2026-05-18T01:47:49 - INFO: Slick 0.0.8a11

🟢 Starting Calibration Pipeline

=== Processing MDC018_W044(6)_2026_05_06 ===
2026-05-18T01:47:49 - INFO: Camera ID: 15091857
2026-05-18T01:47:49 - INFO: Wand ID: 
2026-05-18T01:47:49 - INFO: Recorded At: 2026-05-06T13:40:48Z

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

[🔄] Full PTD mode: Processing ALL images then creating calibration subset
[📸] Digitizing ALL images...
[📸] 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 618 stationary frames, 944 remain


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                                                                           [PASS2] Summary: 0 frames fixed, 0 untrusted, 944 total


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→ 1500 Phase 3: finalize:  61%|██████▏   | 580/944 [00:10<00:06, 52.86it/s]

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→ 1500 Phase 3: finalize:  66%|██████▌   | 622/944 [00:11<00:06, 51.01it/s]

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→ 1500 Phase 3: finalize:  74%|███████▍  | 700/944 [00:13<00:04, 53.13it/s]

→ 1500 Phase 3: finalize:  75%|███████▍  | 706/944 [00:13<00:04, 53.36it/s]

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→ 1500 Phase 3: finalize:  89%|████████▉ | 844/944 [00:15<00:01, 54.33it/s]

→ 1500 Phase 3: finalize:  90%|█████████ | 850/944 [00:15<00:01, 54.34it/s]

→ 1500 Phase 3: finalize:  91%|█████████ | 856/944 [00:16<00:01, 54.43it/s]

→ 1500 Phase 3: finalize:  91%|█████████▏| 862/944 [00:16<00:01, 54.47it/s]

→ 1500 Phase 3: finalize:  92%|█████████▏| 868/944 [00:16<00:01, 54.51it/s]

→ 1500 Phase 3: finalize:  93%|█████████▎| 874/944 [00:16<00:01, 54.44it/s]

→ 1500 Phase 3: finalize:  93%|█████████▎| 880/944 [00:16<00:01, 54.49it/s]

→ 1500 Phase 3: finalize:  94%|█████████▍| 886/944 [00:16<00:01, 54.20it/s]

→ 1500 Phase 3: finalize:  94%|█████████▍| 892/944 [00:16<00:00, 53.77it/s]

→ 1500 Phase 3: finalize:  95%|█████████▌| 898/944 [00:16<00:00, 53.81it/s]

→ 1500 Phase 3: finalize:  96%|█████████▌| 904/944 [00:16<00:00, 53.90it/s]

→ 1500 Phase 3: finalize:  96%|█████████▋| 910/944 [00:17<00:00, 53.93it/s]

→ 1500 Phase 3: finalize:  97%|█████████▋| 916/944 [00:17<00:00, 53.94it/s]

→ 1500 Phase 3: finalize:  98%|█████████▊| 922/944 [00:17<00:00, 53.96it/s]

→ 1500 Phase 3: finalize:  98%|█████████▊| 928/944 [00:17<00:00, 53.94it/s]

→ 1500 Phase 3: finalize:  99%|█████████▉| 934/944 [00:17<00:00, 53.87it/s]

→ 1500 Phase 3: finalize: 100%|█████████▉| 940/944 [00:17<00:00, 53.87it/s]

                                                                           
[TIMING] 1500 — 944 frames
  Phase 1  radial detect   (parallel)  :  13.36s  (14.1 ms/frame)
  Phase 2a corner detect   (parallel)  :   6.42s  (6.8 ms/frame)
  Phase 2b corner fix      (sequential):   0.20s
  Phase 3  finalize        (sequential):  17.67s  (18.7 ms/frame)
    decode + undistort                 :   9.32s  (9.9 ms/frame)
    corner apply + refinement          :   3.73s  (4.0 ms/frame)
    segment                            :   3.76s  (4.0 ms/frame)
    smooth                             :   0.52s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  37.64s


Processing Rigs:  25%|██▌       | 1/4 [00:42<02:07, 42.48s/it][INFO] Filtered 699 stationary frames, 689 remain


→ 2000R (689 images) Phase 1:   0%|          | 0/689 [00:00<?, ?it/s]

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→ 2000R (689 images) Phase 1:  46%|████▋     | 320/689 [00:06<00:04, 86.64it/s]

→ 2000R (689 images) Phase 1:  48%|████▊     | 332/689 [00:06<00:05, 65.59it/s]

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→ 2000R (689 images) Phase 1:  53%|█████▎    | 364/689 [00:06<00:04, 66.00it/s]

→ 2000R (689 images) Phase 1:  56%|█████▌    | 383/689 [00:07<00:03, 83.68it/s]

→ 2000R (689 images) Phase 1:  57%|█████▋    | 395/689 [00:07<00:04, 64.86it/s]

→ 2000R (689 images) Phase 1:  60%|██████    | 415/689 [00:07<00:03, 84.04it/s]

→ 2000R (689 images) Phase 1:  62%|██████▏   | 427/689 [00:07<00:04, 64.91it/s]

→ 2000R (689 images) Phase 1:  65%|██████▍   | 447/689 [00:07<00:02, 84.21it/s]

→ 2000R (689 images) Phase 1:  67%|██████▋   | 459/689 [00:08<00:03, 63.76it/s]

→ 2000R (689 images) Phase 1:  70%|██████▉   | 480/689 [00:08<00:02, 81.45it/s]

→ 2000R (689 images) Phase 1:  71%|███████▏  | 492/689 [00:08<00:02, 65.74it/s]

→ 2000R (689 images) Phase 1:  74%|███████▍  | 511/689 [00:08<00:02, 84.81it/s]

→ 2000R (689 images) Phase 1:  76%|███████▌  | 524/689 [00:09<00:02, 65.61it/s]

→ 2000R (689 images) Phase 1:  79%|███████▉  | 544/689 [00:09<00:01, 80.20it/s]

→ 2000R (689 images) Phase 1:  81%|████████  | 555/689 [00:09<00:02, 65.19it/s]

→ 2000R (689 images) Phase 1:  84%|████████▎ | 576/689 [00:09<00:01, 78.58it/s]

→ 2000R (689 images) Phase 1:  85%|████████▌ | 586/689 [00:09<00:01, 65.85it/s]

→ 2000R (689 images) Phase 1:  88%|████████▊ | 606/689 [00:10<00:00, 86.59it/s]

→ 2000R (689 images) Phase 1:  90%|████████▉ | 618/689 [00:10<00:01, 65.39it/s]

→ 2000R (689 images) Phase 1:  93%|█████████▎| 639/689 [00:10<00:00, 87.77it/s]

→ 2000R (689 images) Phase 1:  95%|█████████▍| 652/689 [00:10<00:00, 66.06it/s]

→ 2000R (689 images) Phase 1:  98%|█████████▊| 672/689 [00:10<00:00, 84.31it/s]

→ 2000R (689 images) Phase 1:  99%|█████████▉| 685/689 [00:11<00:00, 82.61it/s]

                                                                               

→ 2000R Phase 2: corners:   0%|          | 0/689 [00:00<?, ?it/s]

→ 2000R Phase 2: corners:   0%|          | 1/689 [00:01<18:22,  1.60s/it]

→ 2000R Phase 2: corners:   2%|▏         | 12/689 [00:01<01:11,  9.53it/s]

→ 2000R Phase 2: corners:   3%|▎         | 24/689 [00:01<00:32, 20.64it/s]

→ 2000R Phase 2: corners:   6%|▌         | 39/689 [00:01<00:17, 36.86it/s]

→ 2000R Phase 2: corners:   8%|▊         | 52/689 [00:02<00:12, 50.84it/s]

→ 2000R Phase 2: corners:  10%|▉         | 67/689 [00:02<00:09, 67.41it/s]

→ 2000R Phase 2: corners:  12%|█▏        | 80/689 [00:02<00:07, 78.31it/s]

→ 2000R Phase 2: corners:  13%|█▎        | 93/689 [00:02<00:06, 88.90it/s]

→ 2000R Phase 2: corners:  16%|█▌        | 108/689 [00:02<00:05, 99.98it/s]

→ 2000R Phase 2: corners:  18%|█▊        | 122/689 [00:02<00:05, 108.05it/s]

→ 2000R Phase 2: corners:  20%|█▉        | 135/689 [00:02<00:04, 111.98it/s]

→ 2000R Phase 2: corners:  21%|██▏       | 148/689 [00:02<00:04, 115.10it/s]

→ 2000R Phase 2: corners:  24%|██▍       | 165/689 [00:02<00:04, 128.39it/s]

→ 2000R Phase 2: corners:  26%|██▋       | 182/689 [00:03<00:03, 138.47it/s]

→ 2000R Phase 2: corners:  29%|██▊       | 197/689 [00:03<00:03, 138.35it/s]

→ 2000R Phase 2: corners:  31%|███       | 212/689 [00:03<00:03, 138.02it/s]

→ 2000R Phase 2: corners:  33%|███▎      | 228/689 [00:03<00:03, 139.68it/s]

→ 2000R Phase 2: corners:  36%|███▌      | 246/689 [00:03<00:02, 150.28it/s]

→ 2000R Phase 2: corners:  38%|███▊      | 262/689 [00:03<00:02, 145.35it/s]

→ 2000R Phase 2: corners:  40%|████      | 277/689 [00:03<00:02, 142.18it/s]

→ 2000R Phase 2: corners:  43%|████▎     | 294/689 [00:03<00:02, 146.74it/s]

→ 2000R Phase 2: corners:  45%|████▍     | 309/689 [00:03<00:02, 142.97it/s]

→ 2000R Phase 2: corners:  47%|████▋     | 326/689 [00:03<00:02, 148.62it/s]

→ 2000R Phase 2: corners:  49%|████▉     | 341/689 [00:04<00:02, 147.84it/s]

→ 2000R Phase 2: corners:  52%|█████▏    | 357/689 [00:04<00:02, 148.40it/s]

→ 2000R Phase 2: corners:  54%|█████▍    | 374/689 [00:04<00:02, 150.48it/s]

→ 2000R Phase 2: corners:  57%|█████▋    | 390/689 [00:04<00:02, 149.36it/s]

→ 2000R Phase 2: corners:  59%|█████▉    | 407/689 [00:04<00:01, 154.44it/s]

→ 2000R Phase 2: corners:  62%|██████▏   | 426/689 [00:04<00:01, 161.39it/s]

→ 2000R Phase 2: corners:  65%|██████▌   | 448/689 [00:04<00:01, 175.77it/s]

→ 2000R Phase 2: corners:  68%|██████▊   | 466/689 [00:04<00:01, 173.10it/s]

→ 2000R Phase 2: corners:  70%|███████   | 485/689 [00:04<00:01, 176.82it/s]

→ 2000R Phase 2: corners:  73%|███████▎  | 505/689 [00:05<00:01, 182.64it/s]

→ 2000R Phase 2: corners:  76%|███████▌  | 525/689 [00:05<00:00, 185.00it/s]

→ 2000R Phase 2: corners:  79%|███████▉  | 545/689 [00:05<00:00, 189.29it/s]

→ 2000R Phase 2: corners:  82%|████████▏ | 564/689 [00:05<00:00, 178.89it/s]

→ 2000R Phase 2: corners:  85%|████████▍ | 583/689 [00:05<00:00, 171.71it/s]

→ 2000R Phase 2: corners:  87%|████████▋ | 602/689 [00:05<00:00, 176.60it/s]

→ 2000R Phase 2: corners:  90%|████████▉ | 620/689 [00:05<00:00, 175.54it/s]

→ 2000R Phase 2: corners:  93%|█████████▎| 639/689 [00:05<00:00, 178.76it/s]

→ 2000R Phase 2: corners:  96%|█████████▌| 661/689 [00:05<00:00, 190.59it/s]

                                                                            [PASS2] Frame 0000423: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000424: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000425: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000426: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000429: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000430: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000431: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000432: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000436: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000437: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000438: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000439: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000560: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000562: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000563: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000566: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000596: 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=False)
[PASS2] Frame 0000601: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000610: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000611: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000613: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000614: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000618: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000619: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000620: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000621: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000956: fixed corners {0} (was_fixed=True, trusted=True)
[PASS2] Frame 0001010: fixed corners {0} (was_fixed=True, trusted=True)
[PASS2] Frame 0000425: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000431: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000438: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000563: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000599: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000613: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000620: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 16 frames fixed, 14 untrusted, 689 total


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→ 2000R Phase 3: finalize:  92%|█████████▏| 631/689 [00:10<00:01, 54.86it/s]

→ 2000R Phase 3: finalize:  92%|█████████▏| 637/689 [00:11<00:00, 54.95it/s]

→ 2000R Phase 3: finalize:  93%|█████████▎| 643/689 [00:11<00:00, 55.11it/s]

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→ 2000R Phase 3: finalize:  95%|█████████▌| 655/689 [00:11<00:00, 55.41it/s]

→ 2000R Phase 3: finalize:  96%|█████████▌| 661/689 [00:11<00:00, 55.49it/s]

→ 2000R Phase 3: finalize:  97%|█████████▋| 667/689 [00:11<00:00, 55.75it/s]

→ 2000R Phase 3: finalize:  98%|█████████▊| 673/689 [00:11<00:00, 55.88it/s]

→ 2000R Phase 3: finalize:  99%|█████████▊| 679/689 [00:11<00:00, 56.01it/s]

→ 2000R Phase 3: finalize:  99%|█████████▉| 685/689 [00:11<00:00, 56.18it/s]

                                                                            
[TIMING] 2000R — 689 frames
  Phase 1  radial detect   (parallel)  :  11.41s  (16.6 ms/frame)
  Phase 2a corner detect   (parallel)  :   6.14s  (8.9 ms/frame)
  Phase 2b corner fix      (sequential):   0.97s
  Phase 3  finalize        (sequential):  11.99s  (17.4 ms/frame)
    decode + undistort                 :   5.58s  (8.1 ms/frame)
    corner apply + refinement          :   3.03s  (4.4 ms/frame)
    segment                            :   2.76s  (4.0 ms/frame)
    smooth                             :   0.38s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  30.52s


Processing Rigs:  50%|█████     | 2/4 [01:17<01:15, 37.98s/it][INFO] Filtered 553 stationary frames, 599 remain


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→ 1000 (599 images) Phase 1:  87%|████████▋ | 523/599 [00:09<00:01, 67.86it/s]

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→ 1000 (599 images) Phase 1:  92%|█████████▏| 552/599 [00:09<00:00, 68.06it/s]

→ 1000 (599 images) Phase 1:  94%|█████████▎| 561/599 [00:09<00:00, 71.81it/s]

→ 1000 (599 images) Phase 1:  96%|█████████▋| 577/599 [00:09<00:00, 89.27it/s]

→ 1000 (599 images) Phase 1:  98%|█████████▊| 588/599 [00:09<00:00, 78.92it/s]

                                                                              

→ 1000 Phase 2: corners:   0%|          | 0/599 [00:00<?, ?it/s]

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→ 1000 Phase 2: corners:   3%|▎         | 16/599 [00:01<00:47, 12.17it/s]

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→ 1000 Phase 2: corners:   7%|▋         | 41/599 [00:02<00:15, 36.02it/s]

→ 1000 Phase 2: corners:   9%|▉         | 54/599 [00:02<00:10, 49.89it/s]

→ 1000 Phase 2: corners:  11%|█         | 67/599 [00:02<00:08, 63.68it/s]

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→ 1000 Phase 2: corners:  20%|█▉        | 117/599 [00:02<00:05, 82.47it/s]

→ 1000 Phase 2: corners:  21%|██▏       | 128/599 [00:02<00:05, 87.00it/s]

→ 1000 Phase 2: corners:  23%|██▎       | 140/599 [00:02<00:04, 94.28it/s]

→ 1000 Phase 2: corners:  26%|██▌       | 153/599 [00:03<00:04, 102.31it/s]

→ 1000 Phase 2: corners:  28%|██▊       | 167/599 [00:03<00:03, 111.78it/s]

→ 1000 Phase 2: corners:  30%|███       | 180/599 [00:03<00:03, 115.23it/s]

→ 1000 Phase 2: corners:  33%|███▎      | 196/599 [00:03<00:03, 125.71it/s]

→ 1000 Phase 2: corners:  35%|███▌      | 210/599 [00:03<00:03, 126.83it/s]

→ 1000 Phase 2: corners:  38%|███▊      | 226/599 [00:03<00:02, 134.48it/s]

→ 1000 Phase 2: corners:  40%|████      | 240/599 [00:03<00:02, 133.99it/s]

→ 1000 Phase 2: corners:  43%|████▎     | 255/599 [00:03<00:02, 132.23it/s]

→ 1000 Phase 2: corners:  45%|████▌     | 272/599 [00:03<00:02, 140.29it/s]

→ 1000 Phase 2: corners:  48%|████▊     | 288/599 [00:03<00:02, 145.42it/s]

→ 1000 Phase 2: corners:  51%|█████     | 304/599 [00:04<00:01, 148.63it/s]

→ 1000 Phase 2: corners:  54%|█████▍    | 322/599 [00:04<00:01, 150.47it/s]

→ 1000 Phase 2: corners:  57%|█████▋    | 340/599 [00:04<00:01, 157.91it/s]

→ 1000 Phase 2: corners:  60%|█████▉    | 357/599 [00:04<00:01, 160.39it/s]

→ 1000 Phase 2: corners:  62%|██████▏   | 374/599 [00:04<00:01, 152.16it/s]

→ 1000 Phase 2: corners:  65%|██████▌   | 390/599 [00:04<00:01, 151.33it/s]

→ 1000 Phase 2: corners:  68%|██████▊   | 407/599 [00:04<00:01, 156.47it/s]

→ 1000 Phase 2: corners:  71%|███████   | 425/599 [00:04<00:01, 161.34it/s]

→ 1000 Phase 2: corners:  74%|███████▍  | 442/599 [00:04<00:01, 155.49it/s]

→ 1000 Phase 2: corners:  76%|███████▋  | 458/599 [00:05<00:00, 146.74it/s]

→ 1000 Phase 2: corners:  79%|███████▉  | 476/599 [00:05<00:00, 153.16it/s]

→ 1000 Phase 2: corners:  83%|████████▎ | 495/599 [00:05<00:00, 159.68it/s]

→ 1000 Phase 2: corners:  85%|████████▌ | 512/599 [00:05<00:00, 154.35it/s]

→ 1000 Phase 2: corners:  88%|████████▊ | 528/599 [00:05<00:00, 144.28it/s]

→ 1000 Phase 2: corners:  91%|█████████ | 545/599 [00:05<00:00, 149.87it/s]

→ 1000 Phase 2: corners:  94%|█████████▎| 561/599 [00:05<00:00, 151.68it/s]

                                                                           [PASS2] Frame 0000297: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000298: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000299: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000300: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000299: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 2 frames fixed, 2 untrusted, 599 total


→ 1000 Phase 3: finalize:   0%|          | 0/599 [00:00<?, ?it/s]

→ 1000 Phase 3: finalize:   1%|          | 6/599 [00:00<00:10, 56.36it/s]

→ 1000 Phase 3: finalize:   2%|▏         | 12/599 [00:00<00:10, 58.39it/s]

→ 1000 Phase 3: finalize:   3%|▎         | 19/599 [00:00<00:09, 59.67it/s]

→ 1000 Phase 3: finalize:   4%|▍         | 26/599 [00:00<00:09, 60.14it/s]

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→ 1000 Phase 3: finalize:   8%|▊         | 47/599 [00:00<00:09, 61.20it/s]

→ 1000 Phase 3: finalize:   9%|▉         | 54/599 [00:00<00:08, 61.26it/s]

→ 1000 Phase 3: finalize:  10%|█         | 61/599 [00:01<00:08, 61.36it/s]

→ 1000 Phase 3: finalize:  11%|█▏        | 68/599 [00:01<00:08, 61.47it/s]

→ 1000 Phase 3: finalize:  13%|█▎        | 75/599 [00:01<00:08, 61.30it/s]

→ 1000 Phase 3: finalize:  14%|█▎        | 82/599 [00:01<00:08, 61.29it/s]

→ 1000 Phase 3: finalize:  15%|█▍        | 89/599 [00:01<00:08, 61.30it/s]

→ 1000 Phase 3: finalize:  16%|█▌        | 96/599 [00:01<00:08, 61.14it/s]

→ 1000 Phase 3: finalize:  17%|█▋        | 103/599 [00:01<00:08, 61.17it/s]

→ 1000 Phase 3: finalize:  18%|█▊        | 110/599 [00:01<00:07, 61.30it/s]

→ 1000 Phase 3: finalize:  20%|█▉        | 117/599 [00:01<00:07, 61.23it/s]

→ 1000 Phase 3: finalize:  21%|██        | 124/599 [00:02<00:07, 61.15it/s]

→ 1000 Phase 3: finalize:  22%|██▏       | 131/599 [00:02<00:07, 60.67it/s]

→ 1000 Phase 3: finalize:  23%|██▎       | 138/599 [00:02<00:07, 60.77it/s]

→ 1000 Phase 3: finalize:  24%|██▍       | 145/599 [00:02<00:07, 60.82it/s]

→ 1000 Phase 3: finalize:  25%|██▌       | 152/599 [00:02<00:07, 60.80it/s]

→ 1000 Phase 3: finalize:  27%|██▋       | 159/599 [00:02<00:07, 60.76it/s]

→ 1000 Phase 3: finalize:  28%|██▊       | 166/599 [00:02<00:07, 60.67it/s]

→ 1000 Phase 3: finalize:  29%|██▉       | 173/599 [00:02<00:07, 60.70it/s]

→ 1000 Phase 3: finalize:  30%|███       | 180/599 [00:02<00:06, 60.10it/s]

→ 1000 Phase 3: finalize:  31%|███       | 187/599 [00:03<00:06, 59.73it/s]

→ 1000 Phase 3: finalize:  32%|███▏      | 193/599 [00:03<00:06, 59.76it/s]

→ 1000 Phase 3: finalize:  33%|███▎      | 200/599 [00:03<00:06, 59.94it/s]

→ 1000 Phase 3: finalize:  35%|███▍      | 207/599 [00:03<00:06, 60.42it/s]

→ 1000 Phase 3: finalize:  36%|███▌      | 214/599 [00:03<00:06, 60.89it/s]

→ 1000 Phase 3: finalize:  37%|███▋      | 221/599 [00:03<00:06, 61.31it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 228/599 [00:03<00:06, 61.66it/s]

→ 1000 Phase 3: finalize:  39%|███▉      | 235/599 [00:03<00:05, 61.93it/s]

→ 1000 Phase 3: finalize:  40%|████      | 242/599 [00:03<00:05, 62.10it/s]

→ 1000 Phase 3: finalize:  42%|████▏     | 249/599 [00:04<00:05, 62.20it/s]

→ 1000 Phase 3: finalize:  43%|████▎     | 256/599 [00:04<00:05, 62.41it/s]

→ 1000 Phase 3: finalize:  44%|████▍     | 263/599 [00:04<00:05, 62.55it/s]

→ 1000 Phase 3: finalize:  45%|████▌     | 270/599 [00:04<00:05, 62.62it/s]

→ 1000 Phase 3: finalize:  46%|████▌     | 277/599 [00:04<00:05, 62.70it/s]

→ 1000 Phase 3: finalize:  47%|████▋     | 284/599 [00:04<00:05, 62.78it/s]

→ 1000 Phase 3: finalize:  49%|████▊     | 291/599 [00:04<00:04, 62.83it/s]

→ 1000 Phase 3: finalize:  50%|████▉     | 298/599 [00:04<00:04, 62.77it/s]

→ 1000 Phase 3: finalize:  51%|█████     | 305/599 [00:04<00:04, 62.86it/s]

→ 1000 Phase 3: finalize:  52%|█████▏    | 312/599 [00:05<00:04, 62.89it/s]

→ 1000 Phase 3: finalize:  53%|█████▎    | 319/599 [00:05<00:04, 62.80it/s]

→ 1000 Phase 3: finalize:  54%|█████▍    | 326/599 [00:05<00:04, 62.63it/s]

→ 1000 Phase 3: finalize:  56%|█████▌    | 333/599 [00:05<00:04, 62.62it/s]

→ 1000 Phase 3: finalize:  57%|█████▋    | 340/599 [00:05<00:04, 62.50it/s]

→ 1000 Phase 3: finalize:  58%|█████▊    | 347/599 [00:05<00:04, 62.45it/s]

→ 1000 Phase 3: finalize:  59%|█████▉    | 354/599 [00:05<00:03, 62.40it/s]

→ 1000 Phase 3: finalize:  60%|██████    | 361/599 [00:05<00:03, 62.28it/s]

→ 1000 Phase 3: finalize:  61%|██████▏   | 368/599 [00:05<00:03, 62.23it/s]

→ 1000 Phase 3: finalize:  63%|██████▎   | 375/599 [00:06<00:03, 62.14it/s]

→ 1000 Phase 3: finalize:  64%|██████▍   | 382/599 [00:06<00:03, 61.96it/s]

→ 1000 Phase 3: finalize:  65%|██████▍   | 389/599 [00:06<00:03, 61.62it/s]

→ 1000 Phase 3: finalize:  66%|██████▌   | 396/599 [00:06<00:03, 61.19it/s]

→ 1000 Phase 3: finalize:  67%|██████▋   | 403/599 [00:06<00:03, 60.83it/s]

→ 1000 Phase 3: finalize:  68%|██████▊   | 410/599 [00:06<00:03, 60.62it/s]

→ 1000 Phase 3: finalize:  70%|██████▉   | 417/599 [00:06<00:03, 60.49it/s]

→ 1000 Phase 3: finalize:  71%|███████   | 424/599 [00:06<00:02, 60.44it/s]

→ 1000 Phase 3: finalize:  72%|███████▏  | 431/599 [00:07<00:02, 59.98it/s]

→ 1000 Phase 3: finalize:  73%|███████▎  | 438/599 [00:07<00:02, 60.06it/s]

→ 1000 Phase 3: finalize:  74%|███████▍  | 445/599 [00:07<00:02, 60.15it/s]

→ 1000 Phase 3: finalize:  75%|███████▌  | 452/599 [00:07<00:02, 60.38it/s]

→ 1000 Phase 3: finalize:  77%|███████▋  | 459/599 [00:07<00:02, 60.49it/s]

→ 1000 Phase 3: finalize:  78%|███████▊  | 466/599 [00:07<00:02, 60.63it/s]

→ 1000 Phase 3: finalize:  79%|███████▉  | 473/599 [00:07<00:02, 60.74it/s]

→ 1000 Phase 3: finalize:  80%|████████  | 480/599 [00:07<00:01, 60.85it/s]

→ 1000 Phase 3: finalize:  81%|████████▏ | 487/599 [00:07<00:01, 60.86it/s]

→ 1000 Phase 3: finalize:  82%|████████▏ | 494/599 [00:08<00:01, 60.94it/s]

→ 1000 Phase 3: finalize:  84%|████████▎ | 501/599 [00:08<00:01, 61.02it/s]

→ 1000 Phase 3: finalize:  85%|████████▍ | 508/599 [00:08<00:01, 61.08it/s]

→ 1000 Phase 3: finalize:  86%|████████▌ | 515/599 [00:08<00:01, 61.16it/s]

→ 1000 Phase 3: finalize:  87%|████████▋ | 522/599 [00:08<00:01, 61.09it/s]

→ 1000 Phase 3: finalize:  88%|████████▊ | 529/599 [00:08<00:01, 61.10it/s]

→ 1000 Phase 3: finalize:  89%|████████▉ | 536/599 [00:08<00:01, 61.20it/s]

→ 1000 Phase 3: finalize:  91%|█████████ | 543/599 [00:08<00:00, 61.24it/s]

→ 1000 Phase 3: finalize:  92%|█████████▏| 550/599 [00:08<00:00, 61.19it/s]

→ 1000 Phase 3: finalize:  93%|█████████▎| 557/599 [00:09<00:00, 61.27it/s]

→ 1000 Phase 3: finalize:  94%|█████████▍| 564/599 [00:09<00:00, 61.23it/s]

→ 1000 Phase 3: finalize:  95%|█████████▌| 571/599 [00:09<00:00, 61.10it/s]

→ 1000 Phase 3: finalize:  96%|█████████▋| 578/599 [00:09<00:00, 61.13it/s]

→ 1000 Phase 3: finalize:  98%|█████████▊| 585/599 [00:09<00:00, 60.91it/s]

→ 1000 Phase 3: finalize:  99%|█████████▉| 592/599 [00:09<00:00, 60.81it/s]

→ 1000 Phase 3: finalize: 100%|██████████| 599/599 [00:09<00:00, 60.21it/s]

                                                                           
[TIMING] 1000 — 599 frames
  Phase 1  radial detect   (parallel)  :  10.26s  (17.1 ms/frame)
  Phase 2a corner detect   (parallel)  :   6.06s  (10.1 ms/frame)
  Phase 2b corner fix      (sequential):   0.42s
  Phase 3  finalize        (sequential):   9.79s  (16.3 ms/frame)
    decode + undistort                 :   4.74s  (7.9 ms/frame)
    corner apply + refinement          :   2.15s  (3.6 ms/frame)
    segment                            :   2.36s  (3.9 ms/frame)
    smooth                             :   0.33s  (0.5 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  26.53s


Processing Rigs:  75%|███████▌  | 3/4 [01:47<00:34, 34.34s/it][INFO] Filtered 778 stationary frames, 698 remain


→ 2000L (698 images) Phase 1:   0%|          | 0/698 [00:00<?, ?it/s]

→ 2000L (698 images) Phase 1:   0%|          | 1/698 [00:02<24:30,  2.11s/it]

→ 2000L (698 images) Phase 1:   5%|▍         | 33/698 [00:02<00:38, 17.17it/s]

→ 2000L (698 images) Phase 1:   9%|▉         | 65/698 [00:02<00:19, 32.38it/s]

