2026-05-17T22:43:05 - INFO: Slick 0.0.8a11

🟢 Starting Calibration Pipeline

=== Processing MDC045_W022(6)_2023-10-25 ===
2026-05-17T22:43:05 - INFO: Camera ID: 6393992
2026-05-17T22:43:05 - INFO: Wand ID: 
2026-05-17T22:43:05 - INFO: Recorded At: 2023-10-25T15:06:35Z

-------------------------------------------------------------------
                        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 1024 stationary frames, 182 remain


→ 2000L (182 images) Phase 1:   0%|          | 0/182 [00:00<?, ?it/s]

→ 2000L (182 images) Phase 1:   1%|          | 1/182 [00:00<01:27,  2.08it/s]

→ 2000L (182 images) Phase 1:   5%|▌         | 10/182 [00:00<00:08, 19.65it/s]

→ 2000L (182 images) Phase 1:  18%|█▊        | 33/182 [00:00<00:03, 46.03it/s]

→ 2000L (182 images) Phase 1:  21%|██▏       | 39/182 [00:01<00:03, 47.56it/s]

→ 2000L (182 images) Phase 1:  25%|██▍       | 45/182 [00:01<00:02, 47.36it/s]

→ 2000L (182 images) Phase 1:  36%|███▌      | 65/182 [00:01<00:01, 67.10it/s]

→ 2000L (182 images) Phase 1:  40%|███▉      | 72/182 [00:01<00:01, 61.38it/s]

→ 2000L (182 images) Phase 1:  43%|████▎     | 79/182 [00:01<00:01, 60.69it/s]

→ 2000L (182 images) Phase 1:  53%|█████▎    | 97/182 [00:01<00:01, 75.79it/s]

→ 2000L (182 images) Phase 1:  58%|█████▊    | 105/182 [00:01<00:01, 69.46it/s]

→ 2000L (182 images) Phase 1:  62%|██████▏   | 112/182 [00:02<00:01, 65.30it/s]

→ 2000L (182 images) Phase 1:  71%|███████   | 129/182 [00:02<00:00, 79.41it/s]

→ 2000L (182 images) Phase 1:  75%|███████▌  | 137/182 [00:02<00:00, 70.20it/s]

→ 2000L (182 images) Phase 1:  79%|███████▉  | 144/182 [00:02<00:00, 67.41it/s]

→ 2000L (182 images) Phase 1:  88%|████████▊ | 161/182 [00:02<00:00, 88.53it/s]

→ 2000L (182 images) Phase 1:  94%|█████████▍| 171/182 [00:02<00:00, 80.34it/s]

→ 2000L (182 images) Phase 1: 100%|██████████| 182/182 [00:02<00:00, 85.03it/s]

                                                                               

→ 2000L Phase 2: corners:   0%|          | 0/182 [00:00<?, ?it/s]

→ 2000L Phase 2: corners:   1%|          | 1/182 [00:00<00:33,  5.45it/s]

→ 2000L Phase 2: corners:   9%|▉         | 17/182 [00:00<00:02, 72.28it/s]

→ 2000L Phase 2: corners:  16%|█▋        | 30/182 [00:00<00:01, 92.72it/s]

→ 2000L Phase 2: corners:  25%|██▌       | 46/182 [00:00<00:01, 111.37it/s]

→ 2000L Phase 2: corners:  33%|███▎      | 60/182 [00:00<00:01, 118.91it/s]

→ 2000L Phase 2: corners:  40%|████      | 73/182 [00:00<00:00, 118.46it/s]

→ 2000L Phase 2: corners:  47%|████▋     | 86/182 [00:00<00:00, 117.84it/s]

→ 2000L Phase 2: corners:  55%|█████▌    | 101/182 [00:00<00:00, 123.43it/s]

→ 2000L Phase 2: corners:  63%|██████▎   | 114/182 [00:01<00:00, 117.29it/s]

→ 2000L Phase 2: corners:  71%|███████   | 129/182 [00:01<00:00, 126.31it/s]

→ 2000L Phase 2: corners:  80%|███████▉  | 145/182 [00:01<00:00, 132.00it/s]

→ 2000L Phase 2: corners:  88%|████████▊ | 161/182 [00:01<00:00, 137.94it/s]

→ 2000L Phase 2: corners: 100%|██████████| 182/182 [00:01<00:00, 156.37it/s]

                                                                            [PASS2] Frame 0000738: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000743: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000744: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000961: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000962: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000963: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000964: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000980: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000981: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000982: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000983: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000984: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000743: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000963: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000982: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000743: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Summary: 7 frames fixed, 6 untrusted, 182 total


→ 2000L Phase 3: finalize:   0%|          | 0/182 [00:00<?, ?it/s]

→ 2000L Phase 3: finalize:   3%|▎         | 5/182 [00:00<00:03, 47.47it/s]

→ 2000L Phase 3: finalize:   6%|▌         | 11/182 [00:00<00:03, 50.27it/s]

→ 2000L Phase 3: finalize:   9%|▉         | 17/182 [00:00<00:03, 51.34it/s]

→ 2000L Phase 3: finalize:  13%|█▎        | 23/182 [00:00<00:03, 51.91it/s]

→ 2000L Phase 3: finalize:  16%|█▌        | 29/182 [00:00<00:02, 52.04it/s]

→ 2000L Phase 3: finalize:  19%|█▉        | 35/182 [00:00<00:02, 52.06it/s]

→ 2000L Phase 3: finalize:  23%|██▎       | 41/182 [00:00<00:02, 52.21it/s]

→ 2000L Phase 3: finalize:  26%|██▌       | 47/182 [00:00<00:02, 51.65it/s]

→ 2000L Phase 3: finalize:  29%|██▉       | 53/182 [00:01<00:02, 51.29it/s]

→ 2000L Phase 3: finalize:  32%|███▏      | 59/182 [00:01<00:02, 51.09it/s]

→ 2000L Phase 3: finalize:  36%|███▌      | 65/182 [00:01<00:02, 51.23it/s]

→ 2000L Phase 3: finalize:  39%|███▉      | 71/182 [00:01<00:02, 50.95it/s]

→ 2000L Phase 3: finalize:  42%|████▏     | 77/182 [00:01<00:02, 50.83it/s]

→ 2000L Phase 3: finalize:  46%|████▌     | 83/182 [00:01<00:01, 50.69it/s]

→ 2000L Phase 3: finalize:  49%|████▉     | 89/182 [00:01<00:01, 50.83it/s]

→ 2000L Phase 3: finalize:  52%|█████▏    | 95/182 [00:01<00:01, 51.50it/s]

→ 2000L Phase 3: finalize:  55%|█████▌    | 101/182 [00:01<00:01, 51.83it/s]

→ 2000L Phase 3: finalize:  59%|█████▉    | 107/182 [00:02<00:01, 52.01it/s]

→ 2000L Phase 3: finalize:  62%|██████▏   | 113/182 [00:02<00:01, 52.17it/s]

→ 2000L Phase 3: finalize:  65%|██████▌   | 119/182 [00:02<00:01, 52.19it/s]

→ 2000L Phase 3: finalize:  69%|██████▊   | 125/182 [00:02<00:01, 52.32it/s]

→ 2000L Phase 3: finalize:  72%|███████▏  | 131/182 [00:02<00:00, 52.81it/s]

→ 2000L Phase 3: finalize:  75%|███████▌  | 137/182 [00:02<00:00, 53.46it/s]

→ 2000L Phase 3: finalize:  79%|███████▊  | 143/182 [00:02<00:00, 53.87it/s]

→ 2000L Phase 3: finalize:  82%|████████▏ | 149/182 [00:02<00:00, 54.37it/s]

→ 2000L Phase 3: finalize:  85%|████████▌ | 155/182 [00:02<00:00, 54.63it/s]

→ 2000L Phase 3: finalize:  88%|████████▊ | 161/182 [00:03<00:00, 54.74it/s]

→ 2000L Phase 3: finalize:  92%|█████████▏| 167/182 [00:03<00:00, 54.33it/s]

→ 2000L Phase 3: finalize:  95%|█████████▌| 173/182 [00:03<00:00, 53.80it/s]

→ 2000L Phase 3: finalize:  98%|█████████▊| 179/182 [00:03<00:00, 53.15it/s]

                                                                            
[TIMING] 2000L — 182 frames
  Phase 1  radial detect   (parallel)  :   2.98s  (16.4 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.52s  (8.4 ms/frame)
  Phase 2b corner fix      (sequential):   0.32s
  Phase 3  finalize        (sequential):   3.48s  (19.1 ms/frame)
    decode + undistort                 :   1.82s  (10.0 ms/frame)
    corner apply + refinement          :   0.78s  (4.3 ms/frame)
    segment                            :   0.71s  (3.9 ms/frame)
    smooth                             :   0.11s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   8.30s


Processing Rigs:  25%|██▌       | 1/4 [00:13<00:40, 13.52s/it][INFO] Filtered 1064 stationary frames, 217 remain


→ 1500 (217 images) Phase 1:   0%|          | 0/217 [00:00<?, ?it/s]

→ 1500 (217 images) Phase 1:   0%|          | 1/217 [00:00<02:06,  1.71it/s]

→ 1500 (217 images) Phase 1:  15%|█▌        | 33/217 [00:00<00:04, 45.47it/s]

→ 1500 (217 images) Phase 1:  18%|█▊        | 40/217 [00:01<00:03, 46.61it/s]

→ 1500 (217 images) Phase 1:  28%|██▊       | 60/217 [00:01<00:02, 74.49it/s]

→ 1500 (217 images) Phase 1:  33%|███▎      | 72/217 [00:01<00:02, 56.34it/s]

→ 1500 (217 images) Phase 1:  42%|████▏     | 92/217 [00:01<00:01, 79.72it/s]

→ 1500 (217 images) Phase 1:  48%|████▊     | 105/217 [00:01<00:01, 59.71it/s]

→ 1500 (217 images) Phase 1:  59%|█████▊    | 127/217 [00:02<00:01, 77.54it/s]

→ 1500 (217 images) Phase 1:  64%|██████▎   | 138/217 [00:02<00:01, 63.27it/s]

→ 1500 (217 images) Phase 1:  73%|███████▎  | 159/217 [00:02<00:00, 80.19it/s]

→ 1500 (217 images) Phase 1:  78%|███████▊  | 170/217 [00:02<00:00, 64.54it/s]

→ 1500 (217 images) Phase 1:  88%|████████▊ | 191/217 [00:02<00:00, 84.41it/s]

→ 1500 (217 images) Phase 1:  94%|█████████▎| 203/217 [00:03<00:00, 73.92it/s]

                                                                              

→ 1500 Phase 2: corners:   0%|          | 0/217 [00:00<?, ?it/s]

→ 1500 Phase 2: corners:   0%|          | 1/217 [00:00<00:36,  5.95it/s]

→ 1500 Phase 2: corners:   6%|▌         | 12/217 [00:00<00:03, 52.60it/s]

→ 1500 Phase 2: corners:  12%|█▏        | 25/217 [00:00<00:02, 82.84it/s]

→ 1500 Phase 2: corners:  17%|█▋        | 37/217 [00:00<00:01, 96.11it/s]

→ 1500 Phase 2: corners:  24%|██▎       | 51/217 [00:00<00:01, 110.29it/s]

→ 1500 Phase 2: corners:  30%|███       | 66/217 [00:00<00:01, 120.09it/s]

→ 1500 Phase 2: corners:  37%|███▋      | 80/217 [00:00<00:01, 124.16it/s]

→ 1500 Phase 2: corners:  43%|████▎     | 93/217 [00:00<00:01, 120.98it/s]

→ 1500 Phase 2: corners:  49%|████▉     | 107/217 [00:01<00:00, 125.46it/s]

→ 1500 Phase 2: corners:  56%|█████▌    | 121/217 [00:01<00:00, 129.10it/s]

→ 1500 Phase 2: corners:  62%|██████▏   | 135/217 [00:01<00:00, 115.17it/s]

→ 1500 Phase 2: corners:  69%|██████▊   | 149/217 [00:01<00:00, 120.68it/s]

→ 1500 Phase 2: corners:  76%|███████▌  | 165/217 [00:01<00:00, 129.60it/s]

→ 1500 Phase 2: corners:  82%|████████▏ | 179/217 [00:01<00:00, 130.15it/s]

→ 1500 Phase 2: corners: 100%|██████████| 217/217 [00:01<00:00, 199.93it/s]

                                                                           [PASS2] Summary: 0 frames fixed, 1 untrusted, 217 total


→ 1500 Phase 3: finalize:   0%|          | 0/217 [00:00<?, ?it/s]

→ 1500 Phase 3: finalize:   3%|▎         | 6/217 [00:00<00:03, 58.67it/s]

→ 1500 Phase 3: finalize:   6%|▌         | 12/217 [00:00<00:03, 55.19it/s]

→ 1500 Phase 3: finalize:   8%|▊         | 18/217 [00:00<00:03, 55.17it/s]

→ 1500 Phase 3: finalize:  11%|█         | 24/217 [00:00<00:03, 55.19it/s]

→ 1500 Phase 3: finalize:  14%|█▍        | 30/217 [00:00<00:03, 55.21it/s]

→ 1500 Phase 3: finalize:  17%|█▋        | 36/217 [00:00<00:03, 55.24it/s]

→ 1500 Phase 3: finalize:  19%|█▉        | 42/217 [00:00<00:03, 55.19it/s]

→ 1500 Phase 3: finalize:  22%|██▏       | 48/217 [00:00<00:03, 55.17it/s]

→ 1500 Phase 3: finalize:  25%|██▍       | 54/217 [00:00<00:02, 55.15it/s]

→ 1500 Phase 3: finalize:  28%|██▊       | 60/217 [00:01<00:02, 55.06it/s]

→ 1500 Phase 3: finalize:  30%|███       | 66/217 [00:01<00:02, 54.93it/s]

→ 1500 Phase 3: finalize:  33%|███▎      | 72/217 [00:01<00:02, 54.76it/s]

→ 1500 Phase 3: finalize:  36%|███▌      | 78/217 [00:01<00:02, 54.40it/s]

→ 1500 Phase 3: finalize:  39%|███▊      | 84/217 [00:01<00:02, 54.29it/s]

→ 1500 Phase 3: finalize:  41%|████▏     | 90/217 [00:01<00:02, 54.24it/s]

→ 1500 Phase 3: finalize:  44%|████▍     | 96/217 [00:01<00:02, 54.18it/s]

→ 1500 Phase 3: finalize:  47%|████▋     | 102/217 [00:01<00:02, 54.13it/s]

→ 1500 Phase 3: finalize:  50%|████▉     | 108/217 [00:01<00:02, 54.16it/s]

→ 1500 Phase 3: finalize:  53%|█████▎    | 114/217 [00:02<00:01, 54.15it/s]

→ 1500 Phase 3: finalize:  55%|█████▌    | 120/217 [00:02<00:01, 53.90it/s]

→ 1500 Phase 3: finalize:  58%|█████▊    | 126/217 [00:02<00:01, 53.48it/s]

→ 1500 Phase 3: finalize:  61%|██████    | 132/217 [00:02<00:01, 53.58it/s]

→ 1500 Phase 3: finalize:  64%|██████▎   | 138/217 [00:02<00:01, 53.70it/s]

→ 1500 Phase 3: finalize:  66%|██████▋   | 144/217 [00:02<00:01, 53.86it/s]

→ 1500 Phase 3: finalize:  69%|██████▉   | 150/217 [00:02<00:01, 54.03it/s]

→ 1500 Phase 3: finalize:  72%|███████▏  | 156/217 [00:02<00:01, 54.36it/s]

→ 1500 Phase 3: finalize:  75%|███████▍  | 162/217 [00:02<00:01, 54.59it/s]

→ 1500 Phase 3: finalize:  77%|███████▋  | 168/217 [00:03<00:00, 54.82it/s]

→ 1500 Phase 3: finalize:  80%|████████  | 174/217 [00:03<00:00, 54.82it/s]

→ 1500 Phase 3: finalize:  83%|████████▎ | 180/217 [00:03<00:00, 54.98it/s]

→ 1500 Phase 3: finalize:  86%|████████▌ | 186/217 [00:03<00:00, 55.08it/s]

→ 1500 Phase 3: finalize:  88%|████████▊ | 192/217 [00:03<00:00, 55.04it/s]

→ 1500 Phase 3: finalize:  91%|█████████ | 198/217 [00:03<00:00, 55.10it/s]

→ 1500 Phase 3: finalize:  94%|█████████▍| 204/217 [00:03<00:00, 54.99it/s]

→ 1500 Phase 3: finalize:  97%|█████████▋| 210/217 [00:03<00:00, 54.75it/s]

→ 1500 Phase 3: finalize: 100%|█████████▉| 216/217 [00:03<00:00, 54.78it/s]

                                                                           
[TIMING] 1500 — 217 frames
  Phase 1  radial detect   (parallel)  :   3.31s  (15.2 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.73s  (8.0 ms/frame)
  Phase 2b corner fix      (sequential):   0.04s
  Phase 3  finalize        (sequential):   3.97s  (18.3 ms/frame)
    decode + undistort                 :   2.15s  (9.9 ms/frame)
    corner apply + refinement          :   0.79s  (3.7 ms/frame)
    segment                            :   0.84s  (3.9 ms/frame)
    smooth                             :   0.12s  (0.5 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   9.06s


Processing Rigs:  50%|█████     | 2/4 [00:26<00:26, 13.20s/it][INFO] Filtered 904 stationary frames, 177 remain


→ 2000R (177 images) Phase 1:   0%|          | 0/177 [00:00<?, ?it/s]

→ 2000R (177 images) Phase 1:   1%|          | 1/177 [00:00<01:35,  1.85it/s]

→ 2000R (177 images) Phase 1:  11%|█▏        | 20/177 [00:00<00:03, 40.80it/s]

→ 2000R (177 images) Phase 1:  19%|█▊        | 33/177 [00:00<00:03, 41.22it/s]

→ 2000R (177 images) Phase 1:  24%|██▎       | 42/177 [00:01<00:02, 49.53it/s]

→ 2000R (177 images) Phase 1:  37%|███▋      | 65/177 [00:01<00:01, 59.17it/s]

→ 2000R (177 images) Phase 1:  41%|████      | 73/177 [00:01<00:01, 62.29it/s]

→ 2000R (177 images) Phase 1:  55%|█████▍    | 97/177 [00:01<00:01, 65.77it/s]

→ 2000R (177 images) Phase 1:  59%|█████▉    | 105/177 [00:01<00:01, 67.54it/s]

→ 2000R (177 images) Phase 1:  73%|███████▎  | 129/177 [00:02<00:00, 69.57it/s]

→ 2000R (177 images) Phase 1:  77%|███████▋  | 137/177 [00:02<00:00, 69.24it/s]

→ 2000R (177 images) Phase 1:  91%|█████████ | 161/177 [00:02<00:00, 86.12it/s]

→ 2000R (177 images) Phase 1:  98%|█████████▊| 173/177 [00:02<00:00, 87.97it/s]

                                                                               

→ 2000R Phase 2: corners:   0%|          | 0/177 [00:00<?, ?it/s]

→ 2000R Phase 2: corners:   1%|          | 1/177 [00:00<00:41,  4.27it/s]

→ 2000R Phase 2: corners:  10%|▉         | 17/177 [00:00<00:02, 62.60it/s]

→ 2000R Phase 2: corners:  16%|█▋        | 29/177 [00:00<00:01, 79.37it/s]

→ 2000R Phase 2: corners:  24%|██▎       | 42/177 [00:00<00:01, 94.85it/s]

→ 2000R Phase 2: corners:  32%|███▏      | 56/177 [00:00<00:01, 106.82it/s]

→ 2000R Phase 2: corners:  40%|███▉      | 70/177 [00:00<00:00, 113.84it/s]

→ 2000R Phase 2: corners:  47%|████▋     | 83/177 [00:00<00:00, 117.66it/s]

→ 2000R Phase 2: corners:  54%|█████▍    | 96/177 [00:00<00:00, 115.66it/s]

→ 2000R Phase 2: corners:  63%|██████▎   | 112/177 [00:01<00:00, 125.35it/s]

→ 2000R Phase 2: corners:  71%|███████   | 125/177 [00:01<00:00, 123.35it/s]

→ 2000R Phase 2: corners:  78%|███████▊  | 138/177 [00:01<00:00, 118.73it/s]

→ 2000R Phase 2: corners:  85%|████████▌ | 151/177 [00:01<00:00, 109.41it/s]

→ 2000R Phase 2: corners:  97%|█████████▋| 172/177 [00:01<00:00, 135.71it/s]

                                                                            [PASS2] Frame 0000299: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000440: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000441: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000442: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000446: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000447: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000448: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000449: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000450: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000451: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000452: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000465: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000441: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000448: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000450: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000451: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000465: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000465: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Summary: 7 frames fixed, 6 untrusted, 177 total


→ 2000R Phase 3: finalize:   0%|          | 0/177 [00:00<?, ?it/s]

→ 2000R Phase 3: finalize:   3%|▎         | 5/177 [00:00<00:03, 49.61it/s]

→ 2000R Phase 3: finalize:   6%|▌         | 11/177 [00:00<00:03, 51.91it/s]

→ 2000R Phase 3: finalize:  10%|▉         | 17/177 [00:00<00:03, 52.73it/s]

→ 2000R Phase 3: finalize:  13%|█▎        | 23/177 [00:00<00:02, 53.49it/s]

→ 2000R Phase 3: finalize:  16%|█▋        | 29/177 [00:00<00:02, 53.36it/s]

→ 2000R Phase 3: finalize:  20%|█▉        | 35/177 [00:00<00:02, 53.17it/s]

→ 2000R Phase 3: finalize:  23%|██▎       | 41/177 [00:00<00:02, 53.24it/s]

→ 2000R Phase 3: finalize:  27%|██▋       | 47/177 [00:00<00:02, 52.97it/s]

→ 2000R Phase 3: finalize:  30%|██▉       | 53/177 [00:01<00:02, 52.78it/s]

→ 2000R Phase 3: finalize:  33%|███▎      | 59/177 [00:01<00:02, 52.50it/s]

→ 2000R Phase 3: finalize:  37%|███▋      | 65/177 [00:01<00:02, 52.45it/s]

→ 2000R Phase 3: finalize:  40%|████      | 71/177 [00:01<00:02, 52.38it/s]

→ 2000R Phase 3: finalize:  44%|████▎     | 77/177 [00:01<00:01, 52.22it/s]

→ 2000R Phase 3: finalize:  47%|████▋     | 83/177 [00:01<00:01, 51.91it/s]

→ 2000R Phase 3: finalize:  50%|█████     | 89/177 [00:01<00:01, 50.49it/s]

→ 2000R Phase 3: finalize:  54%|█████▎    | 95/177 [00:01<00:01, 50.95it/s]

→ 2000R Phase 3: finalize:  57%|█████▋    | 101/177 [00:01<00:01, 51.18it/s]

→ 2000R Phase 3: finalize:  60%|██████    | 107/177 [00:02<00:01, 51.31it/s]

→ 2000R Phase 3: finalize:  64%|██████▍   | 113/177 [00:02<00:01, 51.63it/s]

→ 2000R Phase 3: finalize:  67%|██████▋   | 119/177 [00:02<00:01, 51.89it/s]

→ 2000R Phase 3: finalize:  71%|███████   | 125/177 [00:02<00:00, 52.05it/s]

→ 2000R Phase 3: finalize:  74%|███████▍  | 131/177 [00:02<00:00, 51.91it/s]

