter/s]
Best score: 0.1878: : 723iter [01:08, 11.49iter/s]
Best score: 0.1878: : 723iter [01:08, 11.49iter/s]
Best score: 0.1878: : 724iter [01:08, 11.49iter/s]
Best score: 0.1878: : 725iter [01:08, 11.53iter/s]
Best score: 0.1878: : 725iter [01:09, 11.53iter/s]
Best score: 0.1878: : 726iter [01:09, 11.53iter/s]
Best score: 0.1878: : 727iter [01:09, 11.60iter/s]
Best score: 0.1878: : 727iter [01:09, 11.60iter/s]
Best score: 0.1878: : 728iter [01:09, 11.60iter/s]
Best score: 0.1878: : 729iter [01:09, 11.64iter/s]
Best score: 0.1878: : 729iter [01:09, 11.64iter/s]
Best score: 0.1878: : 730iter [01:09, 11.64iter/s]
Best score: 0.1878: : 731iter [01:09, 11.44iter/s]
Best score: 0.1878: : 731iter [01:09, 11.44iter/s]
Best score: 0.1878: : 732iter [01:09, 11.44iter/s]
Best score: 0.1878: : 733iter [01:09, 11.55iter/s]
Best score: 0.1878: : 733iter [01:09, 11.55iter/s]
Best score: 0.1878: : 734iter [01:09, 11.55iter/s]
Best score: 0.1878: : 735iter [01:09, 11.64iter/s]
Best score: 0.1878: : 735iter [01:09, 11.64iter/s]
Best score: 0.1878: : 736iter [01:10, 11.64iter/s]
Best score: 0.1878: : 737iter [01:10, 11.69iter/s]
Best score: 0.1878: : 737iter [01:10, 11.69iter/s]
Best score: 0.1878: : 738iter [01:10, 11.69iter/s]
Best score: 0.1878: : 739iter [01:10, 11.69iter/s]
Best score: 0.1872: : 739iter [01:10, 11.69iter/s]
Best score: 0.1872: : 740iter [01:10, 11.69iter/s]
Best score: 0.1872: : 741iter [01:10, 11.53iter/s]
Best score: 0.1872: : 741iter [01:10, 11.53iter/s]
Best score: 0.1872: : 742iter [01:10, 11.53iter/s]
Best score: 0.1872: : 743iter [01:10, 11.56iter/s]
Best score: 0.1872: : 743iter [01:10, 11.56iter/s]
Best score: 0.1872: : 744iter [01:10, 11.56iter/s]
Best score: 0.1872: : 745iter [01:10, 11.60iter/s]
Best score: 0.1872: : 745iter [01:10, 11.60iter/s]
Best score: 0.1872: : 746iter [01:10, 11.60iter/s]
Best score: 0.1872: : 747iter [01:10, 11.67iter/s]
Best score: 0.1872: : 747iter [01:10, 11.67iter/s]
Best score: 0.1872: : 748iter [01:11, 11.67iter/s]
Best score: 0.1872: : 749iter [01:11, 11.72iter/s]
[ITER 750] Best: 0.1872
[PARAMS] Current best parameters:
  fx: 529.2234
  fy: 529.3706
  px: 909.9322
  py: 920.5189
  k1: 0.02261117
  k2: -0.03761509
  k3: 0.02477632
  k4: -0.00628657
  p1: -0.00527782
  p2: -0.00270263
  p3: 0.00163274
  p4: 0.01464534
  s1: -0.0018
  s2: -0.0131
  s3: -0.0006
  s4: -0.0164
  tilt_x: 0.0050
  tilt_y: -0.0173
  scale: 2.9587
  rotation: -0.5178

Best score: 0.1872: : 749iter [01:11, 11.72iter/s]
Best score: 0.1872: : 750iter [01:11, 11.72iter/s]
Best score: 0.1872: : 751iter [01:11,  7.52iter/s]
Best score: 0.1872: : 751iter [01:11,  7.52iter/s]
Best score: 0.1872: : 752iter [01:11,  7.52iter/s]
Best score: 0.1872: : 753iter [01:11,  8.42iter/s]
Best score: 0.1872: : 753iter [01:11,  8.42iter/s]
Best score: 0.1872: : 754iter [01:11,  8.42iter/s]
Best score: 0.1872: : 755iter [01:11,  9.19iter/s]
Best score: 0.1872: : 755iter [01:11,  9.19iter/s]
Best score: 0.1872: : 756iter [01:12,  9.19iter/s]
Best score: 0.1872: : 757iter [01:12,  9.84iter/s]
Best score: 0.1872: : 757iter [01:12,  9.84iter/s]
Best score: 0.1872: : 758iter [01:12,  9.84iter/s]
Best score: 0.1872: : 759iter [01:12, 10.35iter/s]
Best score: 0.1864: : 759iter [01:12, 10.35iter/s]
Best score: 0.1864: : 760iter [01:12, 10.35iter/s]
Best score: 0.1864: : 761iter [01:12, 10.57iter/s]
Best score: 0.1864: : 761iter [01:12, 10.57iter/s]
Best score: 0.1864: : 762iter [01:12, 10.57iter/s]
Best score: 0.1864: : 763iter [01:12, 10.83iter/s]
Best score: 0.1864: : 763iter [01:12, 10.83iter/s]
Best score: 0.1864: : 764iter [01:12, 10.83iter/s]
Best score: 0.1864: : 765iter [01:12, 11.08iter/s]
Best score: 0.1864: : 765iter [01:12, 11.08iter/s]
Best score: 0.1864: : 766iter [01:12, 11.08iter/s]
Best score: 0.1864: : 767iter [01:12, 11.29iter/s]
Best score: 0.1864: : 767iter [01:12, 11.29iter/s]
Best score: 0.1864: : 768iter [01:13, 11.29iter/s]
Best score: 0.1864: : 769iter [01:13, 11.37iter/s]
Best score: 0.1864: : 769iter [01:13, 11.37iter/s]
Best score: 0.1864: : 770iter [01:13, 11.37iter/s]
Best score: 0.1864: : 771iter [01:13, 11.24iter/s]
Best score: 0.1864: : 771iter [01:13, 11.24iter/s]
Best score: 0.1864: : 772iter [01:13, 11.24iter/s]
Best score: 0.1864: : 773iter [01:13, 11.36iter/s]
Best score: 0.1864: : 773iter [01:13, 11.36iter/s]
Best score: 0.1864: : 774iter [01:13, 11.36iter/s]
Best score: 0.1864: : 775iter [01:13, 11.47iter/s]
Best score: 0.1864: : 775iter [01:13, 11.47iter/s]
Best score: 0.1864: : 776iter [01:13, 11.47iter/s]
Best score: 0.1864: : 777iter [01:13, 11.57iter/s]
Best score: 0.1864: : 777iter [01:13, 11.57iter/s]
Best score: 0.1864: : 778iter [01:13, 11.57iter/s]
Best score: 0.1864: : 779iter [01:13, 11.65iter/s]
Best score: 0.1863: : 779iter [01:14, 11.65iter/s]
Best score: 0.1863: : 780iter [01:14, 11.65iter/s]
Best score: 0.1863: : 781iter [01:14, 11.47iter/s]
Best score: 0.1863: : 781iter [01:14, 11.47iter/s]
Best score: 0.1863: : 782iter [01:14, 11.47iter/s]
Best score: 0.1863: : 783iter [01:14, 11.56iter/s]
Best score: 0.1863: : 783iter [01:14, 11.56iter/s]
Best score: 0.1863: : 784iter [01:14, 11.56iter/s]
Best score: 0.1863: : 785iter [01:14, 11.63iter/s]
Best score: 0.1863: : 785iter [01:14, 11.63iter/s]
Best score: 0.1863: : 786iter [01:14, 11.63iter/s]
Best score: 0.1863: : 787iter [01:14, 11.59iter/s]
Best score: 0.1863: : 787iter [01:14, 11.59iter/s]
Best score: 0.1863: : 788iter [01:14, 11.59iter/s]
Best score: 0.1863: : 789iter [01:14, 11.67iter/s]
Best score: 0.1855: : 789iter [01:14, 11.67iter/s]
Best score: 0.1855: : 790iter [01:14, 11.67iter/s]
Best score: 0.1855: : 791iter [01:14, 11.50iter/s]
Best score: 0.1855: : 791iter [01:15, 11.50iter/s]
Best score: 0.1855: : 792iter [01:15, 11.50iter/s]
Best score: 0.1855: : 793iter [01:15, 11.59iter/s]
Best score: 0.1855: : 793iter [01:15, 11.59iter/s]
Best score: 0.1855: : 794iter [01:15, 11.59iter/s]
Best score: 0.1855: : 795iter [01:15, 11.62iter/s]
Best score: 0.1855: : 795iter [01:15, 11.62iter/s]
Best score: 0.1855: : 796iter [01:15, 11.62iter/s]
Best score: 0.1855: : 797iter [01:15, 11.61iter/s]
Best score: 0.1855: : 797iter [01:15, 11.61iter/s]
Best score: 0.1855: : 798iter [01:15, 11.61iter/s]
Best score: 0.1855: : 799iter [01:15, 11.67iter/s]
[ITER 800] Best: 0.1853
[PARAMS] Current best parameters:
  fx: 529.9280
  fy: 530.0138
  px: 908.6068
  py: 919.6500
  k1: 0.02293163
  k2: -0.03708857
  k3: 0.02309811
  k4: -0.00563569
  p1: -0.00786400
  p2: -0.00636004
  p3: 0.00536988
  p4: 0.01566780
  s1: -0.0026
  s2: -0.0144
  s3: -0.0031
  s4: -0.0173
  tilt_x: 0.0062
  tilt_y: -0.0184
  scale: 2.9555
  rotation: -0.5089