→ 2000L (698 images) Phase 1:  11%|█         | 76/698 [00:03<00:16, 38.24it/s]

→ 2000L (698 images) Phase 1:  14%|█▍        | 97/698 [00:03<00:13, 44.86it/s]

→ 2000L (698 images) Phase 1:  16%|█▌        | 110/698 [00:03<00:11, 53.18it/s]

→ 2000L (698 images) Phase 1:  18%|█▊        | 129/698 [00:03<00:10, 54.81it/s]

→ 2000L (698 images) Phase 1:  20%|██        | 141/698 [00:03<00:09, 61.64it/s]

→ 2000L (698 images) Phase 1:  23%|██▎       | 161/698 [00:04<00:08, 63.16it/s]

→ 2000L (698 images) Phase 1:  24%|██▍       | 170/698 [00:04<00:08, 65.77it/s]

→ 2000L (698 images) Phase 1:  27%|██▋       | 191/698 [00:04<00:05, 89.26it/s]

→ 2000L (698 images) Phase 1:  29%|██▉       | 203/698 [00:04<00:07, 66.30it/s]

→ 2000L (698 images) Phase 1:  32%|███▏      | 222/698 [00:04<00:05, 84.47it/s]

→ 2000L (698 images) Phase 1:  34%|███▎      | 234/698 [00:05<00:07, 63.60it/s]

→ 2000L (698 images) Phase 1:  37%|███▋      | 255/698 [00:05<00:05, 85.76it/s]

→ 2000L (698 images) Phase 1:  38%|███▊      | 268/698 [00:05<00:06, 65.54it/s]

→ 2000L (698 images) Phase 1:  41%|████▏     | 288/698 [00:05<00:04, 85.02it/s]

→ 2000L (698 images) Phase 1:  43%|████▎     | 301/698 [00:06<00:05, 66.23it/s]

→ 2000L (698 images) Phase 1:  46%|████▌     | 320/698 [00:06<00:04, 84.71it/s]

→ 2000L (698 images) Phase 1:  48%|████▊     | 333/698 [00:06<00:05, 65.23it/s]

→ 2000L (698 images) Phase 1:  51%|█████     | 353/698 [00:06<00:05, 66.47it/s]

→ 2000L (698 images) Phase 1:  52%|█████▏    | 363/698 [00:06<00:04, 67.65it/s]

→ 2000L (698 images) Phase 1:  55%|█████▌    | 384/698 [00:07<00:03, 90.62it/s]

→ 2000L (698 images) Phase 1:  57%|█████▋    | 397/698 [00:07<00:04, 65.88it/s]

→ 2000L (698 images) Phase 1:  60%|█████▉    | 417/698 [00:07<00:04, 68.49it/s]

→ 2000L (698 images) Phase 1:  61%|██████    | 426/698 [00:07<00:04, 67.83it/s]

→ 2000L (698 images) Phase 1:  64%|██████▎   | 444/698 [00:07<00:02, 85.78it/s]

→ 2000L (698 images) Phase 1:  65%|██████▌   | 455/698 [00:08<00:03, 64.81it/s]

→ 2000L (698 images) Phase 1:  67%|██████▋   | 470/698 [00:08<00:02, 78.18it/s]

→ 2000L (698 images) Phase 1:  69%|██████▉   | 481/698 [00:08<00:03, 68.75it/s]

→ 2000L (698 images) Phase 1:  70%|███████   | 490/698 [00:08<00:03, 68.52it/s]

→ 2000L (698 images) Phase 1:  73%|███████▎  | 507/698 [00:08<00:02, 88.15it/s]

→ 2000L (698 images) Phase 1:  74%|███████▍  | 518/698 [00:09<00:02, 63.98it/s]

→ 2000L (698 images) Phase 1:  77%|███████▋  | 535/698 [00:09<00:01, 82.65it/s]

→ 2000L (698 images) Phase 1:  78%|███████▊  | 547/698 [00:09<00:02, 66.53it/s]

→ 2000L (698 images) Phase 1:  80%|███████▉  | 557/698 [00:09<00:01, 70.67it/s]

→ 2000L (698 images) Phase 1:  83%|████████▎ | 577/698 [00:09<00:01, 74.24it/s]

→ 2000L (698 images) Phase 1:  84%|████████▍ | 586/698 [00:10<00:01, 65.71it/s]

→ 2000L (698 images) Phase 1:  85%|████████▌ | 594/698 [00:10<00:01, 66.03it/s]

→ 2000L (698 images) Phase 1:  87%|████████▋ | 609/698 [00:10<00:01, 63.30it/s]

→ 2000L (698 images) Phase 1:  88%|████████▊ | 616/698 [00:10<00:01, 61.12it/s]

→ 2000L (698 images) Phase 1:  91%|█████████ | 632/698 [00:10<00:00, 79.83it/s]

→ 2000L (698 images) Phase 1:  92%|█████████▏| 642/698 [00:10<00:00, 65.69it/s]

→ 2000L (698 images) Phase 1:  93%|█████████▎| 650/698 [00:10<00:00, 66.70it/s]

→ 2000L (698 images) Phase 1:  96%|█████████▌| 667/698 [00:11<00:00, 88.45it/s]

→ 2000L (698 images) Phase 1:  97%|█████████▋| 678/698 [00:11<00:00, 73.29it/s]

→ 2000L (698 images) Phase 1:  99%|█████████▊| 689/698 [00:11<00:00, 80.68it/s]

                                                                               

→ 2000L Phase 2: corners:   0%|          | 0/698 [00:00<?, ?it/s]

→ 2000L Phase 2: corners:   0%|          | 1/698 [00:01<20:00,  1.72s/it]

→ 2000L Phase 2: corners:   2%|▏         | 13/698 [00:01<01:10,  9.70it/s]

→ 2000L Phase 2: corners:   4%|▍         | 27/698 [00:01<00:29, 22.51it/s]

→ 2000L Phase 2: corners:   6%|▌         | 40/698 [00:02<00:18, 35.17it/s]

→ 2000L Phase 2: corners:   8%|▊         | 57/698 [00:02<00:11, 54.91it/s]

→ 2000L Phase 2: corners:  11%|█         | 75/698 [00:02<00:08, 76.02it/s]

→ 2000L Phase 2: corners:  13%|█▎        | 90/698 [00:02<00:06, 90.61it/s]

→ 2000L Phase 2: corners:  15%|█▌        | 105/698 [00:02<00:05, 103.59it/s]

→ 2000L Phase 2: corners:  17%|█▋        | 120/698 [00:02<00:05, 112.77it/s]

→ 2000L Phase 2: corners:  19%|█▉        | 135/698 [00:02<00:04, 116.67it/s]

→ 2000L Phase 2: corners:  22%|██▏       | 154/698 [00:02<00:04, 132.89it/s]

→ 2000L Phase 2: corners:  24%|██▍       | 170/698 [00:02<00:03, 133.07it/s]

→ 2000L Phase 2: corners:  27%|██▋       | 185/698 [00:03<00:03, 133.37it/s]

→ 2000L Phase 2: corners:  29%|██▊       | 200/698 [00:03<00:03, 129.36it/s]

→ 2000L Phase 2: corners:  31%|███       | 214/698 [00:03<00:03, 130.00it/s]

→ 2000L Phase 2: corners:  33%|███▎      | 228/698 [00:03<00:03, 132.23it/s]

→ 2000L Phase 2: corners:  35%|███▍      | 243/698 [00:03<00:03, 136.67it/s]

→ 2000L Phase 2: corners:  37%|███▋      | 258/698 [00:03<00:03, 140.28it/s]

→ 2000L Phase 2: corners:  39%|███▉      | 273/698 [00:03<00:03, 140.82it/s]

→ 2000L Phase 2: corners:  42%|████▏     | 291/698 [00:03<00:02, 150.69it/s]

→ 2000L Phase 2: corners:  44%|████▍     | 307/698 [00:03<00:02, 150.65it/s]

→ 2000L Phase 2: corners:  46%|████▋     | 323/698 [00:03<00:02, 151.17it/s]

→ 2000L Phase 2: corners:  49%|████▊     | 340/698 [00:04<00:02, 156.04it/s]

→ 2000L Phase 2: corners:  51%|█████     | 356/698 [00:04<00:02, 150.72it/s]

→ 2000L Phase 2: corners:  53%|█████▎    | 373/698 [00:04<00:02, 151.80it/s]

→ 2000L Phase 2: corners:  56%|█████▌    | 390/698 [00:04<00:02, 153.81it/s]

→ 2000L Phase 2: corners:  59%|█████▊    | 409/698 [00:04<00:01, 161.37it/s]

→ 2000L Phase 2: corners:  61%|██████    | 427/698 [00:04<00:01, 165.28it/s]

→ 2000L Phase 2: corners:  64%|██████▎   | 444/698 [00:04<00:01, 164.76it/s]

→ 2000L Phase 2: corners:  66%|██████▌   | 462/698 [00:04<00:01, 167.63it/s]

→ 2000L Phase 2: corners:  69%|██████▊   | 479/698 [00:04<00:01, 167.77it/s]

→ 2000L Phase 2: corners:  71%|███████   | 496/698 [00:05<00:01, 167.83it/s]

→ 2000L Phase 2: corners:  73%|███████▎  | 513/698 [00:05<00:01, 167.62it/s]

→ 2000L Phase 2: corners:  76%|███████▌  | 531/698 [00:05<00:00, 169.15it/s]

→ 2000L Phase 2: corners:  79%|███████▊  | 549/698 [00:05<00:00, 167.37it/s]

→ 2000L Phase 2: corners:  81%|████████▏ | 568/698 [00:05<00:00, 171.44it/s]

→ 2000L Phase 2: corners:  84%|████████▍ | 586/698 [00:05<00:00, 170.06it/s]

→ 2000L Phase 2: corners:  87%|████████▋ | 605/698 [00:05<00:00, 173.30it/s]

→ 2000L Phase 2: corners:  89%|████████▉ | 623/698 [00:05<00:00, 171.16it/s]

→ 2000L Phase 2: corners:  92%|█████████▏| 641/698 [00:05<00:00, 173.34it/s]

→ 2000L Phase 2: corners:  94%|█████████▍| 659/698 [00:05<00:00, 173.90it/s]

→ 2000L Phase 2: corners:  97%|█████████▋| 677/698 [00:06<00:00, 138.37it/s]

                                                                            [PASS2] Frame 0001181: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001182: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001183: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001184: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001186: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001187: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001212: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001214: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001217: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001218: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001332: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001333: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001334: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001335: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001336: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001337: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001338: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001371: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001372: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001373: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001374: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001183: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001186: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001217: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001334: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001337: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001373: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 12 frames fixed, 12 untrusted, 698 total


→ 2000L Phase 3: finalize:   0%|          | 0/698 [00:00<?, ?it/s]

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→ 2000L Phase 3: finalize:  65%|██████▌   | 456/698 [00:07<00:04, 60.39it/s]

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→ 2000L Phase 3: finalize:  78%|███████▊  | 547/698 [00:09<00:02, 61.02it/s]

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→ 2000L Phase 3: finalize:  85%|████████▌ | 596/698 [00:10<00:01, 61.87it/s]

→ 2000L Phase 3: finalize:  86%|████████▋ | 603/698 [00:10<00:01, 61.95it/s]

→ 2000L Phase 3: finalize:  87%|████████▋ | 610/698 [00:10<00:01, 61.89it/s]

→ 2000L Phase 3: finalize:  88%|████████▊ | 617/698 [00:10<00:01, 61.88it/s]

→ 2000L Phase 3: finalize:  89%|████████▉ | 624/698 [00:10<00:01, 61.79it/s]

→ 2000L Phase 3: finalize:  90%|█████████ | 631/698 [00:10<00:01, 61.65it/s]

→ 2000L Phase 3: finalize:  91%|█████████▏| 638/698 [00:10<00:00, 61.48it/s]

→ 2000L Phase 3: finalize:  92%|█████████▏| 645/698 [00:10<00:00, 61.35it/s]

→ 2000L Phase 3: finalize:  93%|█████████▎| 652/698 [00:11<00:00, 60.80it/s]

→ 2000L Phase 3: finalize:  94%|█████████▍| 659/698 [00:11<00:00, 60.58it/s]

→ 2000L Phase 3: finalize:  95%|█████████▌| 666/698 [00:11<00:00, 60.40it/s]

→ 2000L Phase 3: finalize:  96%|█████████▋| 673/698 [00:11<00:00, 60.22it/s]

→ 2000L Phase 3: finalize:  97%|█████████▋| 680/698 [00:11<00:00, 59.97it/s]

→ 2000L Phase 3: finalize:  98%|█████████▊| 686/698 [00:11<00:00, 59.73it/s]

→ 2000L Phase 3: finalize:  99%|█████████▉| 692/698 [00:11<00:00, 59.62it/s]

→ 2000L Phase 3: finalize: 100%|██████████| 698/698 [00:11<00:00, 59.23it/s]

                                                                            
[TIMING] 2000L — 698 frames
  Phase 1  radial detect   (parallel)  :  11.68s  (16.7 ms/frame)
  Phase 2a corner detect   (parallel)  :   6.41s  (9.2 ms/frame)
  Phase 2b corner fix      (sequential):   0.83s
  Phase 3  finalize        (sequential):  11.86s  (17.0 ms/frame)
    decode + undistort                 :   5.60s  (8.0 ms/frame)
    corner apply + refinement          :   2.85s  (4.1 ms/frame)
    segment                            :   2.79s  (4.0 ms/frame)
    smooth                             :   0.38s  (0.5 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  30.78s


Processing Rigs: 100%|██████████| 4/4 [02:22<00:00, 34.71s/it]
Processing Rigs: 100%|██████████| 4/4 [02:22<00:00, 35.65s/it]
[💾] Saved RigFrameDataset to /working/MDC018_W044(6)_2026_05_06/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 2930 frames from 4 rigs to /working/MDC018_W044(6)_2026_05_06/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC018_W044(6)_2026_05_06/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 1500: 100 frames selected from 944
[📋] 2000R: 100 frames selected from 689
[📋] 1000: 100 frames selected from 599
[📋] 2000L: 100 frames selected from 698
[💾] Saved RigFrameDataset to /working/MDC018_W044(6)_2026_05_06/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC018_W044(6)_2026_05_06/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 [00:03<04:18,  3.27s/it]
Computing max image from bright frames:   2%|▎         | 2/80 [00:06<04:13,  3.25s/it]
Computing max image from bright frames:   4%|▍         | 3/80 [00:09<04:10,  3.25s/it]
Computing max image from bright frames:   5%|▌         | 4/80 [00:12<04:06,  3.24s/it]
Computing max image from bright frames:   6%|▋         | 5/80 [00:16<04:02,  3.24s/it]
Computing max image from bright frames:   8%|▊         | 6/80 [00:19<03:59,  3.24s/it]
Computing max image from bright frames:   9%|▉         | 7/80 [00:22<03:56,  3.23s/it]
Computing max image from bright frames:  10%|█         | 8/80 [00:25<03:53,  3.25s/it]
Computing max image from bright frames:  11%|█▏        | 9/80 [00:29<03:50,  3.25s/it]
Computing max image from bright frames:  12%|█▎        | 10/80 [00:32<03:54,  3.35s/it]
Computing max image from bright frames:  14%|█▍        | 11/80 [00:36<03:54,  3.40s/it]
Computing max image from bright frames:  15%|█▌        | 12/80 [00:39<03:50,  3.39s/it]
Computing max image from bright frames:  16%|█▋        | 13/80 [00:43<03:47,  3.39s/it]
Computing max image from bright frames:  18%|█▊        | 14/80 [00:46<03:42,  3.37s/it]
Computing max image from bright frames:  19%|█▉        | 15/80 [00:49<03:37,  3.34s/it]
Computing max image from bright frames:  20%|██        | 16/80 [00:52<03:31,  3.30s/it]
Computing max image from bright frames:  21%|██▏       | 17/80 [00:56<03:26,  3.28s/it]
Computing max image from bright frames:  22%|██▎       | 18/80 [00:59<03:22,  3.26s/it]
Computing max image from bright frames:  24%|██▍       | 19/80 [01:02<03:18,  3.25s/it]
Computing max image from bright frames:  25%|██▌       | 20/80 [01:03<02:42,  2.71s/it]
Computing max image from bright frames:  26%|██▋       | 21/80 [01:07<02:48,  2.86s/it]
Computing max image from bright frames:  28%|██▊       | 22/80 [01:10<02:52,  2.97s/it]
Computing max image from bright frames:  29%|██▉       | 23/80 [01:13<02:53,  3.04s/it]
Computing max image from bright frames:  30%|███       | 24/80 [01:16<02:52,  3.09s/it]
Computing max image from bright frames:  31%|███▏      | 25/80 [01:20<02:52,  3.13s/it]
Computing max image from bright frames:  32%|███▎      | 26/80 [01:23<02:50,  3.16s/it]
Computing max image from bright frames:  34%|███▍      | 27/80 [01:26<02:48,  3.18s/it]
Computing max image from bright frames:  35%|███▌      | 28/80 [01:29<02:45,  3.18s/it]
Computing max image from bright frames:  36%|███▋      | 29/80 [01:33<02:44,  3.23s/it]
Computing max image from bright frames:  38%|███▊      | 30/80 [01:36<02:44,  3.29s/it]
Computing max image from bright frames:  39%|███▉      | 31/80 [01:39<02:43,  3.34s/it]
Computing max image from bright frames:  40%|████      | 32/80 [01:43<02:41,  3.37s/it]
Computing max image from bright frames:  41%|████▏     | 33/80 [01:46<02:39,  3.39s/it]
Computing max image from bright frames:  42%|████▎     | 34/80 [01:50<02:37,  3.43s/it]
Computing max image from bright frames:  44%|████▍     | 35/80 [01:53<02:36,  3.49s/it]
Computing max image from bright frames:  45%|████▌     | 36/80 [01:57<02:29,  3.41s/it]
Computing max image from bright frames:  46%|████▋     | 37/80 [02:00<02:24,  3.36s/it]
Computing max image from bright frames:  48%|████▊     | 38/80 [02:03<02:19,  3.31s/it]
Computing max image from bright frames:  49%|████▉     | 39/80 [02:06<02:14,  3.29s/it]
Computing max image from bright frames:  50%|█████     | 40/80 [02:08<01:49,  2.73s/it]
Computing max image from bright frames:  51%|█████▏    | 41/80 [02:11<01:52,  2.88s/it]
Computing max image from bright frames:  52%|█████▎    | 42/80 [02:14<01:53,  2.99s/it]
Computing max image from bright frames:  54%|█████▍    | 43/80 [02:17<01:53,  3.06s/it]
Computing max image from bright frames:  55%|█████▌    | 44/80 [02:21<01:52,  3.11s/it]
Computing max image from bright frames:  56%|█████▋    | 45/80 [02:24<01:49,  3.14s/it]
Computing max image from bright frames:  57%|█████▊    | 46/80 [02:27<01:47,  3.17s/it]
Computing max image from bright frames:  59%|█████▉    | 47/80 [02:30<01:45,  3.19s/it]
Computing max image from bright frames:  60%|██████    | 48/80 [02:34<01:42,  3.19s/it]
Computing max image from bright frames:  61%|██████▏   | 49/80 [02:37<01:39,  3.20s/it]
Computing max image from bright frames:  62%|██████▎   | 50/80 [02:40<01:39,  3.30s/it]
Computing max image from bright frames:  64%|██████▍   | 51/80 [02:44<01:37,  3.36s/it]
Computing max image from bright frames:  65%|██████▌   | 52/80 [02:47<01:34,  3.39s/it]
Computing max image from bright frames:  66%|██████▋   | 53/80 [02:51<01:32,  3.43s/it]
Computing max image from bright frames:  68%|██████▊   | 54/80 [02:54<01:30,  3.46s/it]
Computing max image from bright frames:  69%|██████▉   | 55/80 [02:58<01:27,  3.48s/it]
Computing max image from bright frames:  70%|███████   | 56/80 [03:01<01:21,  3.41s/it]
Computing max image from bright frames:  71%|███████▏  | 57/80 [03:04<01:16,  3.34s/it]
Computing max image from bright frames:  72%|███████▎  | 58/80 [03:08<01:12,  3.31s/it]
Computing max image from bright frames:  74%|███████▍  | 59/80 [03:11<01:08,  3.28s/it]
Computing max image from bright frames:  75%|███████▌  | 60/80 [03:13<01:01,  3.08s/it]
Computing max image from bright frames:  76%|███████▋  | 61/80 [03:17<00:59,  3.13s/it]
Computing max image from bright frames:  78%|███████▊  | 62/80 [03:20<00:56,  3.17s/it]
Computing max image from bright frames:  79%|███████▉  | 63/80 [03:23<00:54,  3.18s/it]
Computing max image from bright frames:  80%|████████  | 64/80 [03:26<00:51,  3.19s/it]
Computing max image from bright frames:  81%|████████▏ | 65/80 [03:30<00:48,  3.20s/it]
Computing max image from bright frames:  82%|████████▎ | 66/80 [03:33<00:44,  3.20s/it]
Computing max image from bright frames:  84%|████████▍ | 67/80 [03:36<00:41,  3.21s/it]
Computing max image from bright frames:  85%|████████▌ | 68/80 [03:39<00:38,  3.21s/it]
Computing max image from bright frames:  86%|████████▋ | 69/80 [03:43<00:36,  3.31s/it]
Computing max image from bright frames:  88%|████████▊ | 70/80 [03:46<00:33,  3.38s/it]
Computing max image from bright frames:  89%|████████▉ | 71/80 [03:50<00:30,  3.40s/it]
Computing max image from bright frames:  90%|█████████ | 72/80 [03:53<00:27,  3.43s/it]
Computing max image from bright frames:  91%|█████████▏| 73/80 [03:57<00:24,  3.43s/it]
Computing max image from bright frames:  92%|█████████▎| 74/80 [04:00<00:20,  3.48s/it]
Computing max image from bright frames:  94%|█████████▍| 75/80 [04:03<00:16,  3.39s/it]
Computing max image from bright frames:  95%|█████████▌| 76/80 [04:07<00:13,  3.35s/it]
Computing max image from bright frames:  96%|█████████▋| 77/80 [04:10<00:09,  3.31s/it]
Computing max image from bright frames:  98%|█████████▊| 78/80 [04:13<00:06,  3.27s/it]
Computing max image from bright frames:  99%|█████████▉| 79/80 [04:16<00:03,  3.26s/it]
Computing max image from bright frames: 100%|██████████| 80/80 [04:19<00:00,  3.24s/it]
                                                                                       
[✅] Casing detection complete: cx=1016.0, cy=765.0

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


  0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:25,  3.81it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:25,  3.81it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   2%|▏         | 2/100 [00:00<00:25,  3.81it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   3%|▎         | 3/100 [00:00<00:11,  8.61it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 321.212} (0.000):   3%|▎         | 3/100 [00:00<00:11,  8.61it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   4%|▍         | 4/100 [00:00<00:11,  8.61it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 335.354} (0.000):   5%|▌         | 5/100 [00:00<00:11,  8.61it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 335.354} (0.000):   6%|▌         | 6/100 [00:00<00:06, 14.12it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   6%|▌         | 6/100 [00:00<00:06, 14.12it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 349.495} (0.001):   7%|▋         | 7/100 [00:00<00:06, 14.12it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   8%|▊         | 8/100 [00:00<00:06, 14.12it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   9%|▉         | 9/100 [00:00<00:05, 17.81it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 363.636} (0.001):   9%|▉         | 9/100 [00:00<00:05, 17.81it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.002 | Best: {'fx': 370.707} (0.002):  10%|█         | 10/100 [00:00<00:05, 17.81it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.003 | Best: {'fx': 377.778} (0.003):  11%|█         | 11/100 [00:00<00:04, 17.81it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.003 | Best: {'fx': 377.778} (0.003):  12%|█▏        | 12/100 [00:00<00:04, 19.55it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.003 | Best: {'fx': 384.848} (0.003):  12%|█▏        | 12/100 [00:00<00:04, 19.55it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 391.919} (0.004):  13%|█▎        | 13/100 [00:00<00:04, 19.55it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  14%|█▍        | 14/100 [00:00<00:04, 19.55it/s] 
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  15%|█▌        | 15/100 [00:00<00:04, 20.98it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 406.061} (0.004):  15%|█▌        | 15/100 [00:00<00:04, 20.98it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  16%|█▌        | 16/100 [00:00<00:04, 20.98it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.005 | Best: {'fx': 420.202} (0.005):  17%|█▋        | 17/100 [00:01<00:03, 20.98it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.005 | Best: {'fx': 420.202} (0.005):  18%|█▊        | 18/100 [00:01<00:03, 22.00it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  18%|█▊        | 18/100 [00:01<00:03, 22.00it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.007 | Best: {'fx': 434.343} (0.007):  19%|█▉        | 19/100 [00:01<00:03, 22.00it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.010 | Best: {'fx': 448.485} (0.010):  20%|██        | 20/100 [00:01<00:03, 22.00it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.010 | Best: {'fx': 448.485} (0.010):  21%|██        | 21/100 [00:01<00:03, 19.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.009 | Best: {'fx': 448.485} (0.010):  21%|██        | 21/100 [00:01<00:03, 19.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.012 | Best: {'fx': 455.556} (0.012):  22%|██▏       | 22/100 [00:01<00:03, 19.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.015 | Best: {'fx': 462.626} (0.015):  23%|██▎       | 23/100 [00:01<00:03, 19.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.015 | Best: {'fx': 462.626} (0.015):  24%|██▍       | 24/100 [00:01<00:03, 22.32it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 469.697} (0.017):  24%|██▍       | 24/100 [00:01<00:03, 22.32it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 476.768} (0.020):  25%|██▌       | 25/100 [00:01<00:03, 22.32it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 483.838} (0.025):  26%|██▌       | 26/100 [00:01<00:03, 22.32it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 483.838} (0.025):  27%|██▋       | 27/100 [00:01<00:03, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.037 | Best: {'fx': 497.98} (0.037):  27%|██▋       | 27/100 [00:01<00:03, 22.05it/s] 
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.030 | Best: {'fx': 497.98} (0.037):  28%|██▊       | 28/100 [00:01<00:03, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.045 | Best: {'fx': 505.051} (0.045):  29%|██▉       | 29/100 [00:01<00:03, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.045 | Best: {'fx': 505.051} (0.045):  30%|███       | 30/100 [00:01<00:03, 23.29it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.055 | Best: {'fx': 512.121} (0.055):  30%|███       | 30/100 [00:01<00:03, 23.29it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.085 | Best: {'fx': 526.263} (0.085):  31%|███       | 31/100 [00:01<00:02, 23.29it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.085 | Best: {'fx': 533.333} (0.085):  32%|███▏      | 32/100 [00:01<00:02, 23.29it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.085 | Best: {'fx': 533.333} (0.085):  33%|███▎      | 33/100 [00:01<00:04, 14.06it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.076 | Best: {'fx': 533.333} (0.085):  33%|███▎      | 33/100 [00:01<00:04, 14.06it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.067 | Best: {'fx': 533.333} (0.085):  34%|███▍      | 34/100 [00:01<00:04, 14.06it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.066 | Best: {'fx': 533.333} (0.085):  35%|███▌      | 35/100 [00:02<00:04, 14.06it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.058 | Best: {'fx': 533.333} (0.085):  36%|███▌      | 36/100 [00:02<00:04, 14.06it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.058 | Best: {'fx': 533.333} (0.085):  37%|███▋      | 37/100 [00:02<00:03, 17.83it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.051 | Best: {'fx': 533.333} (0.085):  37%|███▋      | 37/100 [00:02<00:03, 17.83it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.043 | Best: {'fx': 533.333} (0.085):  38%|███▊      | 38/100 [00:02<00:03, 17.83it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.041 | Best: {'fx': 533.333} (0.085):  39%|███▉      | 39/100 [00:02<00:03, 17.83it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.041 | Best: {'fx': 533.333} (0.085):  40%|████      | 40/100 [00:02<00:03, 18.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.047 | Best: {'fx': 533.333} (0.085):  40%|████      | 40/100 [00:02<00:03, 18.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.036 | Best: {'fx': 533.333} (0.085):  41%|████      | 41/100 [00:02<00:03, 18.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.034 | Best: {'fx': 533.333} (0.085):  42%|████▏     | 42/100 [00:02<00:03, 18.97it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.034 | Best: {'fx': 533.333} (0.085):  43%|████▎     | 43/100 [00:02<00:02, 19.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.038 | Best: {'fx': 533.333} (0.085):  43%|████▎     | 43/100 [00:02<00:02, 19.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.032 | Best: {'fx': 533.333} (0.085):  44%|████▍     | 44/100 [00:02<00:02, 19.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.031 | Best: {'fx': 533.333} (0.085):  45%|████▌     | 45/100 [00:02<00:02, 19.77it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.031 | Best: {'fx': 533.333} (0.085):  46%|████▌     | 46/100 [00:02<00:02, 21.42it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.030 | Best: {'fx': 533.333} (0.085):  46%|████▌     | 46/100 [00:02<00:02, 21.42it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.085):  47%|████▋     | 47/100 [00:02<00:02, 21.42it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  48%|████▊     | 48/100 [00:02<00:02, 21.42it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.028 | Best: {'fx': 533.333} (0.085):  49%|████▉     | 49/100 [00:02<00:02, 18.50it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.029 | Best: {'fx': 533.333} (0.085):  49%|████▉     | 49/100 [00:02<00:02, 18.50it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  50%|█████     | 50/100 [00:02<00:02, 18.50it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.027 | Best: {'fx': 533.333} (0.085):  51%|█████     | 51/100 [00:02<00:02, 18.50it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  52%|█████▏    | 52/100 [00:02<00:02, 18.50it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  53%|█████▎    | 53/100 [00:02<00:02, 18.50it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.026 | Best: {'fx': 533.333} (0.085):  54%|█████▍    | 54/100 [00:02<00:01, 23.75it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 533.333} (0.085):  54%|█████▍    | 54/100 [00:02<00:01, 23.75it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 533.333} (0.085):  55%|█████▌    | 55/100 [00:02<00:01, 23.75it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.085):  56%|█████▌    | 56/100 [00:02<00:01, 23.75it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.085):  57%|█████▋    | 57/100 [00:02<00:01, 23.75it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.085):  58%|█████▊    | 58/100 [00:02<00:01, 23.75it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.085):  59%|█████▉    | 59/100 [00:02<00:01, 28.18it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.085):  59%|█████▉    | 59/100 [00:02<00:01, 28.18it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.085):  60%|██████    | 60/100 [00:02<00:01, 28.18it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.085):  61%|██████    | 61/100 [00:02<00:01, 28.18it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.085):  62%|██████▏   | 62/100 [00:03<00:01, 28.18it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.085):  63%|██████▎   | 63/100 [00:03<00:01, 29.78it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.085):  63%|██████▎   | 63/100 [00:03<00:01, 29.78it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.085):  64%|██████▍   | 64/100 [00:03<00:01, 29.78it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.085):  65%|██████▌   | 65/100 [00:03<00:01, 29.78it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.085):  66%|██████▌   | 66/100 [00:03<00:01, 29.78it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.085):  67%|██████▋   | 67/100 [00:03<00:01, 29.78it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.085):  68%|██████▊   | 68/100 [00:03<00:01, 29.78it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.085):  69%|██████▉   | 69/100 [00:03<00:01, 29.78it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.085):  70%|███████   | 70/100 [00:03<00:00, 38.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.085):  70%|███████   | 70/100 [00:03<00:00, 38.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.085):  71%|███████   | 71/100 [00:03<00:00, 38.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.085):  72%|███████▏  | 72/100 [00:03<00:00, 38.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.085):  73%|███████▎  | 73/100 [00:03<00:00, 38.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.085):  74%|███████▍  | 74/100 [00:03<00:00, 38.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.085):  75%|███████▌  | 75/100 [00:03<00:00, 29.10it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.085):  75%|███████▌  | 75/100 [00:03<00:00, 29.10it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.085):  76%|███████▌  | 76/100 [00:03<00:00, 29.10it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  77%|███████▋  | 77/100 [00:03<00:00, 29.10it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.085):  78%|███████▊  | 78/100 [00:03<00:00, 29.10it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.085):  79%|███████▉  | 79/100 [00:03<00:00, 29.88it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  79%|███████▉  | 79/100 [00:03<00:00, 29.88it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  80%|████████  | 80/100 [00:03<00:00, 29.88it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  81%|████████  | 81/100 [00:03<00:00, 29.88it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  82%|████████▏ | 82/100 [00:03<00:00, 29.88it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  83%|████████▎ | 83/100 [00:03<00:00, 28.90it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.085):  83%|████████▎ | 83/100 [00:03<00:00, 28.90it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  84%|████████▍ | 84/100 [00:03<00:00, 28.90it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  85%|████████▌ | 85/100 [00:03<00:00, 28.90it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  86%|████████▌ | 86/100 [00:03<00:00, 28.90it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  87%|████████▋ | 87/100 [00:03<00:00, 30.32it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  87%|████████▋ | 87/100 [00:03<00:00, 30.32it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  88%|████████▊ | 88/100 [00:03<00:00, 30.32it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  89%|████████▉ | 89/100 [00:04<00:00, 30.32it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  90%|█████████ | 90/100 [00:04<00:00, 30.32it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  91%|█████████ | 91/100 [00:04<00:00, 23.23it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  91%|█████████ | 91/100 [00:04<00:00, 23.23it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  92%|█████████▏| 92/100 [00:04<00:00, 23.23it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  93%|█████████▎| 93/100 [00:04<00:00, 23.23it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  94%|█████████▍| 94/100 [00:04<00:00, 23.23it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  95%|█████████▌| 95/100 [00:04<00:00, 24.63it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  95%|█████████▌| 95/100 [00:04<00:00, 24.63it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.085):  96%|█████████▌| 96/100 [00:04<00:00, 24.63it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  97%|█████████▋| 97/100 [00:04<00:00, 24.63it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.085):  98%|█████████▊| 98/100 [00:04<00:00, 22.78it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.085):  98%|█████████▊| 98/100 [00:04<00:00, 22.78it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.085):  99%|█████████▉| 99/100 [00:04<00:00, 22.78it/s]
                                                                                                                                       