→ 2000R Phase 3: finalize:  77%|███████▋  | 137/177 [00:02<00:00, 52.12it/s]

→ 2000R Phase 3: finalize:  81%|████████  | 143/177 [00:02<00:00, 52.19it/s]

→ 2000R Phase 3: finalize:  84%|████████▍ | 149/177 [00:02<00:00, 52.22it/s]

→ 2000R Phase 3: finalize:  88%|████████▊ | 155/177 [00:02<00:00, 52.16it/s]

→ 2000R Phase 3: finalize:  91%|█████████ | 161/177 [00:03<00:00, 52.14it/s]

→ 2000R Phase 3: finalize:  94%|█████████▍| 167/177 [00:03<00:00, 52.35it/s]

→ 2000R Phase 3: finalize:  98%|█████████▊| 173/177 [00:03<00:00, 52.49it/s]

                                                                            
[TIMING] 2000R — 177 frames
  Phase 1  radial detect   (parallel)  :   2.82s  (15.9 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.65s  (9.3 ms/frame)
  Phase 2b corner fix      (sequential):   0.36s
  Phase 3  finalize        (sequential):   3.39s  (19.2 ms/frame)
    decode + undistort                 :   1.78s  (10.0 ms/frame)
    corner apply + refinement          :   0.75s  (4.3 ms/frame)
    segment                            :   0.70s  (3.9 ms/frame)
    smooth                             :   0.10s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   8.22s


Processing Rigs:  75%|███████▌  | 3/4 [00:38<00:12, 12.43s/it][INFO] Filtered 745 stationary frames, 152 remain


→ 1000 (152 images) Phase 1:   0%|          | 0/152 [00:00<?, ?it/s]

→ 1000 (152 images) Phase 1:   1%|          | 1/152 [00:00<01:28,  1.70it/s]

→ 1000 (152 images) Phase 1:  21%|██        | 32/152 [00:00<00:01, 60.33it/s]

→ 1000 (152 images) Phase 1:  32%|███▏      | 49/152 [00:01<00:01, 51.73it/s]

→ 1000 (152 images) Phase 1:  43%|████▎     | 65/152 [00:01<00:01, 54.16it/s]

→ 1000 (152 images) Phase 1:  49%|████▊     | 74/152 [00:01<00:01, 56.41it/s]

→ 1000 (152 images) Phase 1:  62%|██████▏   | 94/152 [00:01<00:00, 80.23it/s]

→ 1000 (152 images) Phase 1:  70%|██████▉   | 106/152 [00:01<00:00, 59.82it/s]

→ 1000 (152 images) Phase 1:  84%|████████▎ | 127/152 [00:02<00:00, 81.79it/s]

→ 1000 (152 images) Phase 1:  92%|█████████▏| 140/152 [00:02<00:00, 69.53it/s]

                                                                              

→ 1000 Phase 2: corners:   0%|          | 0/152 [00:00<?, ?it/s]

→ 1000 Phase 2: corners:   1%|          | 1/152 [00:00<00:35,  4.31it/s]

→ 1000 Phase 2: corners:  12%|█▏        | 18/152 [00:00<00:01, 67.41it/s]

→ 1000 Phase 2: corners:  21%|██        | 32/152 [00:00<00:01, 91.55it/s]

→ 1000 Phase 2: corners:  30%|██▉       | 45/152 [00:00<00:01, 102.16it/s]

→ 1000 Phase 2: corners:  38%|███▊      | 57/152 [00:00<00:00, 106.54it/s]

→ 1000 Phase 2: corners:  48%|████▊     | 73/152 [00:00<00:00, 117.21it/s]

→ 1000 Phase 2: corners:  57%|█████▋    | 86/152 [00:00<00:00, 120.25it/s]

→ 1000 Phase 2: corners:  67%|██████▋   | 102/152 [00:00<00:00, 125.92it/s]

→ 1000 Phase 2: corners:  76%|███████▋  | 116/152 [00:01<00:00, 126.53it/s]

→ 1000 Phase 2: corners:  87%|████████▋ | 132/152 [00:01<00:00, 131.97it/s]

→ 1000 Phase 2: corners:  97%|█████████▋| 148/152 [00:01<00:00, 138.70it/s]

                                                                           [PASS2] Summary: 0 frames fixed, 0 untrusted, 152 total


→ 1000 Phase 3: finalize:   0%|          | 0/152 [00:00<?, ?it/s]

→ 1000 Phase 3: finalize:   4%|▍         | 6/152 [00:00<00:02, 55.95it/s]

→ 1000 Phase 3: finalize:   8%|▊         | 12/152 [00:00<00:02, 56.02it/s]

→ 1000 Phase 3: finalize:  12%|█▏        | 18/152 [00:00<00:02, 55.95it/s]

→ 1000 Phase 3: finalize:  16%|█▌        | 24/152 [00:00<00:02, 56.13it/s]

→ 1000 Phase 3: finalize:  20%|█▉        | 30/152 [00:00<00:02, 56.14it/s]

→ 1000 Phase 3: finalize:  24%|██▎       | 36/152 [00:00<00:02, 56.09it/s]

→ 1000 Phase 3: finalize:  28%|██▊       | 42/152 [00:00<00:01, 56.19it/s]

→ 1000 Phase 3: finalize:  32%|███▏      | 48/152 [00:00<00:01, 56.12it/s]

→ 1000 Phase 3: finalize:  36%|███▌      | 54/152 [00:00<00:01, 55.80it/s]

→ 1000 Phase 3: finalize:  39%|███▉      | 60/152 [00:01<00:01, 55.71it/s]

→ 1000 Phase 3: finalize:  43%|████▎     | 66/152 [00:01<00:01, 55.60it/s]

→ 1000 Phase 3: finalize:  47%|████▋     | 72/152 [00:01<00:01, 55.18it/s]

→ 1000 Phase 3: finalize:  51%|█████▏    | 78/152 [00:01<00:01, 55.27it/s]

→ 1000 Phase 3: finalize:  55%|█████▌    | 84/152 [00:01<00:01, 55.31it/s]

→ 1000 Phase 3: finalize:  59%|█████▉    | 90/152 [00:01<00:01, 54.91it/s]

→ 1000 Phase 3: finalize:  63%|██████▎   | 96/152 [00:01<00:01, 54.98it/s]

→ 1000 Phase 3: finalize:  67%|██████▋   | 102/152 [00:01<00:00, 54.85it/s]

→ 1000 Phase 3: finalize:  71%|███████   | 108/152 [00:01<00:00, 55.19it/s]

→ 1000 Phase 3: finalize:  75%|███████▌  | 114/152 [00:02<00:00, 55.53it/s]

→ 1000 Phase 3: finalize:  79%|███████▉  | 120/152 [00:02<00:00, 55.85it/s]

→ 1000 Phase 3: finalize:  83%|████████▎ | 126/152 [00:02<00:00, 56.13it/s]

→ 1000 Phase 3: finalize:  87%|████████▋ | 132/152 [00:02<00:00, 56.29it/s]

→ 1000 Phase 3: finalize:  91%|█████████ | 138/152 [00:02<00:00, 56.46it/s]

→ 1000 Phase 3: finalize:  95%|█████████▍| 144/152 [00:02<00:00, 56.52it/s]

→ 1000 Phase 3: finalize:  99%|█████████▊| 150/152 [00:02<00:00, 56.64it/s]

                                                                           
[TIMING] 1000 — 152 frames
  Phase 1  radial detect   (parallel)  :   2.48s  (16.3 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.40s  (9.2 ms/frame)
  Phase 2b corner fix      (sequential):   0.03s
  Phase 3  finalize        (sequential):   2.72s  (17.9 ms/frame)
    decode + undistort                 :   1.52s  (10.0 ms/frame)
    corner apply + refinement          :   0.50s  (3.3 ms/frame)
    segment                            :   0.57s  (3.8 ms/frame)
    smooth                             :   0.08s  (0.5 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   6.63s


Processing Rigs: 100%|██████████| 4/4 [00:47<00:00, 11.22s/it]
Processing Rigs: 100%|██████████| 4/4 [00:47<00:00, 11.85s/it]
[💾] Saved RigFrameDataset to /working/MDC045_W022(6)_2023-10-25/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 728 frames from 4 rigs to /working/MDC045_W022(6)_2023-10-25/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC045_W022(6)_2023-10-25/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 2000L: 100 frames selected from 182
[📋] 1500: 100 frames selected from 217
[📋] 2000R: 100 frames selected from 177
[📋] 1000: 100 frames selected from 152
[💾] Saved RigFrameDataset to /working/MDC045_W022(6)_2023-10-25/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC045_W022(6)_2023-10-25/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<04:22,  3.32s/it]
Computing max image from bright frames:   2%|▎         | 2/80 [00:06<04:16,  3.29s/it]
Computing max image from bright frames:   4%|▍         | 3/80 [00:09<04:11,  3.27s/it]
Computing max image from bright frames:   5%|▌         | 4/80 [00:13<04:07,  3.26s/it]
Computing max image from bright frames:   6%|▋         | 5/80 [00:16<04:04,  3.26s/it]
Computing max image from bright frames:   8%|▊         | 6/80 [00:19<04:01,  3.26s/it]
Computing max image from bright frames:   9%|▉         | 7/80 [00:22<03:58,  3.27s/it]
Computing max image from bright frames:  10%|█         | 8/80 [00:26<03:55,  3.27s/it]
Computing max image from bright frames:  11%|█▏        | 9/80 [00:29<03:51,  3.26s/it]
Computing max image from bright frames:  12%|█▎        | 10/80 [00:32<03:47,  3.25s/it]
Computing max image from bright frames:  14%|█▍        | 11/80 [00:35<03:43,  3.24s/it]
Computing max image from bright frames:  15%|█▌        | 12/80 [00:39<03:40,  3.24s/it]
Computing max image from bright frames:  16%|█▋        | 13/80 [00:42<03:37,  3.24s/it]
Computing max image from bright frames:  18%|█▊        | 14/80 [00:45<03:34,  3.25s/it]
Computing max image from bright frames:  19%|█▉        | 15/80 [00:48<03:31,  3.25s/it]
Computing max image from bright frames:  20%|██        | 16/80 [00:52<03:27,  3.25s/it]
Computing max image from bright frames:  21%|██▏       | 17/80 [00:55<03:24,  3.25s/it]
Computing max image from bright frames:  22%|██▎       | 18/80 [00:58<03:21,  3.25s/it]
Computing max image from bright frames:  24%|██▍       | 19/80 [01:01<03:18,  3.25s/it]
Computing max image from bright frames:  25%|██▌       | 20/80 [01:03<02:43,  2.73s/it]
Computing max image from bright frames:  26%|██▋       | 21/80 [01:06<02:50,  2.89s/it]
Computing max image from bright frames:  28%|██▊       | 22/80 [01:09<02:53,  2.99s/it]
Computing max image from bright frames:  29%|██▉       | 23/80 [01:13<02:55,  3.08s/it]
Computing max image from bright frames:  30%|███       | 24/80 [01:16<02:55,  3.14s/it]
Computing max image from bright frames:  31%|███▏      | 25/80 [01:19<02:54,  3.18s/it]
Computing max image from bright frames:  32%|███▎      | 26/80 [01:22<02:53,  3.21s/it]
Computing max image from bright frames:  34%|███▍      | 27/80 [01:26<02:50,  3.22s/it]
Computing max image from bright frames:  35%|███▌      | 28/80 [01:29<02:48,  3.24s/it]
Computing max image from bright frames:  36%|███▋      | 29/80 [01:32<02:45,  3.25s/it]
Computing max image from bright frames:  38%|███▊      | 30/80 [01:36<02:42,  3.25s/it]
Computing max image from bright frames:  39%|███▉      | 31/80 [01:39<02:39,  3.25s/it]
Computing max image from bright frames:  40%|████      | 32/80 [01:42<02:36,  3.26s/it]
Computing max image from bright frames:  41%|████▏     | 33/80 [01:45<02:33,  3.26s/it]
Computing max image from bright frames:  42%|████▎     | 34/80 [01:49<02:30,  3.27s/it]
Computing max image from bright frames:  44%|████▍     | 35/80 [01:52<02:27,  3.27s/it]
Computing max image from bright frames:  45%|████▌     | 36/80 [01:55<02:23,  3.27s/it]
Computing max image from bright frames:  46%|████▋     | 37/80 [01:58<02:20,  3.27s/it]
Computing max image from bright frames:  48%|████▊     | 38/80 [02:02<02:17,  3.27s/it]
Computing max image from bright frames:  49%|████▉     | 39/80 [02:05<02:14,  3.28s/it]
Computing max image from bright frames:  50%|█████     | 40/80 [02:08<02:10,  3.26s/it]
Computing max image from bright frames:  51%|█████▏    | 41/80 [02:11<02:07,  3.26s/it]
Computing max image from bright frames:  52%|█████▎    | 42/80 [02:15<02:03,  3.26s/it]
Computing max image from bright frames:  54%|█████▍    | 43/80 [02:18<02:00,  3.25s/it]
Computing max image from bright frames:  55%|█████▌    | 44/80 [02:21<01:57,  3.25s/it]
Computing max image from bright frames:  56%|█████▋    | 45/80 [02:24<01:53,  3.26s/it]
Computing max image from bright frames:  57%|█████▊    | 46/80 [02:28<01:50,  3.26s/it]
Computing max image from bright frames:  59%|█████▉    | 47/80 [02:31<01:47,  3.25s/it]
Computing max image from bright frames:  60%|██████    | 48/80 [02:34<01:44,  3.25s/it]
Computing max image from bright frames:  61%|██████▏   | 49/80 [02:37<01:40,  3.25s/it]
Computing max image from bright frames:  62%|██████▎   | 50/80 [02:41<01:37,  3.24s/it]
Computing max image from bright frames:  64%|██████▍   | 51/80 [02:44<01:33,  3.24s/it]
Computing max image from bright frames:  65%|██████▌   | 52/80 [02:47<01:30,  3.24s/it]
Computing max image from bright frames:  66%|██████▋   | 53/80 [02:50<01:27,  3.23s/it]
Computing max image from bright frames:  68%|██████▊   | 54/80 [02:54<01:24,  3.24s/it]
Computing max image from bright frames:  69%|██████▉   | 55/80 [02:57<01:20,  3.24s/it]
Computing max image from bright frames:  70%|███████   | 56/80 [03:00<01:17,  3.23s/it]
Computing max image from bright frames:  71%|███████▏  | 57/80 [03:03<01:14,  3.24s/it]
Computing max image from bright frames:  72%|███████▎  | 58/80 [03:07<01:11,  3.24s/it]
Computing max image from bright frames:  74%|███████▍  | 59/80 [03:10<01:08,  3.24s/it]
Computing max image from bright frames:  75%|███████▌  | 60/80 [03:12<00:59,  2.96s/it]
Computing max image from bright frames:  76%|███████▋  | 61/80 [03:15<00:57,  3.05s/it]
Computing max image from bright frames:  78%|███████▊  | 62/80 [03:19<00:56,  3.11s/it]
Computing max image from bright frames:  79%|███████▉  | 63/80 [03:22<00:53,  3.16s/it]
Computing max image from bright frames:  80%|████████  | 64/80 [03:25<00:51,  3.19s/it]
Computing max image from bright frames:  81%|████████▏ | 65/80 [03:28<00:48,  3.22s/it]
Computing max image from bright frames:  82%|████████▎ | 66/80 [03:32<00:45,  3.23s/it]
Computing max image from bright frames:  84%|████████▍ | 67/80 [03:35<00:42,  3.24s/it]
Computing max image from bright frames:  85%|████████▌ | 68/80 [03:38<00:38,  3.24s/it]
Computing max image from bright frames:  86%|████████▋ | 69/80 [03:42<00:35,  3.25s/it]
Computing max image from bright frames:  88%|████████▊ | 70/80 [03:45<00:32,  3.26s/it]
Computing max image from bright frames:  89%|████████▉ | 71/80 [03:48<00:29,  3.26s/it]
Computing max image from bright frames:  90%|█████████ | 72/80 [03:51<00:26,  3.26s/it]
Computing max image from bright frames:  91%|█████████▏| 73/80 [03:55<00:22,  3.27s/it]
Computing max image from bright frames:  92%|█████████▎| 74/80 [03:58<00:19,  3.27s/it]
Computing max image from bright frames:  94%|█████████▍| 75/80 [04:01<00:16,  3.27s/it]
Computing max image from bright frames:  95%|█████████▌| 76/80 [04:04<00:13,  3.26s/it]
Computing max image from bright frames:  96%|█████████▋| 77/80 [04:08<00:09,  3.27s/it]
Computing max image from bright frames:  98%|█████████▊| 78/80 [04:11<00:06,  3.27s/it]
Computing max image from bright frames:  99%|█████████▉| 79/80 [04:14<00:03,  3.26s/it]
Computing max image from bright frames: 100%|██████████| 80/80 [04:17<00:00,  3.27s/it]
                                                                                       
[✅] Casing detection complete: cx=983.0, cy=769.0

-------------------------------------------------------------------
                        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,  3.93it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:25,  3.93it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   2%|▏         | 2/100 [00:00<00:24,  3.93it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   3%|▎         | 3/100 [00:00<00:24,  3.93it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   4%|▍         | 4/100 [00:00<00:08, 11.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   4%|▍         | 4/100 [00:00<00:08, 11.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 335.354} (0.000):   5%|▌         | 5/100 [00:00<00:08, 11.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   6%|▌         | 6/100 [00:00<00:08, 11.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 349.495} (0.000):   7%|▋         | 7/100 [00:00<00:08, 11.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   8%|▊         | 8/100 [00:00<00:07, 11.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   9%|▉         | 9/100 [00:00<00:04, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 363.636} (0.001):   9%|▉         | 9/100 [00:00<00:04, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.002 | Best: {'fx': 370.707} (0.002):  10%|█         | 10/100 [00:00<00:04, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.002 | Best: {'fx': 377.778} (0.002):  11%|█         | 11/100 [00:00<00:04, 22.05it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.002 | Best: {'fx': 377.778} (0.002):  12%|█▏        | 12/100 [00:00<00:03, 22.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.003 | Best: {'fx': 384.848} (0.003):  12%|█▏        | 12/100 [00:00<00:03, 22.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 391.919} (0.004):  13%|█▎        | 13/100 [00:00<00:03, 22.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.005 | Best: {'fx': 406.061} (0.005):  14%|█▍        | 14/100 [00:00<00:03, 22.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 406.061} (0.005):  15%|█▌        | 15/100 [00:00<00:03, 22.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 406.061} (0.005):  16%|█▌        | 16/100 [00:00<00:03, 25.85it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  16%|█▌        | 16/100 [00:00<00:03, 25.85it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.006 | Best: {'fx': 420.202} (0.006):  17%|█▋        | 17/100 [00:00<00:03, 25.85it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.007 | Best: {'fx': 434.343} (0.007):  18%|█▊        | 18/100 [00:00<00:03, 25.85it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.007 | Best: {'fx': 434.343} (0.007):  19%|█▉        | 19/100 [00:00<00:03, 25.83it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.006 | Best: {'fx': 434.343} (0.007):  19%|█▉        | 19/100 [00:00<00:03, 25.83it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.010 | Best: {'fx': 448.485} (0.010):  20%|██        | 20/100 [00:00<00:03, 25.83it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.008 | Best: {'fx': 448.485} (0.010):  21%|██        | 21/100 [00:01<00:03, 25.83it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.008 | Best: {'fx': 448.485} (0.010):  22%|██▏       | 22/100 [00:01<00:03, 24.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.012 | Best: {'fx': 455.556} (0.012):  22%|██▏       | 22/100 [00:01<00:03, 24.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 483.838} (0.025):  23%|██▎       | 23/100 [00:01<00:03, 24.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.014 | Best: {'fx': 483.838} (0.025):  24%|██▍       | 24/100 [00:01<00:03, 24.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.016 | Best: {'fx': 483.838} (0.025):  25%|██▌       | 25/100 [00:01<00:03, 24.44it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.016 | Best: {'fx': 483.838} (0.025):  26%|██▌       | 26/100 [00:01<00:02, 26.88it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.030 | Best: {'fx': 490.909} (0.030):  26%|██▌       | 26/100 [00:01<00:02, 26.88it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 490.909} (0.030):  27%|██▋       | 27/100 [00:01<00:02, 26.88it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.036 | Best: {'fx': 497.98} (0.036):  28%|██▊       | 28/100 [00:01<00:02, 26.88it/s] 
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.046 | Best: {'fx': 505.051} (0.046):  29%|██▉       | 29/100 [00:01<00:02, 26.88it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.055 | Best: {'fx': 512.121} (0.055):  30%|███       | 30/100 [00:01<00:02, 26.88it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.055 | Best: {'fx': 512.121} (0.055):  31%|███       | 31/100 [00:01<00:02, 29.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.070 | Best: {'fx': 519.192} (0.070):  31%|███       | 31/100 [00:01<00:02, 29.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.087 | Best: {'fx': 526.263} (0.087):  32%|███▏      | 32/100 [00:01<00:02, 29.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.088 | Best: {'fx': 533.333} (0.088):  33%|███▎      | 33/100 [00:01<00:02, 29.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.078 | Best: {'fx': 533.333} (0.088):  34%|███▍      | 34/100 [00:01<00:02, 29.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.078 | Best: {'fx': 533.333} (0.088):  35%|███▌      | 35/100 [00:01<00:03, 20.57it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.058 | Best: {'fx': 533.333} (0.088):  35%|███▌      | 35/100 [00:01<00:03, 20.57it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.043 | Best: {'fx': 533.333} (0.088):  36%|███▌      | 36/100 [00:01<00:03, 20.57it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.040 | Best: {'fx': 533.333} (0.088):  37%|███▋      | 37/100 [00:01<00:03, 20.57it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.040 | Best: {'fx': 533.333} (0.088):  38%|███▊      | 38/100 [00:01<00:02, 21.03it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.046 | Best: {'fx': 533.333} (0.088):  38%|███▊      | 38/100 [00:01<00:02, 21.03it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.036 | Best: {'fx': 533.333} (0.088):  39%|███▉      | 39/100 [00:01<00:02, 21.03it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.066 | Best: {'fx': 533.333} (0.088):  40%|████      | 40/100 [00:01<00:02, 21.03it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.051 | Best: {'fx': 533.333} (0.088):  41%|████      | 41/100 [00:01<00:02, 21.03it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.051 | Best: {'fx': 533.333} (0.088):  42%|████▏     | 42/100 [00:01<00:02, 24.63it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.035 | Best: {'fx': 533.333} (0.088):  42%|████▏     | 42/100 [00:01<00:02, 24.63it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.038 | Best: {'fx': 533.333} (0.088):  43%|████▎     | 43/100 [00:01<00:02, 24.63it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.029 | Best: {'fx': 533.333} (0.088):  44%|████▍     | 44/100 [00:01<00:02, 24.63it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.029 | Best: {'fx': 533.333} (0.088):  45%|████▌     | 45/100 [00:01<00:02, 24.25it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.032 | Best: {'fx': 533.333} (0.088):  45%|████▌     | 45/100 [00:01<00:02, 24.25it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.033 | Best: {'fx': 533.333} (0.088):  46%|████▌     | 46/100 [00:01<00:02, 24.25it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.028 | Best: {'fx': 533.333} (0.088):  47%|████▋     | 47/100 [00:02<00:02, 24.25it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.030 | Best: {'fx': 533.333} (0.088):  48%|████▊     | 48/100 [00:02<00:02, 24.25it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.026 | Best: {'fx': 533.333} (0.088):  49%|████▉     | 49/100 [00:02<00:02, 24.25it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.026 | Best: {'fx': 533.333} (0.088):  50%|█████     | 50/100 [00:02<00:01, 30.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.088):  50%|█████     | 50/100 [00:02<00:01, 30.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.029 | Best: {'fx': 533.333} (0.088):  51%|█████     | 51/100 [00:02<00:01, 30.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.027 | Best: {'fx': 533.333} (0.088):  52%|█████▏    | 52/100 [00:02<00:01, 30.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 533.333} (0.088):  53%|█████▎    | 53/100 [00:02<00:01, 30.11it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 533.333} (0.088):  54%|█████▍    | 54/100 [00:02<00:01, 31.57it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.026 | Best: {'fx': 533.333} (0.088):  54%|█████▍    | 54/100 [00:02<00:01, 31.57it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 533.333} (0.088):  55%|█████▌    | 55/100 [00:02<00:01, 31.57it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.088):  56%|█████▌    | 56/100 [00:02<00:01, 31.57it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.088):  57%|█████▋    | 57/100 [00:02<00:01, 31.57it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.088):  58%|█████▊    | 58/100 [00:02<00:01, 31.57it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.088):  59%|█████▉    | 59/100 [00:02<00:01, 36.17it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.088):  59%|█████▉    | 59/100 [00:02<00:01, 36.17it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.088):  60%|██████    | 60/100 [00:02<00:01, 36.17it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.088):  61%|██████    | 61/100 [00:02<00:01, 36.17it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.088):  62%|██████▏   | 62/100 [00:02<00:01, 36.17it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.088):  63%|██████▎   | 63/100 [00:02<00:01, 36.38it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.088):  63%|██████▎   | 63/100 [00:02<00:01, 36.38it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.088):  64%|██████▍   | 64/100 [00:02<00:00, 36.38it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.088):  65%|██████▌   | 65/100 [00:02<00:00, 36.38it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.088):  66%|██████▌   | 66/100 [00:02<00:00, 36.38it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.088):  67%|██████▋   | 67/100 [00:02<00:00, 36.38it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.088):  68%|██████▊   | 68/100 [00:02<00:00, 36.38it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.088):  69%|██████▉   | 69/100 [00:02<00:00, 36.38it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.088):  70%|███████   | 70/100 [00:02<00:00, 36.38it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  71%|███████   | 71/100 [00:02<00:00, 36.38it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  72%|███████▏  | 72/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  72%|███████▏  | 72/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  73%|███████▎  | 73/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.088):  74%|███████▍  | 74/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  75%|███████▌  | 75/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  76%|███████▌  | 76/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  77%|███████▋  | 77/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  78%|███████▊  | 78/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.088):  79%|███████▉  | 79/100 [00:02<00:00, 42.62it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.088):  80%|████████  | 80/100 [00:02<00:00, 46.93it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  80%|████████  | 80/100 [00:02<00:00, 46.93it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  81%|████████  | 81/100 [00:02<00:00, 46.93it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  82%|████████▏ | 82/100 [00:02<00:00, 46.93it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  83%|████████▎ | 83/100 [00:02<00:00, 46.93it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  84%|████████▍ | 84/100 [00:02<00:00, 46.93it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  85%|████████▌ | 85/100 [00:02<00:00, 40.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.088):  85%|████████▌ | 85/100 [00:02<00:00, 40.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  86%|████████▌ | 86/100 [00:02<00:00, 40.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  87%|████████▋ | 87/100 [00:03<00:00, 40.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  88%|████████▊ | 88/100 [00:03<00:00, 40.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  89%|████████▉ | 89/100 [00:03<00:00, 40.08it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  90%|█████████ | 90/100 [00:03<00:00, 36.74it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  90%|█████████ | 90/100 [00:03<00:00, 36.74it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  91%|█████████ | 91/100 [00:03<00:00, 36.74it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  92%|█████████▏| 92/100 [00:03<00:00, 36.74it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  93%|█████████▎| 93/100 [00:03<00:00, 36.74it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  94%|█████████▍| 94/100 [00:03<00:00, 35.39it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.088):  94%|█████████▍| 94/100 [00:03<00:00, 35.39it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  95%|█████████▌| 95/100 [00:03<00:00, 35.39it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  96%|█████████▌| 96/100 [00:03<00:00, 35.39it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.088):  97%|█████████▋| 97/100 [00:03<00:00, 35.39it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  98%|█████████▊| 98/100 [00:03<00:00, 35.39it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  99%|█████████▉| 99/100 [00:03<00:00, 37.23it/s]
Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.088):  99%|█████████▉| 99/100 [00:03<00:00, 37.23it/s]
                                                                                                                                       