Best score: 0.1853: : 799iter [01:15, 11.67iter/s]
Best score: 0.1853: : 800iter [01:16, 11.67iter/s]
Best score: 0.1853: : 801iter [01:16,  7.48iter/s]
Best score: 0.1853: : 801iter [01:16,  7.48iter/s]
Best score: 0.1853: : 802iter [01:16,  7.48iter/s]
Best score: 0.1853: : 803iter [01:16,  8.38iter/s]
Best score: 0.1853: : 803iter [01:16,  8.38iter/s]
Best score: 0.1853: : 804iter [01:16,  8.38iter/s]
Best score: 0.1853: : 805iter [01:16,  9.18iter/s]
Best score: 0.1853: : 805iter [01:16,  9.18iter/s]
Best score: 0.1853: : 806iter [01:16,  9.18iter/s]
Best score: 0.1853: : 807iter [01:16,  9.84iter/s]
Best score: 0.1853: : 807iter [01:16,  9.84iter/s]
Best score: 0.1853: : 808iter [01:16,  9.84iter/s]
Best score: 0.1853: : 809iter [01:16, 10.37iter/s]
Best score: 0.1846: : 809iter [01:16, 10.37iter/s]
Best score: 0.1846: : 810iter [01:17, 10.37iter/s]
Best score: 0.1846: : 811iter [01:17, 10.60iter/s]
Best score: 0.1846: : 811iter [01:17, 10.60iter/s]
Best score: 0.1846: : 812iter [01:17, 10.60iter/s]
Best score: 0.1846: : 813iter [01:17, 10.94iter/s]
Best score: 0.1846: : 813iter [01:17, 10.94iter/s]
Best score: 0.1846: : 814iter [01:17, 10.94iter/s]
Best score: 0.1846: : 815iter [01:17, 11.20iter/s]
Best score: 0.1846: : 815iter [01:17, 11.20iter/s]
Best score: 0.1846: : 816iter [01:17, 11.20iter/s]
Best score: 0.1846: : 817iter [01:17, 11.37iter/s]
Best score: 0.1846: : 817iter [01:17, 11.37iter/s]
Best score: 0.1846: : 818iter [01:17, 11.37iter/s]
Best score: 0.1846: : 819iter [01:17, 11.46iter/s]
Best score: 0.1835: : 819iter [01:17, 11.46iter/s]
Best score: 0.1835: : 820iter [01:17, 11.46iter/s]
Best score: 0.1835: : 821iter [01:17, 11.39iter/s]
Best score: 0.1835: : 821iter [01:17, 11.39iter/s]
Best score: 0.1835: : 822iter [01:18, 11.39iter/s]
Best score: 0.1835: : 823iter [01:18, 11.50iter/s]
Best score: 0.1835: : 823iter [01:18, 11.50iter/s]
Best score: 0.1835: : 824iter [01:18, 11.50iter/s]
Best score: 0.1835: : 825iter [01:18, 11.60iter/s]
Best score: 0.1835: : 825iter [01:18, 11.60iter/s]
Best score: 0.1835: : 826iter [01:18, 11.60iter/s]
Best score: 0.1835: : 827iter [01:18, 11.65iter/s]
Best score: 0.1835: : 827iter [01:18, 11.65iter/s]
Best score: 0.1835: : 828iter [01:18, 11.65iter/s]
Best score: 0.1835: : 829iter [01:18, 11.70iter/s]
Best score: 0.1835: : 829iter [01:18, 11.70iter/s]
Best score: 0.1835: : 830iter [01:18, 11.70iter/s]
Best score: 0.1835: : 831iter [01:18, 11.53iter/s]
Best score: 0.1835: : 831iter [01:18, 11.53iter/s]
Best score: 0.1835: : 832iter [01:18, 11.53iter/s]
Best score: 0.1835: : 833iter [01:18, 11.54iter/s]
Best score: 0.1835: : 833iter [01:18, 11.54iter/s]
Best score: 0.1835: : 834iter [01:19, 11.54iter/s]
Best score: 0.1835: : 835iter [01:19, 11.61iter/s]
Best score: 0.1835: : 835iter [01:19, 11.61iter/s]
Best score: 0.1835: : 836iter [01:19, 11.61iter/s]
Best score: 0.1835: : 837iter [01:19, 11.64iter/s]
Best score: 0.1835: : 837iter [01:19, 11.64iter/s]
Best score: 0.1835: : 838iter [01:19, 11.64iter/s]
Best score: 0.1835: : 839iter [01:19, 11.62iter/s]
Best score: 0.1818: : 839iter [01:19, 11.62iter/s]
Best score: 0.1818: : 840iter [01:19, 11.62iter/s]
Best score: 0.1818: : 841iter [01:19, 11.44iter/s]
Best score: 0.1818: : 841iter [01:19, 11.44iter/s]
Best score: 0.1818: : 842iter [01:19, 11.44iter/s]
Best score: 0.1818: : 843iter [01:19, 11.56iter/s]
Best score: 0.1818: : 843iter [01:19, 11.56iter/s]
Best score: 0.1818: : 844iter [01:19, 11.56iter/s]
Best score: 0.1818: : 845iter [01:19, 11.62iter/s]
Best score: 0.1818: : 845iter [01:20, 11.62iter/s]
Best score: 0.1818: : 846iter [01:20, 11.62iter/s]
Best score: 0.1818: : 847iter [01:20, 11.61iter/s]
Best score: 0.1818: : 847iter [01:20, 11.61iter/s]
Best score: 0.1818: : 848iter [01:20, 11.61iter/s]
Best score: 0.1818: : 849iter [01:20, 11.67iter/s]
[ITER 850] Best: 0.1818
[PARAMS] Current best parameters:
  fx: 532.7871
  fy: 532.8605
  px: 907.7800
  py: 919.4656
  k1: 0.01064141
  k2: -0.02413048
  k3: 0.01713978
  k4: -0.00471090
  p1: -0.00946266
  p2: -0.00751226
  p3: 0.00942890
  p4: 0.01545226
  s1: -0.0060
  s2: -0.0145
  s3: -0.0055
  s4: -0.0171
  tilt_x: 0.0083
  tilt_y: -0.0167
  scale: 2.9638
  rotation: -0.5116

Best score: 0.1818: : 849iter [01:20, 11.67iter/s]
Best score: 0.1818: : 850iter [01:20, 11.67iter/s]
Best score: 0.1818: : 851iter [01:20,  7.47iter/s]
Best score: 0.1818: : 851iter [01:20,  7.47iter/s]
Best score: 0.1818: : 852iter [01:20,  7.47iter/s]
Best score: 0.1818: : 853iter [01:20,  8.39iter/s]
Best score: 0.1818: : 853iter [01:21,  8.39iter/s]
Best score: 0.1818: : 854iter [01:21,  8.39iter/s]
Best score: 0.1818: : 855iter [01:21,  9.17iter/s]
Best score: 0.1818: : 855iter [01:21,  9.17iter/s]
Best score: 0.1818: : 856iter [01:21,  9.17iter/s]
Best score: 0.1818: : 857iter [01:21,  9.80iter/s]
Best score: 0.1818: : 857iter [01:21,  9.80iter/s]
Best score: 0.1818: : 858iter [01:21,  9.80iter/s]
Best score: 0.1818: : 859iter [01:21, 10.33iter/s]
Best score: 0.1812: : 859iter [01:21, 10.33iter/s]
Best score: 0.1812: : 860iter [01:21, 10.33iter/s]
Best score: 0.1812: : 861iter [01:21, 10.56iter/s]
Best score: 0.1812: : 861iter [01:21, 10.56iter/s]
Best score: 0.1812: : 862iter [01:21, 10.56iter/s]
Best score: 0.1812: : 863iter [01:21, 10.85iter/s]
Best score: 0.1812: : 863iter [01:21, 10.85iter/s]
Best score: 0.1812: : 864iter [01:21, 10.85iter/s]
Best score: 0.1812: : 865iter [01:21, 11.09iter/s]
Best score: 0.1812: : 865iter [01:22, 11.09iter/s]
Best score: 0.1812: : 866iter [01:22, 11.09iter/s]
Best score: 0.1812: : 867iter [01:22, 11.25iter/s]
Best score: 0.1812: : 867iter [01:22, 11.25iter/s]
Best score: 0.1812: : 868iter [01:22, 11.25iter/s]
Best score: 0.1812: : 869iter [01:22, 11.37iter/s]
Best score: 0.1795: : 869iter [01:22, 11.37iter/s]
Best score: 0.1795: : 870iter [01:22, 11.37iter/s]
Best score: 0.1795: : 871iter [01:22, 11.23iter/s]
Best score: 0.1795: : 871iter [01:22, 11.23iter/s]
Best score: 0.1795: : 872iter [01:22, 11.23iter/s]
Best score: 0.1795: : 873iter [01:22, 11.40iter/s]
Best score: 0.1795: : 873iter [01:22, 11.40iter/s]
Best score: 0.1795: : 874iter [01:22, 11.40iter/s]
Best score: 0.1795: : 875iter [01:22, 11.52iter/s]
Best score: 0.1795: : 875iter [01:22, 11.52iter/s]
Best score: 0.1795: : 876iter [01:23, 11.52iter/s]
Best score: 0.1795: : 877iter [01:23, 11.60iter/s]
Best score: 0.1795: : 877iter [01:23, 11.60iter/s]
Best score: 0.1795: : 878iter [01:23, 11.60iter/s]
Best score: 0.1795: : 879iter [01:23, 11.66iter/s]
Best score: 0.1792: : 879iter [01:23, 11.66iter/s]
Best score: 0.1792: : 880iter [01:23, 11.66iter/s]
Best score: 0.1792: : 881iter [01:23, 11.51iter/s]
Best score: 0.1792: : 881iter [01:23, 11.51iter/s]
Best score: 0.1792: : 882iter [01:23, 11.51iter/s]
Best score: 0.1792: : 883iter [01:23, 11.59iter/s]
Best score: 0.1792: : 883iter [01:23, 11.59iter/s]
Best score: 0.1792: : 884iter [01:23, 11.59iter/s]
Best score: 0.1792: : 885iter [01:23, 11.66iter/s]
Best score: 0.1792: : 885iter [01:23, 11.66iter/s]
Best score: 0.1792: : 886iter [01:23, 11.66iter/s]
Best score: 0.1792: : 887iter [01:23, 11.65iter/s]
Best score: 0.1792: : 887iter [01:23, 11.65iter/s]
Best score: 0.1792: : 888iter [01:24, 11.65iter/s]
Best score: 0.1792: : 889iter [01:24, 11.67iter/s]
Best score: 0.1775: : 889iter [01:24, 11.67iter/s]
Best score: 0.1775: : 890iter [01:24, 11.67iter/s]
Best score: 0.1775: : 891iter [01:24, 11.43iter/s]
Best score: 0.1775: : 891iter [01:24, 11.43iter/s]
Best score: 0.1775: : 892iter [01:24, 11.43iter/s]
Best score: 0.1775: : 893iter [01:24, 11.52iter/s]
Best score: 0.1775: : 893iter [01:24, 11.52iter/s]
Best score: 0.1775: : 894iter [01:24, 11.52iter/s]
Best score: 0.1775: : 895iter [01:24, 11.60iter/s]
Best score: 0.1775: : 895iter [01:24, 11.60iter/s]
Best score: 0.1775: : 896iter [01:24, 11.60iter/s]
Best score: 0.1775: : 897iter [01:24, 11.67iter/s]
Best score: 0.1775: : 897iter [01:24, 11.67iter/s]
Best score: 0.1775: : 898iter [01:24, 11.67iter/s]
Best score: 0.1775: : 899iter [01:24, 11.72iter/s]
[ITER 900] Best: 0.1772
[PARAMS] Current best parameters:
  fx: 536.2428
  fy: 536.3484
  px: 907.1538
  py: 918.4603
  k1: -0.00644087
  k2: 0.00124060
  k3: 0.00016905
  k4: -0.00070836
  p1: -0.01229819
  p2: -0.00924986
  p3: 0.01794558
  p4: 0.01229971
  s1: -0.0132
  s2: -0.0115
  s3: -0.0119
  s4: -0.0141
  tilt_x: 0.0089
  tilt_y: -0.0170
  scale: 2.9715
  rotation: -0.5167