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.049 | Best: {'fx': 508.333} (0.049):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.049 | Best: {'fx': 508.333} (0.049):   2%|▏         | 1/50 [00:00<00:31,  1.58it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.050 | Best: {'fx': 509.354} (0.050):   2%|▏         | 1/50 [00:00<00:31,  1.58it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.052 | Best: {'fx': 510.374} (0.052):   4%|▍         | 2/50 [00:00<00:30,  1.58it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.053 | Best: {'fx': 511.395} (0.053):   6%|▌         | 3/50 [00:00<00:29,  1.58it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.053 | Best: {'fx': 511.395} (0.053):   8%|▊         | 4/50 [00:00<00:07,  5.82it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.055 | Best: {'fx': 512.415} (0.055):   8%|▊         | 4/50 [00:00<00:07,  5.82it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.057 | Best: {'fx': 513.435} (0.057):  10%|█         | 5/50 [00:00<00:07,  5.82it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.058 | Best: {'fx': 514.456} (0.058):  12%|█▏        | 6/50 [00:00<00:07,  5.82it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.061 | Best: {'fx': 516.497} (0.061):  14%|█▍        | 7/50 [00:01<00:07,  5.82it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.061 | Best: {'fx': 516.497} (0.061):  16%|█▌        | 8/50 [00:01<00:04,  9.52it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.060 | Best: {'fx': 516.497} (0.061):  16%|█▌        | 8/50 [00:01<00:04,  9.52it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.063 | Best: {'fx': 517.517} (0.063):  18%|█▊        | 9/50 [00:01<00:04,  9.52it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.065 | Best: {'fx': 518.537} (0.065):  20%|██        | 10/50 [00:01<00:04,  9.52it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.067 | Best: {'fx': 519.558} (0.067):  22%|██▏       | 11/50 [00:01<00:04,  9.52it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.067 | Best: {'fx': 519.558} (0.067):  24%|██▍       | 12/50 [00:01<00:02, 14.72it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.070 | Best: {'fx': 520.578} (0.070):  24%|██▍       | 12/50 [00:01<00:02, 14.72it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.078 | Best: {'fx': 522.619} (0.078):  26%|██▌       | 13/50 [00:01<00:02, 14.72it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.083 | Best: {'fx': 524.66} (0.083):  28%|██▊       | 14/50 [00:01<00:02, 14.72it/s] 
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.083 | Best: {'fx': 524.66} (0.083):  30%|███       | 15/50 [00:01<00:02, 12.54it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.086 | Best: {'fx': 525.68} (0.086):  30%|███       | 15/50 [00:01<00:02, 12.54it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.074 | Best: {'fx': 525.68} (0.086):  32%|███▏      | 16/50 [00:01<00:02, 12.54it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.087 | Best: {'fx': 527.721} (0.087):  34%|███▍      | 17/50 [00:01<00:02, 12.54it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.079 | Best: {'fx': 527.721} (0.087):  36%|███▌      | 18/50 [00:01<00:02, 12.54it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.087 | Best: {'fx': 528.741} (0.087):  38%|███▊      | 19/50 [00:01<00:02, 12.54it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.087 | Best: {'fx': 528.741} (0.087):  40%|████      | 20/50 [00:01<00:02, 12.54it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.087 | Best: {'fx': 528.741} (0.087):  42%|████▏     | 21/50 [00:01<00:01, 18.78it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.088 | Best: {'fx': 529.762} (0.088):  42%|████▏     | 21/50 [00:01<00:01, 18.78it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.088 | Best: {'fx': 531.803} (0.088):  44%|████▍     | 22/50 [00:01<00:01, 18.78it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.088 | Best: {'fx': 530.782} (0.088):  46%|████▌     | 23/50 [00:01<00:01, 18.78it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.088 | Best: {'fx': 530.782} (0.088):  48%|████▊     | 24/50 [00:01<00:01, 18.70it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.085 | Best: {'fx': 530.782} (0.088):  48%|████▊     | 24/50 [00:01<00:01, 18.70it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.075 | Best: {'fx': 530.782} (0.088):  50%|█████     | 25/50 [00:01<00:01, 18.70it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.085 | Best: {'fx': 530.782} (0.088):  52%|█████▏    | 26/50 [00:01<00:01, 18.70it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.085 | Best: {'fx': 530.782} (0.088):  54%|█████▍    | 27/50 [00:01<00:01, 19.27it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.077 | Best: {'fx': 530.782} (0.088):  54%|█████▍    | 27/50 [00:01<00:01, 19.27it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.072 | Best: {'fx': 530.782} (0.088):  56%|█████▌    | 28/50 [00:01<00:01, 19.27it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.074 | Best: {'fx': 530.782} (0.088):  58%|█████▊    | 29/50 [00:01<00:01, 19.27it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.072 | Best: {'fx': 530.782} (0.088):  60%|██████    | 30/50 [00:02<00:01, 19.27it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.072 | Best: {'fx': 530.782} (0.088):  62%|██████▏   | 31/50 [00:02<00:00, 21.90it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.069 | Best: {'fx': 530.782} (0.088):  62%|██████▏   | 31/50 [00:02<00:00, 21.90it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.085 | Best: {'fx': 530.782} (0.088):  64%|██████▍   | 32/50 [00:02<00:00, 21.90it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.083 | Best: {'fx': 530.782} (0.088):  66%|██████▌   | 33/50 [00:02<00:00, 21.90it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.082 | Best: {'fx': 530.782} (0.088):  68%|██████▊   | 34/50 [00:02<00:00, 21.90it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.081 | Best: {'fx': 530.782} (0.088):  70%|███████   | 35/50 [00:02<00:00, 21.90it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.079 | Best: {'fx': 530.782} (0.088):  72%|███████▏  | 36/50 [00:02<00:00, 21.90it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.066 | Best: {'fx': 530.782} (0.088):  74%|███████▍  | 37/50 [00:02<00:00, 21.90it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.068 | Best: {'fx': 530.782} (0.088):  76%|███████▌  | 38/50 [00:02<00:00, 21.90it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.068 | Best: {'fx': 530.782} (0.088):  78%|███████▊  | 39/50 [00:02<00:00, 33.45it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.065 | Best: {'fx': 530.782} (0.088):  78%|███████▊  | 39/50 [00:02<00:00, 33.45it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.063 | Best: {'fx': 530.782} (0.088):  80%|████████  | 40/50 [00:02<00:00, 33.45it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.064 | Best: {'fx': 530.782} (0.088):  82%|████████▏ | 41/50 [00:02<00:00, 33.45it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.062 | Best: {'fx': 530.782} (0.088):  84%|████████▍ | 42/50 [00:02<00:00, 33.45it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.062 | Best: {'fx': 530.782} (0.088):  86%|████████▌ | 43/50 [00:02<00:00, 33.48it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.061 | Best: {'fx': 530.782} (0.088):  86%|████████▌ | 43/50 [00:02<00:00, 33.48it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.059 | Best: {'fx': 530.782} (0.088):  88%|████████▊ | 44/50 [00:02<00:00, 33.48it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.058 | Best: {'fx': 530.782} (0.088):  90%|█████████ | 45/50 [00:02<00:00, 33.48it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.057 | Best: {'fx': 530.782} (0.088):  92%|█████████▏| 46/50 [00:02<00:00, 33.48it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.057 | Best: {'fx': 530.782} (0.088):  94%|█████████▍| 47/50 [00:02<00:00, 31.77it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.055 | Best: {'fx': 530.782} (0.088):  94%|█████████▍| 47/50 [00:02<00:00, 31.77it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.054 | Best: {'fx': 530.782} (0.088):  96%|█████████▌| 48/50 [00:02<00:00, 31.77it/s]
Brute | Start: {'fx': 533.333} (0.085) | Current: 0.054 | Best: {'fx': 530.782} (0.088):  98%|█████████▊| 49/50 [00:02<00:00, 31.77it/s]
                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 530.7823129251701
    px: 1016.0
    py: 765.0
    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, 2000R(2000mm):20/20, 1000(1000mm):20/20, 2000L(2000mm):20/20
  Total: 80/80 frames used for optimization

Initial score: 30.8812: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 30.8812, picklable_objective(x0) = 30.8862

Best score: 30.8862: : 0iter [00:02, ?iter/s] 
Best score: 30.8862: : 1iter [00:02,  2.00s/iter]
Best score: 30.8862: : 1iter [00:02,  2.00s/iter]
Best score: 30.8862: : 2iter [00:02,  2.00s/iter]
Best score: 30.8862: : 3iter [00:02,  1.71iter/s]
Best score: 30.8862: : 3iter [00:02,  1.71iter/s]
Best score: 30.8862: : 4iter [00:02,  1.71iter/s]
Best score: 30.8862: : 5iter [00:02,  3.03iter/s]
Best score: 30.8862: : 5iter [00:02,  3.03iter/s]
Best score: 30.8862: : 6iter [00:02,  3.03iter/s]
Best score: 30.8862: : 7iter [00:02,  4.40iter/s]
Best score: 30.8862: : 7iter [00:02,  4.40iter/s]
Best score: 30.8862: : 8iter [00:02,  4.40iter/s]
Best score: 30.8862: : 9iter [00:02,  5.73iter/s]
Best score: 30.8862: : 9iter [00:02,  5.73iter/s]
Best score: 30.8862: : 10iter [00:02,  5.73iter/s]
Best score: 30.8862: : 11iter [00:02,  6.87iter/s]
Best score: 30.8862: : 11iter [00:02,  6.87iter/s]
Best score: 30.8862: : 12iter [00:03,  6.87iter/s]
Best score: 30.8862: : 13iter [00:03,  7.93iter/s]
Best score: 30.8862: : 13iter [00:03,  7.93iter/s]
Best score: 30.8862: : 14iter [00:03,  7.93iter/s]
Best score: 30.8862: : 15iter [00:03,  8.77iter/s]
Best score: 30.8862: : 15iter [00:03,  8.77iter/s]
Best score: 30.8862: : 16iter [00:03,  8.77iter/s]
Best score: 30.8862: : 17iter [00:03,  9.47iter/s]
Best score: 30.8862: : 17iter [00:03,  9.47iter/s]
Best score: 30.8862: : 18iter [00:03,  9.47iter/s]
Best score: 30.8862: : 19iter [00:03,  9.99iter/s]
Best score: 30.8862: : 19iter [00:03,  9.99iter/s]
Best score: 30.8862: : 20iter [00:03,  9.99iter/s]
Best score: 30.8862: : 21iter [00:03, 10.29iter/s]
Best score: 30.8862: : 21iter [00:03, 10.29iter/s]
Best score: 30.8862: : 22iter [00:03, 10.29iter/s]
Best score: 30.8862: : 23iter [00:03, 10.65iter/s]
Best score: 30.8862: : 23iter [00:04, 10.65iter/s]
Best score: 30.8862: : 24iter [00:04, 10.65iter/s]
Best score: 30.8862: : 25iter [00:04, 10.90iter/s]
Best score: 30.8862: : 25iter [00:04, 10.90iter/s]
Best score: 30.8862: : 26iter [00:04, 10.90iter/s]
Best score: 30.8862: : 27iter [00:04, 11.05iter/s]
Best score: 30.8862: : 27iter [00:04, 11.05iter/s]
Best score: 30.8862: : 28iter [00:04, 11.05iter/s]
Best score: 30.8862: : 29iter [00:04, 11.19iter/s]
Best score: 30.8862: : 29iter [00:04, 11.19iter/s]
Best score: 30.8862: : 30iter [00:04, 11.19iter/s]
Best score: 30.8862: : 31iter [00:04, 11.20iter/s]
Best score: 30.8862: : 31iter [00:04, 11.20iter/s]
Best score: 30.8862: : 32iter [00:04, 11.20iter/s]
Best score: 30.8862: : 33iter [00:04, 11.34iter/s]
Best score: 30.8862: : 33iter [00:04, 11.34iter/s]
Best score: 30.8862: : 34iter [00:04, 11.34iter/s]
Best score: 30.8862: : 35iter [00:04, 11.36iter/s]
Best score: 30.8862: : 35iter [00:05, 11.36iter/s]
Best score: 30.8862: : 36iter [00:05, 11.36iter/s]
Best score: 30.8862: : 37iter [00:05, 11.46iter/s]
Best score: 30.8862: : 37iter [00:05, 11.46iter/s]
Best score: 30.8862: : 38iter [00:05, 11.46iter/s]
Best score: 30.8862: : 39iter [00:05, 11.47iter/s]
Best score: 30.8862: : 39iter [00:05, 11.47iter/s]
Best score: 30.8862: : 40iter [00:05, 11.47iter/s]
Best score: 30.8862: : 41iter [00:05, 11.32iter/s]
Best score: 30.8862: : 41iter [00:05, 11.32iter/s]
Best score: 30.8862: : 42iter [00:05, 11.32iter/s]
Best score: 30.8862: : 43iter [00:05, 11.41iter/s]
Best score: 30.8862: : 43iter [00:05, 11.41iter/s]
Best score: 30.8862: : 44iter [00:05, 11.41iter/s]
Best score: 30.8862: : 45iter [00:05, 11.51iter/s]
Best score: 30.8862: : 45iter [00:05, 11.51iter/s]
Best score: 30.8862: : 46iter [00:06, 11.51iter/s]
Best score: 30.8862: : 47iter [00:06, 11.58iter/s]
Best score: 30.8862: : 47iter [00:06, 11.58iter/s]
Best score: 30.8862: : 48iter [00:06, 11.58iter/s]
Best score: 30.8862: : 49iter [00:06, 11.60iter/s]
[ITER 50] Best: 30.8862
[PARAMS] Current best parameters:
  fx: 530.7823
  fy: 530.7823
  px: 1016.0000
  py: 765.0000
  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: 30.8862: : 49iter [00:06, 11.60iter/s]
Best score: 30.8862: : 50iter [00:06, 11.60iter/s]
Best score: 30.8862: : 51iter [00:06, 11.47iter/s]
Best score: 30.8862: : 51iter [00:06, 11.47iter/s]
Best score: 30.8862: : 52iter [00:06, 11.47iter/s]
Best score: 30.8862: : 53iter [00:06, 11.55iter/s]
Best score: 30.8862: : 53iter [00:06, 11.55iter/s]
Best score: 30.8862: : 54iter [00:06, 11.55iter/s]
Best score: 30.8862: : 55iter [00:06, 11.61iter/s]
Best score: 30.8862: : 55iter [00:06, 11.61iter/s]
Best score: 30.8862: : 56iter [00:06, 11.61iter/s]
Best score: 30.8862: : 57iter [00:06, 11.61iter/s]
Best score: 30.8862: : 57iter [00:06, 11.61iter/s]
Best score: 30.8862: : 58iter [00:07, 11.61iter/s]
Best score: 30.8862: : 59iter [00:07, 11.59iter/s]
Best score: 30.8862: : 59iter [00:07, 11.59iter/s]
Best score: 30.8862: : 60iter [00:07, 11.59iter/s]
Best score: 30.8862: : 61iter [00:07, 11.40iter/s]
Best score: 30.8862: : 61iter [00:07, 11.40iter/s]
Best score: 30.8862: : 62iter [00:07, 11.40iter/s]
Best score: 30.8862: : 63iter [00:07, 11.47iter/s]
Best score: 30.8862: : 63iter [00:07, 11.47iter/s]
Best score: 30.8862: : 64iter [00:07, 11.47iter/s]
Best score: 30.8862: : 65iter [00:07, 11.51iter/s]
Best score: 30.8862: : 65iter [00:07, 11.51iter/s]
Best score: 30.8862: : 66iter [00:07, 11.51iter/s]
Best score: 30.8862: : 67iter [00:07, 11.55iter/s]
Best score: 30.8862: : 67iter [00:07, 11.55iter/s]
Best score: 30.8862: : 68iter [00:07, 11.55iter/s]
Best score: 30.8862: : 69iter [00:07, 11.56iter/s]
Best score: 30.8862: : 69iter [00:08, 11.56iter/s]
Best score: 30.8862: : 70iter [00:08, 11.56iter/s]
Best score: 30.8862: : 71iter [00:08, 11.44iter/s]
Best score: 30.8862: : 71iter [00:08, 11.44iter/s]
Best score: 30.8862: : 72iter [00:08, 11.44iter/s]
Best score: 30.8862: : 73iter [00:08, 11.47iter/s]
Best score: 30.8862: : 73iter [00:08, 11.47iter/s]
Best score: 30.8862: : 74iter [00:08, 11.47iter/s]
Best score: 30.8862: : 75iter [00:08, 11.54iter/s]
Best score: 30.8862: : 75iter [00:08, 11.54iter/s]
Best score: 30.8862: : 76iter [00:08, 11.54iter/s]
Best score: 30.8862: : 77iter [00:08, 11.55iter/s]
Best score: 30.8862: : 77iter [00:08, 11.55iter/s]
Best score: 30.8862: : 78iter [00:08, 11.55iter/s]
Best score: 30.8862: : 79iter [00:08, 11.55iter/s]
Best score: 22.5141: : 79iter [00:08, 11.55iter/s]
Best score: 22.5141: : 80iter [00:08, 11.55iter/s]
Best score: 22.5141: : 81iter [00:08, 11.40iter/s]
Best score: 22.5141: : 81iter [00:09, 11.40iter/s]
Best score: 22.5141: : 82iter [00:09, 11.40iter/s]
Best score: 22.5141: : 83iter [00:09, 11.48iter/s]
Best score: 22.5141: : 83iter [00:09, 11.48iter/s]
Best score: 22.5141: : 84iter [00:09, 11.48iter/s]
Best score: 22.5141: : 85iter [00:09, 11.56iter/s]
Best score: 22.5141: : 85iter [00:09, 11.56iter/s]
Best score: 22.5141: : 86iter [00:09, 11.56iter/s]
Best score: 22.5141: : 87iter [00:09, 11.62iter/s]
Best score: 22.5141: : 87iter [00:09, 11.62iter/s]
Best score: 22.5141: : 88iter [00:09, 11.62iter/s]
Best score: 22.5141: : 89iter [00:09, 11.64iter/s]
Best score: 19.0682: : 89iter [00:09, 11.64iter/s]
Best score: 19.0682: : 90iter [00:09, 11.64iter/s]
Best score: 19.0682: : 91iter [00:09, 11.49iter/s]
Best score: 19.0682: : 91iter [00:09, 11.49iter/s]
Best score: 19.0682: : 92iter [00:10, 11.49iter/s]
Best score: 19.0682: : 93iter [00:10, 11.55iter/s]
Best score: 19.0682: : 93iter [00:10, 11.55iter/s]
Best score: 19.0682: : 94iter [00:10, 11.55iter/s]
Best score: 19.0682: : 95iter [00:10, 11.57iter/s]
Best score: 19.0682: : 95iter [00:10, 11.57iter/s]
Best score: 19.0682: : 96iter [00:10, 11.57iter/s]
Best score: 19.0682: : 97iter [00:10, 11.58iter/s]
Best score: 19.0682: : 97iter [00:10, 11.58iter/s]
Best score: 19.0682: : 98iter [00:10, 11.58iter/s]
Best score: 19.0682: : 99iter [00:10, 11.63iter/s]
[ITER 100] Best: 18.5180
[PARAMS] Current best parameters:
  fx: 530.0396
  fy: 534.3831
  px: 1014.6231
  py: 769.2319
  k1: -0.02470263
  k2: 0.02226571
  k3: -0.02126676
  k4: 0.00932579
  p1: 0.00862376
  p2: 0.01162476
  p3: 0.00311304
  p4: -0.01308364
  s1: 0.0154
  s2: 0.0062
  s3: -0.0254
  s4: 0.0324
  tilt_x: -0.0376
  tilt_y: 0.0128
  scale: 3.0790
  rotation: -0.0967

Best score: 18.5180: : 99iter [00:10, 11.63iter/s]
Best score: 18.5180: : 100iter [00:10, 11.63iter/s]
Best score: 18.5180: : 101iter [00:10,  9.92iter/s]
Best score: 18.5180: : 101iter [00:10,  9.92iter/s]
Best score: 18.5180: : 102iter [00:10,  9.92iter/s]
Best score: 18.5180: : 103iter [00:10, 10.32iter/s]
Best score: 18.5180: : 103iter [00:11, 10.32iter/s]
Best score: 18.5180: : 104iter [00:11, 10.32iter/s]
Best score: 18.5180: : 105iter [00:11, 10.61iter/s]
Best score: 18.5180: : 105iter [00:11, 10.61iter/s]
Best score: 18.5180: : 106iter [00:11, 10.61iter/s]
Best score: 18.5180: : 107iter [00:11, 10.85iter/s]
Best score: 18.5180: : 107iter [00:11, 10.85iter/s]
Best score: 18.5180: : 108iter [00:11, 10.85iter/s]
Best score: 18.5180: : 109iter [00:11, 10.98iter/s]
Best score: 18.5180: : 109iter [00:11, 10.98iter/s]
Best score: 18.5180: : 110iter [00:11, 10.98iter/s]
Best score: 18.5180: : 111iter [00:11, 10.91iter/s]
Best score: 18.5180: : 111iter [00:11, 10.91iter/s]
Best score: 18.5180: : 112iter [00:11, 10.91iter/s]
Best score: 18.5180: : 113iter [00:11, 11.07iter/s]
Best score: 18.5180: : 113iter [00:11, 11.07iter/s]
Best score: 18.5180: : 114iter [00:12, 11.07iter/s]
Best score: 18.5180: : 115iter [00:12, 11.19iter/s]
Best score: 18.5180: : 115iter [00:12, 11.19iter/s]
Best score: 18.5180: : 116iter [00:12, 11.19iter/s]
Best score: 18.5180: : 117iter [00:12, 11.24iter/s]
Best score: 18.5180: : 117iter [00:12, 11.24iter/s]
Best score: 18.5180: : 118iter [00:12, 11.24iter/s]
Best score: 18.5180: : 119iter [00:12, 11.31iter/s]
Best score: 18.5180: : 119iter [00:12, 11.31iter/s]
Best score: 18.5180: : 120iter [00:12, 11.31iter/s]
Best score: 18.5180: : 121iter [00:12, 11.20iter/s]
Best score: 18.5180: : 121iter [00:12, 11.20iter/s]
Best score: 18.5180: : 122iter [00:12, 11.20iter/s]
Best score: 18.5180: : 123iter [00:12, 11.27iter/s]
Best score: 18.5180: : 123iter [00:12, 11.27iter/s]
Best score: 18.5180: : 124iter [00:12, 11.27iter/s]
Best score: 18.5180: : 125iter [00:12, 11.36iter/s]
Best score: 18.5180: : 125iter [00:13, 11.36iter/s]
Best score: 18.5180: : 126iter [00:13, 11.36iter/s]
Best score: 18.5180: : 127iter [00:13, 11.43iter/s]
Best score: 18.5180: : 127iter [00:13, 11.43iter/s]
Best score: 18.5180: : 128iter [00:13, 11.43iter/s]
Best score: 18.5180: : 129iter [00:13, 11.46iter/s]
Best score: 18.5180: : 129iter [00:13, 11.46iter/s]
Best score: 18.5180: : 130iter [00:13, 11.46iter/s]
Best score: 18.5180: : 131iter [00:13, 11.30iter/s]
Best score: 18.5180: : 131iter [00:13, 11.30iter/s]
Best score: 18.5180: : 132iter [00:13, 11.30iter/s]
Best score: 18.5180: : 133iter [00:13, 11.37iter/s]
Best score: 18.5180: : 133iter [00:13, 11.37iter/s]
Best score: 18.5180: : 134iter [00:13, 11.37iter/s]
Best score: 18.5180: : 135iter [00:13, 11.42iter/s]
Best score: 18.5180: : 135iter [00:13, 11.42iter/s]
Best score: 18.5180: : 136iter [00:13, 11.42iter/s]
Best score: 18.5180: : 137iter [00:13, 11.47iter/s]
Best score: 18.5180: : 137iter [00:14, 11.47iter/s]
Best score: 18.5180: : 138iter [00:14, 11.47iter/s]
Best score: 18.5180: : 139iter [00:14, 11.55iter/s]
Best score: 18.5180: : 139iter [00:14, 11.55iter/s]
Best score: 18.5180: : 140iter [00:14, 11.55iter/s]
Best score: 18.5180: : 141iter [00:14, 11.42iter/s]
Best score: 18.5180: : 141iter [00:14, 11.42iter/s]
Best score: 18.5180: : 142iter [00:14, 11.42iter/s]
Best score: 18.5180: : 143iter [00:14, 11.50iter/s]
Best score: 18.5180: : 143iter [00:14, 11.50iter/s]
Best score: 18.5180: : 144iter [00:14, 11.50iter/s]
Best score: 18.5180: : 145iter [00:14, 11.58iter/s]
Best score: 18.5180: : 145iter [00:14, 11.58iter/s]
Best score: 18.5180: : 146iter [00:14, 11.58iter/s]
Best score: 18.5180: : 147iter [00:14, 11.63iter/s]
Best score: 18.5180: : 147iter [00:14, 11.63iter/s]
Best score: 18.5180: : 148iter [00:15, 11.63iter/s]
Best score: 18.5180: : 149iter [00:15, 11.66iter/s]
[ITER 150] Best: 18.3696
[PARAMS] Current best parameters:
  fx: 520.0041
  fy: 520.2944
  px: 1007.4271
  py: 778.2334
  k1: 0.04782015
  k2: -0.02872797
  k3: -0.00355601
  k4: 0.00531986
  p1: 0.02793888
  p2: -0.00764934
  p3: -0.02499333
  p4: -0.00059021
  s1: 0.0089
  s2: 0.0220
  s3: -0.0150
  s4: 0.0437
  tilt_x: -0.0681
  tilt_y: 0.0299
  scale: 2.9170
  rotation: 0.3491