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.051 | Best: {'fx': 509.354} (0.051):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.051 | Best: {'fx': 509.354} (0.051):   2%|▏         | 1/50 [00:00<00:24,  1.96it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.053 | Best: {'fx': 510.374} (0.053):   2%|▏         | 1/50 [00:00<00:24,  1.96it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.050 | Best: {'fx': 510.374} (0.053):   4%|▍         | 2/50 [00:00<00:24,  1.96it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.056 | Best: {'fx': 512.415} (0.056):   6%|▌         | 3/50 [00:00<00:23,  1.96it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.056 | Best: {'fx': 512.415} (0.056):   8%|▊         | 4/50 [00:00<00:06,  7.54it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.058 | Best: {'fx': 513.435} (0.058):   8%|▊         | 4/50 [00:00<00:06,  7.54it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.055 | Best: {'fx': 513.435} (0.058):  10%|█         | 5/50 [00:00<00:05,  7.54it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.059 | Best: {'fx': 514.456} (0.059):  12%|█▏        | 6/50 [00:00<00:05,  7.54it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.061 | Best: {'fx': 515.476} (0.061):  14%|█▍        | 7/50 [00:00<00:05,  7.54it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.061 | Best: {'fx': 515.476} (0.061):  16%|█▌        | 8/50 [00:00<00:02, 14.53it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.065 | Best: {'fx': 517.517} (0.065):  16%|█▌        | 8/50 [00:00<00:02, 14.53it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.063 | Best: {'fx': 517.517} (0.065):  18%|█▊        | 9/50 [00:00<00:02, 14.53it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.068 | Best: {'fx': 518.537} (0.068):  20%|██        | 10/50 [00:00<00:02, 14.53it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.068 | Best: {'fx': 518.537} (0.068):  22%|██▏       | 11/50 [00:00<00:02, 16.41it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.071 | Best: {'fx': 519.558} (0.071):  22%|██▏       | 11/50 [00:00<00:02, 16.41it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.075 | Best: {'fx': 521.599} (0.075):  24%|██▍       | 12/50 [00:00<00:02, 16.41it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.073 | Best: {'fx': 521.599} (0.075):  26%|██▌       | 13/50 [00:01<00:02, 16.41it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.073 | Best: {'fx': 521.599} (0.075):  28%|██▊       | 14/50 [00:01<00:01, 19.57it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.077 | Best: {'fx': 522.619} (0.077):  28%|██▊       | 14/50 [00:01<00:01, 19.57it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.080 | Best: {'fx': 523.639} (0.080):  30%|███       | 15/50 [00:01<00:01, 19.57it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.084 | Best: {'fx': 525.68} (0.084):  32%|███▏      | 16/50 [00:01<00:01, 19.57it/s] 
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.084 | Best: {'fx': 525.68} (0.084):  34%|███▍      | 17/50 [00:01<00:01, 16.96it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.091 | Best: {'fx': 528.741} (0.091):  34%|███▍      | 17/50 [00:01<00:01, 16.96it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.089 | Best: {'fx': 528.741} (0.091):  36%|███▌      | 18/50 [00:01<00:01, 16.96it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.081 | Best: {'fx': 528.741} (0.091):  38%|███▊      | 19/50 [00:01<00:01, 16.96it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.081 | Best: {'fx': 528.741} (0.091):  40%|████      | 20/50 [00:01<00:01, 19.63it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.089 | Best: {'fx': 528.741} (0.091):  40%|████      | 20/50 [00:01<00:01, 19.63it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.091 | Best: {'fx': 528.741} (0.091):  42%|████▏     | 21/50 [00:01<00:01, 19.63it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.090 | Best: {'fx': 528.741} (0.091):  44%|████▍     | 22/50 [00:01<00:01, 19.63it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.087 | Best: {'fx': 528.741} (0.091):  46%|████▌     | 23/50 [00:01<00:01, 19.63it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.088 | Best: {'fx': 528.741} (0.091):  48%|████▊     | 24/50 [00:01<00:01, 19.63it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.084 | Best: {'fx': 528.741} (0.091):  50%|█████     | 25/50 [00:01<00:01, 19.63it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.084 | Best: {'fx': 528.741} (0.091):  52%|█████▏    | 26/50 [00:01<00:01, 22.74it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.077 | Best: {'fx': 528.741} (0.091):  52%|█████▏    | 26/50 [00:01<00:01, 22.74it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.072 | Best: {'fx': 528.741} (0.091):  54%|█████▍    | 27/50 [00:01<00:01, 22.74it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.084 | Best: {'fx': 528.741} (0.091):  56%|█████▌    | 28/50 [00:01<00:00, 22.74it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.084 | Best: {'fx': 528.741} (0.091):  58%|█████▊    | 29/50 [00:01<00:00, 22.74it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.080 | Best: {'fx': 528.741} (0.091):  60%|██████    | 30/50 [00:01<00:00, 22.74it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.088 | Best: {'fx': 528.741} (0.091):  62%|██████▏   | 31/50 [00:01<00:00, 22.74it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.074 | Best: {'fx': 528.741} (0.091):  64%|██████▍   | 32/50 [00:01<00:00, 22.74it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.068 | Best: {'fx': 528.741} (0.091):  66%|██████▌   | 33/50 [00:01<00:00, 22.74it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.068 | Best: {'fx': 528.741} (0.091):  68%|██████▊   | 34/50 [00:01<00:00, 31.62it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.083 | Best: {'fx': 528.741} (0.091):  68%|██████▊   | 34/50 [00:01<00:00, 31.62it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.065 | Best: {'fx': 528.741} (0.091):  70%|███████   | 35/50 [00:01<00:00, 31.62it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.066 | Best: {'fx': 528.741} (0.091):  72%|███████▏  | 36/50 [00:01<00:00, 31.62it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.081 | Best: {'fx': 528.741} (0.091):  74%|███████▍  | 37/50 [00:01<00:00, 31.62it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.070 | Best: {'fx': 528.741} (0.091):  76%|███████▌  | 38/50 [00:01<00:00, 31.62it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.070 | Best: {'fx': 528.741} (0.091):  78%|███████▊  | 39/50 [00:01<00:00, 31.62it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.066 | Best: {'fx': 528.741} (0.091):  80%|████████  | 40/50 [00:01<00:00, 31.62it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.061 | Best: {'fx': 528.741} (0.091):  82%|████████▏ | 41/50 [00:01<00:00, 31.62it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.063 | Best: {'fx': 528.741} (0.091):  84%|████████▍ | 42/50 [00:01<00:00, 31.62it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.063 | Best: {'fx': 528.741} (0.091):  86%|████████▌ | 43/50 [00:01<00:00, 42.38it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.061 | Best: {'fx': 528.741} (0.091):  86%|████████▌ | 43/50 [00:01<00:00, 42.38it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.058 | Best: {'fx': 528.741} (0.091):  88%|████████▊ | 44/50 [00:01<00:00, 42.38it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.060 | Best: {'fx': 528.741} (0.091):  90%|█████████ | 45/50 [00:01<00:00, 42.38it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.057 | Best: {'fx': 528.741} (0.091):  92%|█████████▏| 46/50 [00:01<00:00, 42.38it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.055 | Best: {'fx': 528.741} (0.091):  94%|█████████▍| 47/50 [00:01<00:00, 42.38it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.055 | Best: {'fx': 528.741} (0.091):  96%|█████████▌| 48/50 [00:01<00:00, 42.71it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.057 | Best: {'fx': 528.741} (0.091):  96%|█████████▌| 48/50 [00:01<00:00, 42.71it/s]
Brute | Start: {'fx': 533.333} (0.088) | Current: 0.054 | Best: {'fx': 528.741} (0.091):  98%|█████████▊| 49/50 [00:01<00:00, 42.71it/s]
                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 528.7414965986395
    px: 983.0
    py: 769.0
    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: 2000L(2000mm):20/20, 1500(1500mm):20/20, 2000R(2000mm):20/20, 1000(1000mm):20/20
  Total: 80/80 frames used for optimization

Initial score: 42.9254: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 42.9254, picklable_objective(x0) = 42.9396

Best score: 42.9396: : 0iter [00:01, ?iter/s] 
Best score: 42.9396: : 1iter [00:01,  1.98s/iter]
Best score: 42.9396: : 1iter [00:02,  1.98s/iter]
Best score: 42.9396: : 2iter [00:02,  1.98s/iter]
Best score: 42.9396: : 3iter [00:02,  1.73iter/s]
Best score: 42.9396: : 3iter [00:02,  1.73iter/s]
Best score: 42.9396: : 4iter [00:02,  1.73iter/s]
Best score: 42.9396: : 5iter [00:02,  3.08iter/s]
Best score: 42.9396: : 5iter [00:02,  3.08iter/s]
Best score: 42.9396: : 6iter [00:02,  3.08iter/s]
Best score: 42.9396: : 7iter [00:02,  4.48iter/s]
Best score: 42.9396: : 7iter [00:02,  4.48iter/s]
Best score: 42.9396: : 8iter [00:02,  4.48iter/s]
Best score: 42.9396: : 9iter [00:02,  5.84iter/s]
Best score: 42.9396: : 9iter [00:02,  5.84iter/s]
Best score: 42.9396: : 10iter [00:02,  5.84iter/s]
Best score: 42.9396: : 11iter [00:02,  7.03iter/s]
Best score: 42.9396: : 11iter [00:02,  7.03iter/s]
Best score: 42.9396: : 12iter [00:03,  7.03iter/s]
Best score: 42.9396: : 13iter [00:03,  8.10iter/s]
Best score: 42.9396: : 13iter [00:03,  8.10iter/s]
Best score: 42.9396: : 14iter [00:03,  8.10iter/s]
Best score: 42.9396: : 15iter [00:03,  8.99iter/s]
Best score: 42.9396: : 15iter [00:03,  8.99iter/s]
Best score: 42.9396: : 16iter [00:03,  8.99iter/s]
Best score: 42.9396: : 17iter [00:03,  9.67iter/s]
Best score: 42.9396: : 17iter [00:03,  9.67iter/s]
Best score: 42.9396: : 18iter [00:03,  9.67iter/s]
Best score: 42.9396: : 19iter [00:03, 10.23iter/s]
Best score: 42.9396: : 19iter [00:03, 10.23iter/s]
Best score: 42.9396: : 20iter [00:03, 10.23iter/s]
Best score: 42.9396: : 21iter [00:03, 10.53iter/s]
Best score: 42.9396: : 21iter [00:03, 10.53iter/s]
Best score: 42.9396: : 22iter [00:03, 10.53iter/s]
Best score: 42.9396: : 23iter [00:03, 10.90iter/s]
Best score: 42.9396: : 23iter [00:03, 10.90iter/s]
Best score: 42.9396: : 24iter [00:04, 10.90iter/s]
Best score: 42.9396: : 25iter [00:04, 11.14iter/s]
Best score: 42.9396: : 25iter [00:04, 11.14iter/s]
Best score: 42.9396: : 26iter [00:04, 11.14iter/s]
Best score: 42.9396: : 27iter [00:04, 11.32iter/s]
Best score: 42.9396: : 27iter [00:04, 11.32iter/s]
Best score: 42.9396: : 28iter [00:04, 11.32iter/s]
Best score: 42.9396: : 29iter [00:04, 11.43iter/s]
Best score: 42.9396: : 29iter [00:04, 11.43iter/s]
Best score: 42.9396: : 30iter [00:04, 11.43iter/s]
Best score: 42.9396: : 31iter [00:04, 11.36iter/s]
Best score: 42.9396: : 31iter [00:04, 11.36iter/s]
Best score: 42.9396: : 32iter [00:04, 11.36iter/s]
Best score: 42.9396: : 33iter [00:04, 11.45iter/s]
Best score: 42.9396: : 33iter [00:04, 11.45iter/s]
Best score: 42.9396: : 34iter [00:04, 11.45iter/s]
Best score: 42.9396: : 35iter [00:04, 11.56iter/s]
Best score: 42.9396: : 35iter [00:04, 11.56iter/s]
Best score: 42.9396: : 36iter [00:05, 11.56iter/s]
Best score: 42.9396: : 37iter [00:05, 11.66iter/s]
Best score: 42.9396: : 37iter [00:05, 11.66iter/s]
Best score: 42.9396: : 38iter [00:05, 11.66iter/s]
Best score: 42.9396: : 39iter [00:05, 11.73iter/s]
Best score: 42.9396: : 39iter [00:05, 11.73iter/s]
Best score: 42.9396: : 40iter [00:05, 11.73iter/s]
Best score: 42.9396: : 41iter [00:05, 11.57iter/s]
Best score: 42.9396: : 41iter [00:05, 11.57iter/s]
Best score: 42.9396: : 42iter [00:05, 11.57iter/s]
Best score: 42.9396: : 43iter [00:05, 11.57iter/s]
Best score: 42.9396: : 43iter [00:05, 11.57iter/s]
Best score: 42.9396: : 44iter [00:05, 11.57iter/s]
Best score: 42.9396: : 45iter [00:05, 11.62iter/s]
Best score: 42.9396: : 45iter [00:05, 11.62iter/s]
Best score: 42.9396: : 46iter [00:05, 11.62iter/s]
Best score: 42.9396: : 47iter [00:05, 11.65iter/s]
Best score: 42.9396: : 47iter [00:06, 11.65iter/s]
Best score: 42.9396: : 48iter [00:06, 11.65iter/s]
Best score: 42.9396: : 49iter [00:06, 11.70iter/s]
[ITER 50] Best: 42.9396
[PARAMS] Current best parameters:
  fx: 528.7415
  fy: 528.7415
  px: 983.0000
  py: 769.0000
  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: 42.9396: : 49iter [00:06, 11.70iter/s]
Best score: 42.9396: : 50iter [00:06, 11.70iter/s]
Best score: 42.9396: : 51iter [00:06, 11.57iter/s]
Best score: 42.9396: : 51iter [00:06, 11.57iter/s]
Best score: 42.9396: : 52iter [00:06, 11.57iter/s]
Best score: 42.9396: : 53iter [00:06, 11.69iter/s]
Best score: 42.9396: : 53iter [00:06, 11.69iter/s]
Best score: 42.9396: : 54iter [00:06, 11.69iter/s]
Best score: 42.9396: : 55iter [00:06, 11.76iter/s]
Best score: 42.9396: : 55iter [00:06, 11.76iter/s]
Best score: 42.9396: : 56iter [00:06, 11.76iter/s]
Best score: 42.9396: : 57iter [00:06, 11.83iter/s]
Best score: 42.9396: : 57iter [00:06, 11.83iter/s]
Best score: 42.9396: : 58iter [00:06, 11.83iter/s]
Best score: 42.9396: : 59iter [00:06, 11.78iter/s]
Best score: 42.9396: : 59iter [00:07, 11.78iter/s]
Best score: 42.9396: : 60iter [00:07, 11.78iter/s]
Best score: 42.9396: : 61iter [00:07, 11.63iter/s]
Best score: 42.9396: : 61iter [00:07, 11.63iter/s]
Best score: 42.9396: : 62iter [00:07, 11.63iter/s]
Best score: 42.9396: : 63iter [00:07, 11.73iter/s]
Best score: 42.9396: : 63iter [00:07, 11.73iter/s]
Best score: 42.9396: : 64iter [00:07, 11.73iter/s]
Best score: 42.9396: : 65iter [00:07, 11.80iter/s]
Best score: 42.9396: : 65iter [00:07, 11.80iter/s]
Best score: 42.9396: : 66iter [00:07, 11.80iter/s]
Best score: 42.9396: : 67iter [00:07, 11.84iter/s]
Best score: 42.9396: : 67iter [00:07, 11.84iter/s]
Best score: 42.9396: : 68iter [00:07, 11.84iter/s]
Best score: 42.9396: : 69iter [00:07, 11.80iter/s]
Best score: 42.9396: : 69iter [00:07, 11.80iter/s]
Best score: 42.9396: : 70iter [00:07, 11.80iter/s]
Best score: 42.9396: : 71iter [00:07, 11.67iter/s]
Best score: 42.9396: : 71iter [00:08, 11.67iter/s]
Best score: 42.9396: : 72iter [00:08, 11.67iter/s]
Best score: 42.9396: : 73iter [00:08, 11.73iter/s]
Best score: 42.9396: : 73iter [00:08, 11.73iter/s]
Best score: 42.9396: : 74iter [00:08, 11.73iter/s]
Best score: 42.9396: : 75iter [00:08, 11.83iter/s]
Best score: 42.9396: : 75iter [00:08, 11.83iter/s]
Best score: 42.9396: : 76iter [00:08, 11.83iter/s]
Best score: 42.9396: : 77iter [00:08, 11.86iter/s]
Best score: 42.9396: : 77iter [00:08, 11.86iter/s]
Best score: 42.9396: : 78iter [00:08, 11.86iter/s]
Best score: 42.9396: : 79iter [00:08, 11.88iter/s]
Best score: 25.0879: : 79iter [00:08, 11.88iter/s]
Best score: 25.0879: : 80iter [00:08, 11.88iter/s]
Best score: 25.0879: : 81iter [00:08, 11.73iter/s]
Best score: 25.0879: : 81iter [00:08, 11.73iter/s]
Best score: 25.0879: : 82iter [00:08, 11.73iter/s]
Best score: 25.0879: : 83iter [00:08, 11.82iter/s]
Best score: 25.0879: : 83iter [00:09, 11.82iter/s]
Best score: 25.0879: : 84iter [00:09, 11.82iter/s]
Best score: 25.0879: : 85iter [00:09, 11.85iter/s]
Best score: 25.0879: : 85iter [00:09, 11.85iter/s]
Best score: 25.0879: : 86iter [00:09, 11.85iter/s]
Best score: 25.0879: : 87iter [00:09, 11.91iter/s]
Best score: 25.0879: : 87iter [00:09, 11.91iter/s]
Best score: 25.0879: : 88iter [00:09, 11.91iter/s]
Best score: 25.0879: : 89iter [00:09, 11.89iter/s]
Best score: 18.1540: : 89iter [00:09, 11.89iter/s]
Best score: 18.1540: : 90iter [00:09, 11.89iter/s]
Best score: 18.1540: : 91iter [00:09, 11.72iter/s]
Best score: 18.1540: : 91iter [00:09, 11.72iter/s]
Best score: 18.1540: : 92iter [00:09, 11.72iter/s]
Best score: 18.1540: : 93iter [00:09, 11.76iter/s]
Best score: 18.1540: : 93iter [00:09, 11.76iter/s]
Best score: 18.1540: : 94iter [00:10, 11.76iter/s]
Best score: 18.1540: : 95iter [00:10, 11.84iter/s]
Best score: 18.1540: : 95iter [00:10, 11.84iter/s]
Best score: 18.1540: : 96iter [00:10, 11.84iter/s]
Best score: 18.1540: : 97iter [00:10, 11.90iter/s]
Best score: 18.1540: : 97iter [00:10, 11.90iter/s]
Best score: 18.1540: : 98iter [00:10, 11.90iter/s]
Best score: 18.1540: : 99iter [00:10, 11.92iter/s]
[ITER 100] Best: 10.7180
[PARAMS] Current best parameters:
  fx: 538.6763
  fy: 538.1780
  px: 980.1999
  py: 775.4893
  k1: -0.12292714
  k2: 0.07698137
  k3: 0.00967080
  k4: -0.01043823
  p1: 0.00831866
  p2: 0.01285692
  p3: 0.00167929
  p4: -0.01233503
  s1: -0.0454
  s2: 0.0253
  s3: -0.0078
  s4: 0.0227
  tilt_x: -0.0400
  tilt_y: 0.0396
  scale: 3.2242
  rotation: 0.7224