Best score: 0.1772: : 899iter [01:24, 11.72iter/s]
Best score: 0.1772: : 900iter [01:25, 11.72iter/s]
Best score: 0.1772: : 901iter [01:25,  7.54iter/s]
Best score: 0.1772: : 901iter [01:25,  7.54iter/s]
Best score: 0.1772: : 902iter [01:25,  7.54iter/s]
Best score: 0.1772: : 903iter [01:25,  8.43iter/s]
Best score: 0.1772: : 903iter [01:25,  8.43iter/s]
Best score: 0.1772: : 904iter [01:25,  8.43iter/s]
Best score: 0.1772: : 905iter [01:25,  9.22iter/s]
Best score: 0.1772: : 905iter [01:25,  9.22iter/s]
Best score: 0.1772: : 906iter [01:25,  9.22iter/s]
Best score: 0.1772: : 907iter [01:25,  9.86iter/s]
Best score: 0.1772: : 907iter [01:25,  9.86iter/s]
Best score: 0.1772: : 908iter [01:26,  9.86iter/s]
Best score: 0.1772: : 909iter [01:26, 10.36iter/s]
Best score: 0.1772: : 909iter [01:26, 10.36iter/s]
Best score: 0.1772: : 910iter [01:26, 10.36iter/s]
Best score: 0.1772: : 911iter [01:26, 10.58iter/s]
Best score: 0.1772: : 911iter [01:26, 10.58iter/s]
Best score: 0.1772: : 912iter [01:26, 10.58iter/s]
Best score: 0.1772: : 913iter [01:26, 10.87iter/s]
Best score: 0.1772: : 913iter [01:26, 10.87iter/s]
Best score: 0.1772: : 914iter [01:26, 10.87iter/s]
Best score: 0.1772: : 915iter [01:26, 11.13iter/s]
Best score: 0.1772: : 915iter [01:26, 11.13iter/s]
Best score: 0.1772: : 916iter [01:26, 11.13iter/s]
Best score: 0.1772: : 917iter [01:26, 11.31iter/s]
Best score: 0.1772: : 917iter [01:26, 11.31iter/s]
Best score: 0.1772: : 918iter [01:26, 11.31iter/s]
Best score: 0.1772: : 919iter [01:26, 11.46iter/s]
Best score: 0.1772: : 919iter [01:27, 11.46iter/s]
Best score: 0.1772: : 920iter [01:27, 11.46iter/s]
Best score: 0.1772: : 921iter [01:27, 11.35iter/s]
Best score: 0.1772: : 921iter [01:27, 11.35iter/s]
Best score: 0.1772: : 922iter [01:27, 11.35iter/s]
Best score: 0.1772: : 923iter [01:27, 11.43iter/s]
Best score: 0.1772: : 923iter [01:27, 11.43iter/s]
Best score: 0.1772: : 924iter [01:27, 11.43iter/s]
Best score: 0.1772: : 925iter [01:27, 11.55iter/s]
Best score: 0.1772: : 925iter [01:27, 11.55iter/s]
Best score: 0.1772: : 926iter [01:27, 11.55iter/s]
Best score: 0.1772: : 927iter [01:27, 11.63iter/s]
Best score: 0.1772: : 927iter [01:27, 11.63iter/s]
Best score: 0.1772: : 928iter [01:27, 11.63iter/s]
Best score: 0.1772: : 929iter [01:27, 11.61iter/s]
Best score: 0.1772: : 929iter [01:27, 11.61iter/s]
Best score: 0.1772: : 930iter [01:27, 11.61iter/s]
Best score: 0.1772: : 931iter [01:27, 11.45iter/s]
Best score: 0.1772: : 931iter [01:28, 11.45iter/s]
Best score: 0.1772: : 932iter [01:28, 11.45iter/s]
Best score: 0.1772: : 933iter [01:28, 11.57iter/s]
Best score: 0.1772: : 933iter [01:28, 11.57iter/s]
Best score: 0.1772: : 934iter [01:28, 11.57iter/s]
Best score: 0.1772: : 935iter [01:28, 11.59iter/s]
Best score: 0.1772: : 935iter [01:28, 11.59iter/s]
Best score: 0.1772: : 936iter [01:28, 11.59iter/s]
Best score: 0.1772: : 937iter [01:28, 11.61iter/s]
Best score: 0.1772: : 937iter [01:28, 11.61iter/s]
Best score: 0.1772: : 938iter [01:28, 11.61iter/s]
Best score: 0.1772: : 939iter [01:28, 11.61iter/s]
Best score: 0.1756: : 939iter [01:28, 11.61iter/s]
Best score: 0.1756: : 940iter [01:28, 11.61iter/s]
Best score: 0.1756: : 941iter [01:28, 11.40iter/s]
Best score: 0.1756: : 941iter [01:28, 11.40iter/s]
Best score: 0.1756: : 942iter [01:29, 11.40iter/s]
Best score: 0.1756: : 943iter [01:29, 11.52iter/s]
Best score: 0.1756: : 943iter [01:29, 11.52iter/s]
Best score: 0.1756: : 944iter [01:29, 11.52iter/s]
Best score: 0.1756: : 945iter [01:29, 11.59iter/s]
Best score: 0.1756: : 945iter [01:29, 11.59iter/s]
Best score: 0.1756: : 946iter [01:29, 11.59iter/s]
Best score: 0.1756: : 947iter [01:29, 11.65iter/s]
Best score: 0.1756: : 947iter [01:29, 11.65iter/s]
Best score: 0.1756: : 948iter [01:29, 11.65iter/s]
Best score: 0.1756: : 949iter [01:29, 11.69iter/s]
[ITER 950] Best: 0.1750
[PARAMS] Current best parameters:
  fx: 536.5747
  fy: 536.7363
  px: 907.4643
  py: 918.4061
  k1: -0.01547300
  k2: 0.01704620
  k3: -0.01043837
  k4: 0.00180791
  p1: -0.01154484
  p2: -0.00743585
  p3: 0.02299329
  p4: 0.00707778
  s1: -0.0204
  s2: -0.0058
  s3: -0.0185
  s4: -0.0083
  tilt_x: 0.0072
  tilt_y: -0.0151
  scale: 2.9774
  rotation: -0.5197

Best score: 0.1750: : 949iter [01:29, 11.69iter/s]
Best score: 0.1750: : 950iter [01:30, 11.69iter/s]
Best score: 0.1750: : 951iter [01:30,  7.50iter/s]
Best score: 0.1750: : 951iter [01:30,  7.50iter/s]
Best score: 0.1750: : 952iter [01:30,  7.50iter/s]
Best score: 0.1750: : 953iter [01:30,  8.42iter/s]
Best score: 0.1750: : 953iter [01:30,  8.42iter/s]
Best score: 0.1750: : 954iter [01:30,  8.42iter/s]
Best score: 0.1750: : 955iter [01:30,  9.22iter/s]
Best score: 0.1750: : 955iter [01:30,  9.22iter/s]
Best score: 0.1750: : 956iter [01:30,  9.22iter/s]
Best score: 0.1750: : 957iter [01:30,  9.87iter/s]
Best score: 0.1750: : 957iter [01:30,  9.87iter/s]
Best score: 0.1750: : 958iter [01:30,  9.87iter/s]
Best score: 0.1750: : 959iter [01:30, 10.38iter/s]
Best score: 0.1750: : 959iter [01:30, 10.38iter/s]
Best score: 0.1750: : 960iter [01:30, 10.38iter/s]
Best score: 0.1750: : 961iter [01:30, 10.62iter/s]
Best score: 0.1750: : 961iter [01:30, 10.62iter/s]
Best score: 0.1750: : 962iter [01:31, 10.62iter/s]
Best score: 0.1750: : 963iter [01:31, 10.96iter/s]
Best score: 0.1750: : 963iter [01:31, 10.96iter/s]
Best score: 0.1750: : 964iter [01:31, 10.96iter/s]
Best score: 0.1750: : 965iter [01:31, 11.19iter/s]
Best score: 0.1750: : 965iter [01:31, 11.19iter/s]
Best score: 0.1750: : 966iter [01:31, 11.19iter/s]
Best score: 0.1750: : 967iter [01:31, 11.36iter/s]
Best score: 0.1750: : 967iter [01:31, 11.36iter/s]
Best score: 0.1750: : 968iter [01:31, 11.36iter/s]
Best score: 0.1750: : 969iter [01:31, 11.45iter/s]
Best score: 0.1749: : 969iter [01:31, 11.45iter/s]
Best score: 0.1749: : 970iter [01:31, 11.45iter/s]
Best score: 0.1749: : 971iter [01:31, 11.29iter/s]
Best score: 0.1749: : 971iter [01:31, 11.29iter/s]
Best score: 0.1749: : 972iter [01:31, 11.29iter/s]
Best score: 0.1749: : 973iter [01:31, 11.40iter/s]
Best score: 0.1749: : 973iter [01:31, 11.40iter/s]
Best score: 0.1749: : 974iter [01:32, 11.40iter/s]
Best score: 0.1749: : 975iter [01:32, 11.54iter/s]
Best score: 0.1749: : 975iter [01:32, 11.54iter/s]
Best score: 0.1749: : 976iter [01:32, 11.54iter/s]
Best score: 0.1749: : 977iter [01:32, 11.60iter/s]
Best score: 0.1749: : 977iter [01:32, 11.60iter/s]
Best score: 0.1749: : 978iter [01:32, 11.60iter/s]
Best score: 0.1749: : 979iter [01:32, 11.67iter/s]
Best score: 0.1746: : 979iter [01:32, 11.67iter/s]
Best score: 0.1746: : 980iter [01:32, 11.67iter/s]
Best score: 0.1746: : 981iter [01:32, 11.51iter/s]
Best score: 0.1746: : 981iter [01:32, 11.51iter/s]
Best score: 0.1746: : 982iter [01:32, 11.51iter/s]
Best score: 0.1746: : 983iter [01:32, 11.61iter/s]
Best score: 0.1746: : 983iter [01:32, 11.61iter/s]
Best score: 0.1746: : 984iter [01:32, 11.61iter/s]
Best score: 0.1746: : 985iter [01:32, 11.67iter/s]
Best score: 0.1746: : 985iter [01:33, 11.67iter/s]
Best score: 0.1746: : 986iter [01:33, 11.67iter/s]
Best score: 0.1746: : 987iter [01:33, 11.73iter/s]
Best score: 0.1746: : 987iter [01:33, 11.73iter/s]
Best score: 0.1746: : 988iter [01:33, 11.73iter/s]
Best score: 0.1746: : 989iter [01:33, 11.74iter/s]
Best score: 0.1744: : 989iter [01:33, 11.74iter/s]
Best score: 0.1744: : 990iter [01:33, 11.74iter/s]
Best score: 0.1744: : 991iter [01:33, 11.52iter/s]
Best score: 0.1744: : 991iter [01:33, 11.52iter/s]
Best score: 0.1744: : 992iter [01:33, 11.52iter/s]
Best score: 0.1744: : 993iter [01:33, 11.54iter/s]
Best score: 0.1744: : 993iter [01:33, 11.54iter/s]
Best score: 0.1744: : 994iter [01:33, 11.54iter/s]
Best score: 0.1744: : 995iter [01:33, 11.62iter/s]
Best score: 0.1744: : 995iter [01:33, 11.62iter/s]
Best score: 0.1744: : 996iter [01:33, 11.62iter/s]
Best score: 0.1744: : 997iter [01:33, 11.67iter/s]
Best score: 0.1744: : 997iter [01:34, 11.67iter/s]
Best score: 0.1744: : 998iter [01:34, 11.67iter/s]
Best score: 0.1744: : 999iter [01:34, 11.72iter/s]
[ITER 1000] Best: 0.1738
[PARAMS] Current best parameters:
  fx: 535.4475
  fy: 535.6208
  px: 907.3403
  py: 918.5614
  k1: -0.01066284
  k2: 0.01092518
  k3: -0.00689455
  k4: 0.00107976
  p1: -0.01009410
  p2: -0.00540445
  p3: 0.02335774
  p4: 0.00479910
  s1: -0.0226
  s2: -0.0038
  s3: -0.0197
  s4: -0.0064
  tilt_x: 0.0051
  tilt_y: -0.0106
  scale: 2.9749
  rotation: -0.5213