Best score: 18.3696: : 149iter [00:15, 11.66iter/s]
Best score: 18.3696: : 150iter [00:15, 11.66iter/s]
Best score: 18.3696: : 151iter [00:15,  7.50iter/s]
Best score: 18.3696: : 151iter [00:15,  7.50iter/s]
Best score: 18.3696: : 152iter [00:15,  7.50iter/s]
Best score: 18.3696: : 153iter [00:15,  8.39iter/s]
Best score: 18.3696: : 153iter [00:15,  8.39iter/s]
Best score: 18.3696: : 154iter [00:15,  8.39iter/s]
Best score: 18.3696: : 155iter [00:15,  9.20iter/s]
Best score: 18.3696: : 155iter [00:15,  9.20iter/s]
Best score: 18.3696: : 156iter [00:16,  9.20iter/s]
Best score: 18.3696: : 157iter [00:16,  9.80iter/s]
Best score: 18.3696: : 157iter [00:16,  9.80iter/s]
Best score: 18.3696: : 158iter [00:16,  9.80iter/s]
Best score: 18.3696: : 159iter [00:16, 10.34iter/s]
Best score: 17.8254: : 159iter [00:16, 10.34iter/s]
Best score: 17.8254: : 160iter [00:16, 10.34iter/s]
Best score: 17.8254: : 161iter [00:16, 10.54iter/s]
Best score: 17.8254: : 161iter [00:16, 10.54iter/s]
Best score: 17.8254: : 162iter [00:16, 10.54iter/s]
Best score: 17.8254: : 163iter [00:16, 10.88iter/s]
Best score: 17.8254: : 163iter [00:16, 10.88iter/s]
Best score: 17.8254: : 164iter [00:16, 10.88iter/s]
Best score: 17.8254: : 165iter [00:16, 11.07iter/s]
Best score: 17.8254: : 165iter [00:16, 11.07iter/s]
Best score: 17.8254: : 166iter [00:16, 11.07iter/s]
Best score: 17.8254: : 167iter [00:16, 11.27iter/s]
Best score: 17.8254: : 167iter [00:16, 11.27iter/s]
Best score: 17.8254: : 168iter [00:17, 11.27iter/s]
Best score: 17.8254: : 169iter [00:17, 11.37iter/s]
Best score: 11.6001: : 169iter [00:17, 11.37iter/s]
Best score: 11.6001: : 170iter [00:17, 11.37iter/s]
Best score: 11.6001: : 171iter [00:17, 11.23iter/s]
Best score: 11.6001: : 171iter [00:17, 11.23iter/s]
Best score: 11.6001: : 172iter [00:17, 11.23iter/s]
Best score: 11.6001: : 173iter [00:17, 11.34iter/s]
Best score: 11.6001: : 173iter [00:17, 11.34iter/s]
Best score: 11.6001: : 174iter [00:17, 11.34iter/s]
Best score: 11.6001: : 175iter [00:17, 11.42iter/s]
Best score: 11.6001: : 175iter [00:17, 11.42iter/s]
Best score: 11.6001: : 176iter [00:17, 11.42iter/s]
Best score: 11.6001: : 177iter [00:17, 11.49iter/s]
Best score: 11.6001: : 177iter [00:18, 11.49iter/s]
Best score: 11.6001: : 178iter [00:18, 11.49iter/s]
Best score: 11.6001: : 179iter [00:18,  8.52iter/s]
Best score: 10.6606: : 179iter [00:18,  8.52iter/s]
Best score: 10.6606: : 180iter [00:18,  8.52iter/s]
Best score: 10.6606: : 181iter [00:18,  9.16iter/s]
Best score: 10.6606: : 181iter [00:18,  9.16iter/s]
Best score: 10.6606: : 182iter [00:18,  9.16iter/s]
Best score: 10.6606: : 183iter [00:18,  9.77iter/s]
Best score: 10.6606: : 183iter [00:18,  9.77iter/s]
Best score: 10.6606: : 184iter [00:18,  9.77iter/s]
Best score: 10.6606: : 185iter [00:18, 10.23iter/s]
Best score: 10.6606: : 185iter [00:18, 10.23iter/s]
Best score: 10.6606: : 186iter [00:18, 10.23iter/s]
Best score: 10.6606: : 187iter [00:18, 10.59iter/s]
Best score: 10.6606: : 187iter [00:18, 10.59iter/s]
Best score: 10.6606: : 188iter [00:18, 10.59iter/s]
Best score: 10.6606: : 189iter [00:18, 10.89iter/s]
Best score: 8.1267: : 189iter [00:19, 10.89iter/s] 
Best score: 8.1267: : 190iter [00:19, 10.89iter/s]
Best score: 8.1267: : 191iter [00:19, 10.96iter/s]
Best score: 8.1267: : 191iter [00:19, 10.96iter/s]
Best score: 8.1267: : 192iter [00:19, 10.96iter/s]
Best score: 8.1267: : 193iter [00:19, 11.17iter/s]
Best score: 8.1267: : 193iter [00:19, 11.17iter/s]
Best score: 8.1267: : 194iter [00:19, 11.17iter/s]
Best score: 8.1267: : 195iter [00:19, 11.33iter/s]
Best score: 8.1267: : 195iter [00:19, 11.33iter/s]
Best score: 8.1267: : 196iter [00:19, 11.33iter/s]
Best score: 8.1267: : 197iter [00:19, 11.48iter/s]
Best score: 8.1267: : 197iter [00:19, 11.48iter/s]
Best score: 8.1267: : 198iter [00:19, 11.48iter/s]
Best score: 8.1267: : 199iter [00:19, 11.56iter/s]
[ITER 200] Best: 4.1690
[PARAMS] Current best parameters:
  fx: 550.1204
  fy: 550.1346
  px: 1021.0443
  py: 761.1550
  k1: -0.03802196
  k2: -0.02935163
  k3: 0.05969365
  k4: -0.02183650
  p1: -0.00235663
  p2: 0.00622514
  p3: -0.01848257
  p4: -0.01313863
  s1: 0.0022
  s2: 0.0332
  s3: 0.0076
  s4: 0.0175
  tilt_x: -0.0555
  tilt_y: -0.0235
  scale: 3.0513
  rotation: -0.6303

Best score: 4.1690: : 199iter [00:19, 11.56iter/s]
Best score: 4.1690: : 200iter [00:20, 11.56iter/s]
Best score: 4.1690: : 201iter [00:20,  7.45iter/s]
Best score: 4.1690: : 201iter [00:20,  7.45iter/s]
Best score: 4.1690: : 202iter [00:20,  7.45iter/s]
Best score: 4.1690: : 203iter [00:20,  8.37iter/s]
Best score: 4.1690: : 203iter [00:20,  8.37iter/s]
Best score: 4.1690: : 204iter [00:20,  8.37iter/s]
Best score: 4.1690: : 205iter [00:20,  9.17iter/s]
Best score: 4.1690: : 205iter [00:20,  9.17iter/s]
Best score: 4.1690: : 206iter [00:20,  9.17iter/s]
Best score: 4.1690: : 207iter [00:20,  9.84iter/s]
Best score: 4.1690: : 207iter [00:20,  9.84iter/s]
Best score: 4.1690: : 208iter [00:21,  9.84iter/s]
Best score: 4.1690: : 209iter [00:21, 10.34iter/s]
Best score: 4.1690: : 209iter [00:21, 10.34iter/s]
Best score: 4.1690: : 210iter [00:21, 10.34iter/s]
Best score: 4.1690: : 211iter [00:21, 10.53iter/s]
Best score: 4.1690: : 211iter [00:21, 10.53iter/s]
Best score: 4.1690: : 212iter [00:21, 10.53iter/s]
Best score: 4.1690: : 213iter [00:21, 10.86iter/s]
Best score: 4.1690: : 213iter [00:21, 10.86iter/s]
Best score: 4.1690: : 214iter [00:21, 10.86iter/s]
Best score: 4.1690: : 215iter [00:21, 11.12iter/s]
Best score: 4.1690: : 215iter [00:21, 11.12iter/s]
Best score: 4.1690: : 216iter [00:21, 11.12iter/s]
Best score: 4.1690: : 217iter [00:21, 11.31iter/s]
Best score: 4.1690: : 217iter [00:21, 11.31iter/s]
Best score: 4.1690: : 218iter [00:21, 11.31iter/s]
Best score: 4.1690: : 219iter [00:21, 11.44iter/s]
Best score: 4.1690: : 219iter [00:21, 11.44iter/s]
Best score: 4.1690: : 220iter [00:22, 11.44iter/s]
Best score: 4.1690: : 221iter [00:22, 11.35iter/s]
Best score: 4.1690: : 221iter [00:22, 11.35iter/s]
Best score: 4.1690: : 222iter [00:22, 11.35iter/s]
Best score: 4.1690: : 223iter [00:22, 11.43iter/s]
Best score: 4.1690: : 223iter [00:22, 11.43iter/s]
Best score: 4.1690: : 224iter [00:22, 11.43iter/s]
Best score: 4.1690: : 225iter [00:22, 11.54iter/s]
Best score: 4.1690: : 225iter [00:22, 11.54iter/s]
Best score: 4.1690: : 226iter [00:22, 11.54iter/s]
Best score: 4.1690: : 227iter [00:22, 11.58iter/s]
Best score: 4.1690: : 227iter [00:22, 11.58iter/s]
Best score: 4.1690: : 228iter [00:22, 11.58iter/s]
Best score: 4.1690: : 229iter [00:22, 11.63iter/s]
Best score: 3.4097: : 229iter [00:22, 11.63iter/s]
Best score: 3.4097: : 230iter [00:22, 11.63iter/s]
Best score: 3.4097: : 231iter [00:22, 11.46iter/s]
Best score: 3.4097: : 231iter [00:23, 11.46iter/s]
Best score: 3.4097: : 232iter [00:23, 11.46iter/s]
Best score: 3.4097: : 233iter [00:23, 11.53iter/s]
Best score: 3.4097: : 233iter [00:23, 11.53iter/s]
Best score: 3.4097: : 234iter [00:23, 11.53iter/s]
Best score: 3.4097: : 235iter [00:23, 11.60iter/s]
Best score: 3.4097: : 235iter [00:23, 11.60iter/s]
Best score: 3.4097: : 236iter [00:23, 11.60iter/s]
Best score: 3.4097: : 237iter [00:23, 11.65iter/s]
Best score: 3.4097: : 237iter [00:23, 11.65iter/s]
Best score: 3.4097: : 238iter [00:23, 11.65iter/s]
Best score: 3.4097: : 239iter [00:23, 11.67iter/s]
Best score: 2.7476: : 239iter [00:23, 11.67iter/s]
Best score: 2.7476: : 240iter [00:23, 11.67iter/s]
Best score: 2.7476: : 241iter [00:23, 11.47iter/s]
Best score: 2.7476: : 241iter [00:23, 11.47iter/s]
Best score: 2.7476: : 242iter [00:23, 11.47iter/s]
Best score: 2.7476: : 243iter [00:23, 11.56iter/s]
Best score: 2.7476: : 243iter [00:24, 11.56iter/s]
Best score: 2.7476: : 244iter [00:24, 11.56iter/s]
Best score: 2.7476: : 245iter [00:24, 11.60iter/s]
Best score: 2.7476: : 245iter [00:24, 11.60iter/s]
Best score: 2.7476: : 246iter [00:24, 11.60iter/s]
Best score: 2.7476: : 247iter [00:24, 11.64iter/s]
Best score: 2.7476: : 247iter [00:24, 11.64iter/s]
Best score: 2.7476: : 248iter [00:24, 11.64iter/s]
Best score: 2.7476: : 249iter [00:24, 11.70iter/s]
[ITER 250] Best: 1.7502
[PARAMS] Current best parameters:
  fx: 570.7231
  fy: 568.6151
  px: 1017.2612
  py: 760.4060
  k1: -0.01540688
  k2: -0.07123326
  k3: 0.07142211
  k4: -0.02173557
  p1: -0.00824268
  p2: -0.00441871
  p3: -0.00187287
  p4: -0.01076402
  s1: -0.0104
  s2: 0.0274
  s3: 0.0247
  s4: -0.0089
  tilt_x: -0.0642
  tilt_y: -0.0280
  scale: 2.9748
  rotation: -0.2080

Best score: 1.7502: : 249iter [00:24, 11.70iter/s]
Best score: 1.7502: : 250iter [00:24, 11.70iter/s]
Best score: 1.7502: : 251iter [00:24,  7.43iter/s]
Best score: 1.7502: : 251iter [00:25,  7.43iter/s]
Best score: 1.7502: : 252iter [00:25,  7.43iter/s]
Best score: 1.7502: : 253iter [00:25,  8.34iter/s]
Best score: 1.7502: : 253iter [00:25,  8.34iter/s]
Best score: 1.7502: : 254iter [00:25,  8.34iter/s]
Best score: 1.7502: : 255iter [00:25,  9.11iter/s]
Best score: 1.7502: : 255iter [00:25,  9.11iter/s]
Best score: 1.7502: : 256iter [00:25,  9.11iter/s]
Best score: 1.7502: : 257iter [00:25,  9.72iter/s]
Best score: 1.7502: : 257iter [00:25,  9.72iter/s]
Best score: 1.7502: : 258iter [00:25,  9.72iter/s]
Best score: 1.7502: : 259iter [00:25, 10.24iter/s]
Best score: 1.6251: : 259iter [00:25, 10.24iter/s]
Best score: 1.6251: : 260iter [00:25, 10.24iter/s]
Best score: 1.6251: : 261iter [00:25, 10.48iter/s]
Best score: 1.6251: : 261iter [00:25, 10.48iter/s]
Best score: 1.6251: : 262iter [00:26, 10.48iter/s]
Best score: 1.6251: : 263iter [00:26, 10.83iter/s]
Best score: 1.6251: : 263iter [00:26, 10.83iter/s]
Best score: 1.6251: : 264iter [00:26, 10.83iter/s]
Best score: 1.6251: : 265iter [00:26, 11.08iter/s]
Best score: 1.6251: : 265iter [00:26, 11.08iter/s]
Best score: 1.6251: : 266iter [00:26, 11.08iter/s]
Best score: 1.6251: : 267iter [00:26, 11.26iter/s]
Best score: 1.6251: : 267iter [00:26, 11.26iter/s]
Best score: 1.6251: : 268iter [00:26, 11.26iter/s]
Best score: 1.6251: : 269iter [00:26, 11.41iter/s]
Best score: 1.6251: : 269iter [00:26, 11.41iter/s]
Best score: 1.6251: : 270iter [00:26, 11.41iter/s]
Best score: 1.6251: : 271iter [00:26, 11.32iter/s]
Best score: 1.6251: : 271iter [00:26, 11.32iter/s]
Best score: 1.6251: : 272iter [00:26, 11.32iter/s]
Best score: 1.6251: : 273iter [00:26, 11.42iter/s]
Best score: 1.6251: : 273iter [00:26, 11.42iter/s]
Best score: 1.6251: : 274iter [00:27, 11.42iter/s]
Best score: 1.6251: : 275iter [00:27, 11.50iter/s]
Best score: 1.6251: : 275iter [00:27, 11.50iter/s]
Best score: 1.6251: : 276iter [00:27, 11.50iter/s]
Best score: 1.6251: : 277iter [00:27, 11.55iter/s]
Best score: 1.6251: : 277iter [00:27, 11.55iter/s]
Best score: 1.6251: : 278iter [00:27, 11.55iter/s]
Best score: 1.6251: : 279iter [00:27, 11.59iter/s]
Best score: 1.4525: : 279iter [00:27, 11.59iter/s]
Best score: 1.4525: : 280iter [00:27, 11.59iter/s]
Best score: 1.4525: : 281iter [00:27, 11.45iter/s]
Best score: 1.4525: : 281iter [00:27, 11.45iter/s]
Best score: 1.4525: : 282iter [00:27, 11.45iter/s]
Best score: 1.4525: : 283iter [00:27, 11.56iter/s]
Best score: 1.4525: : 283iter [00:27, 11.56iter/s]
Best score: 1.4525: : 284iter [00:27, 11.56iter/s]
Best score: 1.4525: : 285iter [00:27, 11.59iter/s]
Best score: 1.4525: : 285iter [00:27, 11.59iter/s]
Best score: 1.4525: : 286iter [00:28, 11.59iter/s]
Best score: 1.4525: : 287iter [00:28, 11.64iter/s]
Best score: 1.4525: : 287iter [00:28, 11.64iter/s]
Best score: 1.4525: : 288iter [00:28, 11.64iter/s]
Best score: 1.4525: : 289iter [00:28, 11.69iter/s]
Best score: 1.4525: : 289iter [00:28, 11.69iter/s]
Best score: 1.4525: : 290iter [00:28, 11.69iter/s]
Best score: 1.4525: : 291iter [00:28, 11.53iter/s]
Best score: 1.4525: : 291iter [00:28, 11.53iter/s]
Best score: 1.4525: : 292iter [00:28, 11.53iter/s]
Best score: 1.4525: : 293iter [00:28, 11.55iter/s]
Best score: 1.4525: : 293iter [00:28, 11.55iter/s]
Best score: 1.4525: : 294iter [00:28, 11.55iter/s]
Best score: 1.4525: : 295iter [00:28, 11.63iter/s]
Best score: 1.4525: : 295iter [00:28, 11.63iter/s]
Best score: 1.4525: : 296iter [00:28, 11.63iter/s]
Best score: 1.4525: : 297iter [00:28, 11.68iter/s]
Best score: 1.4525: : 297iter [00:29, 11.68iter/s]
Best score: 1.4525: : 298iter [00:29, 11.68iter/s]
Best score: 1.4525: : 299iter [00:29, 11.74iter/s]
[ITER 300] Best: 1.3331
[PARAMS] Current best parameters:
  fx: 566.6676
  fy: 567.4548
  px: 1014.7625
  py: 758.9924
  k1: 0.00175676
  k2: -0.08834888
  k3: 0.07061621
  k4: -0.01821529
  p1: -0.00647459
  p2: -0.01104786
  p3: -0.01237817
  p4: -0.01934287
  s1: 0.0120
  s2: 0.0269
  s3: 0.0105
  s4: 0.0112
  tilt_x: -0.0647
  tilt_y: -0.0311
  scale: 2.9763
  rotation: -0.3205

Best score: 1.3331: : 299iter [00:29, 11.74iter/s]
Best score: 1.3331: : 300iter [00:29, 11.74iter/s]
Best score: 1.3331: : 301iter [00:29,  7.49iter/s]
Best score: 1.3331: : 301iter [00:29,  7.49iter/s]
Best score: 1.3331: : 302iter [00:29,  7.49iter/s]
Best score: 1.3331: : 303iter [00:29,  8.39iter/s]
Best score: 1.3331: : 303iter [00:29,  8.39iter/s]
Best score: 1.3331: : 304iter [00:29,  8.39iter/s]
Best score: 1.3331: : 305iter [00:29,  9.16iter/s]
Best score: 1.3331: : 305iter [00:30,  9.16iter/s]
Best score: 1.3331: : 306iter [00:30,  9.16iter/s]
Best score: 1.3331: : 307iter [00:30,  9.83iter/s]
Best score: 1.3331: : 307iter [00:30,  9.83iter/s]
Best score: 1.3331: : 308iter [00:30,  9.83iter/s]
Best score: 1.3331: : 309iter [00:30, 10.35iter/s]
Best score: 1.1943: : 309iter [00:30, 10.35iter/s]
Best score: 1.1943: : 310iter [00:30, 10.35iter/s]
Best score: 1.1943: : 311iter [00:30, 10.58iter/s]
Best score: 1.1943: : 311iter [00:30, 10.58iter/s]
Best score: 1.1943: : 312iter [00:30, 10.58iter/s]
Best score: 1.1943: : 313iter [00:30, 10.91iter/s]
Best score: 1.1943: : 313iter [00:30, 10.91iter/s]
Best score: 1.1943: : 314iter [00:30, 10.91iter/s]
Best score: 1.1943: : 315iter [00:30, 11.15iter/s]
Best score: 1.1943: : 315iter [00:30, 11.15iter/s]
Best score: 1.1943: : 316iter [00:30, 11.15iter/s]
Best score: 1.1943: : 317iter [00:30, 11.32iter/s]
Best score: 1.1943: : 317iter [00:31, 11.32iter/s]
Best score: 1.1943: : 318iter [00:31, 11.32iter/s]
Best score: 1.1943: : 319iter [00:31, 11.46iter/s]
Best score: 0.7600: : 319iter [00:31, 11.46iter/s]
Best score: 0.7600: : 320iter [00:31, 11.46iter/s]
Best score: 0.7600: : 321iter [00:31, 11.34iter/s]
Best score: 0.7600: : 321iter [00:31, 11.34iter/s]
Best score: 0.7600: : 322iter [00:31, 11.34iter/s]
Best score: 0.7600: : 323iter [00:31, 11.47iter/s]
Best score: 0.7600: : 323iter [00:31, 11.47iter/s]
Best score: 0.7600: : 324iter [00:31, 11.47iter/s]
Best score: 0.7600: : 325iter [00:31, 11.57iter/s]
Best score: 0.7600: : 325iter [00:31, 11.57iter/s]
Best score: 0.7600: : 326iter [00:31, 11.57iter/s]
Best score: 0.7600: : 327iter [00:31, 11.60iter/s]
Best score: 0.7600: : 327iter [00:31, 11.60iter/s]
Best score: 0.7600: : 328iter [00:31, 11.60iter/s]
Best score: 0.7600: : 329iter [00:31, 11.67iter/s]
Best score: 0.6172: : 329iter [00:32, 11.67iter/s]
Best score: 0.6172: : 330iter [00:32, 11.67iter/s]
Best score: 0.6172: : 331iter [00:32, 11.52iter/s]
Best score: 0.6172: : 331iter [00:32, 11.52iter/s]
Best score: 0.6172: : 332iter [00:32, 11.52iter/s]
Best score: 0.6172: : 333iter [00:32, 11.59iter/s]
Best score: 0.6172: : 333iter [00:32, 11.59iter/s]
Best score: 0.6172: : 334iter [00:32, 11.59iter/s]
Best score: 0.6172: : 335iter [00:32, 11.65iter/s]
Best score: 0.6172: : 335iter [00:32, 11.65iter/s]
Best score: 0.6172: : 336iter [00:32, 11.65iter/s]
Best score: 0.6172: : 337iter [00:32, 11.71iter/s]
Best score: 0.6172: : 337iter [00:32, 11.71iter/s]
Best score: 0.6172: : 338iter [00:32, 11.71iter/s]
Best score: 0.6172: : 339iter [00:32, 11.76iter/s]
Best score: 0.5083: : 339iter [00:32, 11.76iter/s]
Best score: 0.5083: : 340iter [00:33, 11.76iter/s]
Best score: 0.5083: : 341iter [00:33, 11.58iter/s]
Best score: 0.5083: : 341iter [00:33, 11.58iter/s]
Best score: 0.5083: : 342iter [00:33, 11.58iter/s]
Best score: 0.5083: : 343iter [00:33, 11.57iter/s]
Best score: 0.5083: : 343iter [00:33, 11.57iter/s]
Best score: 0.5083: : 344iter [00:33, 11.57iter/s]
Best score: 0.5083: : 345iter [00:33, 11.65iter/s]
Best score: 0.5083: : 345iter [00:33, 11.65iter/s]
Best score: 0.5083: : 346iter [00:33, 11.65iter/s]
Best score: 0.5083: : 347iter [00:33, 11.67iter/s]
Best score: 0.5083: : 347iter [00:33, 11.67iter/s]
Best score: 0.5083: : 348iter [00:33, 11.67iter/s]
Best score: 0.5083: : 349iter [00:33, 11.70iter/s]
[ITER 350] Best: 0.5083
[PARAMS] Current best parameters:
  fx: 574.5960
  fy: 574.9513
  px: 1016.4004
  py: 762.7791
  k1: -0.00672394
  k2: -0.07811009
  k3: 0.06285068
  k4: -0.01652000
  p1: 0.00293426
  p2: -0.00353496
  p3: -0.00957832
  p4: -0.01691793
  s1: 0.0084
  s2: 0.0201
  s3: 0.0108
  s4: 0.0077
  tilt_x: -0.0687
  tilt_y: -0.0228
  scale: 2.9589
  rotation: -0.2442

Best score: 0.5083: : 349iter [00:33, 11.70iter/s]
Best score: 0.5083: : 350iter [00:34, 11.70iter/s]
Best score: 0.5083: : 351iter [00:34,  7.46iter/s]
Best score: 0.5083: : 351iter [00:34,  7.46iter/s]
Best score: 0.5083: : 352iter [00:34,  7.46iter/s]
Best score: 0.5083: : 353iter [00:34,  8.39iter/s]
Best score: 0.5083: : 353iter [00:34,  8.39iter/s]
Best score: 0.5083: : 354iter [00:34,  8.39iter/s]
Best score: 0.5083: : 355iter [00:34,  9.19iter/s]
Best score: 0.5083: : 355iter [00:34,  9.19iter/s]
Best score: 0.5083: : 356iter [00:34,  9.19iter/s]
Best score: 0.5083: : 357iter [00:34,  9.85iter/s]
Best score: 0.5083: : 357iter [00:34,  9.85iter/s]
Best score: 0.5083: : 358iter [00:34,  9.85iter/s]
Best score: 0.5083: : 359iter [00:34, 10.38iter/s]
Best score: 0.4797: : 359iter [00:34, 10.38iter/s]
Best score: 0.4797: : 360iter [00:35, 10.38iter/s]
Best score: 0.4797: : 361iter [00:35, 10.61iter/s]
Best score: 0.4797: : 361iter [00:35, 10.61iter/s]
Best score: 0.4797: : 362iter [00:35, 10.61iter/s]
Best score: 0.4797: : 363iter [00:35, 10.95iter/s]
Best score: 0.4797: : 363iter [00:35, 10.95iter/s]
Best score: 0.4797: : 364iter [00:35, 10.95iter/s]
Best score: 0.4797: : 365iter [00:35, 11.21iter/s]
Best score: 0.4797: : 365iter [00:35, 11.21iter/s]
Best score: 0.4797: : 366iter [00:35, 11.21iter/s]
Best score: 0.4797: : 367iter [00:35, 11.40iter/s]
Best score: 0.4797: : 367iter [00:35, 11.40iter/s]
Best score: 0.4797: : 368iter [00:35, 11.40iter/s]
Best score: 0.4797: : 369iter [00:35, 11.52iter/s]
Best score: 0.4349: : 369iter [00:35, 11.52iter/s]
Best score: 0.4349: : 370iter [00:35, 11.52iter/s]
Best score: 0.4349: : 371iter [00:35, 11.39iter/s]
Best score: 0.4349: : 371iter [00:36, 11.39iter/s]
Best score: 0.4349: : 372iter [00:36, 11.39iter/s]
Best score: 0.4349: : 373iter [00:36, 11.47iter/s]
Best score: 0.4349: : 373iter [00:36, 11.47iter/s]
Best score: 0.4349: : 374iter [00:36, 11.47iter/s]
Best score: 0.4349: : 375iter [00:36, 11.56iter/s]
Best score: 0.4349: : 375iter [00:36, 11.56iter/s]
Best score: 0.4349: : 376iter [00:36, 11.56iter/s]
Best score: 0.4349: : 377iter [00:36, 11.65iter/s]
Best score: 0.4349: : 377iter [00:36, 11.65iter/s]
Best score: 0.4349: : 378iter [00:36, 11.65iter/s]
Best score: 0.4349: : 379iter [00:36, 11.68iter/s]
Best score: 0.4292: : 379iter [00:36, 11.68iter/s]
Best score: 0.4292: : 380iter [00:36, 11.68iter/s]
Best score: 0.4292: : 381iter [00:36, 11.52iter/s]
Best score: 0.4292: : 381iter [00:36, 11.52iter/s]
Best score: 0.4292: : 382iter [00:36, 11.52iter/s]
Best score: 0.4292: : 383iter [00:36, 11.61iter/s]
Best score: 0.4292: : 383iter [00:37, 11.61iter/s]
Best score: 0.4292: : 384iter [00:37, 11.61iter/s]
Best score: 0.4292: : 385iter [00:37, 11.67iter/s]
Best score: 0.4292: : 385iter [00:37, 11.67iter/s]
Best score: 0.4292: : 386iter [00:37, 11.67iter/s]
Best score: 0.4292: : 387iter [00:37, 11.72iter/s]
Best score: 0.4292: : 387iter [00:37, 11.72iter/s]
Best score: 0.4292: : 388iter [00:37, 11.72iter/s]
Best score: 0.4292: : 389iter [00:37, 11.77iter/s]
Best score: 0.3983: : 389iter [00:37, 11.77iter/s]
Best score: 0.3983: : 390iter [00:37, 11.77iter/s]
Best score: 0.3983: : 391iter [00:37, 11.60iter/s]
Best score: 0.3983: : 391iter [00:37, 11.60iter/s]
Best score: 0.3983: : 392iter [00:37, 11.60iter/s]
Best score: 0.3983: : 393iter [00:37, 11.66iter/s]
Best score: 0.3983: : 393iter [00:37, 11.66iter/s]
Best score: 0.3983: : 394iter [00:37, 11.66iter/s]
Best score: 0.3983: : 395iter [00:37, 11.71iter/s]
Best score: 0.3983: : 395iter [00:38, 11.71iter/s]
Best score: 0.3983: : 396iter [00:38, 11.71iter/s]
Best score: 0.3983: : 397iter [00:38, 11.75iter/s]
Best score: 0.3983: : 397iter [00:38, 11.75iter/s]
Best score: 0.3983: : 398iter [00:38, 11.75iter/s]
Best score: 0.3983: : 399iter [00:38, 11.76iter/s]
[ITER 400] Best: 0.3604
[PARAMS] Current best parameters:
  fx: 576.3076
  fy: 576.4063
  px: 1014.1828
  py: 766.0175
  k1: -0.00599636
  k2: -0.08745779
  k3: 0.07074161
  k4: -0.01830436
  p1: 0.00699937
  p2: -0.00212346
  p3: -0.01127853
  p4: -0.01629721
  s1: 0.0107
  s2: 0.0162
  s3: 0.0099
  s4: 0.0106
  tilt_x: -0.0621
  tilt_y: -0.0052
  scale: 2.9626
  rotation: -0.2991