Best score: 10.7180: : 99iter [00:10, 11.92iter/s]
Best score: 10.7180: : 100iter [00:10, 11.92iter/s]
Best score: 10.7180: : 101iter [00:10, 10.19iter/s]
Best score: 10.7180: : 101iter [00:10, 10.19iter/s]
Best score: 10.7180: : 102iter [00:10, 10.19iter/s]
Best score: 10.7180: : 103iter [00:10, 10.58iter/s]
Best score: 10.7180: : 103iter [00:10, 10.58iter/s]
Best score: 10.7180: : 104iter [00:10, 10.58iter/s]
Best score: 10.7180: : 105iter [00:10, 10.86iter/s]
Best score: 10.7180: : 105iter [00:11, 10.86iter/s]
Best score: 10.7180: : 106iter [00:11, 10.86iter/s]
Best score: 10.7180: : 107iter [00:11, 11.12iter/s]
Best score: 10.7180: : 107iter [00:11, 11.12iter/s]
Best score: 10.7180: : 108iter [00:11, 11.12iter/s]
Best score: 10.7180: : 109iter [00:11, 11.31iter/s]
Best score: 10.7180: : 109iter [00:11, 11.31iter/s]
Best score: 10.7180: : 110iter [00:11, 11.31iter/s]
Best score: 10.7180: : 111iter [00:11, 11.24iter/s]
Best score: 10.7180: : 111iter [00:11, 11.24iter/s]
Best score: 10.7180: : 112iter [00:11, 11.24iter/s]
Best score: 10.7180: : 113iter [00:11, 11.41iter/s]
Best score: 10.7180: : 113iter [00:11, 11.41iter/s]
Best score: 10.7180: : 114iter [00:11, 11.41iter/s]
Best score: 10.7180: : 115iter [00:11, 11.49iter/s]
Best score: 10.7180: : 115iter [00:11, 11.49iter/s]
Best score: 10.7180: : 116iter [00:11, 11.49iter/s]
Best score: 10.7180: : 117iter [00:11, 11.56iter/s]
Best score: 10.7180: : 117iter [00:12, 11.56iter/s]
Best score: 10.7180: : 118iter [00:12, 11.56iter/s]
Best score: 10.7180: : 119iter [00:12, 11.60iter/s]
Best score: 10.7180: : 119iter [00:12, 11.60iter/s]
Best score: 10.7180: : 120iter [00:12, 11.60iter/s]
Best score: 10.7180: : 121iter [00:12, 11.43iter/s]
Best score: 10.7180: : 121iter [00:12, 11.43iter/s]
Best score: 10.7180: : 122iter [00:12, 11.43iter/s]
Best score: 10.7180: : 123iter [00:12, 11.53iter/s]
Best score: 10.7180: : 123iter [00:12, 11.53iter/s]
Best score: 10.7180: : 124iter [00:12, 11.53iter/s]
Best score: 10.7180: : 125iter [00:12, 11.61iter/s]
Best score: 10.7180: : 125iter [00:12, 11.61iter/s]
Best score: 10.7180: : 126iter [00:12, 11.61iter/s]
Best score: 10.7180: : 127iter [00:12, 11.62iter/s]
Best score: 10.7180: : 127iter [00:12, 11.62iter/s]
Best score: 10.7180: : 128iter [00:13, 11.62iter/s]
Best score: 10.7180: : 129iter [00:13, 11.65iter/s]
Best score: 10.7180: : 129iter [00:13, 11.65iter/s]
Best score: 10.7180: : 130iter [00:13, 11.65iter/s]
Best score: 10.7180: : 131iter [00:13, 11.45iter/s]
Best score: 10.7180: : 131iter [00:13, 11.45iter/s]
Best score: 10.7180: : 132iter [00:13, 11.45iter/s]
Best score: 10.7180: : 133iter [00:13, 11.52iter/s]
Best score: 10.7180: : 133iter [00:13, 11.52iter/s]
Best score: 10.7180: : 134iter [00:13, 11.52iter/s]
Best score: 10.7180: : 135iter [00:13, 11.60iter/s]
Best score: 10.7180: : 135iter [00:13, 11.60iter/s]
Best score: 10.7180: : 136iter [00:13, 11.60iter/s]
Best score: 10.7180: : 137iter [00:13, 11.63iter/s]
Best score: 10.7180: : 137iter [00:13, 11.63iter/s]
Best score: 10.7180: : 138iter [00:13, 11.63iter/s]
Best score: 10.7180: : 139iter [00:13, 11.70iter/s]
Best score: 10.7180: : 139iter [00:13, 11.70iter/s]
Best score: 10.7180: : 140iter [00:14, 11.70iter/s]
Best score: 10.7180: : 141iter [00:14, 11.54iter/s]
Best score: 10.7180: : 141iter [00:14, 11.54iter/s]
Best score: 10.7180: : 142iter [00:14, 11.54iter/s]
Best score: 10.7180: : 143iter [00:14, 11.60iter/s]
Best score: 10.7180: : 143iter [00:14, 11.60iter/s]
Best score: 10.7180: : 144iter [00:14, 11.60iter/s]
Best score: 10.7180: : 145iter [00:14, 11.63iter/s]
Best score: 10.7180: : 145iter [00:14, 11.63iter/s]
Best score: 10.7180: : 146iter [00:14, 11.63iter/s]
Best score: 10.7180: : 147iter [00:14, 11.69iter/s]
Best score: 10.7180: : 147iter [00:14, 11.69iter/s]
Best score: 10.7180: : 148iter [00:14, 11.69iter/s]
Best score: 10.7180: : 149iter [00:14, 11.70iter/s]
[ITER 150] Best: 10.7180
[PARAMS] Current best parameters:
  fx: 538.6763
  fy: 538.1780
  px: 980.1999
  py: 775.4893
  k1: -0.12292714
  k2: 0.07698137
  k3: 0.00967080
  k4: -0.01043823
  p1: 0.00831866
  p2: 0.01285692
  p3: 0.00167929
  p4: -0.01233503
  s1: -0.0454
  s2: 0.0253
  s3: -0.0078
  s4: 0.0227
  tilt_x: -0.0400
  tilt_y: 0.0396
  scale: 3.2242
  rotation: 0.7224

Best score: 10.7180: : 149iter [00:14, 11.70iter/s]
Best score: 10.7180: : 150iter [00:15, 11.70iter/s]
Best score: 10.7180: : 151iter [00:15,  7.56iter/s]
Best score: 10.7180: : 151iter [00:15,  7.56iter/s]
Best score: 10.7180: : 152iter [00:15,  7.56iter/s]
Best score: 10.7180: : 153iter [00:15,  8.49iter/s]
Best score: 10.7180: : 153iter [00:15,  8.49iter/s]
Best score: 10.7180: : 154iter [00:15,  8.49iter/s]
Best score: 10.7180: : 155iter [00:15,  9.28iter/s]
Best score: 10.7180: : 155iter [00:15,  9.28iter/s]
Best score: 10.7180: : 156iter [00:15,  9.28iter/s]
Best score: 10.7180: : 157iter [00:15,  9.95iter/s]
Best score: 10.7180: : 157iter [00:15,  9.95iter/s]
Best score: 10.7180: : 158iter [00:15,  9.95iter/s]
Best score: 10.7180: : 159iter [00:15, 10.44iter/s]
Best score: 10.7180: : 159iter [00:15, 10.44iter/s]
Best score: 10.7180: : 160iter [00:16, 10.44iter/s]
Best score: 10.7180: : 161iter [00:16, 10.71iter/s]
Best score: 10.7180: : 161iter [00:16, 10.71iter/s]
Best score: 10.7180: : 162iter [00:16, 10.71iter/s]
Best score: 10.7180: : 163iter [00:16, 11.03iter/s]
Best score: 10.7180: : 163iter [00:16, 11.03iter/s]
Best score: 10.7180: : 164iter [00:16, 11.03iter/s]
Best score: 10.7180: : 165iter [00:16, 11.33iter/s]
Best score: 10.7180: : 165iter [00:16, 11.33iter/s]
Best score: 10.7180: : 166iter [00:16, 11.33iter/s]
Best score: 10.7180: : 167iter [00:16, 11.53iter/s]
Best score: 10.7180: : 167iter [00:16, 11.53iter/s]
Best score: 10.7180: : 168iter [00:16, 11.53iter/s]
Best score: 10.7180: : 169iter [00:16, 11.69iter/s]
Best score: 10.7180: : 169iter [00:16, 11.69iter/s]
Best score: 10.7180: : 170iter [00:16, 11.69iter/s]
Best score: 10.7180: : 171iter [00:16, 11.56iter/s]
Best score: 10.7180: : 171iter [00:16, 11.56iter/s]
Best score: 10.7180: : 172iter [00:17, 11.56iter/s]
Best score: 10.7180: : 173iter [00:17, 11.69iter/s]
Best score: 10.7180: : 173iter [00:17, 11.69iter/s]
Best score: 10.7180: : 174iter [00:17, 11.69iter/s]
Best score: 10.7180: : 175iter [00:17, 11.79iter/s]
Best score: 10.7180: : 175iter [00:17, 11.79iter/s]
Best score: 10.7180: : 176iter [00:17, 11.79iter/s]
Best score: 10.7180: : 177iter [00:17, 11.85iter/s]
Best score: 10.7180: : 177iter [00:17, 11.85iter/s]
Best score: 10.7180: : 178iter [00:17, 11.85iter/s]
Best score: 10.7180: : 179iter [00:17, 11.91iter/s]
Best score: 10.7180: : 179iter [00:17, 11.91iter/s]
Best score: 10.7180: : 180iter [00:17, 11.91iter/s]
Best score: 10.7180: : 181iter [00:17, 11.73iter/s]
Best score: 10.7180: : 181iter [00:17, 11.73iter/s]
Best score: 10.7180: : 182iter [00:17, 11.73iter/s]
Best score: 10.7180: : 183iter [00:17, 11.84iter/s]
Best score: 10.7180: : 183iter [00:17, 11.84iter/s]
Best score: 10.7180: : 184iter [00:18, 11.84iter/s]
Best score: 10.7180: : 185iter [00:18, 11.89iter/s]
Best score: 10.7180: : 185iter [00:18, 11.89iter/s]
Best score: 10.7180: : 186iter [00:18, 11.89iter/s]
Best score: 10.7180: : 187iter [00:18, 11.93iter/s]
Best score: 10.7180: : 187iter [00:18, 11.93iter/s]
Best score: 10.7180: : 188iter [00:18, 11.93iter/s]
Best score: 10.7180: : 189iter [00:18, 11.97iter/s]
Best score: 10.4906: : 189iter [00:18, 11.97iter/s]
Best score: 10.4906: : 190iter [00:18, 11.97iter/s]
Best score: 10.4906: : 191iter [00:18, 11.76iter/s]
Best score: 10.4906: : 191iter [00:18, 11.76iter/s]
Best score: 10.4906: : 192iter [00:18, 11.76iter/s]
Best score: 10.4906: : 193iter [00:18, 11.84iter/s]
Best score: 10.4906: : 193iter [00:18, 11.84iter/s]
Best score: 10.4906: : 194iter [00:18, 11.84iter/s]
Best score: 10.4906: : 195iter [00:18, 11.92iter/s]
Best score: 10.4906: : 195iter [00:19, 11.92iter/s]
Best score: 10.4906: : 196iter [00:19, 11.92iter/s]
Best score: 10.4906: : 197iter [00:19, 11.97iter/s]
Best score: 10.4906: : 197iter [00:19, 11.97iter/s]
Best score: 10.4906: : 198iter [00:19, 11.97iter/s]
Best score: 10.4906: : 199iter [00:19, 11.99iter/s]
[ITER 200] Best: 8.0188
[PARAMS] Current best parameters:
  fx: 607.4422
  fy: 600.0535
  px: 985.6510
  py: 787.4353
  k1: -0.09315058
  k2: 0.02581312
  k3: 0.00411983
  k4: -0.00476664
  p1: 0.01450589
  p2: -0.01607628
  p3: -0.00800177
  p4: 0.00168877
  s1: -0.0060
  s2: 0.0202
  s3: 0.0039
  s4: 0.0035
  tilt_x: 0.0143
  tilt_y: -0.0526
  scale: 2.9570
  rotation: -0.2336

Best score: 8.0188: : 199iter [00:19, 11.99iter/s] 
Best score: 8.0188: : 200iter [00:19, 11.99iter/s]
Best score: 8.0188: : 201iter [00:19,  7.64iter/s]
Best score: 8.0188: : 201iter [00:19,  7.64iter/s]
Best score: 8.0188: : 202iter [00:19,  7.64iter/s]
Best score: 8.0188: : 203iter [00:19,  8.58iter/s]
Best score: 8.0188: : 203iter [00:19,  8.58iter/s]
Best score: 8.0188: : 204iter [00:20,  8.58iter/s]
Best score: 8.0188: : 205iter [00:20,  9.35iter/s]
Best score: 8.0188: : 205iter [00:20,  9.35iter/s]
Best score: 8.0188: : 206iter [00:20,  9.35iter/s]
Best score: 8.0188: : 207iter [00:20, 10.00iter/s]
Best score: 8.0188: : 207iter [00:20, 10.00iter/s]
Best score: 8.0188: : 208iter [00:20, 10.00iter/s]
Best score: 8.0188: : 209iter [00:20, 10.47iter/s]
Best score: 4.7668: : 209iter [00:20, 10.47iter/s]
Best score: 4.7668: : 210iter [00:20, 10.47iter/s]
Best score: 4.7668: : 211iter [00:20, 10.64iter/s]
Best score: 4.7668: : 211iter [00:20, 10.64iter/s]
Best score: 4.7668: : 212iter [00:20, 10.64iter/s]
Best score: 4.7668: : 213iter [00:20, 10.98iter/s]
Best score: 4.7668: : 213iter [00:20, 10.98iter/s]
Best score: 4.7668: : 214iter [00:20, 10.98iter/s]
Best score: 4.7668: : 215iter [00:20, 11.30iter/s]
Best score: 4.7668: : 215iter [00:21, 11.30iter/s]
Best score: 4.7668: : 216iter [00:21, 11.30iter/s]
Best score: 4.7668: : 217iter [00:21, 11.50iter/s]
Best score: 4.7668: : 217iter [00:21, 11.50iter/s]
Best score: 4.7668: : 218iter [00:21, 11.50iter/s]
Best score: 4.7668: : 219iter [00:21, 11.68iter/s]
Best score: 2.8332: : 219iter [00:21, 11.68iter/s]
Best score: 2.8332: : 220iter [00:21, 11.68iter/s]
Best score: 2.8332: : 221iter [00:21, 11.60iter/s]
Best score: 2.8332: : 221iter [00:21, 11.60iter/s]
Best score: 2.8332: : 222iter [00:21, 11.60iter/s]
Best score: 2.8332: : 223iter [00:21, 11.72iter/s]
Best score: 2.8332: : 223iter [00:21, 11.72iter/s]
Best score: 2.8332: : 224iter [00:21, 11.72iter/s]
Best score: 2.8332: : 225iter [00:21, 11.83iter/s]
Best score: 2.8332: : 225iter [00:21, 11.83iter/s]
Best score: 2.8332: : 226iter [00:21, 11.83iter/s]
Best score: 2.8332: : 227iter [00:21, 11.89iter/s]
Best score: 2.8332: : 227iter [00:22, 11.89iter/s]
Best score: 2.8332: : 228iter [00:22, 11.89iter/s]
Best score: 2.8332: : 229iter [00:22, 11.92iter/s]
Best score: 2.7475: : 229iter [00:22, 11.92iter/s]
Best score: 2.7475: : 230iter [00:22, 11.92iter/s]
Best score: 2.7475: : 231iter [00:22, 11.76iter/s]
Best score: 2.7475: : 231iter [00:22, 11.76iter/s]
Best score: 2.7475: : 232iter [00:22, 11.76iter/s]
Best score: 2.7475: : 233iter [00:22, 11.83iter/s]
Best score: 2.7475: : 233iter [00:22, 11.83iter/s]
Best score: 2.7475: : 234iter [00:22, 11.83iter/s]
Best score: 2.7475: : 235iter [00:22, 11.92iter/s]
Best score: 2.7475: : 235iter [00:22, 11.92iter/s]
Best score: 2.7475: : 236iter [00:22, 11.92iter/s]
Best score: 2.7475: : 237iter [00:22, 11.97iter/s]
Best score: 2.7475: : 237iter [00:22, 11.97iter/s]
Best score: 2.7475: : 238iter [00:22, 11.97iter/s]
Best score: 2.7475: : 239iter [00:22, 12.01iter/s]
Best score: 2.5277: : 239iter [00:23, 12.01iter/s]
Best score: 2.5277: : 240iter [00:23, 12.01iter/s]
Best score: 2.5277: : 241iter [00:23, 11.82iter/s]
Best score: 2.5277: : 241iter [00:23, 11.82iter/s]
Best score: 2.5277: : 242iter [00:23, 11.82iter/s]
Best score: 2.5277: : 243iter [00:23, 11.92iter/s]
Best score: 2.5277: : 243iter [00:23, 11.92iter/s]
Best score: 2.5277: : 244iter [00:23, 11.92iter/s]
Best score: 2.5277: : 245iter [00:23, 11.97iter/s]
Best score: 2.5277: : 245iter [00:23, 11.97iter/s]
Best score: 2.5277: : 246iter [00:23, 11.97iter/s]
Best score: 2.5277: : 247iter [00:23, 12.01iter/s]
Best score: 2.5277: : 247iter [00:23, 12.01iter/s]
Best score: 2.5277: : 248iter [00:23, 12.01iter/s]
Best score: 2.5277: : 249iter [00:23, 11.10iter/s]
[ITER 250] Best: 2.3584
[PARAMS] Current best parameters:
  fx: 595.9378
  fy: 595.3347
  px: 988.4265
  py: 786.6131
  k1: -0.11266719
  k2: 0.07979542
  k3: -0.03478862
  k4: 0.00439444
  p1: 0.01216532
  p2: 0.01477905
  p3: -0.02551960
  p4: -0.00380515
  s1: -0.0010
  s2: 0.0134
  s3: -0.0048
  s4: 0.0276
  tilt_x: 0.0150
  tilt_y: -0.0029
  scale: 2.9727
  rotation: 0.1600

Best score: 2.3584: : 249iter [00:23, 11.10iter/s]
Best score: 2.3584: : 250iter [00:24, 11.10iter/s]
Best score: 2.3584: : 251iter [00:24,  7.41iter/s]
Best score: 2.3584: : 251iter [00:24,  7.41iter/s]
Best score: 2.3584: : 252iter [00:24,  7.41iter/s]
Best score: 2.3584: : 253iter [00:24,  8.38iter/s]
Best score: 2.3584: : 253iter [00:24,  8.38iter/s]
Best score: 2.3584: : 254iter [00:24,  8.38iter/s]
Best score: 2.3584: : 255iter [00:24,  9.19iter/s]
Best score: 2.3584: : 255iter [00:24,  9.19iter/s]
Best score: 2.3584: : 256iter [00:24,  9.19iter/s]
Best score: 2.3584: : 257iter [00:24,  9.88iter/s]
Best score: 2.3584: : 257iter [00:24,  9.88iter/s]
Best score: 2.3584: : 258iter [00:24,  9.88iter/s]
Best score: 2.3584: : 259iter [00:24, 10.41iter/s]
Best score: 0.8758: : 259iter [00:25, 10.41iter/s]
Best score: 0.8758: : 260iter [00:25, 10.41iter/s]
Best score: 0.8758: : 261iter [00:25, 10.69iter/s]
Best score: 0.8758: : 261iter [00:25, 10.69iter/s]
Best score: 0.8758: : 262iter [00:25, 10.69iter/s]
Best score: 0.8758: : 263iter [00:25, 11.08iter/s]
Best score: 0.8758: : 263iter [00:25, 11.08iter/s]
Best score: 0.8758: : 264iter [00:25, 11.08iter/s]
Best score: 0.8758: : 265iter [00:25, 11.37iter/s]
Best score: 0.8758: : 265iter [00:25, 11.37iter/s]
Best score: 0.8758: : 266iter [00:25, 11.37iter/s]
Best score: 0.8758: : 267iter [00:25, 11.58iter/s]
Best score: 0.8758: : 267iter [00:25, 11.58iter/s]
Best score: 0.8758: : 268iter [00:25, 11.58iter/s]
Best score: 0.8758: : 269iter [00:25, 11.74iter/s]
Best score: 0.8758: : 269iter [00:26, 11.74iter/s]
Best score: 0.8758: : 270iter [00:26, 11.74iter/s]
Best score: 0.8758: : 271iter [00:26,  9.16iter/s]
Best score: 0.8758: : 271iter [00:26,  9.16iter/s]
Best score: 0.8758: : 272iter [00:26,  9.16iter/s]
Best score: 0.8758: : 273iter [00:26,  9.88iter/s]
Best score: 0.8758: : 273iter [00:26,  9.88iter/s]
Best score: 0.8758: : 274iter [00:26,  9.88iter/s]
Best score: 0.8758: : 275iter [00:26, 10.44iter/s]
Best score: 0.8758: : 275iter [00:26, 10.44iter/s]
Best score: 0.8758: : 276iter [00:26, 10.44iter/s]
Best score: 0.8758: : 277iter [00:26, 10.80iter/s]
Best score: 0.8758: : 277iter [00:26, 10.80iter/s]
Best score: 0.8758: : 278iter [00:26, 10.80iter/s]
Best score: 0.8758: : 279iter [00:26, 11.13iter/s]
Best score: 0.8758: : 279iter [00:26, 11.13iter/s]
Best score: 0.8758: : 280iter [00:26, 11.13iter/s]
Best score: 0.8758: : 281iter [00:26, 11.22iter/s]
Best score: 0.8758: : 281iter [00:27, 11.22iter/s]
Best score: 0.8758: : 282iter [00:27, 11.22iter/s]
Best score: 0.8758: : 283iter [00:27, 11.39iter/s]
Best score: 0.8758: : 283iter [00:27, 11.39iter/s]
Best score: 0.8758: : 284iter [00:27, 11.39iter/s]
Best score: 0.8758: : 285iter [00:27, 11.52iter/s]
Best score: 0.8758: : 285iter [00:27, 11.52iter/s]
Best score: 0.8758: : 286iter [00:27, 11.52iter/s]
Best score: 0.8758: : 287iter [00:27, 11.60iter/s]
Best score: 0.8758: : 287iter [00:27, 11.60iter/s]
Best score: 0.8758: : 288iter [00:27, 11.60iter/s]
Best score: 0.8758: : 289iter [00:27, 11.62iter/s]
Best score: 0.7326: : 289iter [00:27, 11.62iter/s]
Best score: 0.7326: : 290iter [00:27, 11.62iter/s]
Best score: 0.7326: : 291iter [00:27, 11.46iter/s]
Best score: 0.7326: : 291iter [00:27, 11.46iter/s]
Best score: 0.7326: : 292iter [00:28, 11.46iter/s]
Best score: 0.7326: : 293iter [00:28, 11.53iter/s]
Best score: 0.7326: : 293iter [00:28, 11.53iter/s]
Best score: 0.7326: : 294iter [00:28, 11.53iter/s]
Best score: 0.7326: : 295iter [00:28, 11.62iter/s]
Best score: 0.7326: : 295iter [00:28, 11.62iter/s]
Best score: 0.7326: : 296iter [00:28, 11.62iter/s]
Best score: 0.7326: : 297iter [00:28, 11.70iter/s]
Best score: 0.7326: : 297iter [00:28, 11.70iter/s]
Best score: 0.7326: : 298iter [00:28, 11.70iter/s]
Best score: 0.7326: : 299iter [00:28, 11.76iter/s]
[ITER 300] Best: 0.7326
[PARAMS] Current best parameters:
  fx: 567.9686
  fy: 567.7104
  px: 987.6073
  py: 776.5790
  k1: -0.04077603
  k2: 0.01985402
  k3: -0.01611095
  k4: 0.00432371
  p1: 0.00894852
  p2: 0.00354472
  p3: -0.00939404
  p4: -0.01293990
  s1: 0.0114
  s2: 0.0091
  s3: -0.0092
  s4: 0.0224
  tilt_x: -0.0360
  tilt_y: -0.0094
  scale: 2.9506
  rotation: 0.2595