Best score: 0.1738: : 999iter [01:34, 11.72iter/s]
Best score: 0.1738: : 1000iter [01:34, 11.72iter/s]
Best score: 0.1738: : 1001iter [01:34,  7.49iter/s]
Best score: 0.1738: : 1001iter [01:34,  7.49iter/s]
Best score: 0.1738: : 1002iter [01:34,  7.49iter/s]
Best score: 0.1738: : 1003iter [01:34,  8.42iter/s]
Best score: 0.1738: : 1003iter [01:34,  8.42iter/s]
Best score: 0.1738: : 1004iter [01:34,  8.42iter/s]
Best score: 0.1738: : 1005iter [01:34,  9.21iter/s]
Best score: 0.1738: : 1005iter [01:35,  9.21iter/s]
Best score: 0.1738: : 1006iter [01:35,  9.21iter/s]
Best score: 0.1738: : 1007iter [01:35,  9.85iter/s]
Best score: 0.1738: : 1007iter [01:35,  9.85iter/s]
Best score: 0.1738: : 1008iter [01:35,  9.85iter/s]
Best score: 0.1738: : 1009iter [01:35, 10.36iter/s]
Best score: 0.1738: : 1009iter [01:35, 10.36iter/s]
Best score: 0.1738: : 1010iter [01:35, 10.36iter/s]
Best score: 0.1738: : 1011iter [01:35, 10.59iter/s]
Best score: 0.1738: : 1011iter [01:35, 10.59iter/s]
Best score: 0.1738: : 1012iter [01:35, 10.59iter/s]
Best score: 0.1738: : 1013iter [01:35, 10.90iter/s]
Best score: 0.1738: : 1013iter [01:35, 10.90iter/s]
Best score: 0.1738: : 1014iter [01:35, 10.90iter/s]
Best score: 0.1738: : 1015iter [01:35, 11.13iter/s]
Best score: 0.1738: : 1015iter [01:35, 11.13iter/s]
Best score: 0.1738: : 1016iter [01:35, 11.13iter/s]
Best score: 0.1738: : 1017iter [01:35, 11.33iter/s]
Best score: 0.1738: : 1017iter [01:36, 11.33iter/s]
Best score: 0.1738: : 1018iter [01:36, 11.33iter/s]
Best score: 0.1738: : 1019iter [01:36, 11.43iter/s]
Best score: 0.1738: : 1019iter [01:36, 11.43iter/s]
Best score: 0.1738: : 1020iter [01:36, 11.43iter/s]
Best score: 0.1738: : 1021iter [01:36, 11.37iter/s]
Best score: 0.1738: : 1021iter [01:36, 11.37iter/s]
Best score: 0.1738: : 1022iter [01:36, 11.37iter/s]
Best score: 0.1738: : 1023iter [01:36, 11.50iter/s]
Best score: 0.1738: : 1023iter [01:36, 11.50iter/s]
Best score: 0.1738: : 1024iter [01:36, 11.50iter/s]
Best score: 0.1738: : 1025iter [01:36, 11.59iter/s]
Best score: 0.1738: : 1025iter [01:36, 11.59iter/s]
Best score: 0.1738: : 1026iter [01:36, 11.59iter/s]
Best score: 0.1738: : 1027iter [01:36,  9.21iter/s]
Best score: 0.1738: : 1027iter [01:37,  9.21iter/s]
Best score: 0.1738: : 1028iter [01:37,  9.21iter/s]
Best score: 0.1738: : 1029iter [01:37,  9.79iter/s]
Best score: 0.1735: : 1029iter [01:37,  9.79iter/s]
Best score: 0.1735: : 1030iter [01:37,  9.79iter/s]
Best score: 0.1735: : 1031iter [01:37, 10.17iter/s]
Best score: 0.1735: : 1031iter [01:37, 10.17iter/s]
Best score: 0.1735: : 1032iter [01:37, 10.17iter/s]
Best score: 0.1735: : 1033iter [01:37, 10.61iter/s]
Best score: 0.1735: : 1033iter [01:37, 10.61iter/s]
Best score: 0.1735: : 1034iter [01:37, 10.61iter/s]
Best score: 0.1735: : 1035iter [01:37, 10.95iter/s]
Best score: 0.1735: : 1035iter [01:37, 10.95iter/s]
Best score: 0.1735: : 1036iter [01:37, 10.95iter/s]
Best score: 0.1735: : 1037iter [01:37, 11.19iter/s]
Best score: 0.1735: : 1037iter [01:37, 11.19iter/s]
Best score: 0.1735: : 1038iter [01:38, 11.19iter/s]
Best score: 0.1735: : 1039iter [01:38, 11.38iter/s]
Best score: 0.1734: : 1039iter [01:38, 11.38iter/s]
Best score: 0.1734: : 1040iter [01:38, 11.38iter/s]
Best score: 0.1734: : 1041iter [01:38, 11.28iter/s]
Best score: 0.1734: : 1041iter [01:38, 11.28iter/s]
Best score: 0.1734: : 1042iter [01:38, 11.28iter/s]
Best score: 0.1734: : 1043iter [01:38, 11.40iter/s]
Best score: 0.1734: : 1043iter [01:38, 11.40iter/s]
Best score: 0.1734: : 1044iter [01:38, 11.40iter/s]
Best score: 0.1734: : 1045iter [01:38, 11.49iter/s]
Best score: 0.1734: : 1045iter [01:38, 11.49iter/s]
Best score: 0.1734: : 1046iter [01:38, 11.49iter/s]
Best score: 0.1734: : 1047iter [01:38, 11.58iter/s]
Best score: 0.1734: : 1047iter [01:38, 11.58iter/s]
Best score: 0.1734: : 1048iter [01:38, 11.58iter/s]
Best score: 0.1734: : 1049iter [01:38, 11.61iter/s]
[ITER 1050] Best: 0.1734
[PARAMS] Current best parameters:
  fx: 536.0905
  fy: 536.3169
  px: 906.6421
  py: 918.2406
  k1: -0.01442499
  k2: 0.01677389
  k3: -0.01083985
  k4: 0.00201382
  p1: -0.01079413
  p2: -0.00483049
  p3: 0.02690734
  p4: 0.00273540
  s1: -0.0276
  s2: -0.0017
  s3: -0.0230
  s4: -0.0043
  tilt_x: 0.0050
  tilt_y: -0.0061
  scale: 2.9761
  rotation: -0.5135