Best score: 0.3604: : 399iter [00:38, 11.76iter/s]
Best score: 0.3604: : 400iter [00:38, 11.76iter/s]
Best score: 0.3604: : 401iter [00:38,  7.52iter/s]
Best score: 0.3604: : 401iter [00:38,  7.52iter/s]
Best score: 0.3604: : 402iter [00:38,  7.52iter/s]
Best score: 0.3604: : 403iter [00:38,  8.44iter/s]
Best score: 0.3604: : 403iter [00:39,  8.44iter/s]
Best score: 0.3604: : 404iter [00:39,  8.44iter/s]
Best score: 0.3604: : 405iter [00:39,  9.23iter/s]
Best score: 0.3604: : 405iter [00:39,  9.23iter/s]
Best score: 0.3604: : 406iter [00:39,  9.23iter/s]
Best score: 0.3604: : 407iter [00:39,  9.88iter/s]
Best score: 0.3604: : 407iter [00:39,  9.88iter/s]
Best score: 0.3604: : 408iter [00:39,  9.88iter/s]
Best score: 0.3604: : 409iter [00:39, 10.40iter/s]
Best score: 0.3604: : 409iter [00:39, 10.40iter/s]
Best score: 0.3604: : 410iter [00:39, 10.40iter/s]
Best score: 0.3604: : 411iter [00:39, 10.60iter/s]
Best score: 0.3604: : 411iter [00:39, 10.60iter/s]
Best score: 0.3604: : 412iter [00:39, 10.60iter/s]
Best score: 0.3604: : 413iter [00:39, 10.94iter/s]
Best score: 0.3604: : 413iter [00:39, 10.94iter/s]
Best score: 0.3604: : 414iter [00:39, 10.94iter/s]
Best score: 0.3604: : 415iter [00:39, 11.18iter/s]
Best score: 0.3604: : 415iter [00:40, 11.18iter/s]
Best score: 0.3604: : 416iter [00:40, 11.18iter/s]
Best score: 0.3604: : 417iter [00:40, 11.38iter/s]
Best score: 0.3604: : 417iter [00:40, 11.38iter/s]
Best score: 0.3604: : 418iter [00:40, 11.38iter/s]
Best score: 0.3604: : 419iter [00:40, 11.50iter/s]
Best score: 0.3426: : 419iter [00:40, 11.50iter/s]
Best score: 0.3426: : 420iter [00:40, 11.50iter/s]
Best score: 0.3426: : 421iter [00:40, 11.31iter/s]
Best score: 0.3426: : 421iter [00:40, 11.31iter/s]
Best score: 0.3426: : 422iter [00:40, 11.31iter/s]
Best score: 0.3426: : 423iter [00:40, 11.47iter/s]
Best score: 0.3426: : 423iter [00:40, 11.47iter/s]
Best score: 0.3426: : 424iter [00:40, 11.47iter/s]
Best score: 0.3426: : 425iter [00:40, 11.58iter/s]
Best score: 0.3426: : 425iter [00:40, 11.58iter/s]
Best score: 0.3426: : 426iter [00:41, 11.58iter/s]
Best score: 0.3426: : 427iter [00:41, 11.65iter/s]
Best score: 0.3426: : 427iter [00:41, 11.65iter/s]
Best score: 0.3426: : 428iter [00:41, 11.65iter/s]
Best score: 0.3426: : 429iter [00:41, 11.70iter/s]
Best score: 0.3394: : 429iter [00:41, 11.70iter/s]
Best score: 0.3394: : 430iter [00:41, 11.70iter/s]
Best score: 0.3394: : 431iter [00:41, 11.53iter/s]
Best score: 0.3394: : 431iter [00:41, 11.53iter/s]
Best score: 0.3394: : 432iter [00:41, 11.53iter/s]
Best score: 0.3394: : 433iter [00:41, 11.63iter/s]
Best score: 0.3394: : 433iter [00:41, 11.63iter/s]
Best score: 0.3394: : 434iter [00:41, 11.63iter/s]
Best score: 0.3394: : 435iter [00:41, 11.67iter/s]
Best score: 0.3394: : 435iter [00:41, 11.67iter/s]
Best score: 0.3394: : 436iter [00:41, 11.67iter/s]
Best score: 0.3394: : 437iter [00:41, 11.66iter/s]
Best score: 0.3394: : 437iter [00:41, 11.66iter/s]
Best score: 0.3394: : 438iter [00:42, 11.66iter/s]
Best score: 0.3394: : 439iter [00:42, 11.71iter/s]
Best score: 0.3320: : 439iter [00:42, 11.71iter/s]
Best score: 0.3320: : 440iter [00:42, 11.71iter/s]
Best score: 0.3320: : 441iter [00:42, 11.53iter/s]
Best score: 0.3320: : 441iter [00:42, 11.53iter/s]
Best score: 0.3320: : 442iter [00:42, 11.53iter/s]
Best score: 0.3320: : 443iter [00:42, 11.63iter/s]
Best score: 0.3320: : 443iter [00:42, 11.63iter/s]
Best score: 0.3320: : 444iter [00:42, 11.63iter/s]
Best score: 0.3320: : 445iter [00:42, 11.67iter/s]
Best score: 0.3320: : 445iter [00:42, 11.67iter/s]
Best score: 0.3320: : 446iter [00:42, 11.67iter/s]
Best score: 0.3320: : 447iter [00:42, 11.72iter/s]
Best score: 0.3320: : 447iter [00:42, 11.72iter/s]
Best score: 0.3320: : 448iter [00:42, 11.72iter/s]
Best score: 0.3320: : 449iter [00:42, 11.71iter/s]
[ITER 450] Best: 0.3320
[PARAMS] Current best parameters:
  fx: 573.6896
  fy: 573.7737
  px: 1014.3665
  py: 764.0277
  k1: 0.00153288
  k2: -0.08877708
  k3: 0.06645566
  k4: -0.01629932
  p1: 0.00352748
  p2: -0.00058970
  p3: -0.00764716
  p4: -0.01722859
  s1: 0.0073
  s2: 0.0163
  s3: 0.0026
  s4: 0.0174
  tilt_x: -0.0660
  tilt_y: -0.0027
  scale: 2.9538
  rotation: -0.2923

Best score: 0.3320: : 449iter [00:43, 11.71iter/s]
Best score: 0.3320: : 450iter [00:43, 11.71iter/s]
Best score: 0.3320: : 451iter [00:43,  7.51iter/s]
Best score: 0.3320: : 451iter [00:43,  7.51iter/s]
Best score: 0.3320: : 452iter [00:43,  7.51iter/s]
Best score: 0.3320: : 453iter [00:43,  8.43iter/s]
Best score: 0.3320: : 453iter [00:43,  8.43iter/s]
Best score: 0.3320: : 454iter [00:43,  8.43iter/s]
Best score: 0.3320: : 455iter [00:43,  9.21iter/s]
Best score: 0.3320: : 455iter [00:43,  9.21iter/s]
Best score: 0.3320: : 456iter [00:43,  9.21iter/s]
Best score: 0.3320: : 457iter [00:43,  9.84iter/s]
Best score: 0.3320: : 457iter [00:43,  9.84iter/s]
Best score: 0.3320: : 458iter [00:44,  9.84iter/s]
Best score: 0.3320: : 459iter [00:44, 10.35iter/s]
Best score: 0.3320: : 459iter [00:44, 10.35iter/s]
Best score: 0.3320: : 460iter [00:44, 10.35iter/s]
Best score: 0.3320: : 461iter [00:44, 10.58iter/s]
Best score: 0.3320: : 461iter [00:44, 10.58iter/s]
Best score: 0.3320: : 462iter [00:44, 10.58iter/s]
Best score: 0.3320: : 463iter [00:44, 10.93iter/s]
Best score: 0.3320: : 463iter [00:44, 10.93iter/s]
Best score: 0.3320: : 464iter [00:44, 10.93iter/s]
Best score: 0.3320: : 465iter [00:44, 11.18iter/s]
Best score: 0.3320: : 465iter [00:44, 11.18iter/s]
Best score: 0.3320: : 466iter [00:44, 11.18iter/s]
Best score: 0.3320: : 467iter [00:44, 11.38iter/s]
Best score: 0.3320: : 467iter [00:44, 11.38iter/s]
Best score: 0.3320: : 468iter [00:44, 11.38iter/s]
Best score: 0.3320: : 469iter [00:44, 11.47iter/s]
Best score: 0.3194: : 469iter [00:45, 11.47iter/s]
Best score: 0.3194: : 470iter [00:45, 11.47iter/s]
Best score: 0.3194: : 471iter [00:45, 11.38iter/s]
Best score: 0.3194: : 471iter [00:45, 11.38iter/s]
Best score: 0.3194: : 472iter [00:45, 11.38iter/s]
Best score: 0.3194: : 473iter [00:45, 11.52iter/s]
Best score: 0.3194: : 473iter [00:45, 11.52iter/s]
Best score: 0.3194: : 474iter [00:45, 11.52iter/s]
Best score: 0.3194: : 475iter [00:45, 11.61iter/s]
Best score: 0.3194: : 475iter [00:45, 11.61iter/s]
Best score: 0.3194: : 476iter [00:45, 11.61iter/s]
Best score: 0.3194: : 477iter [00:45, 11.67iter/s]
Best score: 0.3194: : 477iter [00:45, 11.67iter/s]
Best score: 0.3194: : 478iter [00:45, 11.67iter/s]
Best score: 0.3194: : 479iter [00:45, 11.72iter/s]
Best score: 0.3194: : 479iter [00:45, 11.72iter/s]
Best score: 0.3194: : 480iter [00:45, 11.72iter/s]
Best score: 0.3194: : 481iter [00:45, 11.54iter/s]
Best score: 0.3194: : 481iter [00:46, 11.54iter/s]
Best score: 0.3194: : 482iter [00:46, 11.54iter/s]
Best score: 0.3194: : 483iter [00:46, 11.63iter/s]
Best score: 0.3194: : 483iter [00:46, 11.63iter/s]
Best score: 0.3194: : 484iter [00:46, 11.63iter/s]
Best score: 0.3194: : 485iter [00:46, 11.70iter/s]
Best score: 0.3194: : 485iter [00:46, 11.70iter/s]
Best score: 0.3194: : 486iter [00:46, 11.70iter/s]
Best score: 0.3194: : 487iter [00:46, 11.74iter/s]
Best score: 0.3194: : 487iter [00:46, 11.74iter/s]
Best score: 0.3194: : 488iter [00:46, 11.74iter/s]
Best score: 0.3194: : 489iter [00:46, 11.78iter/s]
Best score: 0.3174: : 489iter [00:46, 11.78iter/s]
Best score: 0.3174: : 490iter [00:46, 11.78iter/s]
Best score: 0.3174: : 491iter [00:46, 11.58iter/s]
Best score: 0.3174: : 491iter [00:46, 11.58iter/s]
Best score: 0.3174: : 492iter [00:46, 11.58iter/s]
Best score: 0.3174: : 493iter [00:46, 11.65iter/s]
Best score: 0.3174: : 493iter [00:47, 11.65iter/s]
Best score: 0.3174: : 494iter [00:47, 11.65iter/s]
Best score: 0.3174: : 495iter [00:47, 11.69iter/s]
Best score: 0.3174: : 495iter [00:47, 11.69iter/s]
Best score: 0.3174: : 496iter [00:47, 11.69iter/s]
Best score: 0.3174: : 497iter [00:47, 11.66iter/s]
Best score: 0.3174: : 497iter [00:47, 11.66iter/s]
Best score: 0.3174: : 498iter [00:47, 11.66iter/s]
Best score: 0.3174: : 499iter [00:47, 11.70iter/s]
[ITER 500] Best: 0.3142
[PARAMS] Current best parameters:
  fx: 573.4797
  fy: 573.6694
  px: 1015.0005
  py: 763.7518
  k1: 0.00444764
  k2: -0.09193114
  k3: 0.06761539
  k4: -0.01638394
  p1: 0.00350134
  p2: 0.00045590
  p3: -0.00557739
  p4: -0.01610453
  s1: 0.0049
  s2: 0.0148
  s3: 0.0006
  s4: 0.0161
  tilt_x: -0.0668
  tilt_y: -0.0046
  scale: 2.9505
  rotation: -0.2818

Best score: 0.3142: : 499iter [00:47, 11.70iter/s]
Best score: 0.3142: : 500iter [00:47, 11.70iter/s]
Best score: 0.3142: : 501iter [00:47,  7.51iter/s]
Best score: 0.3142: : 501iter [00:48,  7.51iter/s]
Best score: 0.3142: : 502iter [00:48,  7.51iter/s]
Best score: 0.3142: : 503iter [00:48,  8.44iter/s]
Best score: 0.3142: : 503iter [00:48,  8.44iter/s]
Best score: 0.3142: : 504iter [00:48,  8.44iter/s]
Best score: 0.3142: : 505iter [00:48,  9.24iter/s]
Best score: 0.3142: : 505iter [00:48,  9.24iter/s]
Best score: 0.3142: : 506iter [00:48,  9.24iter/s]
Best score: 0.3142: : 507iter [00:48,  9.89iter/s]
Best score: 0.3142: : 507iter [00:48,  9.89iter/s]
Best score: 0.3142: : 508iter [00:48,  9.89iter/s]
Best score: 0.3142: : 509iter [00:48, 10.41iter/s]
Best score: 0.3110: : 509iter [00:48, 10.41iter/s]
Best score: 0.3110: : 510iter [00:48, 10.41iter/s]
Best score: 0.3110: : 511iter [00:48, 10.64iter/s]
Best score: 0.3110: : 511iter [00:48, 10.64iter/s]
Best score: 0.3110: : 512iter [00:49, 10.64iter/s]
Best score: 0.3110: : 513iter [00:49, 10.94iter/s]
Best score: 0.3110: : 513iter [00:49, 10.94iter/s]
Best score: 0.3110: : 514iter [00:49, 10.94iter/s]
Best score: 0.3110: : 515iter [00:49, 11.20iter/s]
Best score: 0.3110: : 515iter [00:49, 11.20iter/s]
Best score: 0.3110: : 516iter [00:49, 11.20iter/s]
Best score: 0.3110: : 517iter [00:49, 11.33iter/s]
Best score: 0.3110: : 517iter [00:49, 11.33iter/s]
Best score: 0.3110: : 518iter [00:49, 11.33iter/s]
Best score: 0.3110: : 519iter [00:49, 11.48iter/s]
Best score: 0.3056: : 519iter [00:49, 11.48iter/s]
Best score: 0.3056: : 520iter [00:49, 11.48iter/s]
Best score: 0.3056: : 521iter [00:49, 11.40iter/s]
Best score: 0.3056: : 521iter [00:49, 11.40iter/s]
Best score: 0.3056: : 522iter [00:49, 11.40iter/s]
Best score: 0.3056: : 523iter [00:49, 11.48iter/s]
Best score: 0.3056: : 523iter [00:49, 11.48iter/s]
Best score: 0.3056: : 524iter [00:50, 11.48iter/s]
Best score: 0.3056: : 525iter [00:50, 11.53iter/s]
Best score: 0.3056: : 525iter [00:50, 11.53iter/s]
Best score: 0.3056: : 526iter [00:50, 11.53iter/s]
Best score: 0.3056: : 527iter [00:50, 11.62iter/s]
Best score: 0.3056: : 527iter [00:50, 11.62iter/s]
Best score: 0.3056: : 528iter [00:50, 11.62iter/s]
Best score: 0.3056: : 529iter [00:50, 11.68iter/s]
Best score: 0.3055: : 529iter [00:50, 11.68iter/s]
Best score: 0.3055: : 530iter [00:50, 11.68iter/s]
Best score: 0.3055: : 531iter [00:50, 11.51iter/s]
Best score: 0.3055: : 531iter [00:50, 11.51iter/s]
Best score: 0.3055: : 532iter [00:50, 11.51iter/s]
Best score: 0.3055: : 533iter [00:50, 11.59iter/s]
Best score: 0.3055: : 533iter [00:50, 11.59iter/s]
Best score: 0.3055: : 534iter [00:50, 11.59iter/s]
Best score: 0.3055: : 535iter [00:50, 11.65iter/s]
Best score: 0.3055: : 535iter [00:50, 11.65iter/s]
Best score: 0.3055: : 536iter [00:51, 11.65iter/s]
Best score: 0.3055: : 537iter [00:51, 11.68iter/s]
Best score: 0.3055: : 537iter [00:51, 11.68iter/s]
Best score: 0.3055: : 538iter [00:51, 11.68iter/s]
Best score: 0.3055: : 539iter [00:51, 11.70iter/s]
Best score: 0.3055: : 539iter [00:51, 11.70iter/s]
Best score: 0.3055: : 540iter [00:51, 11.70iter/s]
Best score: 0.3055: : 541iter [00:51, 11.52iter/s]
Best score: 0.3055: : 541iter [00:51, 11.52iter/s]
Best score: 0.3055: : 542iter [00:51, 11.52iter/s]
Best score: 0.3055: : 543iter [00:51, 11.61iter/s]
Best score: 0.3055: : 543iter [00:51, 11.61iter/s]
Best score: 0.3055: : 544iter [00:51, 11.61iter/s]
Best score: 0.3055: : 545iter [00:51, 11.68iter/s]
Best score: 0.3055: : 545iter [00:51, 11.68iter/s]
Best score: 0.3055: : 546iter [00:51, 11.68iter/s]
Best score: 0.3055: : 547iter [00:51, 11.72iter/s]
Best score: 0.3055: : 547iter [00:52, 11.72iter/s]
Best score: 0.3055: : 548iter [00:52, 11.72iter/s]
Best score: 0.3055: : 549iter [00:52, 11.77iter/s]
[ITER 550] Best: 0.3028
[PARAMS] Current best parameters:
  fx: 573.1194
  fy: 573.0548
  px: 1014.2053
  py: 763.8110
  k1: 0.00163918
  k2: -0.08753178
  k3: 0.06562623
  k4: -0.01609653
  p1: 0.00306976
  p2: 0.00229450
  p3: -0.00350278
  p4: -0.01419316
  s1: 0.0002
  s2: 0.0129
  s3: -0.0017
  s4: 0.0143
  tilt_x: -0.0653
  tilt_y: 0.0030
  scale: 2.9532
  rotation: -0.3072

Best score: 0.3028: : 549iter [00:52, 11.77iter/s]
Best score: 0.3028: : 550iter [00:52, 11.77iter/s]
Best score: 0.3028: : 551iter [00:52,  7.53iter/s]
Best score: 0.3028: : 551iter [00:52,  7.53iter/s]
Best score: 0.3028: : 552iter [00:52,  7.53iter/s]
Best score: 0.3028: : 553iter [00:52,  8.43iter/s]
Best score: 0.3028: : 553iter [00:52,  8.43iter/s]
Best score: 0.3028: : 554iter [00:52,  8.43iter/s]
Best score: 0.3028: : 555iter [00:52,  9.22iter/s]
Best score: 0.3028: : 555iter [00:53,  9.22iter/s]
Best score: 0.3028: : 556iter [00:53,  9.22iter/s]
Best score: 0.3028: : 557iter [00:53,  9.88iter/s]
Best score: 0.3028: : 557iter [00:53,  9.88iter/s]
Best score: 0.3028: : 558iter [00:53,  9.88iter/s]
Best score: 0.3028: : 559iter [00:53, 10.40iter/s]
Best score: 0.3027: : 559iter [00:53, 10.40iter/s]
Best score: 0.3027: : 560iter [00:53, 10.40iter/s]
Best score: 0.3027: : 561iter [00:53, 10.62iter/s]
Best score: 0.3027: : 561iter [00:53, 10.62iter/s]
Best score: 0.3027: : 562iter [00:53, 10.62iter/s]
Best score: 0.3027: : 563iter [00:53, 10.96iter/s]
Best score: 0.3027: : 563iter [00:53, 10.96iter/s]
Best score: 0.3027: : 564iter [00:53, 10.96iter/s]
Best score: 0.3027: : 565iter [00:53, 11.20iter/s]
Best score: 0.3027: : 565iter [00:53, 11.20iter/s]
Best score: 0.3027: : 566iter [00:53, 11.20iter/s]
Best score: 0.3027: : 567iter [00:53, 11.40iter/s]
Best score: 0.3027: : 567iter [00:54, 11.40iter/s]
Best score: 0.3027: : 568iter [00:54, 11.40iter/s]
Best score: 0.3027: : 569iter [00:54, 11.49iter/s]
Best score: 0.3017: : 569iter [00:54, 11.49iter/s]
Best score: 0.3017: : 570iter [00:54, 11.49iter/s]
Best score: 0.3017: : 571iter [00:54, 11.39iter/s]
Best score: 0.3017: : 571iter [00:54, 11.39iter/s]
Best score: 0.3017: : 572iter [00:54, 11.39iter/s]
Best score: 0.3017: : 573iter [00:54, 11.51iter/s]
Best score: 0.3017: : 573iter [00:54, 11.51iter/s]
Best score: 0.3017: : 574iter [00:54, 11.51iter/s]
Best score: 0.3017: : 575iter [00:54, 11.60iter/s]
Best score: 0.3017: : 575iter [00:54, 11.60iter/s]
Best score: 0.3017: : 576iter [00:54, 11.60iter/s]
Best score: 0.3017: : 577iter [00:54, 11.68iter/s]
Best score: 0.3017: : 577iter [00:54, 11.68iter/s]
Best score: 0.3017: : 578iter [00:54, 11.68iter/s]
Best score: 0.3017: : 579iter [00:54, 11.72iter/s]
Best score: 0.3017: : 579iter [00:55, 11.72iter/s]
Best score: 0.3017: : 580iter [00:55, 11.72iter/s]
Best score: 0.3017: : 581iter [00:55, 11.55iter/s]
Best score: 0.3017: : 581iter [00:55, 11.55iter/s]
Best score: 0.3017: : 582iter [00:55, 11.55iter/s]
Best score: 0.3017: : 583iter [00:55, 11.61iter/s]
Best score: 0.3017: : 583iter [00:55, 11.61iter/s]
Best score: 0.3017: : 584iter [00:55, 11.61iter/s]
Best score: 0.3017: : 585iter [00:55, 11.62iter/s]
Best score: 0.3017: : 585iter [00:55, 11.62iter/s]
Best score: 0.3017: : 586iter [00:55, 11.62iter/s]
Best score: 0.3017: : 587iter [00:55, 11.64iter/s]
Best score: 0.3017: : 587iter [00:55, 11.64iter/s]
Best score: 0.3017: : 588iter [00:55, 11.64iter/s]
Best score: 0.3017: : 589iter [00:55, 11.63iter/s]
Best score: 0.3011: : 589iter [00:55, 11.63iter/s]
Best score: 0.3011: : 590iter [00:56, 11.63iter/s]
Best score: 0.3011: : 591iter [00:56, 11.48iter/s]
Best score: 0.3011: : 591iter [00:56, 11.48iter/s]
Best score: 0.3011: : 592iter [00:56, 11.48iter/s]
Best score: 0.3011: : 593iter [00:56, 11.58iter/s]
Best score: 0.3011: : 593iter [00:56, 11.58iter/s]
Best score: 0.3011: : 594iter [00:56, 11.58iter/s]
Best score: 0.3011: : 595iter [00:56, 11.65iter/s]
Best score: 0.3011: : 595iter [00:56, 11.65iter/s]
Best score: 0.3011: : 596iter [00:56, 11.65iter/s]
Best score: 0.3011: : 597iter [00:56, 11.70iter/s]
Best score: 0.3011: : 597iter [00:56, 11.70iter/s]
Best score: 0.3011: : 598iter [00:56, 11.70iter/s]
Best score: 0.3011: : 599iter [00:56, 11.71iter/s]
[ITER 600] Best: 0.2999
[PARAMS] Current best parameters:
  fx: 573.8025
  fy: 573.6927
  px: 1014.9725
  py: 763.9273
  k1: -0.00329021
  k2: -0.08223129
  k3: 0.06337199
  k4: -0.01574252
  p1: 0.00236184
  p2: 0.00260973
  p3: -0.00494917
  p4: -0.01278356
  s1: 0.0015
  s2: 0.0122
  s3: 0.0011
  s4: 0.0132
  tilt_x: -0.0635
  tilt_y: -0.0004
  scale: 2.9589
  rotation: -0.3000

Best score: 0.2999: : 599iter [00:56, 11.71iter/s]
Best score: 0.2999: : 600iter [00:57, 11.71iter/s]
Best score: 0.2999: : 601iter [00:57,  7.51iter/s]
Best score: 0.2999: : 601iter [00:57,  7.51iter/s]
Best score: 0.2999: : 602iter [00:57,  7.51iter/s]
Best score: 0.2999: : 603iter [00:57,  8.41iter/s]
Best score: 0.2999: : 603iter [00:57,  8.41iter/s]
Best score: 0.2999: : 604iter [00:57,  8.41iter/s]
Best score: 0.2999: : 605iter [00:57,  9.21iter/s]
Best score: 0.2999: : 605iter [00:57,  9.21iter/s]
Best score: 0.2999: : 606iter [00:57,  9.21iter/s]
Best score: 0.2999: : 607iter [00:57,  9.84iter/s]
Best score: 0.2999: : 607iter [00:57,  9.84iter/s]
Best score: 0.2999: : 608iter [00:57,  9.84iter/s]
Best score: 0.2999: : 609iter [00:57, 10.36iter/s]
Best score: 0.2960: : 609iter [00:57, 10.36iter/s]
Best score: 0.2960: : 610iter [00:58, 10.36iter/s]
Best score: 0.2960: : 611iter [00:58, 10.56iter/s]
Best score: 0.2960: : 611iter [00:58, 10.56iter/s]
Best score: 0.2960: : 612iter [00:58, 10.56iter/s]
Best score: 0.2960: : 613iter [00:58, 10.93iter/s]
Best score: 0.2960: : 613iter [00:58, 10.93iter/s]
Best score: 0.2960: : 614iter [00:58, 10.93iter/s]
Best score: 0.2960: : 615iter [00:58, 11.19iter/s]
Best score: 0.2960: : 615iter [00:58, 11.19iter/s]
Best score: 0.2960: : 616iter [00:58, 11.19iter/s]
Best score: 0.2960: : 617iter [00:58, 11.38iter/s]
Best score: 0.2960: : 617iter [00:58, 11.38iter/s]
Best score: 0.2960: : 618iter [00:58, 11.38iter/s]
Best score: 0.2960: : 619iter [00:58, 11.52iter/s]
Best score: 0.2913: : 619iter [00:58, 11.52iter/s]
Best score: 0.2913: : 620iter [00:58, 11.52iter/s]
Best score: 0.2913: : 621iter [00:58, 11.41iter/s]
Best score: 0.2913: : 621iter [00:58, 11.41iter/s]
Best score: 0.2913: : 622iter [00:59, 11.41iter/s]
Best score: 0.2913: : 623iter [00:59, 11.52iter/s]
Best score: 0.2913: : 623iter [00:59, 11.52iter/s]
Best score: 0.2913: : 624iter [00:59, 11.52iter/s]
Best score: 0.2913: : 625iter [00:59, 11.61iter/s]
Best score: 0.2913: : 625iter [00:59, 11.61iter/s]
Best score: 0.2913: : 626iter [00:59, 11.61iter/s]
Best score: 0.2913: : 627iter [00:59, 11.64iter/s]
Best score: 0.2913: : 627iter [00:59, 11.64iter/s]
Best score: 0.2913: : 628iter [00:59, 11.64iter/s]
Best score: 0.2913: : 629iter [00:59, 11.71iter/s]
Best score: 0.2884: : 629iter [00:59, 11.71iter/s]
Best score: 0.2884: : 630iter [00:59, 11.71iter/s]
Best score: 0.2884: : 631iter [00:59, 11.55iter/s]
Best score: 0.2884: : 631iter [00:59, 11.55iter/s]
Best score: 0.2884: : 632iter [00:59, 11.55iter/s]
Best score: 0.2884: : 633iter [00:59, 11.61iter/s]
Best score: 0.2884: : 633iter [01:00, 11.61iter/s]
Best score: 0.2884: : 634iter [01:00, 11.61iter/s]
Best score: 0.2884: : 635iter [01:00, 11.68iter/s]
Best score: 0.2884: : 635iter [01:00, 11.68iter/s]
Best score: 0.2884: : 636iter [01:00, 11.68iter/s]
Best score: 0.2884: : 637iter [01:00, 11.72iter/s]
Best score: 0.2884: : 637iter [01:00, 11.72iter/s]
Best score: 0.2884: : 638iter [01:00, 11.72iter/s]
Best score: 0.2884: : 639iter [01:00, 11.75iter/s]
Best score: 0.2884: : 639iter [01:00, 11.75iter/s]
Best score: 0.2884: : 640iter [01:00, 11.75iter/s]
Best score: 0.2884: : 641iter [01:00, 11.52iter/s]
Best score: 0.2884: : 641iter [01:00, 11.52iter/s]
Best score: 0.2884: : 642iter [01:00, 11.52iter/s]
Best score: 0.2884: : 643iter [01:00, 11.61iter/s]
Best score: 0.2884: : 643iter [01:00, 11.61iter/s]
Best score: 0.2884: : 644iter [01:00, 11.61iter/s]
Best score: 0.2884: : 645iter [01:00, 11.68iter/s]
Best score: 0.2884: : 645iter [01:01, 11.68iter/s]
Best score: 0.2884: : 646iter [01:01, 11.68iter/s]
Best score: 0.2884: : 647iter [01:01, 11.72iter/s]
Best score: 0.2884: : 647iter [01:01, 11.72iter/s]
Best score: 0.2884: : 648iter [01:01, 11.72iter/s]
Best score: 0.2884: : 649iter [01:01, 11.77iter/s]
[ITER 650] Best: 0.2879
[PARAMS] Current best parameters:
  fx: 568.6069
  fy: 568.4679
  px: 1016.5671
  py: 763.4303
  k1: -0.00193104
  k2: -0.07248311
  k3: 0.05502516
  k4: -0.01362959
  p1: -0.00183629
  p2: -0.00059124
  p3: -0.00103127
  p4: -0.00848749
  s1: 0.0028
  s2: 0.0078
  s3: -0.0000
  s4: 0.0095
  tilt_x: -0.0572
  tilt_y: -0.0146
  scale: 2.9592
  rotation: -0.2846