Best score: 0.7326: : 299iter [00:28, 11.76iter/s]
Best score: 0.7326: : 300iter [00:28, 11.76iter/s]
Best score: 0.7326: : 301iter [00:28,  7.54iter/s]
Best score: 0.7326: : 301iter [00:29,  7.54iter/s]
Best score: 0.7326: : 302iter [00:29,  7.54iter/s]
Best score: 0.7326: : 303iter [00:29,  8.35iter/s]
Best score: 0.7326: : 303iter [00:29,  8.35iter/s]
Best score: 0.7326: : 304iter [00:29,  8.56iter/s]
Best score: 0.7326: : 304iter [00:29,  8.56iter/s]
Best score: 0.7326: : 305iter [00:29,  8.56iter/s]
Best score: 0.7326: : 306iter [00:29,  9.39iter/s]
Best score: 0.7326: : 306iter [00:29,  9.39iter/s]
Best score: 0.7326: : 307iter [00:29,  9.39iter/s]
Best score: 0.7326: : 308iter [00:29,  9.75iter/s]
Best score: 0.7326: : 308iter [00:29,  9.75iter/s]
Best score: 0.6945: : 309iter [00:29,  9.75iter/s]
Best score: 0.6945: : 310iter [00:29, 10.13iter/s]
Best score: 0.6945: : 310iter [00:29, 10.13iter/s]
Best score: 0.6945: : 311iter [00:29, 10.13iter/s]
Best score: 0.6945: : 312iter [00:29, 10.63iter/s]
Best score: 0.6945: : 312iter [00:30, 10.63iter/s]
Best score: 0.6945: : 313iter [00:30, 10.63iter/s]
Best score: 0.6945: : 314iter [00:30, 10.94iter/s]
Best score: 0.6945: : 314iter [00:30, 10.94iter/s]
Best score: 0.6945: : 315iter [00:30, 10.94iter/s]
Best score: 0.6945: : 316iter [00:30, 11.19iter/s]
Best score: 0.6945: : 316iter [00:30, 11.19iter/s]
Best score: 0.6945: : 317iter [00:30, 11.19iter/s]
Best score: 0.6945: : 318iter [00:30, 11.36iter/s]
Best score: 0.6945: : 318iter [00:30, 11.36iter/s]
Best score: 0.5906: : 319iter [00:30, 11.36iter/s]
Best score: 0.5906: : 320iter [00:30, 11.34iter/s]
Best score: 0.5906: : 320iter [00:30, 11.34iter/s]
Best score: 0.5906: : 321iter [00:30, 11.34iter/s]
Best score: 0.5906: : 322iter [00:30, 10.97iter/s]
Best score: 0.5906: : 322iter [00:30, 10.97iter/s]
Best score: 0.5906: : 323iter [00:31, 10.97iter/s]
Best score: 0.5906: : 324iter [00:31, 11.21iter/s]
Best score: 0.5906: : 324iter [00:31, 11.21iter/s]
Best score: 0.5906: : 325iter [00:31, 11.21iter/s]
Best score: 0.5906: : 326iter [00:31, 11.41iter/s]
Best score: 0.5906: : 326iter [00:31, 11.41iter/s]
Best score: 0.5906: : 327iter [00:31, 11.41iter/s]
Best score: 0.5906: : 328iter [00:31, 11.45iter/s]
Best score: 0.5906: : 328iter [00:31, 11.45iter/s]
Best score: 0.5906: : 329iter [00:31, 11.45iter/s]
Best score: 0.5906: : 330iter [00:31, 11.31iter/s]
Best score: 0.5906: : 330iter [00:31, 11.31iter/s]
Best score: 0.5906: : 331iter [00:31, 11.31iter/s]
Best score: 0.5906: : 332iter [00:31, 11.43iter/s]
Best score: 0.5906: : 332iter [00:31, 11.43iter/s]
Best score: 0.5906: : 333iter [00:31, 11.43iter/s]
Best score: 0.5906: : 334iter [00:31, 11.60iter/s]
Best score: 0.5906: : 334iter [00:31, 11.60iter/s]
Best score: 0.5906: : 335iter [00:32, 11.60iter/s]
Best score: 0.5906: : 336iter [00:32, 11.72iter/s]
Best score: 0.5906: : 336iter [00:32, 11.72iter/s]
Best score: 0.5906: : 337iter [00:32, 11.72iter/s]
Best score: 0.5906: : 338iter [00:32, 11.79iter/s]
Best score: 0.5906: : 338iter [00:32, 11.79iter/s]
Best score: 0.3687: : 339iter [00:32, 11.79iter/s]
Best score: 0.3687: : 340iter [00:32, 11.64iter/s]
Best score: 0.3687: : 340iter [00:32, 11.64iter/s]
Best score: 0.3687: : 341iter [00:32, 11.64iter/s]
Best score: 0.3687: : 342iter [00:32, 11.70iter/s]
Best score: 0.3687: : 342iter [00:32, 11.70iter/s]
Best score: 0.3687: : 343iter [00:32, 11.70iter/s]
Best score: 0.3687: : 344iter [00:32, 11.73iter/s]
Best score: 0.3687: : 344iter [00:32, 11.73iter/s]
Best score: 0.3687: : 345iter [00:32, 11.73iter/s]
Best score: 0.3687: : 346iter [00:32, 11.78iter/s]
Best score: 0.3687: : 346iter [00:33, 11.78iter/s]
Best score: 0.3687: : 347iter [00:33, 11.78iter/s]
Best score: 0.3687: : 348iter [00:33, 11.86iter/s]
Best score: 0.3687: : 348iter [00:33, 11.86iter/s]
[ITER 350] Best: 0.3418
[PARAMS] Current best parameters:
  fx: 561.8420
  fy: 562.1678
  px: 986.5733
  py: 775.4895
  k1: -0.03827106
  k2: 0.00892417
  k3: -0.00183260
  k4: -0.00010737
  p1: 0.00820663
  p2: 0.00591505
  p3: -0.00369525
  p4: -0.01448472
  s1: -0.0019
  s2: 0.0126
  s3: -0.0040
  s4: 0.0149
  tilt_x: -0.0379
  tilt_y: -0.0040
  scale: 2.9828
  rotation: 0.1751

Best score: 0.3418: : 349iter [00:33, 11.86iter/s]
Best score: 0.3418: : 350iter [00:33, 10.77iter/s]
Best score: 0.3418: : 350iter [00:33, 10.77iter/s]
Best score: 0.3418: : 351iter [00:34, 10.77iter/s]
Best score: 0.3418: : 352iter [00:34,  5.32iter/s]
Best score: 0.3418: : 352iter [00:34,  5.32iter/s]
Best score: 0.3418: : 353iter [00:34,  5.59iter/s]
Best score: 0.3418: : 353iter [00:34,  5.59iter/s]
Best score: 0.3418: : 354iter [00:34,  5.84iter/s]
Best score: 0.3418: : 354iter [00:34,  5.84iter/s]
Best score: 0.3418: : 355iter [00:34,  6.11iter/s]
Best score: 0.3418: : 355iter [00:34,  6.11iter/s]
Best score: 0.3418: : 356iter [00:34,  6.29iter/s]
Best score: 0.3418: : 356iter [00:34,  6.29iter/s]
Best score: 0.3418: : 357iter [00:34,  6.36iter/s]
Best score: 0.3418: : 357iter [00:34,  6.36iter/s]
Best score: 0.3418: : 358iter [00:34,  6.45iter/s]
Best score: 0.3418: : 358iter [00:35,  6.45iter/s]
Best score: 0.3418: : 359iter [00:35,  6.41iter/s]
Best score: 0.3418: : 359iter [00:35,  6.41iter/s]
Best score: 0.3418: : 360iter [00:35,  6.33iter/s]
Best score: 0.3418: : 360iter [00:35,  6.33iter/s]
Best score: 0.3418: : 361iter [00:35,  6.43iter/s]
Best score: 0.3418: : 361iter [00:35,  6.43iter/s]
Best score: 0.3418: : 362iter [00:35,  6.57iter/s]
Best score: 0.3418: : 362iter [00:35,  6.57iter/s]
Best score: 0.3418: : 363iter [00:35,  6.71iter/s]
Best score: 0.3418: : 363iter [00:35,  6.71iter/s]
Best score: 0.3418: : 364iter [00:35,  6.81iter/s]
Best score: 0.3418: : 364iter [00:36,  6.81iter/s]
Best score: 0.3418: : 365iter [00:36,  6.89iter/s]
Best score: 0.3418: : 365iter [00:36,  6.89iter/s]
Best score: 0.3418: : 366iter [00:36,  6.84iter/s]
Best score: 0.3418: : 366iter [00:36,  6.84iter/s]
Best score: 0.3418: : 367iter [00:36,  6.92iter/s]
Best score: 0.3418: : 367iter [00:36,  6.92iter/s]
Best score: 0.3418: : 368iter [00:36,  6.93iter/s]
Best score: 0.3418: : 368iter [00:36,  6.93iter/s]
Best score: 0.3418: : 369iter [00:36,  6.96iter/s]
Best score: 0.3418: : 369iter [00:36,  6.96iter/s]
Best score: 0.3418: : 370iter [00:36,  6.72iter/s]
Best score: 0.3418: : 370iter [00:36,  6.72iter/s]
Best score: 0.3418: : 371iter [00:36,  6.76iter/s]
Best score: 0.3418: : 371iter [00:37,  6.76iter/s]
Best score: 0.3418: : 372iter [00:37,  6.88iter/s]
Best score: 0.3418: : 372iter [00:37,  6.88iter/s]
Best score: 0.3418: : 373iter [00:37,  6.98iter/s]
Best score: 0.3418: : 373iter [00:37,  6.98iter/s]
Best score: 0.3418: : 374iter [00:37,  7.01iter/s]
Best score: 0.3418: : 374iter [00:37,  7.01iter/s]
Best score: 0.3418: : 375iter [00:37,  7.01iter/s]
Best score: 0.3418: : 375iter [00:37,  7.01iter/s]
Best score: 0.3418: : 376iter [00:37,  6.92iter/s]
Best score: 0.3418: : 376iter [00:37,  6.92iter/s]
Best score: 0.3418: : 377iter [00:37,  7.14iter/s]
Best score: 0.3418: : 377iter [00:37,  7.14iter/s]
Best score: 0.3418: : 378iter [00:37,  7.09iter/s]
Best score: 0.3418: : 378iter [00:38,  7.09iter/s]
Best score: 0.3418: : 379iter [00:38,  7.08iter/s]
Best score: 0.2961: : 379iter [00:38,  7.08iter/s]
Best score: 0.2961: : 380iter [00:38,  6.82iter/s]
Best score: 0.2961: : 380iter [00:38,  6.82iter/s]
Best score: 0.2961: : 381iter [00:38,  6.96iter/s]
Best score: 0.2961: : 381iter [00:38,  6.96iter/s]
Best score: 0.2961: : 382iter [00:38,  6.94iter/s]
Best score: 0.2961: : 382iter [00:38,  6.94iter/s]
Best score: 0.2961: : 383iter [00:38,  7.00iter/s]
Best score: 0.2961: : 383iter [00:38,  7.00iter/s]
Best score: 0.2961: : 384iter [00:38,  7.13iter/s]
Best score: 0.2961: : 384iter [00:38,  7.13iter/s]
Best score: 0.2961: : 385iter [00:38,  7.22iter/s]
Best score: 0.2961: : 385iter [00:39,  7.22iter/s]
Best score: 0.2961: : 386iter [00:39,  7.38iter/s]
Best score: 0.2961: : 386iter [00:39,  7.38iter/s]
Best score: 0.2961: : 387iter [00:39,  7.45iter/s]
Best score: 0.2961: : 387iter [00:39,  7.45iter/s]
Best score: 0.2961: : 388iter [00:39,  7.46iter/s]
Best score: 0.2961: : 388iter [00:39,  7.46iter/s]
Best score: 0.2961: : 389iter [00:39,  7.41iter/s]
Best score: 0.2961: : 389iter [00:39,  7.41iter/s]
Best score: 0.2961: : 390iter [00:39,  7.24iter/s]
Best score: 0.2961: : 390iter [00:39,  7.24iter/s]
Best score: 0.2961: : 391iter [00:39,  7.33iter/s]
Best score: 0.2961: : 391iter [00:39,  7.33iter/s]
Best score: 0.2961: : 392iter [00:39,  7.43iter/s]
Best score: 0.2961: : 392iter [00:39,  7.43iter/s]
Best score: 0.2961: : 393iter [00:39,  7.57iter/s]
Best score: 0.2961: : 393iter [00:40,  7.57iter/s]
Best score: 0.2961: : 394iter [00:40,  7.66iter/s]
Best score: 0.2961: : 394iter [00:40,  7.66iter/s]
Best score: 0.2961: : 395iter [00:40,  7.76iter/s]
Best score: 0.2961: : 395iter [00:40,  7.76iter/s]
Best score: 0.2961: : 396iter [00:40,  7.72iter/s]
Best score: 0.2961: : 396iter [00:40,  7.72iter/s]
Best score: 0.2961: : 397iter [00:40,  7.76iter/s]
Best score: 0.2961: : 397iter [00:40,  7.76iter/s]
Best score: 0.2961: : 398iter [00:40,  7.76iter/s]
Best score: 0.2961: : 398iter [00:40,  7.76iter/s]
Best score: 0.2961: : 399iter [00:40,  7.76iter/s]
[ITER 400] Best: 0.2961
[PARAMS] Current best parameters:
  fx: 564.6005
  fy: 564.8009
  px: 985.8589
  py: 775.0402
  k1: -0.03438901
  k2: 0.00436784
  k3: -0.00270244
  k4: 0.00082855
  p1: 0.00439625
  p2: 0.00418107
  p3: 0.00066359
  p4: -0.01515721
  s1: -0.0041
  s2: 0.0147
  s3: -0.0066
  s4: 0.0157
  tilt_x: -0.0314
  tilt_y: -0.0026
  scale: 2.9709
  rotation: 0.3109

Best score: 0.2961: : 399iter [00:40,  7.76iter/s]
Best score: 0.2961: : 400iter [00:40,  8.03iter/s]
Best score: 0.2961: : 400iter [00:41,  8.03iter/s]
Best score: 0.2961: : 401iter [00:41,  3.72iter/s]
Best score: 0.2961: : 401iter [00:41,  3.72iter/s]
Best score: 0.2961: : 402iter [00:41,  4.28iter/s]
Best score: 0.2961: : 402iter [00:41,  4.28iter/s]
Best score: 0.2961: : 403iter [00:41,  4.82iter/s]
Best score: 0.2961: : 403iter [00:41,  4.82iter/s]
Best score: 0.2961: : 404iter [00:41,  5.36iter/s]
Best score: 0.2961: : 404iter [00:42,  5.36iter/s]
Best score: 0.2961: : 405iter [00:42,  5.73iter/s]
Best score: 0.2961: : 405iter [00:42,  5.73iter/s]
Best score: 0.2961: : 406iter [00:42,  5.97iter/s]
Best score: 0.2961: : 406iter [00:42,  5.97iter/s]
Best score: 0.2961: : 407iter [00:42,  6.27iter/s]
Best score: 0.2961: : 407iter [00:42,  6.27iter/s]
Best score: 0.2961: : 408iter [00:42,  6.59iter/s]
Best score: 0.2961: : 408iter [00:42,  6.59iter/s]
Best score: 0.2961: : 409iter [00:42,  6.84iter/s]
Best score: 0.2961: : 409iter [00:42,  6.84iter/s]
Best score: 0.2961: : 410iter [00:42,  6.94iter/s]
Best score: 0.2961: : 410iter [00:42,  6.94iter/s]
Best score: 0.2961: : 411iter [00:42,  7.15iter/s]
Best score: 0.2961: : 411iter [00:42,  7.15iter/s]
Best score: 0.2961: : 412iter [00:42,  7.15iter/s]
Best score: 0.2961: : 412iter [00:43,  7.15iter/s]
Best score: 0.2961: : 413iter [00:43,  7.10iter/s]
Best score: 0.2961: : 413iter [00:43,  7.10iter/s]
Best score: 0.2961: : 414iter [00:43,  7.19iter/s]
Best score: 0.2961: : 414iter [00:43,  7.19iter/s]
Best score: 0.2961: : 415iter [00:43,  7.53iter/s]
Best score: 0.2961: : 415iter [00:43,  7.53iter/s]
Best score: 0.2961: : 416iter [00:43,  7.53iter/s]
Best score: 0.2961: : 417iter [00:43,  8.86iter/s]
Best score: 0.2961: : 417iter [00:43,  8.86iter/s]
Best score: 0.2961: : 418iter [00:43,  8.86iter/s]
Best score: 0.2961: : 419iter [00:43,  9.81iter/s]
Best score: 0.2961: : 419iter [00:43,  9.81iter/s]
Best score: 0.2961: : 420iter [00:43,  9.81iter/s]
Best score: 0.2961: : 421iter [00:43, 10.31iter/s]
Best score: 0.2961: : 421iter [00:43, 10.31iter/s]
Best score: 0.2961: : 422iter [00:44, 10.31iter/s]
Best score: 0.2961: : 423iter [00:44, 10.84iter/s]
Best score: 0.2961: : 423iter [00:44, 10.84iter/s]
Best score: 0.2961: : 424iter [00:44, 10.84iter/s]
Best score: 0.2961: : 425iter [00:44, 11.09iter/s]
Best score: 0.2961: : 425iter [00:44, 11.09iter/s]
Best score: 0.2961: : 426iter [00:44, 11.09iter/s]
Best score: 0.2961: : 427iter [00:44, 10.79iter/s]
Best score: 0.2961: : 427iter [00:44, 10.79iter/s]
Best score: 0.2961: : 428iter [00:44, 10.79iter/s]
Best score: 0.2961: : 429iter [00:44, 10.14iter/s]
Best score: 0.2545: : 429iter [00:44, 10.14iter/s]
Best score: 0.2545: : 430iter [00:44, 10.14iter/s]
Best score: 0.2545: : 431iter [00:44, 10.44iter/s]
Best score: 0.2545: : 431iter [00:44, 10.44iter/s]
Best score: 0.2545: : 432iter [00:45, 10.44iter/s]
Best score: 0.2545: : 433iter [00:45, 10.79iter/s]
Best score: 0.2545: : 433iter [00:45, 10.79iter/s]
Best score: 0.2545: : 434iter [00:45, 10.79iter/s]
Best score: 0.2545: : 435iter [00:45, 11.06iter/s]
Best score: 0.2545: : 435iter [00:45, 11.06iter/s]
Best score: 0.2545: : 436iter [00:45, 11.06iter/s]
Best score: 0.2545: : 437iter [00:45, 11.29iter/s]
Best score: 0.2545: : 437iter [00:45, 11.29iter/s]
Best score: 0.2545: : 438iter [00:45, 11.29iter/s]
Best score: 0.2545: : 439iter [00:45, 10.86iter/s]
Best score: 0.2545: : 439iter [00:45, 10.86iter/s]
Best score: 0.2545: : 440iter [00:45, 10.86iter/s]
Best score: 0.2545: : 441iter [00:45, 11.02iter/s]
Best score: 0.2545: : 441iter [00:45, 11.02iter/s]
Best score: 0.2545: : 442iter [00:45, 11.02iter/s]
Best score: 0.2545: : 443iter [00:45, 10.80iter/s]
Best score: 0.2545: : 443iter [00:46, 10.80iter/s]
Best score: 0.2545: : 444iter [00:46, 10.80iter/s]
Best score: 0.2545: : 445iter [00:46, 11.04iter/s]
Best score: 0.2545: : 445iter [00:46, 11.04iter/s]
Best score: 0.2545: : 446iter [00:46, 11.04iter/s]
Best score: 0.2545: : 447iter [00:46, 11.27iter/s]
Best score: 0.2545: : 447iter [00:46, 11.27iter/s]
Best score: 0.2545: : 448iter [00:46, 11.27iter/s]
Best score: 0.2545: : 449iter [00:46, 11.42iter/s]
[ITER 450] Best: 0.2482
[PARAMS] Current best parameters:
  fx: 561.2145
  fy: 561.3297
  px: 985.9907
  py: 772.9317
  k1: -0.02658022
  k2: -0.00268813
  k3: 0.00091668
  k4: 0.00016626
  p1: 0.00224100
  p2: 0.00372601
  p3: 0.00443646
  p4: -0.01762284
  s1: -0.0064
  s2: 0.0164
  s3: -0.0083
  s4: 0.0165
  tilt_x: -0.0388
  tilt_y: -0.0043
  scale: 2.9685
  rotation: 0.2929