Best score: 0.1734: : 1049iter [01:38, 11.61iter/s]
Best score: 0.1734: : 1050iter [01:39, 11.61iter/s]
Best score: 0.1734: : 1051iter [01:39,  7.48iter/s]
Best score: 0.1734: : 1051iter [01:39,  7.48iter/s]
Best score: 0.1734: : 1052iter [01:39,  7.48iter/s]
Best score: 0.1734: : 1053iter [01:39,  8.39iter/s]
Best score: 0.1734: : 1053iter [01:39,  8.39iter/s]
Best score: 0.1734: : 1054iter [01:39,  8.39iter/s]
Best score: 0.1734: : 1055iter [01:39,  9.15iter/s]
Best score: 0.1734: : 1055iter [01:39,  9.15iter/s]
Best score: 0.1734: : 1056iter [01:39,  9.15iter/s]
Best score: 0.1734: : 1057iter [01:39,  9.76iter/s]
Best score: 0.1734: : 1057iter [01:39,  9.76iter/s]
Best score: 0.1734: : 1058iter [01:40,  9.76iter/s]
Best score: 0.1734: : 1059iter [01:40, 10.27iter/s]
Best score: 0.1733: : 1059iter [01:40, 10.27iter/s]
Best score: 0.1733: : 1060iter [01:40, 10.27iter/s]
Best score: 0.1733: : 1061iter [01:40, 10.53iter/s]
Best score: 0.1733: : 1061iter [01:40, 10.53iter/s]
Best score: 0.1733: : 1062iter [01:40, 10.53iter/s]
Best score: 0.1733: : 1063iter [01:40, 10.85iter/s]
Best score: 0.1733: : 1063iter [01:40, 10.85iter/s]
Best score: 0.1733: : 1064iter [01:40, 10.85iter/s]
Best score: 0.1733: : 1065iter [01:40, 11.07iter/s]
Best score: 0.1733: : 1065iter [01:40, 11.07iter/s]
Best score: 0.1733: : 1066iter [01:40, 11.07iter/s]
Best score: 0.1733: : 1067iter [01:40, 11.24iter/s]
Best score: 0.1733: : 1067iter [01:40, 11.24iter/s]
Best score: 0.1733: : 1068iter [01:40, 11.24iter/s]
Best score: 0.1733: : 1069iter [01:40, 11.40iter/s]
Best score: 0.1733: : 1069iter [01:41, 11.40iter/s]
Best score: 0.1733: : 1070iter [01:41, 11.40iter/s]
Best score: 0.1733: : 1071iter [01:41, 11.24iter/s]
Best score: 0.1733: : 1071iter [01:41, 11.24iter/s]
Best score: 0.1733: : 1072iter [01:41, 11.24iter/s]
Best score: 0.1733: : 1073iter [01:41, 11.41iter/s]
Best score: 0.1733: : 1073iter [01:41, 11.41iter/s]
Best score: 0.1733: : 1074iter [01:41, 11.41iter/s]
Best score: 0.1733: : 1075iter [01:41, 11.49iter/s]
Best score: 0.1733: : 1075iter [01:41, 11.49iter/s]
Best score: 0.1733: : 1076iter [01:41, 11.49iter/s]
Best score: 0.1733: : 1077iter [01:41, 11.60iter/s]
Best score: 0.1733: : 1077iter [01:41, 11.60iter/s]
Best score: 0.1733: : 1078iter [01:41, 11.60iter/s]
Best score: 0.1733: : 1079iter [01:41, 11.67iter/s]
Best score: 0.1727: : 1079iter [01:41, 11.67iter/s]
Best score: 0.1727: : 1080iter [01:41, 11.67iter/s]
Best score: 0.1727: : 1081iter [01:41, 11.47iter/s]
Best score: 0.1727: : 1081iter [01:42, 11.47iter/s]
Best score: 0.1727: : 1082iter [01:42, 11.47iter/s]
Best score: 0.1727: : 1083iter [01:42, 11.57iter/s]
Best score: 0.1727: : 1083iter [01:42, 11.57iter/s]
Best score: 0.1727: : 1084iter [01:42, 11.57iter/s]
Best score: 0.1727: : 1085iter [01:42, 11.62iter/s]
Best score: 0.1727: : 1085iter [01:42, 11.62iter/s]
Best score: 0.1727: : 1086iter [01:42, 11.62iter/s]
Best score: 0.1727: : 1087iter [01:42, 11.68iter/s]
Best score: 0.1727: : 1087iter [01:42, 11.68iter/s]
Best score: 0.1727: : 1088iter [01:42, 11.68iter/s]
Best score: 0.1727: : 1089iter [01:42, 11.73iter/s]
Best score: 0.1720: : 1089iter [01:42, 11.73iter/s]
Best score: 0.1720: : 1090iter [01:42, 11.73iter/s]
Best score: 0.1720: : 1091iter [01:42, 11.56iter/s]
Best score: 0.1720: : 1091iter [01:42, 11.56iter/s]
Best score: 0.1720: : 1092iter [01:42, 11.56iter/s]
Best score: 0.1720: : 1093iter [01:42, 11.64iter/s]
Best score: 0.1720: : 1093iter [01:43, 11.64iter/s]
Best score: 0.1720: : 1094iter [01:43, 11.64iter/s]
Best score: 0.1720: : 1095iter [01:43, 11.66iter/s]
Best score: 0.1720: : 1095iter [01:43, 11.66iter/s]
Best score: 0.1720: : 1096iter [01:43, 11.66iter/s]
Best score: 0.1720: : 1097iter [01:43, 11.70iter/s]
Best score: 0.1720: : 1097iter [01:43, 11.70iter/s]
Best score: 0.1720: : 1098iter [01:43, 11.70iter/s]
Best score: 0.1720: : 1099iter [01:43, 11.69iter/s]
Best score: 0.1720: : 1099iter [01:43, 11.69iter/s]
[ITER 1100] Best: 0.1720
[PARAMS] Current best parameters:
  fx: 535.9945
  fy: 536.2715
  px: 907.9293
  py: 918.7896
  k1: -0.01452314
  k2: 0.01678632
  k3: -0.01074979
  k4: 0.00198410
  p1: -0.00839363
  p2: -0.00046903
  p3: 0.03248785
  p4: -0.00395642
  s1: -0.0355
  s2: 0.0045
  s3: -0.0300
  s4: 0.0021
  tilt_x: 0.0028
  tilt_y: -0.0033
  scale: 2.9762
  rotation: -0.5168

Best score: 0.1720: : 1100iter [01:43, 10.59iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.172008 -> 0.171266

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 101,336 → 92,946 within 3500mm ring
  Ring polish did not improve score: 0.171266
  Success: True
  Tangential distortion: p1=-0.008383, p2=-0.000454, p3=0.032339, p4=-0.003746
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.1713
[✅] Parameters copied to: /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


-------------------------------------------------------------------
                        Step 4: Undistortion                       
-------------------------------------------------------------------


[DEBUG] Parameters being applied to PTD conversion:
    fx: 535.9944703844436
    fy: 536.2715487698332
    px: 907.9292663423572
    py: 918.7895737974196
    k1: -0.014418677907126044
    k2: 0.016650504029389227
    k3: -0.010795344263461647
    k4: 0.0020380453102003125
    p1: -0.008383382413105262
    p2: -0.00045412302523093547
    p3: 0.0323390591846415
    p4: -0.0037459740712974207
    scale: 2.97638127063223
    rotation: -0.5167893237060172
    mmpp: 3.4003909646866397

[🔄] Converting 1580 frames to PTD, creating debug images for 400 calibration frames...

📁 Rigs:   0%|          | 0/4 [00:00<?, ?rig/s]

   🔄 1500:   0%|          | 0/454 [00:00<?, ?frame/s]

   🔄 1500:   4%|▍         | 18/454 [00:00<00:02, 171.58frame/s]

   🔄 1500:   8%|▊         | 36/454 [00:00<00:02, 171.99frame/s]

   🔄 1500:  12%|█▏        | 54/454 [00:00<00:02, 173.91frame/s]

   🔄 1500:  16%|█▌        | 72/454 [00:00<00:02, 175.33frame/s]

   🔄 1500:  20%|█▉        | 90/454 [00:00<00:02, 174.95frame/s]

   🔄 1500:  24%|██▍       | 108/454 [00:00<00:01, 174.18frame/s]

   🔄 1500:  28%|██▊       | 126/454 [00:00<00:01, 173.91frame/s]

   🔄 1500:  32%|███▏      | 144/454 [00:00<00:01, 173.75frame/s]

   🔄 1500:  36%|███▌      | 162/454 [00:00<00:01, 173.88frame/s]

   🔄 1500:  40%|███▉      | 180/454 [00:01<00:01, 174.39frame/s]

   🔄 1500:  44%|████▎     | 198/454 [00:01<00:01, 174.47frame/s]

   🔄 1500:  48%|████▊     | 216/454 [00:01<00:01, 174.76frame/s]

   🔄 1500:  52%|█████▏    | 234/454 [00:01<00:01, 174.93frame/s]

   🔄 1500:  56%|█████▌    | 252/454 [00:01<00:01, 175.57frame/s]

   🔄 1500:  59%|█████▉    | 270/454 [00:01<00:01, 176.28frame/s]

   🔄 1500:  63%|██████▎   | 288/454 [00:01<00:00, 176.56frame/s]

   🔄 1500:  67%|██████▋   | 306/454 [00:01<00:00, 176.94frame/s]

   🔄 1500:  71%|███████▏  | 324/454 [00:01<00:00, 176.56frame/s]

   🔄 1500:  75%|███████▌  | 342/454 [00:01<00:00, 176.07frame/s]

   🔄 1500:  79%|███████▉  | 360/454 [00:02<00:00, 176.05frame/s]

   🔄 1500:  83%|████████▎ | 378/454 [00:02<00:00, 175.45frame/s]

   🔄 1500:  87%|████████▋ | 396/454 [00:02<00:00, 175.00frame/s]

   🔄 1500:  91%|█████████ | 414/454 [00:02<00:00, 173.79frame/s]

   🔄 1500:  95%|█████████▌| 432/454 [00:02<00:00, 174.41frame/s]

   🔄 1500:  99%|█████████▉| 450/454 [00:02<00:00, 174.01frame/s]

                                                                 
📁 Rigs:  25%|██▌       | 1/4 [00:04<00:14,  4.90s/rig]

   🔄 2000L:   0%|          | 0/420 [00:00<?, ?frame/s]

   🔄 2000L:   4%|▍         | 18/420 [00:00<00:02, 171.70frame/s]

   🔄 2000L:   9%|▊         | 36/420 [00:00<00:02, 172.50frame/s]

   🔄 2000L:  13%|█▎        | 54/420 [00:00<00:02, 174.57frame/s]

   🔄 2000L:  17%|█▋        | 72/420 [00:00<00:01, 175.01frame/s]

   🔄 2000L:  21%|██▏       | 90/420 [00:00<00:01, 174.93frame/s]

   🔄 2000L:  26%|██▌       | 108/420 [00:00<00:01, 174.98frame/s]

   🔄 2000L:  30%|███       | 126/420 [00:00<00:01, 175.09frame/s]

   🔄 2000L:  34%|███▍      | 144/420 [00:00<00:01, 174.53frame/s]

   🔄 2000L:  39%|███▊      | 162/420 [00:00<00:01, 174.18frame/s]

   🔄 2000L:  43%|████▎     | 180/420 [00:01<00:01, 173.85frame/s]

   🔄 2000L:  47%|████▋     | 198/420 [00:01<00:01, 173.15frame/s]

   🔄 2000L:  51%|█████▏    | 216/420 [00:01<00:01, 172.53frame/s]

   🔄 2000L:  56%|█████▌    | 234/420 [00:01<00:01, 171.85frame/s]

   🔄 2000L:  60%|██████    | 252/420 [00:01<00:00, 171.61frame/s]

   🔄 2000L:  64%|██████▍   | 270/420 [00:01<00:00, 171.86frame/s]

   🔄 2000L:  69%|██████▊   | 288/420 [00:01<00:00, 172.28frame/s]

   🔄 2000L:  73%|███████▎  | 306/420 [00:01<00:00, 172.82frame/s]

   🔄 2000L:  77%|███████▋  | 324/420 [00:01<00:00, 173.12frame/s]

   🔄 2000L:  81%|████████▏ | 342/420 [00:01<00:00, 173.14frame/s]

   🔄 2000L:  86%|████████▌ | 360/420 [00:02<00:00, 173.65frame/s]

   🔄 2000L:  90%|█████████ | 378/420 [00:02<00:00, 173.69frame/s]

   🔄 2000L:  94%|█████████▍| 396/420 [00:02<00:00, 173.54frame/s]

   🔄 2000L:  99%|█████████▊| 414/420 [00:02<00:00, 172.50frame/s]

                                                                  
📁 Rigs:  50%|█████     | 2/4 [00:09<00:09,  4.53s/rig]

   🔄 2000R:   0%|          | 0/376 [00:00<?, ?frame/s]