Best score: 0.2879: : 649iter [01:01, 11.77iter/s]
Best score: 0.2879: : 650iter [01:01, 11.77iter/s]
Best score: 0.2879: : 651iter [01:01,  7.54iter/s]
Best score: 0.2879: : 651iter [01:01,  7.54iter/s]
Best score: 0.2879: : 652iter [01:01,  7.54iter/s]
Best score: 0.2879: : 653iter [01:01,  8.45iter/s]
Best score: 0.2879: : 653iter [01:02,  8.45iter/s]
Best score: 0.2879: : 654iter [01:02,  8.45iter/s]
Best score: 0.2879: : 655iter [01:02,  9.25iter/s]
Best score: 0.2879: : 655iter [01:02,  9.25iter/s]
Best score: 0.2879: : 656iter [01:02,  9.25iter/s]
Best score: 0.2879: : 657iter [01:02,  9.85iter/s]
Best score: 0.2879: : 657iter [01:02,  9.85iter/s]
Best score: 0.2879: : 658iter [01:02,  9.85iter/s]
Best score: 0.2879: : 659iter [01:02, 10.35iter/s]
Best score: 0.2793: : 659iter [01:02, 10.35iter/s]
Best score: 0.2793: : 660iter [01:02, 10.35iter/s]
Best score: 0.2793: : 661iter [01:02, 10.57iter/s]
Best score: 0.2793: : 661iter [01:02, 10.57iter/s]
Best score: 0.2793: : 662iter [01:02, 10.57iter/s]
Best score: 0.2793: : 663iter [01:02, 10.90iter/s]
Best score: 0.2793: : 663iter [01:02, 10.90iter/s]
Best score: 0.2793: : 664iter [01:02, 10.90iter/s]
Best score: 0.2793: : 665iter [01:02, 11.17iter/s]
Best score: 0.2793: : 665iter [01:03, 11.17iter/s]
Best score: 0.2793: : 666iter [01:03, 11.17iter/s]
Best score: 0.2793: : 667iter [01:03, 11.37iter/s]
Best score: 0.2793: : 667iter [01:03, 11.37iter/s]
Best score: 0.2793: : 668iter [01:03, 11.37iter/s]
Best score: 0.2793: : 669iter [01:03, 11.50iter/s]
Best score: 0.2744: : 669iter [01:03, 11.50iter/s]
Best score: 0.2744: : 670iter [01:03, 11.50iter/s]
Best score: 0.2744: : 671iter [01:03, 11.38iter/s]
Best score: 0.2744: : 671iter [01:03, 11.38iter/s]
Best score: 0.2744: : 672iter [01:03, 11.38iter/s]
Best score: 0.2744: : 673iter [01:03, 11.51iter/s]
Best score: 0.2744: : 673iter [01:03, 11.51iter/s]
Best score: 0.2744: : 674iter [01:03, 11.51iter/s]
Best score: 0.2744: : 675iter [01:03, 11.61iter/s]
Best score: 0.2744: : 675iter [01:03, 11.61iter/s]
Best score: 0.2744: : 676iter [01:04, 11.61iter/s]
Best score: 0.2744: : 677iter [01:04, 11.69iter/s]
Best score: 0.2744: : 677iter [01:04, 11.69iter/s]
Best score: 0.2744: : 678iter [01:04, 11.69iter/s]
Best score: 0.2744: : 679iter [01:04, 11.73iter/s]
Best score: 0.2744: : 679iter [01:04, 11.73iter/s]
Best score: 0.2744: : 680iter [01:04, 11.73iter/s]
Best score: 0.2744: : 681iter [01:04, 11.56iter/s]
Best score: 0.2744: : 681iter [01:04, 11.56iter/s]
Best score: 0.2744: : 682iter [01:04, 11.56iter/s]
Best score: 0.2744: : 683iter [01:04, 11.63iter/s]
Best score: 0.2744: : 683iter [01:04, 11.63iter/s]
Best score: 0.2744: : 684iter [01:04, 11.63iter/s]
Best score: 0.2744: : 685iter [01:04, 11.70iter/s]
Best score: 0.2744: : 685iter [01:04, 11.70iter/s]
Best score: 0.2744: : 686iter [01:04, 11.70iter/s]
Best score: 0.2744: : 687iter [01:04, 11.75iter/s]
Best score: 0.2744: : 687iter [01:04, 11.75iter/s]
Best score: 0.2744: : 688iter [01:05, 11.75iter/s]
Best score: 0.2744: : 689iter [01:05, 11.78iter/s]
Best score: 0.2741: : 689iter [01:05, 11.78iter/s]
Best score: 0.2741: : 690iter [01:05, 11.78iter/s]
Best score: 0.2741: : 691iter [01:05, 11.59iter/s]
Best score: 0.2741: : 691iter [01:05, 11.59iter/s]
Best score: 0.2741: : 692iter [01:05, 11.59iter/s]
Best score: 0.2741: : 693iter [01:05, 11.62iter/s]
Best score: 0.2741: : 693iter [01:05, 11.62iter/s]
Best score: 0.2741: : 694iter [01:05, 11.62iter/s]
Best score: 0.2741: : 695iter [01:05, 11.69iter/s]
Best score: 0.2741: : 695iter [01:05, 11.69iter/s]
Best score: 0.2741: : 696iter [01:05, 11.69iter/s]
Best score: 0.2741: : 697iter [01:05, 11.75iter/s]
Best score: 0.2741: : 697iter [01:05, 11.75iter/s]
Best score: 0.2741: : 698iter [01:05, 11.75iter/s]
Best score: 0.2741: : 699iter [01:05, 11.78iter/s]
[ITER 700] Best: 0.2712
[PARAMS] Current best parameters:
  fx: 560.7585
  fy: 560.3206
  px: 1017.3476
  py: 762.7934
  k1: -0.00257030
  k2: -0.05267856
  k3: 0.03841295
  k4: -0.00923581
  p1: -0.00703619
  p2: -0.00458978
  p3: -0.00193804
  p4: 0.01062417
  s1: 0.0093
  s2: -0.0121
  s3: 0.0043
  s4: -0.0091
  tilt_x: -0.0482
  tilt_y: -0.0263
  scale: 2.9661
  rotation: -0.2828

Best score: 0.2712: : 699iter [01:05, 11.78iter/s]
Best score: 0.2712: : 700iter [01:06, 11.78iter/s]
Best score: 0.2712: : 701iter [01:06,  7.55iter/s]
Best score: 0.2712: : 701iter [01:06,  7.55iter/s]
Best score: 0.2712: : 702iter [01:06,  7.55iter/s]
Best score: 0.2712: : 703iter [01:06,  8.48iter/s]
Best score: 0.2712: : 703iter [01:06,  8.48iter/s]
Best score: 0.2712: : 704iter [01:06,  8.48iter/s]
Best score: 0.2712: : 705iter [01:06,  9.27iter/s]
Best score: 0.2712: : 705iter [01:06,  9.27iter/s]
Best score: 0.2712: : 706iter [01:06,  9.27iter/s]
Best score: 0.2712: : 707iter [01:06,  9.92iter/s]
Best score: 0.2712: : 707iter [01:06,  9.92iter/s]
Best score: 0.2712: : 708iter [01:07,  9.92iter/s]
Best score: 0.2712: : 709iter [01:07, 10.42iter/s]
Best score: 0.2701: : 709iter [01:07, 10.42iter/s]
Best score: 0.2701: : 710iter [01:07, 10.42iter/s]
Best score: 0.2701: : 711iter [01:07, 10.62iter/s]
Best score: 0.2701: : 711iter [01:07, 10.62iter/s]
Best score: 0.2701: : 712iter [01:07, 10.62iter/s]
Best score: 0.2701: : 713iter [01:07, 10.91iter/s]
Best score: 0.2701: : 713iter [01:07, 10.91iter/s]
Best score: 0.2701: : 714iter [01:07, 10.91iter/s]
Best score: 0.2701: : 715iter [01:07, 11.13iter/s]
Best score: 0.2701: : 715iter [01:07, 11.13iter/s]
Best score: 0.2701: : 716iter [01:07, 11.13iter/s]
Best score: 0.2701: : 717iter [01:07, 11.33iter/s]
Best score: 0.2701: : 717iter [01:07, 11.33iter/s]
Best score: 0.2701: : 718iter [01:07, 11.33iter/s]
Best score: 0.2701: : 719iter [01:07, 11.48iter/s]
Best score: 0.2668: : 719iter [01:08, 11.48iter/s]
Best score: 0.2668: : 720iter [01:08, 11.48iter/s]
Best score: 0.2668: : 721iter [01:08, 11.38iter/s]
Best score: 0.2668: : 721iter [01:08, 11.38iter/s]
Best score: 0.2668: : 722iter [01:08, 11.38iter/s]
Best score: 0.2668: : 723iter [01:08, 11.51iter/s]
Best score: 0.2668: : 723iter [01:08, 11.51iter/s]
Best score: 0.2668: : 724iter [01:08, 11.51iter/s]
Best score: 0.2668: : 725iter [01:08, 11.61iter/s]
Best score: 0.2668: : 725iter [01:08, 11.61iter/s]
Best score: 0.2668: : 726iter [01:08, 11.61iter/s]
Best score: 0.2668: : 727iter [01:08, 11.70iter/s]
Best score: 0.2668: : 727iter [01:08, 11.70iter/s]
Best score: 0.2668: : 728iter [01:08, 11.70iter/s]
Best score: 0.2668: : 729iter [01:08, 11.75iter/s]
Best score: 0.2664: : 729iter [01:08, 11.75iter/s]
Best score: 0.2664: : 730iter [01:08, 11.75iter/s]
Best score: 0.2664: : 731iter [01:08, 11.58iter/s]
Best score: 0.2664: : 731iter [01:09, 11.58iter/s]
Best score: 0.2664: : 732iter [01:09, 11.58iter/s]
Best score: 0.2664: : 733iter [01:09, 11.61iter/s]
Best score: 0.2664: : 733iter [01:09, 11.61iter/s]
Best score: 0.2664: : 734iter [01:09, 11.61iter/s]
Best score: 0.2664: : 735iter [01:09, 11.67iter/s]
Best score: 0.2664: : 735iter [01:09, 11.67iter/s]
Best score: 0.2664: : 736iter [01:09, 11.67iter/s]
Best score: 0.2664: : 737iter [01:09, 11.67iter/s]
Best score: 0.2664: : 737iter [01:09, 11.67iter/s]
Best score: 0.2664: : 738iter [01:09, 11.67iter/s]
Best score: 0.2664: : 739iter [01:09, 11.68iter/s]
Best score: 0.2654: : 739iter [01:09, 11.68iter/s]
Best score: 0.2654: : 740iter [01:09, 11.68iter/s]
Best score: 0.2654: : 741iter [01:09, 11.53iter/s]
Best score: 0.2654: : 741iter [01:09, 11.53iter/s]
Best score: 0.2654: : 742iter [01:09, 11.53iter/s]
Best score: 0.2654: : 743iter [01:09, 11.63iter/s]
Best score: 0.2654: : 743iter [01:10, 11.63iter/s]
Best score: 0.2654: : 744iter [01:10, 11.63iter/s]
Best score: 0.2654: : 745iter [01:10, 11.62iter/s]
Best score: 0.2654: : 745iter [01:10, 11.62iter/s]
Best score: 0.2654: : 746iter [01:10, 11.62iter/s]
Best score: 0.2654: : 747iter [01:10, 11.67iter/s]
Best score: 0.2654: : 747iter [01:10, 11.67iter/s]
Best score: 0.2654: : 748iter [01:10, 11.67iter/s]
Best score: 0.2654: : 749iter [01:10, 11.64iter/s]
[ITER 750] Best: 0.2654
[PARAMS] Current best parameters:
  fx: 557.0439
  fy: 556.5188
  px: 1016.7795
  py: 762.2792
  k1: -0.00743410
  k2: -0.03642381
  k3: 0.02725874
  k4: -0.00672061
  p1: -0.01145596
  p2: -0.00808818
  p3: -0.00452592
  p4: 0.02408518
  s1: 0.0139
  s2: -0.0247
  s3: 0.0108
  s4: -0.0224
  tilt_x: -0.0418
  tilt_y: -0.0307
  scale: 2.9723
  rotation: -0.2834

Best score: 0.2654: : 749iter [01:10, 11.64iter/s]
Best score: 0.2654: : 750iter [01:10, 11.64iter/s]
Best score: 0.2654: : 751iter [01:10,  7.48iter/s]
Best score: 0.2654: : 751iter [01:11,  7.48iter/s]
Best score: 0.2654: : 752iter [01:11,  7.48iter/s]
Best score: 0.2654: : 753iter [01:11,  8.38iter/s]
Best score: 0.2654: : 753iter [01:11,  8.38iter/s]
Best score: 0.2654: : 754iter [01:11,  8.38iter/s]
Best score: 0.2654: : 755iter [01:11,  9.17iter/s]
Best score: 0.2654: : 755iter [01:11,  9.17iter/s]
Best score: 0.2654: : 756iter [01:11,  9.17iter/s]
Best score: 0.2654: : 757iter [01:11,  9.83iter/s]
Best score: 0.2654: : 757iter [01:11,  9.83iter/s]
Best score: 0.2654: : 758iter [01:11,  9.83iter/s]
Best score: 0.2654: : 759iter [01:11, 10.34iter/s]
Best score: 0.2625: : 759iter [01:11, 10.34iter/s]
Best score: 0.2625: : 760iter [01:11, 10.34iter/s]
Best score: 0.2625: : 761iter [01:11, 10.59iter/s]
Best score: 0.2625: : 761iter [01:11, 10.59iter/s]
Best score: 0.2625: : 762iter [01:12, 10.59iter/s]
Best score: 0.2625: : 763iter [01:12, 10.92iter/s]
Best score: 0.2625: : 763iter [01:12, 10.92iter/s]
Best score: 0.2625: : 764iter [01:12, 10.92iter/s]
Best score: 0.2625: : 765iter [01:12, 11.19iter/s]
Best score: 0.2625: : 765iter [01:12, 11.19iter/s]
Best score: 0.2625: : 766iter [01:12, 11.19iter/s]
Best score: 0.2625: : 767iter [01:12, 11.39iter/s]
Best score: 0.2625: : 767iter [01:12, 11.39iter/s]
Best score: 0.2625: : 768iter [01:12, 11.39iter/s]
Best score: 0.2625: : 769iter [01:12, 11.49iter/s]
Best score: 0.2618: : 769iter [01:12, 11.49iter/s]
Best score: 0.2618: : 770iter [01:12, 11.49iter/s]
Best score: 0.2618: : 771iter [01:12, 11.37iter/s]
Best score: 0.2618: : 771iter [01:12, 11.37iter/s]
Best score: 0.2618: : 772iter [01:12, 11.37iter/s]
Best score: 0.2618: : 773iter [01:12, 11.50iter/s]
Best score: 0.2618: : 773iter [01:12, 11.50iter/s]
Best score: 0.2618: : 774iter [01:13, 11.50iter/s]
Best score: 0.2618: : 775iter [01:13, 11.56iter/s]
Best score: 0.2618: : 775iter [01:13, 11.56iter/s]
Best score: 0.2618: : 776iter [01:13, 11.56iter/s]
Best score: 0.2618: : 777iter [01:13, 11.63iter/s]
Best score: 0.2618: : 777iter [01:13, 11.63iter/s]
Best score: 0.2618: : 778iter [01:13, 11.63iter/s]
Best score: 0.2618: : 779iter [01:13, 11.68iter/s]
Best score: 0.2618: : 779iter [01:13, 11.68iter/s]
Best score: 0.2618: : 780iter [01:13, 11.68iter/s]
Best score: 0.2618: : 781iter [01:13, 11.53iter/s]
Best score: 0.2618: : 781iter [01:13, 11.53iter/s]
Best score: 0.2618: : 782iter [01:13, 11.53iter/s]
Best score: 0.2618: : 783iter [01:13, 11.62iter/s]
Best score: 0.2618: : 783iter [01:13, 11.62iter/s]
Best score: 0.2618: : 784iter [01:13, 11.62iter/s]
Best score: 0.2618: : 785iter [01:13, 11.70iter/s]
Best score: 0.2618: : 785iter [01:13, 11.70iter/s]
Best score: 0.2618: : 786iter [01:14, 11.70iter/s]
Best score: 0.2618: : 787iter [01:14, 11.76iter/s]
Best score: 0.2618: : 787iter [01:14, 11.76iter/s]
Best score: 0.2618: : 788iter [01:14, 11.76iter/s]
Best score: 0.2618: : 789iter [01:14, 11.81iter/s]
Best score: 0.2602: : 789iter [01:14, 11.81iter/s]
Best score: 0.2602: : 790iter [01:14, 11.81iter/s]
Best score: 0.2602: : 791iter [01:14, 11.56iter/s]
Best score: 0.2602: : 791iter [01:14, 11.56iter/s]
Best score: 0.2602: : 792iter [01:14, 11.56iter/s]
Best score: 0.2602: : 793iter [01:14, 11.65iter/s]
Best score: 0.2602: : 793iter [01:14, 11.65iter/s]
Best score: 0.2602: : 794iter [01:14, 11.65iter/s]
Best score: 0.2602: : 795iter [01:14, 11.73iter/s]
Best score: 0.2602: : 795iter [01:14, 11.73iter/s]
Best score: 0.2602: : 796iter [01:14, 11.73iter/s]
Best score: 0.2602: : 797iter [01:14, 11.77iter/s]
Best score: 0.2602: : 797iter [01:14, 11.77iter/s]
Best score: 0.2602: : 798iter [01:15, 11.77iter/s]
Best score: 0.2602: : 799iter [01:15, 11.81iter/s]
[ITER 800] Best: 0.2598
[PARAMS] Current best parameters:
  fx: 556.2290
  fy: 555.7238
  px: 1017.8848
  py: 761.4181
  k1: -0.00930443
  k2: -0.03078287
  k3: 0.02296759
  k4: -0.00564374
  p1: -0.01157723
  p2: -0.00656312
  p3: -0.00073808
  p4: 0.01689467
  s1: 0.0102
  s2: -0.0182
  s3: 0.0073
  s4: -0.0165
  tilt_x: -0.0457
  tilt_y: -0.0331
  scale: 2.9747
  rotation: -0.2791

Best score: 0.2598: : 799iter [01:15, 11.81iter/s]
Best score: 0.2598: : 800iter [01:15, 11.81iter/s]
Best score: 0.2598: : 801iter [01:15,  7.55iter/s]
Best score: 0.2598: : 801iter [01:15,  7.55iter/s]
Best score: 0.2598: : 802iter [01:15,  7.55iter/s]
Best score: 0.2598: : 803iter [01:15,  8.48iter/s]
Best score: 0.2598: : 803iter [01:15,  8.48iter/s]
Best score: 0.2598: : 804iter [01:15,  8.48iter/s]
Best score: 0.2598: : 805iter [01:15,  9.24iter/s]
Best score: 0.2598: : 805iter [01:15,  9.24iter/s]
Best score: 0.2598: : 806iter [01:16,  9.24iter/s]
Best score: 0.2598: : 807iter [01:16,  9.87iter/s]
Best score: 0.2598: : 807iter [01:16,  9.87iter/s]
Best score: 0.2598: : 808iter [01:16,  9.87iter/s]
Best score: 0.2598: : 809iter [01:16, 10.37iter/s]
Best score: 0.2586: : 809iter [01:16, 10.37iter/s]
Best score: 0.2586: : 810iter [01:16, 10.37iter/s]
Best score: 0.2586: : 811iter [01:16, 10.62iter/s]
Best score: 0.2586: : 811iter [01:16, 10.62iter/s]
Best score: 0.2586: : 812iter [01:16, 10.62iter/s]
Best score: 0.2586: : 813iter [01:16, 10.97iter/s]
Best score: 0.2586: : 813iter [01:16, 10.97iter/s]
Best score: 0.2586: : 814iter [01:16, 10.97iter/s]
Best score: 0.2586: : 815iter [01:16, 11.21iter/s]
Best score: 0.2586: : 815iter [01:16, 11.21iter/s]
Best score: 0.2586: : 816iter [01:16, 11.21iter/s]
Best score: 0.2586: : 817iter [01:16, 11.41iter/s]
Best score: 0.2586: : 817iter [01:17, 11.41iter/s]
Best score: 0.2586: : 818iter [01:17, 11.41iter/s]
Best score: 0.2586: : 819iter [01:17, 11.55iter/s]
Best score: 0.2586: : 819iter [01:17, 11.55iter/s]
Best score: 0.2586: : 820iter [01:17, 11.55iter/s]
Best score: 0.2586: : 821iter [01:17, 11.44iter/s]
Best score: 0.2586: : 821iter [01:17, 11.44iter/s]
Best score: 0.2586: : 822iter [01:17, 11.44iter/s]
Best score: 0.2586: : 823iter [01:17, 11.57iter/s]
Best score: 0.2586: : 823iter [01:17, 11.57iter/s]
Best score: 0.2586: : 824iter [01:17, 11.57iter/s]
Best score: 0.2586: : 825iter [01:17, 11.61iter/s]
Best score: 0.2586: : 825iter [01:17, 11.61iter/s]
Best score: 0.2586: : 826iter [01:17, 11.61iter/s]
Best score: 0.2586: : 827iter [01:17, 11.68iter/s]
Best score: 0.2586: : 827iter [01:17, 11.68iter/s]
Best score: 0.2586: : 828iter [01:17, 11.68iter/s]
Best score: 0.2586: : 829iter [01:17, 11.75iter/s]
Best score: 0.2586: : 829iter [01:18, 11.75iter/s]
Best score: 0.2586: : 830iter [01:18, 11.75iter/s]
Best score: 0.2586: : 831iter [01:18, 11.60iter/s]
Best score: 0.2586: : 831iter [01:18, 11.60iter/s]
Best score: 0.2586: : 832iter [01:18, 11.60iter/s]
Best score: 0.2586: : 833iter [01:18, 11.68iter/s]
Best score: 0.2586: : 833iter [01:18, 11.68iter/s]
Best score: 0.2586: : 834iter [01:18, 11.68iter/s]
Best score: 0.2586: : 835iter [01:18, 11.73iter/s]
Best score: 0.2586: : 835iter [01:18, 11.73iter/s]
Best score: 0.2586: : 836iter [01:18, 11.73iter/s]
Best score: 0.2586: : 837iter [01:18, 11.78iter/s]
Best score: 0.2586: : 837iter [01:18, 11.78iter/s]
Best score: 0.2586: : 838iter [01:18, 11.78iter/s]
Best score: 0.2586: : 839iter [01:18, 11.81iter/s]
Best score: 0.2578: : 839iter [01:18, 11.81iter/s]
Best score: 0.2578: : 840iter [01:18, 11.81iter/s]
Best score: 0.2578: : 841iter [01:18, 11.61iter/s]
Best score: 0.2578: : 841iter [01:19, 11.61iter/s]
Best score: 0.2578: : 842iter [01:19, 11.61iter/s]
Best score: 0.2578: : 843iter [01:19, 11.69iter/s]
Best score: 0.2578: : 843iter [01:19, 11.69iter/s]
Best score: 0.2578: : 844iter [01:19, 11.69iter/s]
Best score: 0.2578: : 845iter [01:19, 11.69iter/s]
Best score: 0.2578: : 845iter [01:19, 11.69iter/s]
Best score: 0.2578: : 846iter [01:19, 11.69iter/s]
Best score: 0.2578: : 847iter [01:19, 11.75iter/s]
Best score: 0.2578: : 847iter [01:19, 11.75iter/s]
Best score: 0.2578: : 848iter [01:19, 11.75iter/s]
Best score: 0.2578: : 849iter [01:19, 11.76iter/s]
[ITER 850] Best: 0.2578
[PARAMS] Current best parameters:
  fx: 553.6811
  fy: 553.0967
  px: 1017.7841
  py: 760.9797
  k1: -0.01490086
  k2: -0.01644226
  k3: 0.01359210
  k4: -0.00356348
  p1: -0.01347446
  p2: -0.00618737
  p3: -0.00127207
  p4: 0.01637147
  s1: 0.0099
  s2: -0.0176
  s3: 0.0104
  s4: -0.0168
  tilt_x: -0.0439
  tilt_y: -0.0320
  scale: 2.9820
  rotation: -0.2836

Best score: 0.2578: : 849iter [01:19, 11.76iter/s]
Best score: 0.2578: : 850iter [01:20, 11.76iter/s]
Best score: 0.2578: : 851iter [01:20,  7.52iter/s]
Best score: 0.2578: : 851iter [01:20,  7.52iter/s]
Best score: 0.2578: : 852iter [01:20,  7.52iter/s]
Best score: 0.2578: : 853iter [01:20,  8.46iter/s]
Best score: 0.2578: : 853iter [01:20,  8.46iter/s]
Best score: 0.2578: : 854iter [01:20,  8.46iter/s]
Best score: 0.2578: : 855iter [01:20,  9.26iter/s]
Best score: 0.2578: : 855iter [01:20,  9.26iter/s]
Best score: 0.2578: : 856iter [01:20,  9.26iter/s]
Best score: 0.2578: : 857iter [01:20,  9.91iter/s]
Best score: 0.2578: : 857iter [01:20,  9.91iter/s]
Best score: 0.2578: : 858iter [01:20,  9.91iter/s]
Best score: 0.2578: : 859iter [01:20, 10.38iter/s]
Best score: 0.2572: : 859iter [01:20, 10.38iter/s]
Best score: 0.2572: : 860iter [01:21, 10.38iter/s]
Best score: 0.2572: : 861iter [01:21, 10.63iter/s]
Best score: 0.2572: : 861iter [01:21, 10.63iter/s]
Best score: 0.2572: : 862iter [01:21, 10.63iter/s]
Best score: 0.2572: : 863iter [01:21, 10.98iter/s]
Best score: 0.2572: : 863iter [01:21, 10.98iter/s]
Best score: 0.2572: : 864iter [01:21, 10.98iter/s]
Best score: 0.2572: : 865iter [01:21, 11.22iter/s]
Best score: 0.2572: : 865iter [01:21, 11.22iter/s]
Best score: 0.2572: : 866iter [01:21, 11.22iter/s]
Best score: 0.2572: : 867iter [01:21, 11.37iter/s]
Best score: 0.2572: : 867iter [01:21, 11.37iter/s]
Best score: 0.2572: : 868iter [01:21, 11.37iter/s]
Best score: 0.2572: : 869iter [01:21, 11.52iter/s]
Best score: 0.2565: : 869iter [01:21, 11.52iter/s]
Best score: 0.2565: : 870iter [01:21, 11.52iter/s]
Best score: 0.2565: : 871iter [01:21, 11.44iter/s]
Best score: 0.2565: : 871iter [01:21, 11.44iter/s]
Best score: 0.2565: : 872iter [01:22, 11.44iter/s]
Best score: 0.2565: : 873iter [01:22, 11.50iter/s]
Best score: 0.2565: : 873iter [01:22, 11.50iter/s]
Best score: 0.2565: : 874iter [01:22, 11.50iter/s]
Best score: 0.2565: : 875iter [01:22, 11.60iter/s]
Best score: 0.2565: : 875iter [01:22, 11.60iter/s]
Best score: 0.2565: : 876iter [01:22, 11.60iter/s]
Best score: 0.2565: : 877iter [01:22, 11.68iter/s]
Best score: 0.2565: : 877iter [01:22, 11.68iter/s]
Best score: 0.2565: : 878iter [01:22, 11.68iter/s]
Best score: 0.2565: : 879iter [01:22, 11.70iter/s]
Best score: 0.2563: : 879iter [01:22, 11.70iter/s]
Best score: 0.2563: : 880iter [01:22, 11.70iter/s]
Best score: 0.2563: : 881iter [01:22, 11.51iter/s]
Best score: 0.2563: : 881iter [01:22, 11.51iter/s]
Best score: 0.2563: : 882iter [01:22, 11.51iter/s]
Best score: 0.2563: : 883iter [01:22, 11.65iter/s]
Best score: 0.2563: : 883iter [01:22, 11.65iter/s]
Best score: 0.2563: : 884iter [01:23, 11.65iter/s]
Best score: 0.2563: : 885iter [01:23, 11.73iter/s]
Best score: 0.2563: : 885iter [01:23, 11.73iter/s]
Best score: 0.2563: : 886iter [01:23, 11.73iter/s]
Best score: 0.2563: : 887iter [01:23, 11.73iter/s]
Best score: 0.2563: : 887iter [01:23, 11.73iter/s]
Best score: 0.2563: : 888iter [01:23, 11.73iter/s]
Best score: 0.2563: : 889iter [01:23, 11.73iter/s]
Best score: 0.2558: : 889iter [01:23, 11.73iter/s]
Best score: 0.2558: : 890iter [01:23, 11.73iter/s]
Best score: 0.2558: : 891iter [01:23, 11.58iter/s]
Best score: 0.2558: : 891iter [01:23, 11.58iter/s]
Best score: 0.2558: : 892iter [01:23, 11.58iter/s]
Best score: 0.2558: : 893iter [01:23, 11.66iter/s]
Best score: 0.2558: : 893iter [01:23, 11.66iter/s]
Best score: 0.2558: : 894iter [01:23, 11.66iter/s]
Best score: 0.2558: : 895iter [01:23, 11.73iter/s]
Best score: 0.2558: : 895iter [01:23, 11.73iter/s]
Best score: 0.2558: : 896iter [01:24, 11.73iter/s]
Best score: 0.2558: : 897iter [01:24, 11.79iter/s]
Best score: 0.2558: : 897iter [01:24, 11.79iter/s]
Best score: 0.2558: : 898iter [01:24, 11.79iter/s]
Best score: 0.2558: : 899iter [01:24, 11.80iter/s]
[ITER 900] Best: 0.2552
[PARAMS] Current best parameters:
  fx: 556.6591
  fy: 556.2085
  px: 1017.5990
  py: 760.6382
  k1: -0.02375441
  k2: -0.00699589
  k3: 0.00819169
  k4: -0.00239618
  p1: -0.01268061
  p2: -0.00642953
  p3: -0.00175577
  p4: 0.01563835
  s1: 0.0115
  s2: -0.0176
  s3: 0.0095
  s4: -0.0155
  tilt_x: -0.0479
  tilt_y: -0.0313
  scale: 2.9869
  rotation: -0.2803