Best score: 0.2482: : 449iter [00:46, 11.42iter/s]
Best score: 0.2482: : 450iter [00:46, 11.42iter/s]
Best score: 0.2482: : 451iter [00:46,  7.52iter/s]
Best score: 0.2482: : 451iter [00:46,  7.52iter/s]
Best score: 0.2482: : 452iter [00:47,  7.52iter/s]
Best score: 0.2482: : 453iter [00:47,  8.21iter/s]
Best score: 0.2482: : 453iter [00:47,  8.21iter/s]
Best score: 0.2482: : 454iter [00:47,  8.21iter/s]
Best score: 0.2482: : 455iter [00:47,  9.04iter/s]
Best score: 0.2482: : 455iter [00:47,  9.04iter/s]
Best score: 0.2482: : 456iter [00:47,  9.04iter/s]
Best score: 0.2482: : 457iter [00:47,  9.77iter/s]
Best score: 0.2482: : 457iter [00:47,  9.77iter/s]
Best score: 0.2482: : 458iter [00:47,  9.77iter/s]
Best score: 0.2482: : 459iter [00:47, 10.29iter/s]
Best score: 0.2435: : 459iter [00:47, 10.29iter/s]
Best score: 0.2435: : 460iter [00:47, 10.29iter/s]
Best score: 0.2435: : 461iter [00:47, 10.60iter/s]
Best score: 0.2435: : 461iter [00:47, 10.60iter/s]
Best score: 0.2435: : 462iter [00:47, 10.60iter/s]
Best score: 0.2435: : 463iter [00:47, 10.97iter/s]
Best score: 0.2435: : 463iter [00:48, 10.97iter/s]
Best score: 0.2435: : 464iter [00:48, 10.97iter/s]
Best score: 0.2435: : 465iter [00:48, 11.28iter/s]
Best score: 0.2435: : 465iter [00:48, 11.28iter/s]
Best score: 0.2435: : 466iter [00:48, 11.28iter/s]
Best score: 0.2435: : 467iter [00:48, 11.49iter/s]
Best score: 0.2435: : 467iter [00:48, 11.49iter/s]
Best score: 0.2435: : 468iter [00:48, 11.49iter/s]
Best score: 0.2435: : 469iter [00:48, 11.62iter/s]
Best score: 0.2435: : 469iter [00:48, 11.62iter/s]
Best score: 0.2435: : 470iter [00:48, 11.62iter/s]
Best score: 0.2435: : 471iter [00:48, 11.52iter/s]
Best score: 0.2435: : 471iter [00:48, 11.52iter/s]
Best score: 0.2435: : 472iter [00:48, 11.52iter/s]
Best score: 0.2435: : 473iter [00:48, 11.67iter/s]
Best score: 0.2435: : 473iter [00:48, 11.67iter/s]
Best score: 0.2435: : 474iter [00:48, 11.67iter/s]
Best score: 0.2435: : 475iter [00:48, 11.77iter/s]
Best score: 0.2435: : 475iter [00:49, 11.77iter/s]
Best score: 0.2435: : 476iter [00:49, 11.77iter/s]
Best score: 0.2435: : 477iter [00:49, 11.83iter/s]
Best score: 0.2435: : 477iter [00:49, 11.83iter/s]
Best score: 0.2435: : 478iter [00:49, 11.83iter/s]
Best score: 0.2435: : 479iter [00:49, 11.85iter/s]
Best score: 0.2304: : 479iter [00:49, 11.85iter/s]
Best score: 0.2304: : 480iter [00:49, 11.85iter/s]
Best score: 0.2304: : 481iter [00:49, 11.66iter/s]
Best score: 0.2304: : 481iter [00:49, 11.66iter/s]
Best score: 0.2304: : 482iter [00:49, 11.66iter/s]
Best score: 0.2304: : 483iter [00:49, 11.70iter/s]
Best score: 0.2304: : 483iter [00:49, 11.70iter/s]
Best score: 0.2304: : 484iter [00:49, 11.70iter/s]
Best score: 0.2304: : 485iter [00:49, 10.63iter/s]
Best score: 0.2304: : 485iter [00:50, 10.63iter/s]
Best score: 0.2304: : 486iter [00:50, 10.63iter/s]
Best score: 0.2304: : 487iter [00:50,  9.12iter/s]
Best score: 0.2304: : 487iter [00:50,  9.12iter/s]
Best score: 0.2304: : 488iter [00:50,  8.73iter/s]
Best score: 0.2304: : 488iter [00:50,  8.73iter/s]
Best score: 0.2304: : 489iter [00:50,  8.27iter/s]
Best score: 0.2302: : 489iter [00:50,  8.27iter/s]
Best score: 0.2302: : 490iter [00:50,  7.85iter/s]
Best score: 0.2302: : 490iter [00:50,  7.85iter/s]
Best score: 0.2302: : 491iter [00:50,  7.54iter/s]
Best score: 0.2302: : 491iter [00:50,  7.54iter/s]
Best score: 0.2302: : 492iter [00:50,  7.31iter/s]
Best score: 0.2302: : 492iter [00:51,  7.31iter/s]
Best score: 0.2302: : 493iter [00:51,  7.23iter/s]
Best score: 0.2302: : 493iter [00:51,  7.23iter/s]
Best score: 0.2302: : 494iter [00:51,  7.27iter/s]
Best score: 0.2302: : 494iter [00:51,  7.27iter/s]
Best score: 0.2302: : 495iter [00:51,  7.24iter/s]
Best score: 0.2302: : 495iter [00:51,  7.24iter/s]
Best score: 0.2302: : 496iter [00:51,  7.18iter/s]
Best score: 0.2302: : 496iter [00:51,  7.18iter/s]
Best score: 0.2302: : 497iter [00:51,  7.01iter/s]
Best score: 0.2302: : 497iter [00:51,  7.01iter/s]
Best score: 0.2302: : 498iter [00:51,  6.98iter/s]
Best score: 0.2302: : 498iter [00:51,  6.98iter/s]
Best score: 0.2302: : 499iter [00:51,  7.02iter/s]
Best score: 0.2302: : 499iter [00:52,  7.02iter/s]
Best score: 0.2302: : 500iter [00:52,  6.96iter/s]
[ITER 500] Best: 0.2302
[PARAMS] Current best parameters:
  fx: 561.6207
  fy: 561.8156
  px: 987.2895
  py: 770.9534
  k1: -0.04275285
  k2: 0.01878021
  k3: -0.00860946
  k4: 0.00143069
  p1: 0.00457279
  p2: 0.00523933
  p3: 0.00117575
  p4: -0.02018459
  s1: -0.0023
  s2: 0.0185
  s3: -0.0142
  s4: 0.0227
  tilt_x: -0.0532
  tilt_y: -0.0064
  scale: 2.9867
  rotation: 0.2587

Best score: 0.2302: : 500iter [00:52,  6.96iter/s]
Best score: 0.2302: : 501iter [00:52,  3.37iter/s]
Best score: 0.2302: : 501iter [00:52,  3.37iter/s]
Best score: 0.2302: : 502iter [00:52,  4.01iter/s]
Best score: 0.2302: : 502iter [00:52,  4.01iter/s]
Best score: 0.2302: : 503iter [00:52,  4.65iter/s]
Best score: 0.2302: : 503iter [00:53,  4.65iter/s]
Best score: 0.2302: : 504iter [00:53,  5.25iter/s]
Best score: 0.2302: : 504iter [00:53,  5.25iter/s]
Best score: 0.2302: : 505iter [00:53,  5.72iter/s]
Best score: 0.2302: : 505iter [00:53,  5.72iter/s]
Best score: 0.2302: : 506iter [00:53,  6.15iter/s]
Best score: 0.2302: : 506iter [00:53,  6.15iter/s]
Best score: 0.2302: : 507iter [00:53,  6.47iter/s]
Best score: 0.2302: : 507iter [00:53,  6.47iter/s]
Best score: 0.2302: : 508iter [00:53,  6.79iter/s]
Best score: 0.2302: : 508iter [00:53,  6.79iter/s]
Best score: 0.2302: : 509iter [00:53,  6.95iter/s]
Best score: 0.2267: : 509iter [00:53,  6.95iter/s]
Best score: 0.2267: : 510iter [00:53,  7.00iter/s]
Best score: 0.2267: : 510iter [00:54,  7.00iter/s]
Best score: 0.2267: : 511iter [00:54,  7.13iter/s]
Best score: 0.2267: : 511iter [00:54,  7.13iter/s]
Best score: 0.2267: : 512iter [00:54,  7.06iter/s]
Best score: 0.2267: : 512iter [00:54,  7.06iter/s]
Best score: 0.2267: : 513iter [00:54,  7.02iter/s]
Best score: 0.2267: : 513iter [00:54,  7.02iter/s]
Best score: 0.2267: : 514iter [00:54,  7.03iter/s]
Best score: 0.2267: : 514iter [00:54,  7.03iter/s]
Best score: 0.2267: : 515iter [00:54,  6.83iter/s]
Best score: 0.2267: : 515iter [00:54,  6.83iter/s]
Best score: 0.2267: : 516iter [00:54,  6.95iter/s]
Best score: 0.2267: : 516iter [00:54,  6.95iter/s]
Best score: 0.2267: : 517iter [00:54,  6.78iter/s]
Best score: 0.2267: : 517iter [00:55,  6.78iter/s]
Best score: 0.2267: : 518iter [00:55,  6.79iter/s]
Best score: 0.2267: : 518iter [00:55,  6.79iter/s]
Best score: 0.2267: : 519iter [00:55,  6.81iter/s]
Best score: 0.2262: : 519iter [00:55,  6.81iter/s]
Best score: 0.2262: : 520iter [00:55,  6.85iter/s]
Best score: 0.2262: : 520iter [00:55,  6.85iter/s]
Best score: 0.2262: : 521iter [00:55,  6.82iter/s]
Best score: 0.2262: : 521iter [00:55,  6.82iter/s]
Best score: 0.2262: : 522iter [00:55,  6.98iter/s]
Best score: 0.2262: : 522iter [00:55,  6.98iter/s]
Best score: 0.2262: : 523iter [00:55,  7.14iter/s]
Best score: 0.2262: : 523iter [00:55,  7.14iter/s]
Best score: 0.2262: : 524iter [00:55,  7.27iter/s]
Best score: 0.2262: : 524iter [00:56,  7.27iter/s]
Best score: 0.2262: : 525iter [00:56,  7.20iter/s]
Best score: 0.2262: : 525iter [00:56,  7.20iter/s]
Best score: 0.2262: : 526iter [00:56,  7.21iter/s]
Best score: 0.2262: : 526iter [00:56,  7.21iter/s]
Best score: 0.2262: : 527iter [00:56,  7.02iter/s]
Best score: 0.2262: : 527iter [00:56,  7.02iter/s]
Best score: 0.2262: : 528iter [00:56,  7.04iter/s]
Best score: 0.2262: : 528iter [00:56,  7.04iter/s]
Best score: 0.2262: : 529iter [00:56,  7.14iter/s]
Best score: 0.2217: : 529iter [00:56,  7.14iter/s]
Best score: 0.2217: : 530iter [00:56,  6.96iter/s]
Best score: 0.2217: : 530iter [00:56,  6.96iter/s]
Best score: 0.2217: : 531iter [00:56,  6.98iter/s]
Best score: 0.2217: : 531iter [00:57,  6.98iter/s]
Best score: 0.2217: : 532iter [00:57,  7.17iter/s]
Best score: 0.2217: : 532iter [00:57,  7.17iter/s]
Best score: 0.2217: : 533iter [00:57,  7.14iter/s]
Best score: 0.2217: : 533iter [00:57,  7.14iter/s]
Best score: 0.2217: : 534iter [00:57,  7.25iter/s]
Best score: 0.2217: : 534iter [00:57,  7.25iter/s]
Best score: 0.2217: : 535iter [00:57,  7.40iter/s]
Best score: 0.2217: : 535iter [00:57,  7.40iter/s]
Best score: 0.2217: : 536iter [00:57,  7.39iter/s]
Best score: 0.2217: : 536iter [00:57,  7.39iter/s]
Best score: 0.2217: : 537iter [00:57,  7.29iter/s]
Best score: 0.2217: : 537iter [00:57,  7.29iter/s]
Best score: 0.2217: : 538iter [00:57,  7.23iter/s]
Best score: 0.2217: : 538iter [00:58,  7.23iter/s]
Best score: 0.2217: : 539iter [00:58,  7.25iter/s]
Best score: 0.2217: : 539iter [00:58,  7.25iter/s]
Best score: 0.2217: : 540iter [00:58,  7.33iter/s]
Best score: 0.2217: : 540iter [00:58,  7.33iter/s]
Best score: 0.2217: : 541iter [00:58,  7.33iter/s]
Best score: 0.2217: : 542iter [00:58,  7.73iter/s]
Best score: 0.2217: : 542iter [00:58,  7.73iter/s]
Best score: 0.2217: : 543iter [00:58,  7.70iter/s]
Best score: 0.2217: : 543iter [00:58,  7.70iter/s]
Best score: 0.2217: : 544iter [00:58,  7.51iter/s]
Best score: 0.2217: : 544iter [00:58,  7.51iter/s]
Best score: 0.2217: : 545iter [00:58,  7.39iter/s]
Best score: 0.2217: : 545iter [00:58,  7.39iter/s]
Best score: 0.2217: : 546iter [00:58,  7.29iter/s]
Best score: 0.2217: : 546iter [00:59,  7.29iter/s]
Best score: 0.2217: : 547iter [00:59,  7.26iter/s]
Best score: 0.2217: : 547iter [00:59,  7.26iter/s]
Best score: 0.2217: : 548iter [00:59,  7.21iter/s]
Best score: 0.2217: : 548iter [00:59,  7.21iter/s]
Best score: 0.2217: : 549iter [00:59,  7.06iter/s]
Best score: 0.2202: : 549iter [00:59,  7.06iter/s]
Best score: 0.2202: : 550iter [00:59,  6.97iter/s]
[ITER 550] Best: 0.2202
[PARAMS] Current best parameters:
  fx: 563.0953
  fy: 563.0984
  px: 985.8688
  py: 771.3730
  k1: -0.03928443
  k2: 0.00964742
  k3: -0.00221168
  k4: -0.00011200
  p1: 0.00291244
  p2: 0.00312273
  p3: 0.00385284
  p4: -0.01901901
  s1: -0.0054
  s2: 0.0183
  s3: -0.0130
  s4: 0.0203
  tilt_x: -0.0477
  tilt_y: -0.0042
  scale: 2.9827
  rotation: 0.2734

Best score: 0.2202: : 550iter [01:00,  6.97iter/s]
Best score: 0.2202: : 551iter [01:00,  3.37iter/s]
Best score: 0.2202: : 551iter [01:00,  3.37iter/s]
Best score: 0.2202: : 552iter [01:00,  3.98iter/s]
Best score: 0.2202: : 552iter [01:00,  3.98iter/s]
Best score: 0.2202: : 553iter [01:00,  4.52iter/s]
Best score: 0.2202: : 553iter [01:00,  4.52iter/s]
Best score: 0.2202: : 554iter [01:00,  5.06iter/s]
Best score: 0.2202: : 554iter [01:00,  5.06iter/s]
Best score: 0.2202: : 555iter [01:00,  5.42iter/s]
Best score: 0.2202: : 555iter [01:00,  5.42iter/s]
Best score: 0.2202: : 556iter [01:00,  5.76iter/s]
Best score: 0.2202: : 556iter [01:01,  5.76iter/s]
Best score: 0.2202: : 557iter [01:01,  6.15iter/s]
Best score: 0.2202: : 557iter [01:01,  6.15iter/s]
Best score: 0.2202: : 558iter [01:01,  6.41iter/s]
Best score: 0.2202: : 558iter [01:01,  6.41iter/s]
Best score: 0.2202: : 559iter [01:01,  6.70iter/s]
Best score: 0.2148: : 559iter [01:01,  6.70iter/s]
Best score: 0.2148: : 560iter [01:01,  6.69iter/s]
Best score: 0.2148: : 560iter [01:01,  6.69iter/s]
Best score: 0.2148: : 561iter [01:01,  6.81iter/s]
Best score: 0.2148: : 561iter [01:01,  6.81iter/s]
Best score: 0.2148: : 562iter [01:01,  6.72iter/s]
Best score: 0.2148: : 562iter [01:01,  6.72iter/s]
Best score: 0.2148: : 563iter [01:01,  6.89iter/s]
Best score: 0.2148: : 563iter [01:02,  6.89iter/s]
Best score: 0.2148: : 564iter [01:02,  7.16iter/s]
Best score: 0.2148: : 564iter [01:02,  7.16iter/s]
Best score: 0.2148: : 565iter [01:02,  7.49iter/s]
Best score: 0.2148: : 565iter [01:02,  7.49iter/s]
Best score: 0.2148: : 566iter [01:02,  8.02iter/s]
Best score: 0.2148: : 566iter [01:02,  8.02iter/s]
Best score: 0.2148: : 567iter [01:02,  8.02iter/s]
Best score: 0.2148: : 568iter [01:02,  9.18iter/s]
Best score: 0.2148: : 568iter [01:02,  9.18iter/s]
Best score: 0.2148: : 569iter [01:02,  9.18iter/s]
Best score: 0.2148: : 570iter [01:02,  9.84iter/s]
Best score: 0.2148: : 570iter [01:02,  9.84iter/s]
Best score: 0.2148: : 571iter [01:02,  9.84iter/s]
Best score: 0.2148: : 572iter [01:02, 10.49iter/s]
Best score: 0.2148: : 572iter [01:02, 10.49iter/s]
Best score: 0.2148: : 573iter [01:02, 10.49iter/s]
Best score: 0.2148: : 574iter [01:02, 10.90iter/s]
Best score: 0.2148: : 574iter [01:03, 10.90iter/s]
Best score: 0.2148: : 575iter [01:03, 10.90iter/s]
Best score: 0.2148: : 576iter [01:03, 11.21iter/s]
Best score: 0.2148: : 576iter [01:03, 11.21iter/s]
Best score: 0.2148: : 577iter [01:03, 11.21iter/s]
Best score: 0.2148: : 578iter [01:03, 11.42iter/s]
Best score: 0.2148: : 578iter [01:03, 11.42iter/s]
Best score: 0.2148: : 579iter [01:03, 11.42iter/s]
Best score: 0.2148: : 580iter [01:03, 11.31iter/s]
Best score: 0.2148: : 580iter [01:03, 11.31iter/s]
Best score: 0.2148: : 581iter [01:03, 11.31iter/s]
Best score: 0.2148: : 582iter [01:03, 11.49iter/s]
Best score: 0.2148: : 582iter [01:03, 11.49iter/s]
Best score: 0.2148: : 583iter [01:03, 11.49iter/s]
Best score: 0.2148: : 584iter [01:03, 10.47iter/s]
Best score: 0.2148: : 584iter [01:03, 10.47iter/s]
Best score: 0.2148: : 585iter [01:04, 10.47iter/s]
Best score: 0.2148: : 586iter [01:04, 10.67iter/s]
Best score: 0.2148: : 586iter [01:04, 10.67iter/s]
Best score: 0.2148: : 587iter [01:04, 10.67iter/s]
Best score: 0.2148: : 588iter [01:04, 11.04iter/s]
Best score: 0.2148: : 588iter [01:04, 11.04iter/s]
Best score: 0.2146: : 589iter [01:04, 11.04iter/s]
Best score: 0.2146: : 590iter [01:04, 11.09iter/s]
Best score: 0.2146: : 590iter [01:04, 11.09iter/s]
Best score: 0.2146: : 591iter [01:04, 11.09iter/s]
Best score: 0.2146: : 592iter [01:04, 11.33iter/s]
Best score: 0.2146: : 592iter [01:04, 11.33iter/s]
Best score: 0.2146: : 593iter [01:04, 11.33iter/s]
Best score: 0.2146: : 594iter [01:04, 11.39iter/s]
Best score: 0.2146: : 594iter [01:04, 11.39iter/s]
Best score: 0.2146: : 595iter [01:04, 11.39iter/s]
Best score: 0.2146: : 596iter [01:04, 11.07iter/s]
Best score: 0.2146: : 596iter [01:05, 11.07iter/s]
Best score: 0.2146: : 597iter [01:05, 11.07iter/s]
Best score: 0.2146: : 598iter [01:05, 11.27iter/s]
Best score: 0.2146: : 598iter [01:05, 11.27iter/s]
[ITER 600] Best: 0.2135
[PARAMS] Current best parameters:
  fx: 563.2921
  fy: 563.3125
  px: 985.2081
  py: 770.9119
  k1: -0.03979095
  k2: 0.00957586
  k3: -0.00174335
  k4: -0.00029372
  p1: 0.00270700
  p2: 0.00275458
  p3: 0.00582684
  p4: -0.01950797
  s1: -0.0070
  s2: 0.0184
  s3: -0.0141
  s4: 0.0201
  tilt_x: -0.0503
  tilt_y: -0.0016
  scale: 2.9829
  rotation: 0.2641

Best score: 0.2135: : 599iter [01:05, 11.27iter/s]
Best score: 0.2135: : 600iter [01:05, 10.93iter/s]
Best score: 0.2135: : 600iter [01:05, 10.93iter/s]
Best score: 0.2135: : 601iter [01:05, 10.93iter/s]
Best score: 0.2135: : 602iter [01:05,  7.42iter/s]
Best score: 0.2135: : 602iter [01:05,  7.42iter/s]
Best score: 0.2135: : 603iter [01:05,  7.42iter/s]
Best score: 0.2135: : 604iter [01:05,  8.39iter/s]
Best score: 0.2135: : 604iter [01:06,  8.39iter/s]
Best score: 0.2135: : 605iter [01:06,  8.39iter/s]
Best score: 0.2135: : 606iter [01:06,  9.23iter/s]
Best score: 0.2135: : 606iter [01:06,  9.23iter/s]
Best score: 0.2135: : 607iter [01:06,  9.23iter/s]
Best score: 0.2135: : 608iter [01:06,  9.88iter/s]
Best score: 0.2135: : 608iter [01:06,  9.88iter/s]
Best score: 0.2135: : 609iter [01:06,  9.88iter/s]
Best score: 0.2135: : 610iter [01:06,  9.90iter/s]
Best score: 0.2135: : 610iter [01:06,  9.90iter/s]
Best score: 0.2135: : 611iter [01:06,  9.90iter/s]
Best score: 0.2135: : 612iter [01:06, 10.46iter/s]
Best score: 0.2135: : 612iter [01:06, 10.46iter/s]
Best score: 0.2135: : 613iter [01:06, 10.46iter/s]
Best score: 0.2135: : 614iter [01:06, 10.87iter/s]
Best score: 0.2135: : 614iter [01:06, 10.87iter/s]
Best score: 0.2135: : 615iter [01:06, 10.87iter/s]
Best score: 0.2135: : 616iter [01:06, 11.21iter/s]
Best score: 0.2135: : 616iter [01:07, 11.21iter/s]
Best score: 0.2135: : 617iter [01:07, 11.21iter/s]
Best score: 0.2135: : 618iter [01:07, 11.41iter/s]
Best score: 0.2135: : 618iter [01:07, 11.41iter/s]
Best score: 0.2127: : 619iter [01:07, 11.41iter/s]
Best score: 0.2127: : 620iter [01:07, 11.40iter/s]
Best score: 0.2127: : 620iter [01:07, 11.40iter/s]
Best score: 0.2127: : 621iter [01:07, 11.40iter/s]
Best score: 0.2127: : 622iter [01:07, 11.55iter/s]
Best score: 0.2127: : 622iter [01:07, 11.55iter/s]
Best score: 0.2127: : 623iter [01:07, 11.55iter/s]
Best score: 0.2127: : 624iter [01:07, 11.59iter/s]
Best score: 0.2127: : 624iter [01:07, 11.59iter/s]
Best score: 0.2127: : 625iter [01:07, 11.59iter/s]
Best score: 0.2127: : 626iter [01:07, 11.59iter/s]
Best score: 0.2127: : 626iter [01:07, 11.59iter/s]
Best score: 0.2127: : 627iter [01:07, 11.59iter/s]
Best score: 0.2127: : 628iter [01:07, 11.63iter/s]
Best score: 0.2127: : 628iter [01:08, 11.63iter/s]
Best score: 0.2088: : 629iter [01:08, 11.63iter/s]
Best score: 0.2088: : 630iter [01:08, 11.54iter/s]
Best score: 0.2088: : 630iter [01:08, 11.54iter/s]
Best score: 0.2088: : 631iter [01:08, 11.54iter/s]
Best score: 0.2088: : 632iter [01:08, 11.65iter/s]
Best score: 0.2088: : 632iter [01:08, 11.65iter/s]
Best score: 0.2088: : 633iter [01:08, 11.65iter/s]
Best score: 0.2088: : 634iter [01:08, 10.47iter/s]
Best score: 0.2088: : 634iter [01:08, 10.47iter/s]
Best score: 0.2088: : 635iter [01:08, 10.47iter/s]
Best score: 0.2088: : 636iter [01:08,  9.08iter/s]
Best score: 0.2088: : 636iter [01:08,  9.08iter/s]
Best score: 0.2088: : 637iter [01:08,  8.89iter/s]
Best score: 0.2088: : 637iter [01:09,  8.89iter/s]
Best score: 0.2088: : 638iter [01:09,  8.56iter/s]
Best score: 0.2088: : 638iter [01:09,  8.56iter/s]
Best score: 0.2088: : 639iter [01:09,  8.35iter/s]
Best score: 0.2080: : 639iter [01:09,  8.35iter/s]
Best score: 0.2080: : 640iter [01:09,  7.86iter/s]
Best score: 0.2080: : 640iter [01:09,  7.86iter/s]
Best score: 0.2080: : 641iter [01:09,  7.77iter/s]
Best score: 0.2080: : 641iter [01:09,  7.77iter/s]
Best score: 0.2080: : 642iter [01:09,  7.71iter/s]
Best score: 0.2080: : 642iter [01:09,  7.71iter/s]
Best score: 0.2080: : 643iter [01:09,  7.41iter/s]
Best score: 0.2080: : 643iter [01:09,  7.41iter/s]
Best score: 0.2080: : 644iter [01:09,  7.47iter/s]
Best score: 0.2080: : 644iter [01:10,  7.47iter/s]
Best score: 0.2080: : 645iter [01:10,  7.37iter/s]
Best score: 0.2080: : 645iter [01:10,  7.37iter/s]
Best score: 0.2080: : 646iter [01:10,  7.20iter/s]
Best score: 0.2080: : 646iter [01:10,  7.20iter/s]
Best score: 0.2080: : 647iter [01:10,  7.02iter/s]
Best score: 0.2080: : 647iter [01:10,  7.02iter/s]
Best score: 0.2080: : 648iter [01:10,  7.00iter/s]
Best score: 0.2080: : 648iter [01:10,  7.00iter/s]
Best score: 0.2080: : 649iter [01:10,  6.87iter/s]
[ITER 650] Best: 0.2080
[PARAMS] Current best parameters:
  fx: 565.6643
  fy: 565.7053
  px: 984.2933
  py: 770.4997
  k1: -0.04578366
  k2: 0.01559967
  k3: -0.00532281
  k4: 0.00055405
  p1: 0.00099627
  p2: 0.00155837
  p3: 0.01041085
  p4: -0.01973361
  s1: -0.0125
  s2: 0.0197
  s3: -0.0175
  s4: 0.0201
  tilt_x: -0.0484
  tilt_y: 0.0005
  scale: 2.9847
  rotation: 0.2481