   🔄 2000R:   5%|▍         | 17/376 [00:00<00:02, 168.25frame/s]

   🔄 2000R:   9%|▉         | 35/376 [00:00<00:02, 170.10frame/s]

   🔄 2000R:  14%|█▍        | 53/376 [00:00<00:01, 172.43frame/s]

   🔄 2000R:  19%|█▉        | 71/376 [00:00<00:01, 173.58frame/s]

   🔄 2000R:  24%|██▎       | 89/376 [00:00<00:01, 174.14frame/s]

   🔄 2000R:  28%|██▊       | 107/376 [00:00<00:01, 175.01frame/s]

   🔄 2000R:  33%|███▎      | 125/376 [00:00<00:01, 175.41frame/s]

   🔄 2000R:  38%|███▊      | 143/376 [00:00<00:01, 175.76frame/s]

   🔄 2000R:  43%|████▎     | 161/376 [00:00<00:01, 176.16frame/s]

   🔄 2000R:  48%|████▊     | 179/376 [00:01<00:01, 176.00frame/s]

   🔄 2000R:  52%|█████▏    | 197/376 [00:01<00:01, 175.60frame/s]

   🔄 2000R:  57%|█████▋    | 215/376 [00:01<00:00, 174.99frame/s]

   🔄 2000R:  62%|██████▏   | 233/376 [00:01<00:00, 175.05frame/s]

   🔄 2000R:  67%|██████▋   | 251/376 [00:01<00:00, 174.74frame/s]

   🔄 2000R:  72%|███████▏  | 269/376 [00:01<00:00, 175.01frame/s]

   🔄 2000R:  76%|███████▋  | 287/376 [00:01<00:00, 174.81frame/s]

   🔄 2000R:  81%|████████  | 305/376 [00:01<00:00, 175.17frame/s]

   🔄 2000R:  86%|████████▌ | 323/376 [00:01<00:00, 175.49frame/s]

   🔄 2000R:  91%|█████████ | 341/376 [00:01<00:00, 175.15frame/s]

   🔄 2000R:  95%|█████████▌| 359/376 [00:02<00:00, 173.87frame/s]

                                                                  
📁 Rigs:  75%|███████▌  | 3/4 [00:13<00:04,  4.28s/rig]

   🔄 1000:   0%|          | 0/330 [00:00<?, ?frame/s]

   🔄 1000:   5%|▌         | 18/330 [00:00<00:01, 176.82frame/s]

   🔄 1000:  11%|█         | 36/330 [00:00<00:01, 178.47frame/s]

   🔄 1000:  17%|█▋        | 55/330 [00:00<00:01, 179.86frame/s]

   🔄 1000:  22%|██▏       | 74/330 [00:00<00:01, 180.03frame/s]

   🔄 1000:  28%|██▊       | 93/330 [00:00<00:01, 179.89frame/s]

   🔄 1000:  34%|███▎      | 111/330 [00:00<00:01, 179.48frame/s]

   🔄 1000:  39%|███▉      | 130/330 [00:00<00:01, 179.63frame/s]

   🔄 1000:  45%|████▍     | 148/330 [00:00<00:01, 179.65frame/s]

   🔄 1000:  51%|█████     | 167/330 [00:00<00:00, 180.60frame/s]

   🔄 1000:  56%|█████▋    | 186/330 [00:01<00:00, 182.04frame/s]

   🔄 1000:  62%|██████▏   | 205/330 [00:01<00:00, 182.21frame/s]

   🔄 1000:  68%|██████▊   | 224/330 [00:01<00:00, 181.54frame/s]

   🔄 1000:  74%|███████▎  | 243/330 [00:01<00:00, 181.59frame/s]

   🔄 1000:  79%|███████▉  | 262/330 [00:01<00:00, 181.15frame/s]

   🔄 1000:  85%|████████▌ | 281/330 [00:01<00:00, 181.41frame/s]

   🔄 1000:  91%|█████████ | 300/330 [00:01<00:00, 181.55frame/s]

   🔄 1000:  97%|█████████▋| 319/330 [00:01<00:00, 181.90frame/s]

                                                                 
📁 Rigs: 100%|██████████| 4/4 [00:16<00:00,  3.86s/rig]
📁 Rigs: 100%|██████████| 4/4 [00:16<00:00,  4.09s/rig]
[✅] Saved PTDs: /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/4_undistorted/output/ptd

📁 Rigs:   0%|          | 0/4 [00:00<?, ?rig/s]

   🔄 1500:   0%|          | 0/100 [00:00<?, ?frame/s]

   🔄 1500:  18%|█▊        | 18/100 [00:00<00:00, 173.56frame/s]

   🔄 1500:  36%|███▌      | 36/100 [00:00<00:00, 172.53frame/s]

   🔄 1500:  54%|█████▍    | 54/100 [00:00<00:00, 174.03frame/s]

   🔄 1500:  72%|███████▏  | 72/100 [00:00<00:00, 174.09frame/s]

   🔄 1500:  90%|█████████ | 90/100 [00:00<00:00, 173.35frame/s]

                                                                
📁 Rigs:  25%|██▌       | 1/4 [00:00<00:02,  1.09rig/s]

   🔄 2000L:   0%|          | 0/100 [00:00<?, ?frame/s]

   🔄 2000L:  18%|█▊        | 18/100 [00:00<00:00, 172.82frame/s]

   🔄 2000L:  36%|███▌      | 36/100 [00:00<00:00, 172.89frame/s]

   🔄 2000L:  54%|█████▍    | 54/100 [00:00<00:00, 172.80frame/s]

   🔄 2000L:  72%|███████▏  | 72/100 [00:00<00:00, 173.10frame/s]

   🔄 2000L:  90%|█████████ | 90/100 [00:00<00:00, 174.04frame/s]

                                                                 
📁 Rigs:  50%|█████     | 2/4 [00:02<00:02,  1.04s/rig]

   🔄 2000R:   0%|          | 0/100 [00:00<?, ?frame/s]

   🔄 2000R:  18%|█▊        | 18/100 [00:00<00:00, 172.63frame/s]

   🔄 2000R:  36%|███▌      | 36/100 [00:00<00:00, 172.93frame/s]

   🔄 2000R:  54%|█████▍    | 54/100 [00:00<00:00, 172.99frame/s]

   🔄 2000R:  72%|███████▏  | 72/100 [00:00<00:00, 173.06frame/s]

   🔄 2000R:  90%|█████████ | 90/100 [00:00<00:00, 173.99frame/s]

                                                                 
📁 Rigs:  75%|███████▌  | 3/4 [00:02<00:00,  1.00rig/s]

   🔄 1000:   0%|          | 0/100 [00:00<?, ?frame/s]

   🔄 1000:  18%|█▊        | 18/100 [00:00<00:00, 178.10frame/s]

   🔄 1000:  36%|███▌      | 36/100 [00:00<00:00, 178.86frame/s]

   🔄 1000:  55%|█████▌    | 55/100 [00:00<00:00, 179.87frame/s]

   🔄 1000:  73%|███████▎  | 73/100 [00:00<00:00, 179.74frame/s]

   🔄 1000:  91%|█████████ | 91/100 [00:00<00:00, 179.72frame/s]

                                                                
📁 Rigs: 100%|██████████| 4/4 [00:04<00:00,  1.03s/rig]
📁 Rigs: 100%|██████████| 4/4 [00:04<00:00,  1.02s/rig]
[✅] Saved PTDs: /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/4_undistorted/temp_ptd
[WARN] No .tfd files found for serial extraction
[WARN] Failed to extract serial number from .tfd file. Check that .tfd files exist and contain 'LASERbidh' or 'LASERbidg' pattern. Using 'unknown' as fallback.

📤 Writing LUT:   0%|          | 0/3240000 [00:00<?, ?px/s]
📤 Writing LUT:   2%|▏         | 77443/3240000 [00:00<00:04, 774428.89px/s]
📤 Writing LUT:   5%|▍         | 160520/3240000 [00:00<00:03, 807568.89px/s]
📤 Writing LUT:   8%|▊         | 243237/3240000 [00:00<00:03, 816517.73px/s]
📤 Writing LUT:  10%|█         | 326346/3240000 [00:00<00:03, 822267.13px/s]
📤 Writing LUT:  13%|█▎        | 412018/3240000 [00:00<00:03, 834687.73px/s]
📤 Writing LUT:  15%|█▌        | 496878/3240000 [00:00<00:03, 839414.76px/s]
📤 Writing LUT:  18%|█▊        | 581230/3240000 [00:00<00:03, 840756.46px/s]
📤 Writing LUT:  21%|██        | 666436/3240000 [00:00<00:03, 844352.00px/s]
📤 Writing LUT:  23%|██▎       | 752839/3240000 [00:00<00:02, 850503.23px/s]
📤 Writing LUT:  26%|██▌       | 838379/3240000 [00:01<00:02, 852013.33px/s]
📤 Writing LUT:  29%|██▊       | 924135/3240000 [00:01<00:02, 853708.65px/s]
📤 Writing LUT:  31%|███       | 1010983/3240000 [00:01<00:02, 858200.61px/s]
📤 Writing LUT:  34%|███▍      | 1097651/3240000 [00:01<00:02, 860767.06px/s]
📤 Writing LUT:  37%|███▋      | 1183728/3240000 [00:01<00:02, 858640.50px/s]
📤 Writing LUT:  39%|███▉      | 1271307/3240000 [00:01<00:02, 863798.09px/s]
📤 Writing LUT:  42%|████▏     | 1357689/3240000 [00:01<00:02, 859309.88px/s]
📤 Writing LUT:  45%|████▍     | 1443627/3240000 [00:01<00:02, 854637.49px/s]
📤 Writing LUT:  47%|████▋     | 1529656/3240000 [00:01<00:01, 856323.81px/s]
📤 Writing LUT:  50%|████▉     | 1617416/3240000 [00:01<00:01, 862681.14px/s]
📤 Writing LUT:  53%|█████▎    | 1703692/3240000 [00:02<00:01, 859930.33px/s]
📤 Writing LUT:  55%|█████▌    | 1793078/3240000 [00:02<00:01, 870064.73px/s]
📤 Writing LUT:  58%|█████▊    | 1880094/3240000 [00:02<00:01, 866850.80px/s]
📤 Writing LUT:  61%|██████    | 1966788/3240000 [00:02<00:01, 863028.87px/s]
📤 Writing LUT:  63%|██████▎   | 2053693/3240000 [00:02<00:01, 864822.15px/s]
📤 Writing LUT:  66%|██████▌   | 2143027/3240000 [00:02<00:01, 873335.94px/s]
📤 Writing LUT:  69%|██████▉   | 2232829/3240000 [00:02<00:01, 880717.03px/s]
📤 Writing LUT:  72%|███████▏  | 2320910/3240000 [00:02<00:01, 872875.84px/s]
📤 Writing LUT:  74%|███████▍  | 2408218/3240000 [00:02<00:00, 869083.28px/s]
📤 Writing LUT:  77%|███████▋  | 2496157/3240000 [00:02<00:00, 872146.62px/s]
📤 Writing LUT:  80%|███████▉  | 2583962/3240000 [00:03<00:00, 873906.00px/s]
📤 Writing LUT:  82%|████████▏ | 2671954/3240000 [00:03<00:00, 875700.35px/s]
📤 Writing LUT:  85%|████████▌ | 2759891/3240000 [00:03<00:00, 876797.62px/s]
📤 Writing LUT:  88%|████████▊ | 2848227/3240000 [00:03<00:00, 878761.88px/s]
📤 Writing LUT:  91%|█████████ | 2937935/3240000 [00:03<00:00, 884248.97px/s]
📤 Writing LUT:  93%|█████████▎| 3027147/3240000 [00:03<00:00, 886607.50px/s]
📤 Writing LUT:  96%|█████████▌| 3115811/3240000 [00:03<00:00, 874897.56px/s]
📤 Writing LUT:  99%|█████████▉| 3205625/3240000 [00:03<00:00, 881801.68px/s]
📤 Writing LUT: 100%|██████████| 3240000/3240000 [00:03<00:00, 862585.41px/s]
[✅] LUT written to: /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MCDP3D-SL-012_W039(6)_2026-03-04' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/MCDP3D-SL-012_W039(6)_2026-03-04_unknown.lut