Best score: 0.2552: : 899iter [01:24, 11.80iter/s]
Best score: 0.2552: : 900iter [01:24, 11.80iter/s]
Best score: 0.2552: : 901iter [01:24,  7.55iter/s]
Best score: 0.2552: : 901iter [01:24,  7.55iter/s]
Best score: 0.2552: : 902iter [01:24,  7.55iter/s]
Best score: 0.2552: : 903iter [01:24,  8.47iter/s]
Best score: 0.2552: : 903iter [01:24,  8.47iter/s]
Best score: 0.2552: : 904iter [01:25,  8.47iter/s]
Best score: 0.2552: : 905iter [01:25,  9.28iter/s]
Best score: 0.2552: : 905iter [01:25,  9.28iter/s]
Best score: 0.2552: : 906iter [01:25,  9.28iter/s]
Best score: 0.2552: : 907iter [01:25,  9.90iter/s]
Best score: 0.2552: : 907iter [01:25,  9.90iter/s]
Best score: 0.2552: : 908iter [01:25,  9.90iter/s]
Best score: 0.2552: : 909iter [01:25, 10.35iter/s]
Best score: 0.2549: : 909iter [01:25, 10.35iter/s]
Best score: 0.2549: : 910iter [01:25, 10.35iter/s]
Best score: 0.2549: : 911iter [01:25, 10.58iter/s]
Best score: 0.2549: : 911iter [01:25, 10.58iter/s]
Best score: 0.2549: : 912iter [01:25, 10.58iter/s]
Best score: 0.2549: : 913iter [01:25, 10.93iter/s]
Best score: 0.2549: : 913iter [01:25, 10.93iter/s]
Best score: 0.2549: : 914iter [01:25, 10.93iter/s]
Best score: 0.2549: : 915iter [01:25, 11.21iter/s]
Best score: 0.2549: : 915iter [01:26, 11.21iter/s]
Best score: 0.2549: : 916iter [01:26, 11.21iter/s]
Best score: 0.2549: : 917iter [01:26, 11.40iter/s]
Best score: 0.2549: : 917iter [01:26, 11.40iter/s]
Best score: 0.2549: : 918iter [01:26, 11.40iter/s]
Best score: 0.2549: : 919iter [01:26, 11.55iter/s]
Best score: 0.2549: : 919iter [01:26, 11.55iter/s]
Best score: 0.2549: : 920iter [01:26, 11.55iter/s]
Best score: 0.2549: : 921iter [01:26, 11.40iter/s]
Best score: 0.2549: : 921iter [01:26, 11.40iter/s]
Best score: 0.2549: : 922iter [01:26, 11.40iter/s]
Best score: 0.2549: : 923iter [01:26, 11.54iter/s]
Best score: 0.2549: : 923iter [01:26, 11.54iter/s]
Best score: 0.2549: : 924iter [01:26, 11.54iter/s]
Best score: 0.2549: : 925iter [01:26, 11.65iter/s]
Best score: 0.2549: : 925iter [01:26, 11.65iter/s]
Best score: 0.2549: : 926iter [01:26, 11.65iter/s]
Best score: 0.2549: : 927iter [01:26, 11.73iter/s]
Best score: 0.2549: : 927iter [01:27, 11.73iter/s]
Best score: 0.2549: : 928iter [01:27, 11.73iter/s]
Best score: 0.2549: : 929iter [01:27, 11.76iter/s]
Best score: 0.2549: : 929iter [01:27, 11.76iter/s]
Best score: 0.2549: : 930iter [01:27, 11.76iter/s]
Best score: 0.2549: : 931iter [01:27, 11.52iter/s]
Best score: 0.2549: : 931iter [01:27, 11.52iter/s]
Best score: 0.2549: : 932iter [01:27, 11.52iter/s]
Best score: 0.2549: : 933iter [01:27, 11.61iter/s]
Best score: 0.2549: : 933iter [01:27, 11.61iter/s]
Best score: 0.2549: : 934iter [01:27, 11.61iter/s]
Best score: 0.2549: : 935iter [01:27, 11.70iter/s]
Best score: 0.2549: : 935iter [01:27, 11.70iter/s]
Best score: 0.2549: : 936iter [01:27, 11.70iter/s]
Best score: 0.2549: : 937iter [01:27, 11.75iter/s]
Best score: 0.2549: : 937iter [01:27, 11.75iter/s]
Best score: 0.2549: : 938iter [01:27, 11.75iter/s]
Best score: 0.2549: : 939iter [01:27, 11.82iter/s]
Best score: 0.2547: : 939iter [01:28, 11.82iter/s]
Best score: 0.2547: : 940iter [01:28, 11.82iter/s]
Best score: 0.2547: : 941iter [01:28, 11.63iter/s]
Best score: 0.2547: : 941iter [01:28, 11.63iter/s]
Best score: 0.2547: : 942iter [01:28, 11.63iter/s]
Best score: 0.2547: : 943iter [01:28, 11.69iter/s]
Best score: 0.2547: : 943iter [01:28, 11.69iter/s]
Best score: 0.2547: : 944iter [01:28, 11.69iter/s]
Best score: 0.2547: : 945iter [01:28, 11.67iter/s]
Best score: 0.2547: : 945iter [01:28, 11.67iter/s]
Best score: 0.2547: : 946iter [01:28, 11.67iter/s]
Best score: 0.2547: : 947iter [01:28, 11.70iter/s]
Best score: 0.2547: : 947iter [01:28, 11.70iter/s]
Best score: 0.2547: : 948iter [01:28, 11.70iter/s]
Best score: 0.2547: : 949iter [01:28, 11.76iter/s]
[ITER 950] Best: 0.2543
[PARAMS] Current best parameters:
  fx: 556.6119
  fy: 556.1655
  px: 1017.4285
  py: 760.1338
  k1: -0.03023221
  k2: 0.00527836
  k3: -0.00018102
  k4: -0.00040727
  p1: -0.01248951
  p2: -0.00593514
  p3: -0.00319594
  p4: 0.01357434
  s1: 0.0120
  s2: -0.0155
  s3: 0.0101
  s4: -0.0132
  tilt_x: -0.0509
  tilt_y: -0.0295
  scale: 2.9915
  rotation: -0.2743

Best score: 0.2543: : 949iter [01:28, 11.76iter/s]
Best score: 0.2543: : 950iter [01:29, 11.76iter/s]
Best score: 0.2543: : 951iter [01:29,  7.51iter/s]
Best score: 0.2543: : 951iter [01:29,  7.51iter/s]
Best score: 0.2543: : 952iter [01:29,  7.51iter/s]
Best score: 0.2543: : 953iter [01:29,  8.44iter/s]
Best score: 0.2543: : 953iter [01:29,  8.44iter/s]
Best score: 0.2543: : 954iter [01:29,  8.44iter/s]
Best score: 0.2543: : 955iter [01:29,  9.24iter/s]
Best score: 0.2543: : 955iter [01:29,  9.24iter/s]
Best score: 0.2543: : 956iter [01:29,  9.24iter/s]
Best score: 0.2543: : 957iter [01:29,  9.87iter/s]
Best score: 0.2543: : 957iter [01:29,  9.87iter/s]
Best score: 0.2543: : 958iter [01:29,  9.87iter/s]
Best score: 0.2543: : 959iter [01:29, 10.41iter/s]
Best score: 0.2538: : 959iter [01:30, 10.41iter/s]
Best score: 0.2538: : 960iter [01:30, 10.41iter/s]
Best score: 0.2538: : 961iter [01:30, 10.64iter/s]
Best score: 0.2538: : 961iter [01:30, 10.64iter/s]
Best score: 0.2538: : 962iter [01:30, 10.64iter/s]
Best score: 0.2538: : 963iter [01:30, 10.94iter/s]
Best score: 0.2538: : 963iter [01:30, 10.94iter/s]
Best score: 0.2538: : 964iter [01:30, 10.94iter/s]
Best score: 0.2538: : 965iter [01:30, 11.19iter/s]
Best score: 0.2538: : 965iter [01:30, 11.19iter/s]
Best score: 0.2538: : 966iter [01:30, 11.19iter/s]
Best score: 0.2538: : 967iter [01:30, 11.32iter/s]
Best score: 0.2538: : 967iter [01:30, 11.32iter/s]
Best score: 0.2538: : 968iter [01:30, 11.32iter/s]
Best score: 0.2538: : 969iter [01:30, 11.50iter/s]
Best score: 0.2535: : 969iter [01:30, 11.50iter/s]
Best score: 0.2535: : 970iter [01:31, 11.50iter/s]
Best score: 0.2535: : 971iter [01:31, 11.38iter/s]
Best score: 0.2535: : 971iter [01:31, 11.38iter/s]
Best score: 0.2535: : 972iter [01:31, 11.38iter/s]
Best score: 0.2535: : 973iter [01:31, 11.52iter/s]
Best score: 0.2535: : 973iter [01:31, 11.52iter/s]
Best score: 0.2535: : 974iter [01:31, 11.52iter/s]
Best score: 0.2535: : 975iter [01:31, 11.62iter/s]
Best score: 0.2535: : 975iter [01:31, 11.62iter/s]
Best score: 0.2535: : 976iter [01:31, 11.62iter/s]
Best score: 0.2535: : 977iter [01:31, 11.71iter/s]
Best score: 0.2535: : 977iter [01:31, 11.71iter/s]
Best score: 0.2535: : 978iter [01:31, 11.71iter/s]
Best score: 0.2535: : 979iter [01:31, 11.78iter/s]
Best score: 0.2535: : 979iter [01:31, 11.78iter/s]
Best score: 0.2535: : 980iter [01:31, 11.78iter/s]
Best score: 0.2535: : 981iter [01:31, 11.61iter/s]
Best score: 0.2535: : 981iter [01:31, 11.61iter/s]
Best score: 0.2535: : 982iter [01:32, 11.61iter/s]
Best score: 0.2535: : 983iter [01:32, 11.69iter/s]
Best score: 0.2535: : 983iter [01:32, 11.69iter/s]
Best score: 0.2535: : 984iter [01:32, 11.69iter/s]
Best score: 0.2535: : 985iter [01:32, 11.75iter/s]
Best score: 0.2535: : 985iter [01:32, 11.75iter/s]
Best score: 0.2535: : 986iter [01:32, 11.75iter/s]
Best score: 0.2535: : 987iter [01:32, 11.79iter/s]
Best score: 0.2535: : 987iter [01:32, 11.79iter/s]
Best score: 0.2535: : 988iter [01:32, 11.79iter/s]
Best score: 0.2535: : 989iter [01:32, 11.81iter/s]
Best score: 0.2533: : 989iter [01:32, 11.81iter/s]
Best score: 0.2533: : 990iter [01:32, 11.81iter/s]
Best score: 0.2533: : 991iter [01:32, 11.64iter/s]
Best score: 0.2533: : 991iter [01:32, 11.64iter/s]
Best score: 0.2533: : 992iter [01:32, 11.64iter/s]
Best score: 0.2533: : 993iter [01:32, 11.72iter/s]
Best score: 0.2533: : 993iter [01:32, 11.72iter/s]
Best score: 0.2533: : 994iter [01:33, 11.72iter/s]
Best score: 0.2533: : 995iter [01:33, 11.78iter/s]
Best score: 0.2533: : 995iter [01:33, 11.78iter/s]
Best score: 0.2533: : 996iter [01:33, 11.78iter/s]
Best score: 0.2533: : 997iter [01:33, 11.82iter/s]
Best score: 0.2533: : 997iter [01:33, 11.82iter/s]
Best score: 0.2533: : 998iter [01:33, 11.82iter/s]
Best score: 0.2533: : 999iter [01:33, 11.85iter/s]
[ITER 1000] Best: 0.2533
[PARAMS] Current best parameters:
  fx: 552.7466
  fy: 552.3383
  px: 1017.2400
  py: 759.8194
  k1: -0.02455587
  k2: 0.00248539
  k3: 0.00104397
  k4: -0.00066284
  p1: -0.01253576
  p2: -0.00687628
  p3: -0.00101072
  p4: 0.01560798
  s1: 0.0105
  s2: -0.0173
  s3: 0.0074
  s4: -0.0150
  tilt_x: -0.0517
  tilt_y: -0.0305
  scale: 2.9916
  rotation: -0.2714

Best score: 0.2533: : 999iter [01:33, 11.85iter/s]
Best score: 0.2533: : 1000iter [01:33, 11.85iter/s]
Best score: 0.2533: : 1001iter [01:33,  7.51iter/s]
Best score: 0.2533: : 1001iter [01:33,  7.51iter/s]
Best score: 0.2533: : 1002iter [01:34,  7.51iter/s]
Best score: 0.2533: : 1003iter [01:34,  8.45iter/s]
Best score: 0.2533: : 1003iter [01:34,  8.45iter/s]
Best score: 0.2533: : 1004iter [01:34,  8.45iter/s]
Best score: 0.2533: : 1005iter [01:34,  9.22iter/s]
Best score: 0.2533: : 1005iter [01:34,  9.22iter/s]
Best score: 0.2533: : 1006iter [01:34,  9.22iter/s]
Best score: 0.2533: : 1007iter [01:34,  9.88iter/s]
Best score: 0.2533: : 1007iter [01:34,  9.88iter/s]
Best score: 0.2533: : 1008iter [01:34,  9.88iter/s]
Best score: 0.2533: : 1009iter [01:34, 10.41iter/s]
Best score: 0.2533: : 1009iter [01:34, 10.41iter/s]
Best score: 0.2533: : 1010iter [01:34, 10.41iter/s]
Best score: 0.2533: : 1011iter [01:34, 10.65iter/s]
Best score: 0.2533: : 1011iter [01:34, 10.65iter/s]
Best score: 0.2533: : 1012iter [01:34, 10.65iter/s]
Best score: 0.2533: : 1013iter [01:34, 10.96iter/s]
Best score: 0.2533: : 1013iter [01:35, 10.96iter/s]
Best score: 0.2533: : 1014iter [01:35, 10.96iter/s]
Best score: 0.2533: : 1015iter [01:35, 11.23iter/s]
Best score: 0.2533: : 1015iter [01:35, 11.23iter/s]
Best score: 0.2533: : 1016iter [01:35, 11.23iter/s]
Best score: 0.2533: : 1017iter [01:35, 11.41iter/s]
Best score: 0.2533: : 1017iter [01:35, 11.41iter/s]
Best score: 0.2533: : 1018iter [01:35, 11.41iter/s]
Best score: 0.2533: : 1019iter [01:35, 11.45iter/s]
Best score: 0.2532: : 1019iter [01:35, 11.45iter/s]
Best score: 0.2532: : 1020iter [01:35, 11.45iter/s]
Best score: 0.2532: : 1021iter [01:35, 11.35iter/s]
Best score: 0.2532: : 1021iter [01:35, 11.35iter/s]
Best score: 0.2532: : 1022iter [01:35, 11.35iter/s]
Best score: 0.2532: : 1023iter [01:35, 11.50iter/s]
Best score: 0.2532: : 1023iter [01:35, 11.50iter/s]
Best score: 0.2532: : 1024iter [01:35, 11.50iter/s]
Best score: 0.2532: : 1025iter [01:35, 11.62iter/s]
Best score: 0.2532: : 1025iter [01:36, 11.62iter/s]
Best score: 0.2532: : 1026iter [01:36, 11.62iter/s]
Best score: 0.2532: : 1027iter [01:36, 11.72iter/s]
Best score: 0.2532: : 1027iter [01:36, 11.72iter/s]
Best score: 0.2532: : 1028iter [01:36, 11.72iter/s]
Best score: 0.2532: : 1029iter [01:36, 11.72iter/s]
Best score: 0.2532: : 1029iter [01:36, 11.72iter/s]
Best score: 0.2532: : 1030iter [01:36, 11.72iter/s]
Best score: 0.2532: : 1031iter [01:36, 11.58iter/s]
Best score: 0.2532: : 1031iter [01:36, 11.58iter/s]
Best score: 0.2532: : 1032iter [01:36, 11.58iter/s]
Best score: 0.2532: : 1033iter [01:36, 11.68iter/s]
Best score: 0.2532: : 1033iter [01:36, 11.68iter/s]
Best score: 0.2532: : 1034iter [01:36, 11.68iter/s]
Best score: 0.2532: : 1035iter [01:36, 11.74iter/s]
Best score: 0.2532: : 1035iter [01:36, 11.74iter/s]
Best score: 0.2532: : 1036iter [01:36, 11.74iter/s]
Best score: 0.2532: : 1037iter [01:36, 11.78iter/s]
Best score: 0.2532: : 1037iter [01:37, 11.78iter/s]
Best score: 0.2532: : 1038iter [01:37, 11.78iter/s]
Best score: 0.2532: : 1039iter [01:37, 11.82iter/s]
Best score: 0.2532: : 1039iter [01:37, 11.82iter/s]
Best score: 0.2532: : 1040iter [01:37, 11.82iter/s]
Best score: 0.2532: : 1041iter [01:37, 11.63iter/s]
Best score: 0.2532: : 1041iter [01:37, 11.63iter/s]
Best score: 0.2532: : 1042iter [01:37, 11.63iter/s]
Best score: 0.2532: : 1043iter [01:37, 11.71iter/s]
Best score: 0.2532: : 1043iter [01:37, 11.71iter/s]
Best score: 0.2532: : 1044iter [01:37, 11.71iter/s]
Best score: 0.2532: : 1045iter [01:37, 11.76iter/s]
Best score: 0.2532: : 1045iter [01:37, 11.76iter/s]
Best score: 0.2532: : 1046iter [01:37, 11.76iter/s]
Best score: 0.2532: : 1047iter [01:37, 11.74iter/s]
Best score: 0.2532: : 1047iter [01:37, 11.74iter/s]
Best score: 0.2532: : 1048iter [01:37, 11.74iter/s]
Best score: 0.2532: : 1049iter [01:37, 11.69iter/s]
[ITER 1050] Best: 0.2530
[PARAMS] Current best parameters:
  fx: 551.8505
  fy: 551.4805
  px: 1017.1525
  py: 759.7364
  k1: -0.02336002
  k2: 0.00190162
  k3: 0.00142108
  k4: -0.00078129
  p1: -0.01176924
  p2: -0.00680616
  p3: -0.00046342
  p4: 0.01524221
  s1: 0.0093
  s2: -0.0166
  s3: 0.0062
  s4: -0.0148
  tilt_x: -0.0536
  tilt_y: -0.0299
  scale: 2.9921
  rotation: -0.2750

Best score: 0.2530: : 1049iter [01:38, 11.69iter/s]
Best score: 0.2530: : 1050iter [01:38, 11.69iter/s]
Best score: 0.2530: : 1051iter [01:38,  7.51iter/s]
Best score: 0.2530: : 1051iter [01:38,  7.51iter/s]
Best score: 0.2530: : 1052iter [01:38,  7.51iter/s]
Best score: 0.2530: : 1053iter [01:38,  8.44iter/s]
Best score: 0.2530: : 1053iter [01:38,  8.44iter/s]
Best score: 0.2530: : 1054iter [01:38,  8.44iter/s]
Best score: 0.2530: : 1055iter [01:38,  9.24iter/s]
Best score: 0.2530: : 1055iter [01:38,  9.24iter/s]
Best score: 0.2530: : 1056iter [01:38,  9.24iter/s]
Best score: 0.2530: : 1057iter [01:38,  9.87iter/s]
Best score: 0.2530: : 1057iter [01:39,  9.87iter/s]
Best score: 0.2530: : 1058iter [01:39,  9.87iter/s]
Best score: 0.2530: : 1059iter [01:39, 10.41iter/s]
Best score: 0.2530: : 1059iter [01:39, 10.41iter/s]
Best score: 0.2530: : 1060iter [01:39, 10.41iter/s]
Best score: 0.2530: : 1061iter [01:39, 10.61iter/s]
Best score: 0.2530: : 1061iter [01:39, 10.61iter/s]
Best score: 0.2530: : 1062iter [01:39, 10.61iter/s]
Best score: 0.2530: : 1063iter [01:39, 10.96iter/s]
Best score: 0.2530: : 1063iter [01:39, 10.96iter/s]
Best score: 0.2530: : 1064iter [01:39, 10.96iter/s]
Best score: 0.2530: : 1065iter [01:39, 11.22iter/s]
Best score: 0.2530: : 1065iter [01:39, 11.22iter/s]
Best score: 0.2530: : 1066iter [01:39, 11.22iter/s]
Best score: 0.2530: : 1067iter [01:39, 11.38iter/s]
Best score: 0.2530: : 1067iter [01:39, 11.38iter/s]
Best score: 0.2530: : 1068iter [01:40, 11.38iter/s]
Best score: 0.2530: : 1069iter [01:40, 11.52iter/s]
Best score: 0.2530: : 1069iter [01:40, 11.52iter/s]
Best score: 0.2530: : 1070iter [01:40, 11.52iter/s]
Best score: 0.2530: : 1071iter [01:40, 11.44iter/s]
Best score: 0.2530: : 1071iter [01:40, 11.44iter/s]
Best score: 0.2530: : 1072iter [01:40, 11.44iter/s]
Best score: 0.2530: : 1073iter [01:40, 11.55iter/s]
Best score: 0.2530: : 1073iter [01:40, 11.55iter/s]
Best score: 0.2530: : 1074iter [01:40, 11.55iter/s]
Best score: 0.2530: : 1075iter [01:40, 11.67iter/s]
Best score: 0.2530: : 1075iter [01:40, 11.67iter/s]
Best score: 0.2530: : 1076iter [01:40, 11.67iter/s]
Best score: 0.2530: : 1077iter [01:40, 11.70iter/s]
Best score: 0.2530: : 1077iter [01:40, 11.70iter/s]
Best score: 0.2530: : 1078iter [01:40, 11.70iter/s]
Best score: 0.2530: : 1079iter [01:40, 11.77iter/s]
Best score: 0.2529: : 1079iter [01:40, 11.77iter/s]
Best score: 0.2529: : 1080iter [01:41, 11.77iter/s]
Best score: 0.2529: : 1081iter [01:41,  8.70iter/s]
Best score: 0.2529: : 1081iter [01:41,  8.70iter/s]
Best score: 0.2529: : 1082iter [01:41,  8.70iter/s]
Best score: 0.2529: : 1083iter [01:41,  9.39iter/s]
Best score: 0.2529: : 1083iter [01:41,  9.39iter/s]
Best score: 0.2529: : 1084iter [01:41,  9.39iter/s]
Best score: 0.2529: : 1085iter [01:41,  9.97iter/s]
Best score: 0.2529: : 1085iter [01:41,  9.97iter/s]
Best score: 0.2529: : 1086iter [01:41,  9.97iter/s]
Best score: 0.2529: : 1087iter [01:41, 10.48iter/s]
Best score: 0.2529: : 1087iter [01:41, 10.48iter/s]
Best score: 0.2529: : 1088iter [01:41, 10.48iter/s]
Best score: 0.2529: : 1089iter [01:41, 10.83iter/s]
Best score: 0.2529: : 1089iter [01:42, 10.83iter/s]
Best score: 0.2529: : 1090iter [01:42, 10.83iter/s]
Best score: 0.2529: : 1091iter [01:42, 10.90iter/s]
Best score: 0.2529: : 1091iter [01:42, 10.90iter/s]
Best score: 0.2529: : 1092iter [01:42, 10.90iter/s]
Best score: 0.2529: : 1093iter [01:42, 11.17iter/s]
Best score: 0.2529: : 1093iter [01:42, 11.17iter/s]
Best score: 0.2529: : 1094iter [01:42, 11.17iter/s]
Best score: 0.2529: : 1095iter [01:42, 11.34iter/s]
Best score: 0.2529: : 1095iter [01:42, 11.34iter/s]
Best score: 0.2529: : 1096iter [01:42, 11.34iter/s]
Best score: 0.2529: : 1097iter [01:42, 11.49iter/s]
Best score: 0.2529: : 1097iter [01:42, 11.49iter/s]
Best score: 0.2529: : 1098iter [01:42, 11.49iter/s]
Best score: 0.2529: : 1099iter [01:42, 11.55iter/s]
[ITER 1100] Best: 0.2529
[PARAMS] Current best parameters:
  fx: 551.1731
  fy: 550.8042
  px: 1017.2053
  py: 759.7527
  k1: -0.02325132
  k2: 0.00262275
  k3: 0.00103526
  k4: -0.00071414
  p1: -0.01178161
  p2: -0.00675926
  p3: -0.00002356
  p4: 0.01520933
  s1: 0.0091
  s2: -0.0167
  s3: 0.0057
  s4: -0.0147
  tilt_x: -0.0533
  tilt_y: -0.0299
  scale: 2.9931
  rotation: -0.2729

Best score: 0.2529: : 1099iter [01:42, 11.55iter/s]
Best score: 0.2529: : 1100iter [01:43, 10.66iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.252896 -> 0.252606

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 102,409 → 94,684 within 3500mm ring
  Ring polish did not improve score: 0.252606
  Success: True
  Tangential distortion: p1=-0.011790, p2=-0.006719, p3=-0.000061, p4=0.015243
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.2526
[✅] Parameters copied to: /working/MDC018_W044(6)_2026_05_06/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 551.1731285443516
    fy: 550.8041948020215
    px: 1017.2052600372677
    py: 759.7526651149312
    k1: -0.023297568721992203
    k2: 0.0026555555083348312
    k3: 0.0011244708667724175
    k4: -0.0007717367835979438
    p1: -0.011789549075225406
    p2: -0.006719397009344401
    p3: -6.138199174914757e-05
    p4: 0.015242532325610144
    scale: 2.992996897428175
    rotation: -0.27292278094218014
    mmpp: 3.4232692833845437

[🔄] Converting 2930 frames to PTD, creating debug images for 400 calibration frames...