Best score: 0.2080: : 649iter [01:10,  6.87iter/s]
Best score: 0.2080: : 650iter [01:10,  6.68iter/s]
Best score: 0.2080: : 650iter [01:11,  6.68iter/s]
Best score: 0.2080: : 651iter [01:11,  3.49iter/s]
Best score: 0.2080: : 651iter [01:11,  3.49iter/s]
Best score: 0.2080: : 652iter [01:11,  4.13iter/s]
Best score: 0.2080: : 652iter [01:11,  4.13iter/s]
Best score: 0.2080: : 653iter [01:11,  4.75iter/s]
Best score: 0.2080: : 653iter [01:11,  4.75iter/s]
Best score: 0.2080: : 654iter [01:11,  5.36iter/s]
Best score: 0.2080: : 654iter [01:11,  5.36iter/s]
Best score: 0.2080: : 655iter [01:11,  5.90iter/s]
Best score: 0.2080: : 655iter [01:12,  5.90iter/s]
Best score: 0.2080: : 656iter [01:12,  6.26iter/s]
Best score: 0.2080: : 656iter [01:12,  6.26iter/s]
Best score: 0.2080: : 657iter [01:12,  6.36iter/s]
Best score: 0.2080: : 657iter [01:12,  6.36iter/s]
Best score: 0.2080: : 658iter [01:12,  6.50iter/s]
Best score: 0.2080: : 658iter [01:12,  6.50iter/s]
Best score: 0.2080: : 659iter [01:12,  6.69iter/s]
Best score: 0.2080: : 659iter [01:12,  6.69iter/s]
Best score: 0.2080: : 660iter [01:12,  6.73iter/s]
Best score: 0.2080: : 660iter [01:12,  6.73iter/s]
Best score: 0.2080: : 661iter [01:12,  6.74iter/s]
Best score: 0.2080: : 661iter [01:12,  6.74iter/s]
Best score: 0.2080: : 662iter [01:12,  6.78iter/s]
Best score: 0.2080: : 662iter [01:13,  6.78iter/s]
Best score: 0.2080: : 663iter [01:13,  6.99iter/s]
Best score: 0.2080: : 663iter [01:13,  6.99iter/s]
Best score: 0.2080: : 664iter [01:13,  7.16iter/s]
Best score: 0.2080: : 664iter [01:13,  7.16iter/s]
Best score: 0.2080: : 665iter [01:13,  7.27iter/s]
Best score: 0.2080: : 665iter [01:13,  7.27iter/s]
Best score: 0.2080: : 666iter [01:13,  7.30iter/s]
Best score: 0.2080: : 666iter [01:13,  7.30iter/s]
Best score: 0.2080: : 667iter [01:13,  7.23iter/s]
Best score: 0.2080: : 667iter [01:13,  7.23iter/s]
Best score: 0.2080: : 668iter [01:13,  7.23iter/s]
Best score: 0.2080: : 668iter [01:13,  7.23iter/s]
Best score: 0.2080: : 669iter [01:13,  7.11iter/s]
Best score: 0.2080: : 669iter [01:14,  7.11iter/s]
Best score: 0.2080: : 670iter [01:14,  6.80iter/s]
Best score: 0.2080: : 670iter [01:14,  6.80iter/s]
Best score: 0.2080: : 671iter [01:14,  7.00iter/s]
Best score: 0.2080: : 671iter [01:14,  7.00iter/s]
Best score: 0.2080: : 672iter [01:14,  7.07iter/s]
Best score: 0.2080: : 672iter [01:14,  7.07iter/s]
Best score: 0.2080: : 673iter [01:14,  7.17iter/s]
Best score: 0.2080: : 673iter [01:14,  7.17iter/s]
Best score: 0.2080: : 674iter [01:14,  7.26iter/s]
Best score: 0.2080: : 674iter [01:14,  7.26iter/s]
Best score: 0.2080: : 675iter [01:14,  7.25iter/s]
Best score: 0.2080: : 675iter [01:14,  7.25iter/s]
Best score: 0.2080: : 676iter [01:14,  7.40iter/s]
Best score: 0.2080: : 676iter [01:15,  7.40iter/s]
Best score: 0.2080: : 677iter [01:15,  7.49iter/s]
Best score: 0.2080: : 677iter [01:15,  7.49iter/s]
Best score: 0.2080: : 678iter [01:15,  7.49iter/s]
Best score: 0.2080: : 678iter [01:15,  7.49iter/s]
Best score: 0.2080: : 679iter [01:15,  7.56iter/s]
Best score: 0.2080: : 679iter [01:15,  7.56iter/s]
Best score: 0.2080: : 680iter [01:15,  7.33iter/s]
Best score: 0.2080: : 680iter [01:15,  7.33iter/s]
Best score: 0.2080: : 681iter [01:15,  7.53iter/s]
Best score: 0.2080: : 681iter [01:15,  7.53iter/s]
Best score: 0.2080: : 682iter [01:15,  7.66iter/s]
Best score: 0.2080: : 682iter [01:15,  7.66iter/s]
Best score: 0.2080: : 683iter [01:15,  7.87iter/s]
Best score: 0.2080: : 683iter [01:15,  7.87iter/s]
Best score: 0.2080: : 684iter [01:15,  8.23iter/s]
Best score: 0.2080: : 684iter [01:16,  8.23iter/s]
Best score: 0.2080: : 685iter [01:16,  8.23iter/s]
Best score: 0.2080: : 686iter [01:16,  8.89iter/s]
Best score: 0.2080: : 686iter [01:16,  8.89iter/s]
Best score: 0.2080: : 687iter [01:16,  8.59iter/s]
Best score: 0.2080: : 687iter [01:16,  8.59iter/s]
Best score: 0.2080: : 688iter [01:16,  8.38iter/s]
Best score: 0.2080: : 688iter [01:16,  8.38iter/s]
Best score: 0.2080: : 689iter [01:16,  8.03iter/s]
Best score: 0.2068: : 689iter [01:16,  8.03iter/s]
Best score: 0.2068: : 690iter [01:16,  7.58iter/s]
Best score: 0.2068: : 690iter [01:16,  7.58iter/s]
Best score: 0.2068: : 691iter [01:16,  7.46iter/s]
Best score: 0.2068: : 691iter [01:16,  7.46iter/s]
Best score: 0.2068: : 692iter [01:16,  7.34iter/s]
Best score: 0.2068: : 692iter [01:17,  7.34iter/s]
Best score: 0.2068: : 693iter [01:17,  7.30iter/s]
Best score: 0.2068: : 693iter [01:17,  7.30iter/s]
Best score: 0.2068: : 694iter [01:17,  7.29iter/s]
Best score: 0.2068: : 694iter [01:17,  7.29iter/s]
Best score: 0.2068: : 695iter [01:17,  7.34iter/s]
Best score: 0.2068: : 695iter [01:17,  7.34iter/s]
Best score: 0.2068: : 696iter [01:17,  7.39iter/s]
Best score: 0.2068: : 696iter [01:17,  7.39iter/s]
Best score: 0.2068: : 697iter [01:17,  7.23iter/s]
Best score: 0.2068: : 697iter [01:17,  7.23iter/s]
Best score: 0.2068: : 698iter [01:17,  7.12iter/s]
Best score: 0.2068: : 698iter [01:17,  7.12iter/s]
Best score: 0.2068: : 699iter [01:17,  7.14iter/s]
[ITER 700] Best: 0.2068
[PARAMS] Current best parameters:
  fx: 564.5621
  fy: 564.6115
  px: 984.8047
  py: 770.7684
  k1: -0.04548933
  k2: 0.01811492
  k3: -0.00767981
  k4: 0.00119911
  p1: 0.00122017
  p2: 0.00299138
  p3: 0.00895770
  p4: -0.01966297
  s1: -0.0120
  s2: 0.0195
  s3: -0.0160
  s4: 0.0202
  tilt_x: -0.0478
  tilt_y: 0.0007
  scale: 2.9845
  rotation: 0.2522

Best score: 0.2068: : 699iter [01:18,  7.14iter/s]
Best score: 0.2068: : 700iter [01:18,  7.05iter/s]
Best score: 0.2068: : 700iter [01:18,  7.05iter/s]
Best score: 0.2068: : 701iter [01:18,  3.65iter/s]
Best score: 0.2068: : 701iter [01:18,  3.65iter/s]
Best score: 0.2068: : 702iter [01:18,  3.65iter/s]
Best score: 0.2068: : 703iter [01:18,  5.33iter/s]
Best score: 0.2068: : 703iter [01:18,  5.33iter/s]
Best score: 0.2068: : 704iter [01:19,  5.33iter/s]
Best score: 0.2068: : 705iter [01:19,  6.83iter/s]
Best score: 0.2068: : 705iter [01:19,  6.83iter/s]
Best score: 0.2068: : 706iter [01:19,  6.83iter/s]
Best score: 0.2068: : 707iter [01:19,  8.05iter/s]
Best score: 0.2068: : 707iter [01:19,  8.05iter/s]
Best score: 0.2068: : 708iter [01:19,  8.05iter/s]
Best score: 0.2068: : 709iter [01:19,  9.05iter/s]
Best score: 0.2067: : 709iter [01:19,  9.05iter/s]
Best score: 0.2067: : 710iter [01:19,  9.05iter/s]
Best score: 0.2067: : 711iter [01:19,  8.76iter/s]
Best score: 0.2067: : 711iter [01:19,  8.76iter/s]
Best score: 0.2067: : 712iter [01:19,  8.76iter/s]
Best score: 0.2067: : 713iter [01:19,  9.45iter/s]
Best score: 0.2067: : 713iter [01:19,  9.45iter/s]
Best score: 0.2067: : 714iter [01:19,  9.45iter/s]
Best score: 0.2067: : 715iter [01:19, 10.05iter/s]
Best score: 0.2067: : 715iter [01:20, 10.05iter/s]
Best score: 0.2067: : 716iter [01:20, 10.05iter/s]
Best score: 0.2067: : 717iter [01:20, 10.52iter/s]
Best score: 0.2067: : 717iter [01:20, 10.52iter/s]
Best score: 0.2067: : 718iter [01:20, 10.52iter/s]
Best score: 0.2067: : 719iter [01:20, 10.87iter/s]
Best score: 0.2053: : 719iter [01:20, 10.87iter/s]
Best score: 0.2053: : 720iter [01:20, 10.87iter/s]
Best score: 0.2053: : 721iter [01:20, 10.76iter/s]
Best score: 0.2053: : 721iter [01:20, 10.76iter/s]
Best score: 0.2053: : 722iter [01:20, 10.76iter/s]
Best score: 0.2053: : 723iter [01:20,  8.85iter/s]
Best score: 0.2053: : 723iter [01:20,  8.85iter/s]
Best score: 0.2053: : 724iter [01:20,  8.85iter/s]
Best score: 0.2053: : 725iter [01:20,  9.43iter/s]
Best score: 0.2053: : 725iter [01:21,  9.43iter/s]
Best score: 0.2053: : 726iter [01:21,  9.43iter/s]
Best score: 0.2053: : 727iter [01:21, 10.04iter/s]
Best score: 0.2053: : 727iter [01:21, 10.04iter/s]
Best score: 0.2053: : 728iter [01:21, 10.04iter/s]
Best score: 0.2053: : 729iter [01:21, 10.50iter/s]
Best score: 0.2051: : 729iter [01:21, 10.50iter/s]
Best score: 0.2051: : 730iter [01:21, 10.50iter/s]
Best score: 0.2051: : 731iter [01:21, 10.69iter/s]
Best score: 0.2051: : 731iter [01:21, 10.69iter/s]
Best score: 0.2051: : 732iter [01:21, 10.69iter/s]
Best score: 0.2051: : 733iter [01:21, 10.99iter/s]
Best score: 0.2051: : 733iter [01:21, 10.99iter/s]
Best score: 0.2051: : 734iter [01:21, 10.99iter/s]
Best score: 0.2051: : 735iter [01:21, 11.17iter/s]
Best score: 0.2051: : 735iter [01:21, 11.17iter/s]
Best score: 0.2051: : 736iter [01:22, 11.17iter/s]
Best score: 0.2051: : 737iter [01:22, 11.14iter/s]
Best score: 0.2051: : 737iter [01:22, 11.14iter/s]
Best score: 0.2051: : 738iter [01:22, 11.14iter/s]
Best score: 0.2051: : 739iter [01:22, 11.04iter/s]
Best score: 0.2046: : 739iter [01:22, 11.04iter/s]
Best score: 0.2046: : 740iter [01:22, 11.04iter/s]
Best score: 0.2046: : 741iter [01:22, 11.08iter/s]
Best score: 0.2046: : 741iter [01:22, 11.08iter/s]
Best score: 0.2046: : 742iter [01:22, 11.08iter/s]
Best score: 0.2046: : 743iter [01:22, 11.28iter/s]
Best score: 0.2046: : 743iter [01:22, 11.28iter/s]
Best score: 0.2046: : 744iter [01:22, 11.28iter/s]
Best score: 0.2046: : 745iter [01:22, 11.44iter/s]
Best score: 0.2046: : 745iter [01:22, 11.44iter/s]
Best score: 0.2046: : 746iter [01:22, 11.44iter/s]
Best score: 0.2046: : 747iter [01:22, 11.53iter/s]
Best score: 0.2046: : 747iter [01:22, 11.53iter/s]
Best score: 0.2046: : 748iter [01:23, 11.53iter/s]
Best score: 0.2046: : 749iter [01:23, 11.56iter/s]
[ITER 750] Best: 0.2043
[PARAMS] Current best parameters:
  fx: 568.2564
  fy: 568.3263
  px: 983.8323
  py: 769.3327
  k1: -0.05285224
  k2: 0.02353794
  k3: -0.01018978
  k4: 0.00167016
  p1: 0.00002077
  p2: 0.00131883
  p3: 0.01526958
  p4: -0.02193921
  s1: -0.0182
  s2: 0.0219
  s3: -0.0236
  s4: 0.0231
  tilt_x: -0.0527
  tilt_y: 0.0021
  scale: 2.9878
  rotation: 0.2464

Best score: 0.2043: : 749iter [01:23, 11.56iter/s]
Best score: 0.2043: : 750iter [01:23, 11.56iter/s]
Best score: 0.2043: : 751iter [01:23,  7.53iter/s]
Best score: 0.2043: : 751iter [01:23,  7.53iter/s]
Best score: 0.2043: : 752iter [01:23,  7.53iter/s]
Best score: 0.2043: : 753iter [01:23,  8.46iter/s]
Best score: 0.2043: : 753iter [01:23,  8.46iter/s]
Best score: 0.2043: : 754iter [01:23,  8.46iter/s]
Best score: 0.2043: : 755iter [01:23,  9.23iter/s]
Best score: 0.2043: : 755iter [01:23,  9.23iter/s]
Best score: 0.2043: : 756iter [01:24,  9.23iter/s]
Best score: 0.2043: : 757iter [01:24,  9.49iter/s]
Best score: 0.2043: : 757iter [01:24,  9.49iter/s]
Best score: 0.2043: : 758iter [01:24,  9.49iter/s]
Best score: 0.2043: : 759iter [01:24,  8.57iter/s]
Best score: 0.2038: : 759iter [01:24,  8.57iter/s]
Best score: 0.2038: : 760iter [01:24,  8.08iter/s]
Best score: 0.2038: : 760iter [01:24,  8.08iter/s]
Best score: 0.2038: : 761iter [01:24,  7.87iter/s]
Best score: 0.2038: : 761iter [01:24,  7.87iter/s]
Best score: 0.2038: : 762iter [01:24,  7.67iter/s]
Best score: 0.2038: : 762iter [01:24,  7.67iter/s]
Best score: 0.2038: : 763iter [01:24,  7.54iter/s]
Best score: 0.2038: : 763iter [01:25,  7.54iter/s]
Best score: 0.2038: : 764iter [01:25,  7.28iter/s]
Best score: 0.2038: : 764iter [01:25,  7.28iter/s]
Best score: 0.2038: : 765iter [01:25,  7.10iter/s]
Best score: 0.2038: : 765iter [01:25,  7.10iter/s]
Best score: 0.2038: : 766iter [01:25,  7.15iter/s]
Best score: 0.2038: : 766iter [01:25,  7.15iter/s]
Best score: 0.2038: : 767iter [01:25,  7.24iter/s]
Best score: 0.2038: : 767iter [01:25,  7.24iter/s]
Best score: 0.2038: : 768iter [01:25,  7.21iter/s]
Best score: 0.2038: : 768iter [01:25,  7.21iter/s]
Best score: 0.2038: : 769iter [01:25,  7.10iter/s]
Best score: 0.2035: : 769iter [01:25,  7.10iter/s]
Best score: 0.2035: : 770iter [01:25,  6.82iter/s]
Best score: 0.2035: : 770iter [01:26,  6.82iter/s]
Best score: 0.2035: : 771iter [01:26,  6.80iter/s]
Best score: 0.2035: : 771iter [01:26,  6.80iter/s]
Best score: 0.2035: : 772iter [01:26,  6.86iter/s]
Best score: 0.2035: : 772iter [01:26,  6.86iter/s]
Best score: 0.2035: : 773iter [01:26,  7.03iter/s]
Best score: 0.2035: : 773iter [01:26,  7.03iter/s]
Best score: 0.2035: : 774iter [01:26,  7.06iter/s]
Best score: 0.2035: : 774iter [01:26,  7.06iter/s]
Best score: 0.2035: : 775iter [01:26,  7.09iter/s]
Best score: 0.2035: : 775iter [01:26,  7.09iter/s]
Best score: 0.2035: : 776iter [01:26,  7.09iter/s]
Best score: 0.2035: : 776iter [01:26,  7.09iter/s]
Best score: 0.2035: : 777iter [01:26,  7.15iter/s]
Best score: 0.2035: : 777iter [01:27,  7.15iter/s]
Best score: 0.2035: : 778iter [01:27,  7.26iter/s]
Best score: 0.2035: : 778iter [01:27,  7.26iter/s]
Best score: 0.2035: : 779iter [01:27,  7.33iter/s]
Best score: 0.2027: : 779iter [01:27,  7.33iter/s]
Best score: 0.2027: : 780iter [01:27,  7.25iter/s]
Best score: 0.2027: : 780iter [01:27,  7.25iter/s]
Best score: 0.2027: : 781iter [01:27,  7.33iter/s]
Best score: 0.2027: : 781iter [01:27,  7.33iter/s]
Best score: 0.2027: : 782iter [01:27,  7.32iter/s]
Best score: 0.2027: : 782iter [01:27,  7.32iter/s]
Best score: 0.2027: : 783iter [01:27,  7.37iter/s]
Best score: 0.2027: : 783iter [01:27,  7.37iter/s]
Best score: 0.2027: : 784iter [01:27,  7.42iter/s]
Best score: 0.2027: : 784iter [01:28,  7.42iter/s]
Best score: 0.2027: : 785iter [01:28,  7.44iter/s]
Best score: 0.2027: : 785iter [01:28,  7.44iter/s]
Best score: 0.2027: : 786iter [01:28,  7.44iter/s]
Best score: 0.2027: : 786iter [01:28,  7.44iter/s]
Best score: 0.2027: : 787iter [01:28,  7.45iter/s]
Best score: 0.2027: : 787iter [01:28,  7.45iter/s]
Best score: 0.2027: : 788iter [01:28,  7.17iter/s]
Best score: 0.2027: : 788iter [01:28,  7.17iter/s]
Best score: 0.2027: : 789iter [01:28,  7.28iter/s]
Best score: 0.2023: : 789iter [01:28,  7.28iter/s]
Best score: 0.2023: : 790iter [01:28,  7.01iter/s]
Best score: 0.2023: : 790iter [01:28,  7.01iter/s]
Best score: 0.2023: : 791iter [01:28,  7.19iter/s]
Best score: 0.2023: : 791iter [01:28,  7.19iter/s]
Best score: 0.2023: : 792iter [01:28,  7.37iter/s]
Best score: 0.2023: : 792iter [01:29,  7.37iter/s]
Best score: 0.2023: : 793iter [01:29,  7.47iter/s]
Best score: 0.2023: : 793iter [01:29,  7.47iter/s]
Best score: 0.2023: : 794iter [01:29,  7.63iter/s]
Best score: 0.2023: : 794iter [01:29,  7.63iter/s]
Best score: 0.2023: : 795iter [01:29,  7.55iter/s]
Best score: 0.2023: : 795iter [01:29,  7.55iter/s]
Best score: 0.2023: : 796iter [01:29,  7.40iter/s]
Best score: 0.2023: : 796iter [01:29,  7.40iter/s]
Best score: 0.2023: : 797iter [01:29,  7.35iter/s]
Best score: 0.2023: : 797iter [01:29,  7.35iter/s]
Best score: 0.2023: : 798iter [01:29,  7.32iter/s]
Best score: 0.2023: : 798iter [01:29,  7.32iter/s]
Best score: 0.2023: : 799iter [01:29,  7.13iter/s]
[ITER 800] Best: 0.2023
[PARAMS] Current best parameters:
  fx: 565.9974
  fy: 566.1017
  px: 983.2891
  py: 768.6358
  k1: -0.05122675
  k2: 0.02572112
  k3: -0.01258089
  k4: 0.00237442
  p1: -0.00149215
  p2: 0.00094920
  p3: 0.01326626
  p4: -0.01694643
  s1: -0.0154
  s2: 0.0162
  s3: -0.0206
  s4: 0.0182
  tilt_x: -0.0531
  tilt_y: 0.0043
  scale: 2.9884
  rotation: 0.2490