-------------------------------------------------------------------
                          Step 5: Heatmap                          
-------------------------------------------------------------------

[ℹ️] Detected device type: SMD_P3D (rigs: [1000, 1500, 2000]mm)

📁 Rigs (heatmap):   0%|          | 0/4 [00:00<?, ?rig/s]

   🔥 1500:   0%|          | 0/454 [00:00<?, ?frame/s]

   🔥 1500:   2%|▏         | 9/454 [00:00<00:05, 81.99frame/s]

   🔥 1500:   4%|▍         | 19/454 [00:00<00:04, 87.10frame/s]

   🔥 1500:   6%|▋         | 29/454 [00:00<00:04, 88.60frame/s]

   🔥 1500:   8%|▊         | 38/454 [00:00<00:04, 89.00frame/s]

   🔥 1500:  10%|█         | 47/454 [00:00<00:04, 87.95frame/s]

   🔥 1500:  12%|█▏        | 56/454 [00:00<00:04, 87.41frame/s]

   🔥 1500:  14%|█▍        | 65/454 [00:00<00:04, 87.06frame/s]

   🔥 1500:  16%|█▋        | 74/454 [00:00<00:04, 85.63frame/s]

   🔥 1500:  18%|█▊        | 83/454 [00:00<00:04, 83.00frame/s]

   🔥 1500:  20%|██        | 92/454 [00:01<00:04, 81.33frame/s]

   🔥 1500:  22%|██▏       | 101/454 [00:01<00:04, 80.21frame/s]

   🔥 1500:  24%|██▍       | 110/454 [00:01<00:04, 79.85frame/s]

   🔥 1500:  26%|██▌       | 118/454 [00:01<00:04, 79.36frame/s]

   🔥 1500:  28%|██▊       | 126/454 [00:01<00:04, 79.04frame/s]

   🔥 1500:  30%|██▉       | 134/454 [00:01<00:04, 78.91frame/s]

   🔥 1500:  31%|███▏      | 142/454 [00:01<00:03, 78.77frame/s]

   🔥 1500:  33%|███▎      | 150/454 [00:01<00:03, 78.60frame/s]

   🔥 1500:  35%|███▍      | 158/454 [00:01<00:03, 78.28frame/s]

   🔥 1500:  37%|███▋      | 166/454 [00:02<00:03, 77.76frame/s]

   🔥 1500:  38%|███▊      | 174/454 [00:02<00:03, 77.92frame/s]

   🔥 1500:  40%|████      | 182/454 [00:02<00:03, 77.82frame/s]

   🔥 1500:  42%|████▏     | 191/454 [00:02<00:03, 78.62frame/s]

   🔥 1500:  44%|████▍     | 199/454 [00:02<00:03, 78.82frame/s]

   🔥 1500:  46%|████▌     | 208/454 [00:02<00:03, 79.46frame/s]

   🔥 1500:  48%|████▊     | 217/454 [00:02<00:02, 79.69frame/s]

   🔥 1500:  50%|████▉     | 226/454 [00:02<00:02, 80.04frame/s]

   🔥 1500:  52%|█████▏    | 235/454 [00:02<00:02, 80.75frame/s]

   🔥 1500:  54%|█████▎    | 244/454 [00:03<00:02, 81.40frame/s]

   🔥 1500:  56%|█████▌    | 253/454 [00:03<00:02, 81.97frame/s]

   🔥 1500:  58%|█████▊    | 262/454 [00:03<00:02, 83.30frame/s]

   🔥 1500:  60%|█████▉    | 271/454 [00:03<00:02, 84.39frame/s]

   🔥 1500:  62%|██████▏   | 280/454 [00:03<00:02, 85.42frame/s]

   🔥 1500:  64%|██████▎   | 289/454 [00:03<00:01, 84.98frame/s]

   🔥 1500:  66%|██████▌   | 298/454 [00:03<00:01, 83.44frame/s]

   🔥 1500:  68%|██████▊   | 307/454 [00:03<00:01, 81.74frame/s]

   🔥 1500:  70%|██████▉   | 316/454 [00:03<00:01, 80.49frame/s]

   🔥 1500:  72%|███████▏  | 325/454 [00:03<00:01, 79.49frame/s]

   🔥 1500:  73%|███████▎  | 333/454 [00:04<00:01, 79.22frame/s]

   🔥 1500:  75%|███████▌  | 341/454 [00:04<00:01, 78.60frame/s]

   🔥 1500:  77%|███████▋  | 349/454 [00:04<00:01, 77.93frame/s]

   🔥 1500:  79%|███████▊  | 357/454 [00:04<00:01, 76.77frame/s]

   🔥 1500:  80%|████████  | 365/454 [00:04<00:01, 76.49frame/s]

   🔥 1500:  82%|████████▏ | 373/454 [00:04<00:01, 76.40frame/s]

   🔥 1500:  84%|████████▍ | 381/454 [00:04<00:00, 76.70frame/s]

   🔥 1500:  86%|████████▌ | 389/454 [00:04<00:00, 77.27frame/s]

   🔥 1500:  87%|████████▋ | 397/454 [00:04<00:00, 76.98frame/s]

   🔥 1500:  89%|████████▉ | 405/454 [00:05<00:00, 76.88frame/s]

   🔥 1500:  91%|█████████ | 413/454 [00:05<00:00, 76.40frame/s]

   🔥 1500:  93%|█████████▎| 422/454 [00:05<00:00, 78.56frame/s]

   🔥 1500:  95%|█████████▌| 432/454 [00:05<00:00, 82.21frame/s]

   🔥 1500:  97%|█████████▋| 441/454 [00:05<00:00, 84.09frame/s]

   🔥 1500:  99%|█████████▉| 450/454 [00:05<00:00, 85.79frame/s]

                                                                [✅] 1500: /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/5_heatmap/1500_heatmap.png
[✅] 1500 (fitted): /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/5_heatmap/1500_heatmap_fitted.png

📁 Rigs (heatmap):  25%|██▌       | 1/4 [00:07<00:21,  7.12s/rig]

   🔥 2000L:   0%|          | 0/420 [00:00<?, ?frame/s]

   🔥 2000L:   2%|▏         | 8/420 [00:00<00:05, 75.41frame/s]

   🔥 2000L:   4%|▍         | 17/420 [00:00<00:04, 81.74frame/s]

   🔥 2000L:   6%|▌         | 26/420 [00:00<00:04, 83.72frame/s]

   🔥 2000L:   8%|▊         | 35/420 [00:00<00:04, 85.40frame/s]

   🔥 2000L:  11%|█         | 45/420 [00:00<00:04, 89.52frame/s]

   🔥 2000L:  13%|█▎        | 55/420 [00:00<00:04, 89.92frame/s]

   🔥 2000L:  15%|█▌        | 64/420 [00:00<00:04, 88.33frame/s]

   🔥 2000L:  17%|█▋        | 73/420 [00:00<00:03, 86.87frame/s]

   🔥 2000L:  20%|█▉        | 82/420 [00:00<00:03, 85.32frame/s]

   🔥 2000L:  22%|██▏       | 91/420 [00:01<00:03, 84.71frame/s]

   🔥 2000L:  24%|██▍       | 100/420 [00:01<00:03, 83.55frame/s]

   🔥 2000L:  26%|██▌       | 109/420 [00:01<00:03, 83.83frame/s]

   🔥 2000L:  28%|██▊       | 118/420 [00:01<00:03, 84.91frame/s]

   🔥 2000L:  30%|███       | 128/420 [00:01<00:03, 86.74frame/s]

   🔥 2000L:  33%|███▎      | 137/420 [00:01<00:03, 86.62frame/s]

   🔥 2000L:  35%|███▍      | 146/420 [00:01<00:03, 87.15frame/s]

   🔥 2000L:  37%|███▋      | 155/420 [00:01<00:03, 86.57frame/s]

   🔥 2000L:  39%|███▉      | 164/420 [00:01<00:02, 86.80frame/s]

   🔥 2000L:  41%|████      | 173/420 [00:02<00:02, 87.13frame/s]

   🔥 2000L:  43%|████▎     | 182/420 [00:02<00:02, 86.54frame/s]

   🔥 2000L:  45%|████▌     | 191/420 [00:02<00:02, 86.47frame/s]

   🔥 2000L:  48%|████▊     | 200/420 [00:02<00:02, 86.25frame/s]

   🔥 2000L:  50%|████▉     | 209/420 [00:02<00:02, 86.13frame/s]

   🔥 2000L:  52%|█████▏    | 218/420 [00:02<00:02, 86.56frame/s]

   🔥 2000L:  54%|█████▍    | 227/420 [00:02<00:02, 86.37frame/s]

   🔥 2000L:  56%|█████▌    | 236/420 [00:02<00:02, 85.43frame/s]

   🔥 2000L:  58%|█████▊    | 245/420 [00:02<00:02, 84.93frame/s]

   🔥 2000L:  60%|██████    | 254/420 [00:02<00:01, 85.35frame/s]

   🔥 2000L:  63%|██████▎   | 263/420 [00:03<00:01, 85.56frame/s]

   🔥 2000L:  65%|██████▍   | 272/420 [00:03<00:01, 85.59frame/s]