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   🔄 1500:  91%|█████████ | 857/944 [00:04<00:00, 175.93frame/s]

   🔄 1500:  93%|█████████▎| 875/944 [00:04<00:00, 175.24frame/s]

   🔄 1500:  95%|█████████▍| 893/944 [00:05<00:00, 174.66frame/s]

   🔄 1500:  97%|█████████▋| 911/944 [00:05<00:00, 174.34frame/s]

   🔄 1500:  98%|█████████▊| 929/944 [00:05<00:00, 174.12frame/s]

                                                                 
📁 Rigs:  25%|██▌       | 1/4 [00:09<00:29,  9.73s/rig]

   🔄 2000R:   0%|          | 0/689 [00:00<?, ?frame/s]

   🔄 2000R:   3%|▎         | 18/689 [00:00<00:03, 173.07frame/s]

   🔄 2000R:   5%|▌         | 36/689 [00:00<00:03, 172.66frame/s]

   🔄 2000R:   8%|▊         | 54/689 [00:00<00:03, 173.36frame/s]

   🔄 2000R:  10%|█         | 72/689 [00:00<00:03, 173.76frame/s]

   🔄 2000R:  13%|█▎        | 90/689 [00:00<00:03, 175.07frame/s]

   🔄 2000R:  16%|█▌        | 108/689 [00:00<00:03, 176.19frame/s]

   🔄 2000R:  18%|█▊        | 126/689 [00:00<00:03, 177.20frame/s]

   🔄 2000R:  21%|██        | 144/689 [00:00<00:03, 177.73frame/s]

   🔄 2000R:  24%|██▎       | 162/689 [00:00<00:02, 178.17frame/s]

   🔄 2000R:  26%|██▌       | 180/689 [00:01<00:02, 178.45frame/s]

   🔄 2000R:  29%|██▊       | 198/689 [00:01<00:02, 178.23frame/s]

   🔄 2000R:  31%|███▏      | 216/689 [00:01<00:02, 177.86frame/s]

   🔄 2000R:  34%|███▍      | 234/689 [00:01<00:02, 177.39frame/s]

   🔄 2000R:  37%|███▋      | 252/689 [00:01<00:02, 176.55frame/s]

   🔄 2000R:  39%|███▉      | 270/689 [00:01<00:02, 175.88frame/s]

   🔄 2000R:  42%|████▏     | 288/689 [00:01<00:02, 175.47frame/s]

   🔄 2000R:  44%|████▍     | 306/689 [00:01<00:02, 174.92frame/s]

   🔄 2000R:  47%|████▋     | 324/689 [00:01<00:02, 174.57frame/s]

   🔄 2000R:  50%|████▉     | 342/689 [00:01<00:01, 173.91frame/s]

   🔄 2000R:  52%|█████▏    | 360/689 [00:02<00:01, 172.88frame/s]

   🔄 2000R:  55%|█████▍    | 378/689 [00:02<00:01, 172.19frame/s]

   🔄 2000R:  57%|█████▋    | 396/689 [00:02<00:01, 169.91frame/s]

   🔄 2000R:  60%|█████▉    | 413/689 [00:02<00:01, 169.90frame/s]

   🔄 2000R:  63%|██████▎   | 431/689 [00:02<00:01, 170.10frame/s]

   🔄 2000R:  65%|██████▌   | 449/689 [00:02<00:01, 170.94frame/s]

   🔄 2000R:  68%|██████▊   | 467/689 [00:02<00:01, 172.80frame/s]

   🔄 2000R:  70%|███████   | 485/689 [00:02<00:01, 174.33frame/s]

   🔄 2000R:  73%|███████▎  | 503/689 [00:02<00:01, 175.23frame/s]

   🔄 2000R:  76%|███████▌  | 521/689 [00:02<00:00, 175.75frame/s]

   🔄 2000R:  78%|███████▊  | 539/689 [00:03<00:00, 176.34frame/s]

   🔄 2000R:  81%|████████  | 557/689 [00:03<00:00, 176.62frame/s]

   🔄 2000R:  83%|████████▎ | 575/689 [00:03<00:00, 176.53frame/s]

   🔄 2000R:  86%|████████▌ | 593/689 [00:03<00:00, 174.75frame/s]

   🔄 2000R:  89%|████████▊ | 611/689 [00:03<00:00, 173.29frame/s]

   🔄 2000R:  91%|█████████▏| 629/689 [00:03<00:00, 172.25frame/s]

   🔄 2000R:  94%|█████████▍| 647/689 [00:03<00:00, 171.69frame/s]

   🔄 2000R:  97%|█████████▋| 665/689 [00:03<00:00, 171.41frame/s]

   🔄 2000R:  99%|█████████▉| 683/689 [00:03<00:00, 171.36frame/s]

                                                                  
📁 Rigs:  50%|█████     | 2/4 [00:16<00:16,  8.15s/rig]

   🔄 1000:   0%|          | 0/599 [00:00<?, ?frame/s]

   🔄 1000:   3%|▎         | 18/599 [00:00<00:03, 172.80frame/s]

   🔄 1000:   6%|▌         | 36/599 [00:00<00:03, 173.15frame/s]

   🔄 1000:   9%|▉         | 54/599 [00:00<00:03, 173.64frame/s]

   🔄 1000:  12%|█▏        | 72/599 [00:00<00:03, 174.21frame/s]

   🔄 1000:  15%|█▌        | 90/599 [00:00<00:02, 174.07frame/s]

   🔄 1000:  18%|█▊        | 108/599 [00:00<00:02, 174.87frame/s]

   🔄 1000:  21%|██        | 126/599 [00:00<00:02, 175.13frame/s]

   🔄 1000:  24%|██▍       | 144/599 [00:00<00:02, 175.08frame/s]

   🔄 1000:  27%|██▋       | 162/599 [00:00<00:02, 175.10frame/s]

   🔄 1000:  30%|███       | 180/599 [00:01<00:02, 175.01frame/s]

   🔄 1000:  33%|███▎      | 198/599 [00:01<00:02, 174.87frame/s]

   🔄 1000:  36%|███▌      | 217/599 [00:01<00:02, 176.87frame/s]

   🔄 1000:  39%|███▉      | 236/599 [00:01<00:02, 179.11frame/s]

   🔄 1000:  43%|████▎     | 255/599 [00:01<00:01, 180.71frame/s]

   🔄 1000:  46%|████▌     | 274/599 [00:01<00:01, 182.39frame/s]

   🔄 1000:  49%|████▉     | 293/599 [00:01<00:01, 183.57frame/s]

   🔄 1000:  52%|█████▏    | 312/599 [00:01<00:01, 184.32frame/s]

   🔄 1000:  55%|█████▌    | 331/599 [00:01<00:01, 184.72frame/s]

   🔄 1000:  58%|█████▊    | 350/599 [00:01<00:01, 184.54frame/s]

   🔄 1000:  62%|██████▏   | 369/599 [00:02<00:01, 184.52frame/s]

   🔄 1000:  65%|██████▍   | 388/599 [00:02<00:01, 183.44frame/s]

   🔄 1000:  68%|██████▊   | 407/599 [00:02<00:01, 181.13frame/s]

   🔄 1000:  71%|███████   | 426/599 [00:02<00:00, 179.45frame/s]

   🔄 1000:  74%|███████▍  | 444/599 [00:02<00:00, 178.42frame/s]

   🔄 1000:  77%|███████▋  | 462/599 [00:02<00:00, 178.09frame/s]

   🔄 1000:  80%|████████  | 480/599 [00:02<00:00, 177.77frame/s]

   🔄 1000:  83%|████████▎ | 498/599 [00:02<00:00, 177.65frame/s]

   🔄 1000:  86%|████████▌ | 516/599 [00:02<00:00, 177.54frame/s]

   🔄 1000:  89%|████████▉ | 534/599 [00:02<00:00, 177.07frame/s]

   🔄 1000:  92%|█████████▏| 552/599 [00:03<00:00, 176.89frame/s]

   🔄 1000:  95%|█████████▌| 570/599 [00:03<00:00, 176.75frame/s]

   🔄 1000:  98%|█████████▊| 588/599 [00:03<00:00, 176.71frame/s]

                                                                 
📁 Rigs:  75%|███████▌  | 3/4 [00:22<00:07,  7.03s/rig]

   🔄 2000L:   0%|          | 0/698 [00:00<?, ?frame/s]

   🔄 2000L:   3%|▎         | 18/698 [00:00<00:03, 171.94frame/s]

   🔄 2000L:   5%|▌         | 37/698 [00:00<00:03, 177.81frame/s]

   🔄 2000L:   8%|▊         | 55/698 [00:00<00:03, 175.28frame/s]

   🔄 2000L:  10%|█         | 73/698 [00:00<00:03, 173.63frame/s]

   🔄 2000L:  13%|█▎        | 91/698 [00:00<00:03, 172.91frame/s]

   🔄 2000L:  16%|█▌        | 109/698 [00:00<00:03, 172.71frame/s]

   🔄 2000L:  18%|█▊        | 127/698 [00:00<00:03, 173.90frame/s]

   🔄 2000L:  21%|██        | 145/698 [00:00<00:03, 175.63frame/s]

   🔄 2000L:  23%|██▎       | 164/698 [00:00<00:03, 177.32frame/s]

   🔄 2000L:  26%|██▌       | 183/698 [00:01<00:02, 178.48frame/s]

   🔄 2000L:  29%|██▉       | 202/698 [00:01<00:02, 179.18frame/s]

   🔄 2000L:  32%|███▏      | 220/698 [00:01<00:02, 179.29frame/s]

   🔄 2000L:  34%|███▍      | 238/698 [00:01<00:02, 179.37frame/s]

   🔄 2000L:  37%|███▋      | 256/698 [00:01<00:02, 179.43frame/s]

   🔄 2000L:  39%|███▉      | 274/698 [00:01<00:02, 179.19frame/s]

   🔄 2000L:  42%|████▏     | 292/698 [00:01<00:02, 177.54frame/s]

   🔄 2000L:  44%|████▍     | 310/698 [00:01<00:02, 176.25frame/s]

   🔄 2000L:  47%|████▋     | 328/698 [00:01<00:02, 175.20frame/s]

   🔄 2000L:  50%|████▉     | 346/698 [00:01<00:02, 174.58frame/s]

   🔄 2000L:  52%|█████▏    | 364/698 [00:02<00:01, 174.03frame/s]

   🔄 2000L:  55%|█████▍    | 382/698 [00:02<00:01, 173.97frame/s]

   🔄 2000L:  57%|█████▋    | 400/698 [00:02<00:01, 174.02frame/s]

   🔄 2000L:  60%|█████▉    | 418/698 [00:02<00:01, 174.40frame/s]

   🔄 2000L:  62%|██████▏   | 436/698 [00:02<00:01, 174.83frame/s]

   🔄 2000L:  65%|██████▌   | 454/698 [00:02<00:01, 175.50frame/s]

   🔄 2000L:  68%|██████▊   | 472/698 [00:02<00:01, 176.10frame/s]

   🔄 2000L:  70%|███████   | 490/698 [00:02<00:01, 177.04frame/s]

   🔄 2000L:  73%|███████▎  | 508/698 [00:02<00:01, 177.63frame/s]

   🔄 2000L:  75%|███████▌  | 526/698 [00:02<00:00, 178.15frame/s]

   🔄 2000L:  78%|███████▊  | 544/698 [00:03<00:00, 178.51frame/s]

   🔄 2000L:  81%|████████  | 562/698 [00:03<00:00, 178.88frame/s]

   🔄 2000L:  83%|████████▎ | 580/698 [00:03<00:00, 178.93frame/s]

   🔄 2000L:  86%|████████▌ | 598/698 [00:03<00:00, 178.79frame/s]

   🔄 2000L:  88%|████████▊ | 616/698 [00:03<00:00, 178.24frame/s]

   🔄 2000L:  91%|█████████ | 634/698 [00:03<00:00, 177.78frame/s]

   🔄 2000L:  93%|█████████▎| 652/698 [00:03<00:00, 177.16frame/s]

   🔄 2000L:  96%|█████████▌| 670/698 [00:03<00:00, 176.53frame/s]

   🔄 2000L:  99%|█████████▊| 688/698 [00:03<00:00, 175.28frame/s]

                                                                  
📁 Rigs: 100%|██████████| 4/4 [00:29<00:00,  7.15s/rig]
📁 Rigs: 100%|██████████| 4/4 [00:29<00:00,  7.45s/rig]
[✅] Saved PTDs: /working/MDC018_W044(6)_2026_05_06/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, 171.69frame/s]

   🔄 1500:  36%|███▌      | 36/100 [00:00<00:00, 171.94frame/s]

   🔄 1500:  54%|█████▍    | 54/100 [00:00<00:00, 175.07frame/s]

   🔄 1500:  72%|███████▏  | 72/100 [00:00<00:00, 174.94frame/s]

   🔄 1500:  90%|█████████ | 90/100 [00:00<00:00, 174.75frame/s]

                                                                
📁 Rigs:  25%|██▌       | 1/4 [00:00<00:02,  1.08rig/s]

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

   🔄 2000R:  18%|█▊        | 18/100 [00:00<00:00, 173.25frame/s]

   🔄 2000R:  36%|███▌      | 36/100 [00:00<00:00, 173.66frame/s]

   🔄 2000R:  54%|█████▍    | 54/100 [00:00<00:00, 172.06frame/s]

   🔄 2000R:  72%|███████▏  | 72/100 [00:00<00:00, 171.84frame/s]

   🔄 2000R:  90%|█████████ | 90/100 [00:00<00:00, 172.02frame/s]

                                                                 
📁 Rigs:  50%|█████     | 2/4 [00:01<00:01,  1.07rig/s]

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

   🔄 1000:  18%|█▊        | 18/100 [00:00<00:00, 173.61frame/s]

   🔄 1000:  36%|███▌      | 36/100 [00:00<00:00, 173.46frame/s]

   🔄 1000:  55%|█████▌    | 55/100 [00:00<00:00, 176.87frame/s]

   🔄 1000:  73%|███████▎  | 73/100 [00:00<00:00, 176.87frame/s]

   🔄 1000:  91%|█████████ | 91/100 [00:00<00:00, 176.25frame/s]

                                                                
📁 Rigs:  75%|███████▌  | 3/4 [00:02<00:00,  1.07rig/s]

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

   🔄 2000L:  17%|█▋        | 17/100 [00:00<00:00, 169.16frame/s]

   🔄 2000L:  35%|███▌      | 35/100 [00:00<00:00, 173.10frame/s]

   🔄 2000L:  53%|█████▎    | 53/100 [00:00<00:00, 171.87frame/s]

   🔄 2000L:  71%|███████   | 71/100 [00:00<00:00, 171.16frame/s]

   🔄 2000L:  89%|████████▉ | 89/100 [00:00<00:00, 172.30frame/s]

                                                                 
📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.07rig/s]
📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.07rig/s]
[✅] Saved PTDs: /working/MDC018_W044(6)_2026_05_06/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%|          | 0/3080448 [00:00<?, ?px/s]
📤 Writing LUT:   3%|▎         | 97042/3080448 [00:00<00:03, 970409.36px/s]
📤 Writing LUT:   7%|▋         | 200270/3080448 [00:00<00:02, 1006795.78px/s]
📤 Writing LUT:  10%|▉         | 300950/3080448 [00:00<00:02, 998298.21px/s] 
📤 Writing LUT:  13%|█▎        | 401383/3080448 [00:00<00:02, 1000662.96px/s]
📤 Writing LUT:  16%|█▋        | 501456/3080448 [00:00<00:02, 962896.36px/s] 
📤 Writing LUT:  19%|█▉        | 597977/3080448 [00:00<00:02, 944219.95px/s]
📤 Writing LUT:  22%|██▏       | 692574/3080448 [00:00<00:02, 923401.98px/s]
📤 Writing LUT:  25%|██▌       | 785063/3080448 [00:00<00:02, 921198.53px/s]
📤 Writing LUT:  28%|██▊       | 877278/3080448 [00:00<00:02, 904075.85px/s]
📤 Writing LUT:  31%|███▏      | 967775/3080448 [00:01<00:02, 889608.74px/s]
📤 Writing LUT:  34%|███▍      | 1059225/3080448 [00:01<00:02, 896965.34px/s]
📤 Writing LUT:  37%|███▋      | 1148995/3080448 [00:01<00:02, 893042.02px/s]
📤 Writing LUT:  40%|████      | 1238345/3080448 [00:01<00:02, 887775.38px/s]
📤 Writing LUT:  43%|████▎     | 1327152/3080448 [00:01<00:01, 883818.21px/s]
📤 Writing LUT:  46%|████▌     | 1415551/3080448 [00:01<00:01, 880323.94px/s]
📤 Writing LUT:  49%|████▉     | 1507145/3080448 [00:01<00:01, 890891.99px/s]
📤 Writing LUT:  52%|█████▏    | 1596256/3080448 [00:01<00:01, 886230.65px/s]
📤 Writing LUT:  55%|█████▍    | 1686903/3080448 [00:01<00:01, 892247.50px/s]
📤 Writing LUT:  58%|█████▊    | 1776146/3080448 [00:01<00:01, 885288.32px/s]
📤 Writing LUT:  61%|██████    | 1866796/3080448 [00:02<00:01, 891585.76px/s]
📤 Writing LUT:  64%|██████▎   | 1958097/3080448 [00:02<00:01, 897966.57px/s]
📤 Writing LUT:  66%|██████▋   | 2047914/3080448 [00:02<00:01, 893781.22px/s]
📤 Writing LUT:  69%|██████▉   | 2137309/3080448 [00:02<00:01, 889769.10px/s]
📤 Writing LUT:  72%|███████▏  | 2227601/3080448 [00:02<00:00, 893681.54px/s]
📤 Writing LUT:  75%|███████▌  | 2318749/3080448 [00:02<00:00, 898990.44px/s]
📤 Writing LUT:  78%|███████▊  | 2408660/3080448 [00:02<00:00, 897628.40px/s]
📤 Writing LUT:  81%|████████  | 2498431/3080448 [00:02<00:00, 891053.25px/s]
📤 Writing LUT:  84%|████████▍ | 2589492/3080448 [00:02<00:00, 896872.73px/s]
📤 Writing LUT:  87%|████████▋ | 2680478/3080448 [00:02<00:00, 900746.49px/s]
📤 Writing LUT:  90%|████████▉ | 2771067/3080448 [00:03<00:00, 902283.22px/s]
📤 Writing LUT:  93%|█████████▎| 2861305/3080448 [00:03<00:00, 901862.75px/s]
📤 Writing LUT:  96%|█████████▌| 2951914/3080448 [00:03<00:00, 903126.41px/s]
📤 Writing LUT:  99%|█████████▉| 3044650/3080448 [00:03<00:00, 910384.69px/s]
📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 907189.76px/s]
[✅] LUT written to: /working/MDC018_W044(6)_2026_05_06/calibration/debug/4_undistorted/output/LUT.lut
[✅] LUT copied to: /working/MDC018_W044(6)_2026_05_06/calibration/MDC018_W044(6)_unknown_2026_05_06.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%|          | 0/944 [00:00<?, ?frame/s]

   🔥 1500:   1%|          | 9/944 [00:00<00:11, 81.57frame/s]

   🔥 1500:   2%|▏         | 19/944 [00:00<00:10, 86.98frame/s]

   🔥 1500:   3%|▎         | 28/944 [00:00<00:10, 87.07frame/s]

   🔥 1500:   4%|▍         | 37/944 [00:00<00:10, 86.43frame/s]

   🔥 1500:   5%|▍         | 46/944 [00:00<00:10, 85.83frame/s]

   🔥 1500:   6%|▌         | 55/944 [00:00<00:10, 85.09frame/s]

   🔥 1500:   7%|▋         | 64/944 [00:00<00:10, 84.98frame/s]

   🔥 1500:   8%|▊         | 73/944 [00:00<00:10, 84.53frame/s]

   🔥 1500:   9%|▊         | 82/944 [00:00<00:10, 83.52frame/s]

   🔥 1500:  10%|▉         | 91/944 [00:01<00:10, 82.56frame/s]

   🔥 1500:  11%|█         | 100/944 [00:01<00:10, 81.97frame/s]

   🔥 1500:  12%|█▏        | 109/944 [00:01<00:10, 81.16frame/s]

   🔥 1500:  12%|█▎        | 118/944 [00:01<00:10, 80.54frame/s]

   🔥 1500:  13%|█▎        | 127/944 [00:01<00:10, 80.25frame/s]

   🔥 1500:  14%|█▍        | 136/944 [00:01<00:10, 79.57frame/s]

   🔥 1500:  15%|█▌        | 144/944 [00:01<00:10, 79.23frame/s]

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                                                                [✅] 1500: /working/MDC018_W044(6)_2026_05_06/calibration/debug/5_heatmap/1500_heatmap.png
[✅] 1500 (fitted): /working/MDC018_W044(6)_2026_05_06/calibration/debug/5_heatmap/1500_heatmap_fitted.png

📁 Rigs (heatmap):  25%|██▌       | 1/4 [00:12<00:38, 12.75s/rig]

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   🔥 2000R: 100%|█████████▉| 688/689 [00:07<00:00, 77.19frame/s]

                                                                 [✅] 2000R: /working/MDC018_W044(6)_2026_05_06/calibration/debug/5_heatmap/2000R_heatmap.png
[✅] 2000R (fitted): /working/MDC018_W044(6)_2026_05_06/calibration/debug/5_heatmap/2000R_heatmap_fitted.png

📁 Rigs (heatmap):  50%|█████     | 2/4 [00:22<00:21, 10.78s/rig]

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   🔥 1000:  65%|██████▍   | 388/599 [00:04<00:02, 83.12frame/s]

   🔥 1000:  66%|██████▋   | 397/599 [00:04<00:02, 82.64frame/s]

   🔥 1000:  68%|██████▊   | 406/599 [00:04<00:02, 83.09frame/s]

   🔥 1000:  69%|██████▉   | 415/599 [00:04<00:02, 82.65frame/s]

   🔥 1000:  71%|███████   | 424/599 [00:04<00:02, 83.03frame/s]

   🔥 1000:  72%|███████▏  | 433/599 [00:05<00:02, 82.31frame/s]

   🔥 1000:  74%|███████▍  | 442/599 [00:05<00:01, 82.25frame/s]

   🔥 1000:  75%|███████▌  | 451/599 [00:05<00:01, 82.61frame/s]

   🔥 1000:  77%|███████▋  | 460/599 [00:05<00:01, 82.82frame/s]

   🔥 1000:  78%|███████▊  | 469/599 [00:05<00:01, 83.09frame/s]

   🔥 1000:  80%|███████▉  | 478/599 [00:05<00:01, 83.44frame/s]

   🔥 1000:  81%|████████▏ | 487/599 [00:05<00:01, 83.43frame/s]

   🔥 1000:  83%|████████▎ | 496/599 [00:05<00:01, 83.47frame/s]

   🔥 1000:  84%|████████▍ | 505/599 [00:05<00:01, 83.56frame/s]

   🔥 1000:  86%|████████▌ | 514/599 [00:05<00:01, 83.57frame/s]

   🔥 1000:  87%|████████▋ | 523/599 [00:06<00:00, 83.86frame/s]

   🔥 1000:  89%|████████▉ | 532/599 [00:06<00:00, 84.16frame/s]

   🔥 1000:  90%|█████████ | 541/599 [00:06<00:00, 84.60frame/s]

   🔥 1000:  92%|█████████▏| 550/599 [00:06<00:00, 84.44frame/s]

   🔥 1000:  93%|█████████▎| 559/599 [00:06<00:00, 84.26frame/s]

   🔥 1000:  95%|█████████▍| 568/599 [00:06<00:00, 84.31frame/s]

   🔥 1000:  96%|█████████▋| 577/599 [00:06<00:00, 84.43frame/s]

   🔥 1000:  98%|█████████▊| 586/599 [00:06<00:00, 84.25frame/s]

   🔥 1000:  99%|█████████▉| 595/599 [00:06<00:00, 84.08frame/s]

                                                                [✅] 1000: /working/MDC018_W044(6)_2026_05_06/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDC018_W044(6)_2026_05_06/calibration/debug/5_heatmap/1000_heatmap_fitted.png

📁 Rigs (heatmap):  75%|███████▌  | 3/4 [00:29<00:09,  9.36s/rig]

   🔥 2000L:   0%|          | 0/698 [00:00<?, ?frame/s]

   🔥 2000L:   1%|          | 8/698 [00:00<00:08, 77.92frame/s]

   🔥 2000L:   2%|▏         | 16/698 [00:00<00:08, 77.38frame/s]

   🔥 2000L:   4%|▎         | 25/698 [00:00<00:08, 78.91frame/s]

   🔥 2000L:   5%|▍         | 34/698 [00:00<00:08, 82.14frame/s]

   🔥 2000L:   6%|▌         | 43/698 [00:00<00:08, 81.31frame/s]

   🔥 2000L:   7%|▋         | 52/698 [00:00<00:07, 80.84frame/s]

   🔥 2000L:   9%|▊         | 61/698 [00:00<00:08, 79.35frame/s]

   🔥 2000L:  10%|▉         | 69/698 [00:00<00:08, 78.54frame/s]

   🔥 2000L:  11%|█         | 77/698 [00:00<00:07, 77.79frame/s]

   🔥 2000L:  12%|█▏        | 85/698 [00:01<00:07, 77.11frame/s]

   🔥 2000L:  13%|█▎        | 93/698 [00:01<00:07, 77.93frame/s]

   🔥 2000L:  15%|█▍        | 102/698 [00:01<00:07, 79.24frame/s]

   🔥 2000L:  16%|█▌        | 111/698 [00:01<00:07, 80.90frame/s]

   🔥 2000L:  17%|█▋        | 120/698 [00:01<00:06, 82.96frame/s]

   🔥 2000L:  19%|█▊        | 130/698 [00:01<00:06, 85.29frame/s]

   🔥 2000L:  20%|██        | 140/698 [00:01<00:06, 88.09frame/s]

   🔥 2000L:  21%|██▏       | 150/698 [00:01<00:06, 90.26frame/s]

   🔥 2000L:  23%|██▎       | 161/698 [00:01<00:05, 94.46frame/s]

   🔥 2000L:  25%|██▍       | 172/698 [00:02<00:05, 98.24frame/s]

   🔥 2000L:  26%|██▌       | 183/698 [00:02<00:05, 100.39frame/s]

   🔥 2000L:  28%|██▊       | 195/698 [00:02<00:04, 103.60frame/s]

   🔥 2000L:  30%|██▉       | 206/698 [00:02<00:04, 104.75frame/s]

   🔥 2000L:  31%|███       | 218/698 [00:02<00:04, 107.91frame/s]

   🔥 2000L:  33%|███▎      | 230/698 [00:02<00:04, 109.17frame/s]

   🔥 2000L:  35%|███▍      | 241/698 [00:02<00:04, 108.85frame/s]

   🔥 2000L:  36%|███▌      | 252/698 [00:02<00:04, 107.93frame/s]

   🔥 2000L:  38%|███▊      | 263/698 [00:02<00:04, 106.83frame/s]

   🔥 2000L:  39%|███▉      | 274/698 [00:02<00:04, 103.94frame/s]

   🔥 2000L:  41%|████      | 285/698 [00:03<00:04, 101.49frame/s]

   🔥 2000L:  42%|████▏     | 296/698 [00:03<00:04, 99.83frame/s] 

   🔥 2000L:  44%|████▍     | 307/698 [00:03<00:03, 97.78frame/s]

   🔥 2000L:  45%|████▌     | 317/698 [00:03<00:03, 96.58frame/s]

   🔥 2000L:  47%|████▋     | 327/698 [00:03<00:03, 95.89frame/s]

   🔥 2000L:  48%|████▊     | 337/698 [00:03<00:03, 94.24frame/s]

   🔥 2000L:  50%|████▉     | 347/698 [00:03<00:03, 93.79frame/s]

   🔥 2000L:  51%|█████     | 357/698 [00:03<00:03, 92.88frame/s]

   🔥 2000L:  53%|█████▎    | 367/698 [00:03<00:03, 92.57frame/s]

   🔥 2000L:  54%|█████▍    | 377/698 [00:04<00:03, 92.58frame/s]

   🔥 2000L:  55%|█████▌    | 387/698 [00:04<00:03, 92.33frame/s]

   🔥 2000L:  57%|█████▋    | 397/698 [00:04<00:03, 92.24frame/s]

   🔥 2000L:  58%|█████▊    | 407/698 [00:04<00:03, 93.56frame/s]

   🔥 2000L:  60%|█████▉    | 417/698 [00:04<00:03, 93.46frame/s]

   🔥 2000L:  61%|██████    | 427/698 [00:04<00:02, 93.78frame/s]

   🔥 2000L:  63%|██████▎   | 437/698 [00:04<00:02, 94.26frame/s]

   🔥 2000L:  64%|██████▍   | 447/698 [00:04<00:02, 94.92frame/s]

   🔥 2000L:  65%|██████▌   | 457/698 [00:04<00:02, 96.23frame/s]

   🔥 2000L:  67%|██████▋   | 467/698 [00:05<00:02, 96.27frame/s]

   🔥 2000L:  68%|██████▊   | 478/698 [00:05<00:02, 97.58frame/s]

   🔥 2000L:  70%|██████▉   | 488/698 [00:05<00:02, 97.72frame/s]

   🔥 2000L:  71%|███████▏  | 499/698 [00:05<00:01, 99.66frame/s]

   🔥 2000L:  73%|███████▎  | 510/698 [00:05<00:01, 101.05frame/s]

   🔥 2000L:  75%|███████▍  | 521/698 [00:05<00:01, 101.34frame/s]

   🔥 2000L:  76%|███████▌  | 532/698 [00:05<00:01, 101.11frame/s]

   🔥 2000L:  78%|███████▊  | 543/698 [00:05<00:01, 101.40frame/s]

   🔥 2000L:  79%|███████▉  | 554/698 [00:05<00:01, 100.56frame/s]

   🔥 2000L:  81%|████████  | 565/698 [00:06<00:01, 98.94frame/s] 

   🔥 2000L:  82%|████████▏ | 575/698 [00:06<00:01, 96.11frame/s]

   🔥 2000L:  84%|████████▍ | 585/698 [00:06<00:01, 93.74frame/s]

   🔥 2000L:  85%|████████▌ | 595/698 [00:06<00:01, 91.36frame/s]

   🔥 2000L:  87%|████████▋ | 605/698 [00:06<00:01, 89.36frame/s]

   🔥 2000L:  88%|████████▊ | 614/698 [00:06<00:00, 87.62frame/s]

   🔥 2000L:  89%|████████▉ | 623/698 [00:06<00:00, 86.39frame/s]

   🔥 2000L:  91%|█████████ | 632/698 [00:06<00:00, 83.17frame/s]

   🔥 2000L:  92%|█████████▏| 641/698 [00:06<00:00, 83.02frame/s]

   🔥 2000L:  93%|█████████▎| 650/698 [00:07<00:00, 82.75frame/s]

   🔥 2000L:  94%|█████████▍| 659/698 [00:07<00:00, 82.39frame/s]

   🔥 2000L:  96%|█████████▌| 668/698 [00:07<00:00, 81.61frame/s]

   🔥 2000L:  97%|█████████▋| 677/698 [00:07<00:00, 81.36frame/s]

   🔥 2000L:  98%|█████████▊| 686/698 [00:07<00:00, 80.75frame/s]

   🔥 2000L: 100%|█████████▉| 695/698 [00:07<00:00, 80.75frame/s]

                                                                 [✅] 2000L: /working/MDC018_W044(6)_2026_05_06/calibration/debug/5_heatmap/2000L_heatmap.png
[✅] 2000L (fitted): /working/MDC018_W044(6)_2026_05_06/calibration/debug/5_heatmap/2000L_heatmap_fitted.png

📁 Rigs (heatmap): 100%|██████████| 4/4 [00:38<00:00,  9.27s/rig]
📁 Rigs (heatmap): 100%|██████████| 4/4 [00:38<00:00,  9.74s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDC018_W044(6)_2026_05_06/calibration/debug/5_heatmap
[🏁] Finished processing MDC018_W044(6)_2026_05_06


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