   🔥 2000L:  67%|██████▋   | 281/420 [00:03<00:01, 86.21frame/s]

   🔥 2000L:  69%|██████▉   | 290/420 [00:03<00:01, 86.56frame/s]

   🔥 2000L:  71%|███████   | 299/420 [00:03<00:01, 87.38frame/s]

   🔥 2000L:  73%|███████▎  | 308/420 [00:03<00:01, 88.13frame/s]

   🔥 2000L:  76%|███████▌  | 318/420 [00:03<00:01, 89.85frame/s]

   🔥 2000L:  78%|███████▊  | 328/420 [00:03<00:01, 91.15frame/s]

   🔥 2000L:  80%|████████  | 338/420 [00:03<00:00, 90.80frame/s]

   🔥 2000L:  83%|████████▎ | 348/420 [00:04<00:00, 88.75frame/s]

   🔥 2000L:  85%|████████▌ | 357/420 [00:04<00:00, 88.18frame/s]

   🔥 2000L:  87%|████████▋ | 366/420 [00:04<00:00, 88.19frame/s]

   🔥 2000L:  89%|████████▉ | 375/420 [00:04<00:00, 87.96frame/s]

   🔥 2000L:  91%|█████████▏| 384/420 [00:04<00:00, 87.75frame/s]

   🔥 2000L:  94%|█████████▎| 393/420 [00:04<00:00, 87.97frame/s]

   🔥 2000L:  96%|█████████▌| 402/420 [00:04<00:00, 86.84frame/s]

   🔥 2000L:  98%|█████████▊| 411/420 [00:04<00:00, 86.37frame/s]

   🔥 2000L: 100%|██████████| 420/420 [00:04<00:00, 86.65frame/s]

                                                                 [✅] 2000L: /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/5_heatmap/2000L_heatmap.png
[✅] 2000L (fitted): /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/5_heatmap/2000L_heatmap_fitted.png

📁 Rigs (heatmap):  50%|█████     | 2/4 [00:13<00:13,  6.75s/rig]

   🔥 2000R:   0%|          | 0/376 [00:00<?, ?frame/s]

   🔥 2000R:   2%|▏         | 8/376 [00:00<00:04, 78.49frame/s]

   🔥 2000R:   4%|▍         | 16/376 [00:00<00:04, 79.29frame/s]

   🔥 2000R:   7%|▋         | 25/376 [00:00<00:04, 81.17frame/s]

   🔥 2000R:   9%|▉         | 34/376 [00:00<00:04, 82.26frame/s]

   🔥 2000R:  11%|█▏        | 43/376 [00:00<00:04, 82.15frame/s]

   🔥 2000R:  14%|█▍        | 52/376 [00:00<00:03, 81.58frame/s]

   🔥 2000R:  16%|█▌        | 61/376 [00:00<00:03, 81.62frame/s]

   🔥 2000R:  19%|█▊        | 70/376 [00:00<00:03, 81.77frame/s]

   🔥 2000R:  21%|██        | 79/376 [00:00<00:03, 81.49frame/s]

   🔥 2000R:  23%|██▎       | 88/376 [00:01<00:03, 81.58frame/s]

   🔥 2000R:  26%|██▌       | 97/376 [00:01<00:03, 80.64frame/s]

   🔥 2000R:  28%|██▊       | 106/376 [00:01<00:03, 80.80frame/s]

   🔥 2000R:  31%|███       | 115/376 [00:01<00:03, 80.81frame/s]

   🔥 2000R:  33%|███▎      | 124/376 [00:01<00:03, 81.85frame/s]

   🔥 2000R:  36%|███▌      | 134/376 [00:01<00:02, 84.45frame/s]

   🔥 2000R:  38%|███▊      | 144/376 [00:01<00:02, 86.32frame/s]

   🔥 2000R:  41%|████      | 154/376 [00:01<00:02, 87.42frame/s]

   🔥 2000R:  44%|████▎     | 164/376 [00:01<00:02, 89.14frame/s]

   🔥 2000R:  46%|████▌     | 173/376 [00:02<00:02, 88.71frame/s]

   🔥 2000R:  48%|████▊     | 182/376 [00:02<00:02, 88.48frame/s]

   🔥 2000R:  51%|█████     | 191/376 [00:02<00:02, 88.27frame/s]

   🔥 2000R:  53%|█████▎    | 200/376 [00:02<00:01, 88.10frame/s]

   🔥 2000R:  56%|█████▌    | 209/376 [00:02<00:01, 88.51frame/s]

   🔥 2000R:  58%|█████▊    | 218/376 [00:02<00:01, 88.78frame/s]

   🔥 2000R:  61%|██████    | 228/376 [00:02<00:01, 89.72frame/s]

   🔥 2000R:  63%|██████▎   | 238/376 [00:02<00:01, 91.20frame/s]

   🔥 2000R:  66%|██████▌   | 248/376 [00:02<00:01, 91.68frame/s]

   🔥 2000R:  69%|██████▊   | 258/376 [00:03<00:01, 92.10frame/s]

   🔥 2000R:  71%|███████▏  | 268/376 [00:03<00:01, 92.23frame/s]

   🔥 2000R:  74%|███████▍  | 278/376 [00:03<00:01, 90.77frame/s]

   🔥 2000R:  77%|███████▋  | 288/376 [00:03<00:00, 88.49frame/s]

   🔥 2000R:  79%|███████▉  | 297/376 [00:03<00:00, 88.16frame/s]

   🔥 2000R:  81%|████████▏ | 306/376 [00:03<00:00, 88.19frame/s]

   🔥 2000R:  84%|████████▍ | 316/376 [00:03<00:00, 89.32frame/s]

   🔥 2000R:  87%|████████▋ | 326/376 [00:03<00:00, 90.61frame/s]

   🔥 2000R:  89%|████████▉ | 336/376 [00:03<00:00, 90.62frame/s]

   🔥 2000R:  92%|█████████▏| 346/376 [00:03<00:00, 87.86frame/s]

   🔥 2000R:  94%|█████████▍| 355/376 [00:04<00:00, 86.20frame/s]

   🔥 2000R:  97%|█████████▋| 364/376 [00:04<00:00, 85.28frame/s]

   🔥 2000R:  99%|█████████▉| 373/376 [00:04<00:00, 83.95frame/s]

                                                                 [✅] 2000R: /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/5_heatmap/2000R_heatmap.png
[✅] 2000R (fitted): /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/5_heatmap/2000R_heatmap_fitted.png

📁 Rigs (heatmap):  75%|███████▌  | 3/4 [00:19<00:06,  6.41s/rig]

   🔥 1000:   0%|          | 0/330 [00:00<?, ?frame/s]

   🔥 1000:   3%|▎         | 9/330 [00:00<00:03, 87.09frame/s]

   🔥 1000:   6%|▌         | 19/330 [00:00<00:03, 90.67frame/s]

   🔥 1000:   9%|▉         | 29/330 [00:00<00:03, 91.23frame/s]

   🔥 1000:  12%|█▏        | 39/330 [00:00<00:03, 88.97frame/s]

   🔥 1000:  15%|█▍        | 48/330 [00:00<00:03, 86.77frame/s]

   🔥 1000:  17%|█▋        | 57/330 [00:00<00:03, 85.11frame/s]

   🔥 1000:  20%|██        | 66/330 [00:00<00:03, 83.63frame/s]

   🔥 1000:  23%|██▎       | 75/330 [00:00<00:03, 82.73frame/s]

   🔥 1000:  25%|██▌       | 84/330 [00:00<00:02, 82.14frame/s]

   🔥 1000:  28%|██▊       | 93/330 [00:01<00:02, 81.22frame/s]

   🔥 1000:  31%|███       | 102/330 [00:01<00:02, 80.88frame/s]

   🔥 1000:  34%|███▎      | 111/330 [00:01<00:02, 80.73frame/s]

   🔥 1000:  36%|███▋      | 120/330 [00:01<00:02, 81.08frame/s]

   🔥 1000:  39%|███▉      | 129/330 [00:01<00:02, 80.98frame/s]

   🔥 1000:  42%|████▏     | 138/330 [00:01<00:02, 80.74frame/s]

   🔥 1000:  45%|████▍     | 147/330 [00:01<00:02, 80.92frame/s]

   🔥 1000:  47%|████▋     | 156/330 [00:01<00:02, 81.12frame/s]

   🔥 1000:  50%|█████     | 165/330 [00:01<00:02, 82.16frame/s]

   🔥 1000:  53%|█████▎    | 174/330 [00:02<00:01, 82.91frame/s]

   🔥 1000:  56%|█████▌    | 184/330 [00:02<00:01, 85.45frame/s]

   🔥 1000:  59%|█████▉    | 194/330 [00:02<00:01, 87.02frame/s]

   🔥 1000:  62%|██████▏   | 203/330 [00:02<00:01, 86.39frame/s]

   🔥 1000:  64%|██████▍   | 212/330 [00:02<00:01, 83.53frame/s]

   🔥 1000:  67%|██████▋   | 221/330 [00:02<00:01, 82.84frame/s]

   🔥 1000:  70%|██████▉   | 230/330 [00:02<00:01, 81.97frame/s]

   🔥 1000:  72%|███████▏  | 239/330 [00:02<00:01, 80.92frame/s]

   🔥 1000:  75%|███████▌  | 248/330 [00:02<00:01, 80.86frame/s]

   🔥 1000:  78%|███████▊  | 257/330 [00:03<00:00, 80.98frame/s]

   🔥 1000:  81%|████████  | 266/330 [00:03<00:00, 80.95frame/s]

   🔥 1000:  83%|████████▎ | 275/330 [00:03<00:00, 81.44frame/s]

   🔥 1000:  86%|████████▌ | 284/330 [00:03<00:00, 81.77frame/s]

   🔥 1000:  89%|████████▉ | 293/330 [00:03<00:00, 83.57frame/s]

   🔥 1000:  92%|█████████▏| 302/330 [00:03<00:00, 85.38frame/s]

   🔥 1000:  94%|█████████▍| 311/330 [00:03<00:00, 84.80frame/s]

   🔥 1000:  97%|█████████▋| 320/330 [00:03<00:00, 84.05frame/s]

   🔥 1000: 100%|█████████▉| 329/330 [00:03<00:00, 83.66frame/s]

                                                                [✅] 1000: /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/5_heatmap/1000_heatmap_fitted.png

📁 Rigs (heatmap): 100%|██████████| 4/4 [00:24<00:00,  5.74s/rig]
📁 Rigs (heatmap): 100%|██████████| 4/4 [00:24<00:00,  6.08s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MCDP3D-SL-012_W039(6)_2026-03-04/calibration/debug/5_heatmap
[🏁] Finished processing MCDP3D-SL-012_W039(6)_2026-03-04


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