Best score: 0.2023: : 799iter [01:30,  7.13iter/s]
Best score: 0.2023: : 800iter [01:30,  6.90iter/s]
Best score: 0.2023: : 800iter [01:30,  6.90iter/s]
Best score: 0.2023: : 801iter [01:30,  3.30iter/s]
Best score: 0.2023: : 801iter [01:30,  3.30iter/s]
Best score: 0.2023: : 802iter [01:30,  3.85iter/s]
Best score: 0.2023: : 802iter [01:31,  3.85iter/s]
Best score: 0.2023: : 803iter [01:31,  4.45iter/s]
Best score: 0.2023: : 803iter [01:31,  4.45iter/s]
Best score: 0.2023: : 804iter [01:31,  4.96iter/s]
Best score: 0.2023: : 804iter [01:31,  4.96iter/s]
Best score: 0.2023: : 805iter [01:31,  5.38iter/s]
Best score: 0.2023: : 805iter [01:31,  5.38iter/s]
Best score: 0.2023: : 806iter [01:31,  6.00iter/s]
Best score: 0.2023: : 806iter [01:31,  6.00iter/s]
Best score: 0.2023: : 807iter [01:31,  6.71iter/s]
Best score: 0.2023: : 807iter [01:31,  6.71iter/s]
Best score: 0.2023: : 808iter [01:31,  7.26iter/s]
Best score: 0.2023: : 808iter [01:31,  7.26iter/s]
Best score: 0.2023: : 809iter [01:31,  6.98iter/s]
Best score: 0.2023: : 809iter [01:32,  6.98iter/s]
Best score: 0.2023: : 810iter [01:32,  6.98iter/s]
Best score: 0.2023: : 810iter [01:32,  6.98iter/s]
Best score: 0.2023: : 811iter [01:32,  7.13iter/s]
Best score: 0.2023: : 811iter [01:32,  7.13iter/s]
Best score: 0.2023: : 812iter [01:32,  7.23iter/s]
Best score: 0.2023: : 812iter [01:32,  7.23iter/s]
Best score: 0.2023: : 813iter [01:32,  7.33iter/s]
Best score: 0.2023: : 813iter [01:32,  7.33iter/s]
Best score: 0.2023: : 814iter [01:32,  7.26iter/s]
Best score: 0.2023: : 814iter [01:32,  7.26iter/s]
Best score: 0.2023: : 815iter [01:32,  7.34iter/s]
Best score: 0.2023: : 815iter [01:32,  7.34iter/s]
Best score: 0.2023: : 816iter [01:32,  7.42iter/s]
Best score: 0.2023: : 816iter [01:32,  7.42iter/s]
Best score: 0.2023: : 817iter [01:32,  7.47iter/s]
Best score: 0.2023: : 817iter [01:33,  7.47iter/s]
Best score: 0.2023: : 818iter [01:33,  7.52iter/s]
Best score: 0.2023: : 818iter [01:33,  7.52iter/s]
Best score: 0.2023: : 819iter [01:33,  7.53iter/s]
Best score: 0.2022: : 819iter [01:33,  7.53iter/s]
Best score: 0.2022: : 820iter [01:33,  7.28iter/s]
Best score: 0.2022: : 820iter [01:33,  7.28iter/s]
Best score: 0.2022: : 821iter [01:33,  7.38iter/s]
Best score: 0.2022: : 821iter [01:33,  7.38iter/s]
Best score: 0.2022: : 822iter [01:33,  7.44iter/s]
Best score: 0.2022: : 822iter [01:33,  7.44iter/s]
Best score: 0.2022: : 823iter [01:33,  7.34iter/s]
Best score: 0.2022: : 823iter [01:33,  7.34iter/s]
Best score: 0.2022: : 824iter [01:33,  7.24iter/s]
Best score: 0.2022: : 824iter [01:34,  7.24iter/s]
Best score: 0.2022: : 825iter [01:34,  7.22iter/s]
Best score: 0.2022: : 825iter [01:34,  7.22iter/s]
Best score: 0.2022: : 826iter [01:34,  7.10iter/s]
Best score: 0.2022: : 826iter [01:34,  7.10iter/s]
Best score: 0.2022: : 827iter [01:34,  7.11iter/s]
Best score: 0.2022: : 827iter [01:34,  7.11iter/s]
Best score: 0.2022: : 828iter [01:34,  6.97iter/s]
Best score: 0.2022: : 828iter [01:34,  6.97iter/s]
Best score: 0.2022: : 829iter [01:34,  7.08iter/s]
Best score: 0.2022: : 829iter [01:34,  7.08iter/s]
Best score: 0.2022: : 830iter [01:34,  6.87iter/s]
Best score: 0.2022: : 830iter [01:34,  6.87iter/s]
Best score: 0.2022: : 831iter [01:34,  7.24iter/s]
Best score: 0.2022: : 831iter [01:34,  7.24iter/s]
Best score: 0.2022: : 832iter [01:35,  7.24iter/s]
Best score: 0.2022: : 833iter [01:35,  8.66iter/s]
Best score: 0.2022: : 833iter [01:35,  8.66iter/s]
Best score: 0.2022: : 834iter [01:35,  8.66iter/s]
Best score: 0.2022: : 835iter [01:35,  9.67iter/s]
Best score: 0.2022: : 835iter [01:35,  9.67iter/s]
Best score: 0.2022: : 836iter [01:35,  9.67iter/s]
Best score: 0.2022: : 837iter [01:35, 10.35iter/s]
Best score: 0.2022: : 837iter [01:35, 10.35iter/s]
Best score: 0.2022: : 838iter [01:35, 10.35iter/s]
Best score: 0.2022: : 839iter [01:35, 10.80iter/s]
Best score: 0.2021: : 839iter [01:35, 10.80iter/s]
Best score: 0.2021: : 840iter [01:35, 10.80iter/s]
Best score: 0.2021: : 841iter [01:35, 10.07iter/s]
Best score: 0.2021: : 841iter [01:35, 10.07iter/s]
Best score: 0.2021: : 842iter [01:36, 10.07iter/s]
Best score: 0.2021: : 843iter [01:36, 10.11iter/s]
Best score: 0.2021: : 843iter [01:36, 10.11iter/s]
Best score: 0.2021: : 844iter [01:36, 10.11iter/s]
Best score: 0.2021: : 845iter [01:36, 10.60iter/s]
Best score: 0.2021: : 845iter [01:36, 10.60iter/s]
Best score: 0.2021: : 846iter [01:36, 10.60iter/s]
Best score: 0.2021: : 847iter [01:36, 10.95iter/s]
Best score: 0.2021: : 847iter [01:36, 10.95iter/s]
Best score: 0.2021: : 848iter [01:36, 10.95iter/s]
Best score: 0.2021: : 849iter [01:36, 11.29iter/s]
[ITER 850] Best: 0.2019
[PARAMS] Current best parameters:
  fx: 565.0112
  fy: 565.1627
  px: 983.7007
  py: 768.3821
  k1: -0.05035745
  k2: 0.02617566
  k3: -0.01321101
  k4: 0.00256798
  p1: -0.00128955
  p2: 0.00116989
  p3: 0.01140119
  p4: -0.01641316
  s1: -0.0135
  s2: 0.0158
  s3: -0.0191
  s4: 0.0178
  tilt_x: -0.0548
  tilt_y: 0.0026
  scale: 2.9892
  rotation: 0.2502

Best score: 0.2019: : 849iter [01:36, 11.29iter/s]
Best score: 0.2019: : 850iter [01:36, 11.29iter/s]
Best score: 0.2019: : 851iter [01:36,  7.45iter/s]
Best score: 0.2019: : 851iter [01:37,  7.45iter/s]
Best score: 0.2019: : 852iter [01:37,  7.45iter/s]
Best score: 0.2019: : 853iter [01:37,  8.44iter/s]
Best score: 0.2019: : 853iter [01:37,  8.44iter/s]
Best score: 0.2019: : 854iter [01:37,  8.44iter/s]
Best score: 0.2019: : 855iter [01:37,  9.30iter/s]
Best score: 0.2019: : 855iter [01:37,  9.30iter/s]
Best score: 0.2019: : 856iter [01:37,  9.30iter/s]
Best score: 0.2019: : 857iter [01:37,  9.94iter/s]
Best score: 0.2019: : 857iter [01:37,  9.94iter/s]
Best score: 0.2019: : 858iter [01:37,  9.94iter/s]
Best score: 0.2019: : 859iter [01:37, 10.42iter/s]
Best score: 0.2018: : 859iter [01:37, 10.42iter/s]
Best score: 0.2018: : 860iter [01:37, 10.42iter/s]
Best score: 0.2018: : 861iter [01:37, 10.68iter/s]
Best score: 0.2018: : 861iter [01:37, 10.68iter/s]
Best score: 0.2018: : 862iter [01:37, 10.68iter/s]
Best score: 0.2018: : 863iter [01:37, 11.04iter/s]
Best score: 0.2018: : 863iter [01:38, 11.04iter/s]
Best score: 0.2018: : 864iter [01:38, 11.04iter/s]
Best score: 0.2018: : 865iter [01:38, 11.30iter/s]
Best score: 0.2018: : 865iter [01:38, 11.30iter/s]
Best score: 0.2018: : 866iter [01:38, 11.30iter/s]
Best score: 0.2018: : 867iter [01:38, 11.49iter/s]
Best score: 0.2018: : 867iter [01:38, 11.49iter/s]
Best score: 0.2018: : 868iter [01:38, 11.49iter/s]
Best score: 0.2018: : 869iter [01:38, 11.62iter/s]
Best score: 0.2015: : 869iter [01:38, 11.62iter/s]
Best score: 0.2015: : 870iter [01:38, 11.62iter/s]
Best score: 0.2015: : 871iter [01:38, 11.43iter/s]
Best score: 0.2015: : 871iter [01:38, 11.43iter/s]
Best score: 0.2015: : 872iter [01:38, 11.43iter/s]
Best score: 0.2015: : 873iter [01:38, 11.58iter/s]
Best score: 0.2015: : 873iter [01:38, 11.58iter/s]
Best score: 0.2015: : 874iter [01:39, 11.58iter/s]
Best score: 0.2015: : 875iter [01:39, 11.71iter/s]
Best score: 0.2015: : 875iter [01:39, 11.71iter/s]
Best score: 0.2015: : 876iter [01:39, 11.71iter/s]
Best score: 0.2015: : 877iter [01:39, 11.83iter/s]
Best score: 0.2015: : 877iter [01:39, 11.83iter/s]
Best score: 0.2015: : 878iter [01:39, 11.83iter/s]
Best score: 0.2015: : 879iter [01:39, 11.87iter/s]
Best score: 0.2015: : 879iter [01:39, 11.87iter/s]
Best score: 0.2015: : 880iter [01:39, 11.87iter/s]
Best score: 0.2015: : 881iter [01:39, 11.70iter/s]
Best score: 0.2015: : 881iter [01:39, 11.70iter/s]
Best score: 0.2015: : 882iter [01:39, 11.70iter/s]
Best score: 0.2015: : 883iter [01:39, 11.83iter/s]
Best score: 0.2015: : 883iter [01:39, 11.83iter/s]
Best score: 0.2015: : 884iter [01:39, 11.83iter/s]
Best score: 0.2015: : 885iter [01:39, 11.86iter/s]
Best score: 0.2015: : 885iter [01:39, 11.86iter/s]
Best score: 0.2015: : 886iter [01:40, 11.86iter/s]
Best score: 0.2015: : 887iter [01:40, 11.85iter/s]
Best score: 0.2015: : 887iter [01:40, 11.85iter/s]
Best score: 0.2015: : 888iter [01:40, 11.85iter/s]
Best score: 0.2015: : 889iter [01:40, 11.93iter/s]
Best score: 0.2014: : 889iter [01:40, 11.93iter/s]
Best score: 0.2014: : 890iter [01:40, 11.93iter/s]
Best score: 0.2014: : 891iter [01:40, 11.75iter/s]
Best score: 0.2014: : 891iter [01:40, 11.75iter/s]
Best score: 0.2014: : 892iter [01:40, 11.75iter/s]
Best score: 0.2014: : 893iter [01:40, 11.86iter/s]
Best score: 0.2014: : 893iter [01:40, 11.86iter/s]
Best score: 0.2014: : 894iter [01:40, 11.86iter/s]
Best score: 0.2014: : 895iter [01:40, 11.91iter/s]
Best score: 0.2014: : 895iter [01:40, 11.91iter/s]
Best score: 0.2014: : 896iter [01:40, 11.91iter/s]
Best score: 0.2014: : 897iter [01:40, 11.93iter/s]
Best score: 0.2014: : 897iter [01:40, 11.93iter/s]
Best score: 0.2014: : 898iter [01:41, 11.93iter/s]
Best score: 0.2014: : 899iter [01:41, 11.98iter/s]
[ITER 900] Best: 0.2010
[PARAMS] Current best parameters:
  fx: 561.2678
  fy: 561.4114
  px: 983.7758
  py: 767.7720
  k1: -0.04538011
  k2: 0.02540658
  k3: -0.01384134
  k4: 0.00282626
  p1: -0.00202717
  p2: 0.00103538
  p3: 0.01088359
  p4: -0.01392816
  s1: -0.0128
  s2: 0.0134
  s3: -0.0189
  s4: 0.0156
  tilt_x: -0.0559
  tilt_y: 0.0021
  scale: 2.9884
  rotation: 0.2505

Best score: 0.2010: : 899iter [01:41, 11.98iter/s]
Best score: 0.2010: : 900iter [01:41, 11.98iter/s]
Best score: 0.2010: : 901iter [01:41,  7.70iter/s]
Best score: 0.2010: : 901iter [01:41,  7.70iter/s]
Best score: 0.2010: : 902iter [01:41,  7.70iter/s]
Best score: 0.2010: : 903iter [01:41,  8.65iter/s]
Best score: 0.2010: : 903iter [01:41,  8.65iter/s]
Best score: 0.2010: : 904iter [01:41,  8.65iter/s]
Best score: 0.2010: : 905iter [01:41,  9.46iter/s]
Best score: 0.2010: : 905iter [01:41,  9.46iter/s]
Best score: 0.2010: : 906iter [01:41,  9.46iter/s]
Best score: 0.2010: : 907iter [01:41, 10.13iter/s]
Best score: 0.2010: : 907iter [01:42, 10.13iter/s]
Best score: 0.2010: : 908iter [01:42, 10.13iter/s]
Best score: 0.2010: : 909iter [01:42, 10.61iter/s]
Best score: 0.2009: : 909iter [01:42, 10.61iter/s]
Best score: 0.2009: : 910iter [01:42, 10.61iter/s]
Best score: 0.2009: : 911iter [01:42, 10.81iter/s]
Best score: 0.2009: : 911iter [01:42, 10.81iter/s]
Best score: 0.2009: : 912iter [01:42, 10.81iter/s]
Best score: 0.2009: : 913iter [01:42, 11.17iter/s]
Best score: 0.2009: : 913iter [01:42, 11.17iter/s]
Best score: 0.2009: : 914iter [01:42, 11.17iter/s]
Best score: 0.2009: : 915iter [01:42, 11.45iter/s]
Best score: 0.2009: : 915iter [01:42, 11.45iter/s]
Best score: 0.2009: : 916iter [01:42, 11.45iter/s]
Best score: 0.2009: : 917iter [01:42, 11.56iter/s]
Best score: 0.2009: : 917iter [01:42, 11.56iter/s]
Best score: 0.2009: : 918iter [01:43, 11.56iter/s]
Best score: 0.2009: : 919iter [01:43, 11.68iter/s]
Best score: 0.2007: : 919iter [01:43, 11.68iter/s]
Best score: 0.2007: : 920iter [01:43, 11.68iter/s]
Best score: 0.2007: : 921iter [01:43, 11.60iter/s]
Best score: 0.2007: : 921iter [01:43, 11.60iter/s]
Best score: 0.2007: : 922iter [01:43, 11.60iter/s]
Best score: 0.2007: : 923iter [01:43, 11.74iter/s]
Best score: 0.2007: : 923iter [01:43, 11.74iter/s]
Best score: 0.2007: : 924iter [01:43, 11.74iter/s]
Best score: 0.2007: : 925iter [01:43, 11.84iter/s]
Best score: 0.2007: : 925iter [01:43, 11.84iter/s]
Best score: 0.2007: : 926iter [01:43, 11.84iter/s]
Best score: 0.2007: : 927iter [01:43, 11.93iter/s]
Best score: 0.2007: : 927iter [01:43, 11.93iter/s]
Best score: 0.2007: : 928iter [01:43, 11.93iter/s]
Best score: 0.2007: : 929iter [01:43, 11.99iter/s]
Best score: 0.2006: : 929iter [01:43, 11.99iter/s]
Best score: 0.2006: : 930iter [01:44, 11.99iter/s]
Best score: 0.2006: : 931iter [01:44, 11.83iter/s]
Best score: 0.2006: : 931iter [01:44, 11.83iter/s]
Best score: 0.2006: : 932iter [01:44, 11.83iter/s]
Best score: 0.2006: : 933iter [01:44, 11.93iter/s]
Best score: 0.2006: : 933iter [01:44, 11.93iter/s]
Best score: 0.2006: : 934iter [01:44, 11.93iter/s]
Best score: 0.2006: : 935iter [01:44,  9.23iter/s]
Best score: 0.2006: : 935iter [01:44,  9.23iter/s]
Best score: 0.2006: : 936iter [01:44,  9.23iter/s]
Best score: 0.2006: : 937iter [01:44,  9.90iter/s]
Best score: 0.2006: : 937iter [01:44,  9.90iter/s]
Best score: 0.2006: : 938iter [01:44,  9.90iter/s]
Best score: 0.2006: : 939iter [01:44, 10.49iter/s]
Best score: 0.2006: : 939iter [01:44, 10.49iter/s]
Best score: 0.2006: : 940iter [01:45, 10.49iter/s]
Best score: 0.2006: : 941iter [01:45, 10.76iter/s]
Best score: 0.2006: : 941iter [01:45, 10.76iter/s]
Best score: 0.2006: : 942iter [01:45, 10.76iter/s]
Best score: 0.2006: : 943iter [01:45, 11.13iter/s]
Best score: 0.2006: : 943iter [01:45, 11.13iter/s]
Best score: 0.2006: : 944iter [01:45, 11.13iter/s]
Best score: 0.2006: : 945iter [01:45, 11.41iter/s]
Best score: 0.2006: : 945iter [01:45, 11.41iter/s]
Best score: 0.2006: : 946iter [01:45, 11.41iter/s]
Best score: 0.2006: : 947iter [01:45, 11.59iter/s]
Best score: 0.2006: : 947iter [01:45, 11.59iter/s]
Best score: 0.2006: : 948iter [01:45, 11.59iter/s]
Best score: 0.2006: : 949iter [01:45, 11.70iter/s]
[ITER 950] Best: 0.2005
[PARAMS] Current best parameters:
  fx: 559.2231
  fy: 559.3838
  px: 984.1382
  py: 767.4227
  k1: -0.04502046
  k2: 0.02921489
  k3: -0.01688073
  k4: 0.00356226
  p1: -0.00193105
  p2: 0.00151309
  p3: 0.01170856
  p4: -0.01367393
  s1: -0.0137
  s2: 0.0130
  s3: -0.0200
  s4: 0.0152
  tilt_x: -0.0577
  tilt_y: 0.0012
  scale: 2.9896
  rotation: 0.2501

Best score: 0.2005: : 949iter [01:45, 11.70iter/s]
Best score: 0.2005: : 950iter [01:46, 11.70iter/s]
Best score: 0.2005: : 951iter [01:46,  7.60iter/s]
Best score: 0.2005: : 951iter [01:46,  7.60iter/s]
Best score: 0.2005: : 952iter [01:46,  7.60iter/s]
Best score: 0.2005: : 953iter [01:46,  8.53iter/s]
Best score: 0.2005: : 953iter [01:46,  8.53iter/s]
Best score: 0.2005: : 954iter [01:46,  8.53iter/s]
Best score: 0.2005: : 955iter [01:46,  9.36iter/s]
Best score: 0.2005: : 955iter [01:46,  9.36iter/s]
Best score: 0.2005: : 956iter [01:46,  9.36iter/s]
Best score: 0.2005: : 957iter [01:46, 10.04iter/s]
Best score: 0.2005: : 957iter [01:46, 10.04iter/s]
Best score: 0.2005: : 958iter [01:46, 10.04iter/s]
Best score: 0.2005: : 959iter [01:46, 10.57iter/s]
Best score: 0.2005: : 959iter [01:46, 10.57iter/s]
Best score: 0.2005: : 960iter [01:46, 10.57iter/s]
Best score: 0.2005: : 961iter [01:46, 10.82iter/s]
Best score: 0.2005: : 961iter [01:47, 10.82iter/s]
Best score: 0.2005: : 962iter [01:47, 10.82iter/s]
Best score: 0.2005: : 963iter [01:47, 11.22iter/s]
Best score: 0.2005: : 963iter [01:47, 11.22iter/s]
Best score: 0.2005: : 964iter [01:47, 11.22iter/s]
Best score: 0.2005: : 965iter [01:47, 11.47iter/s]
Best score: 0.2005: : 965iter [01:47, 11.47iter/s]
Best score: 0.2005: : 966iter [01:47, 11.47iter/s]
Best score: 0.2005: : 967iter [01:47, 11.60iter/s]
Best score: 0.2005: : 967iter [01:47, 11.60iter/s]
Best score: 0.2005: : 968iter [01:47, 11.60iter/s]
Best score: 0.2005: : 969iter [01:47, 11.74iter/s]
Best score: 0.2005: : 969iter [01:47, 11.74iter/s]
Best score: 0.2005: : 970iter [01:47, 11.74iter/s]
Best score: 0.2005: : 971iter [01:47, 11.61iter/s]
Best score: 0.2005: : 971iter [01:47, 11.61iter/s]
Best score: 0.2005: : 972iter [01:48, 11.61iter/s]
Best score: 0.2005: : 973iter [01:48, 11.70iter/s]
Best score: 0.2005: : 973iter [01:48, 11.70iter/s]
Best score: 0.2005: : 974iter [01:48, 11.70iter/s]
Best score: 0.2005: : 975iter [01:48, 11.76iter/s]
Best score: 0.2005: : 975iter [01:48, 11.76iter/s]
Best score: 0.2005: : 976iter [01:48, 11.76iter/s]
Best score: 0.2005: : 977iter [01:48, 11.87iter/s]
Best score: 0.2005: : 977iter [01:48, 11.87iter/s]
Best score: 0.2005: : 978iter [01:48, 11.87iter/s]
Best score: 0.2005: : 979iter [01:48, 11.95iter/s]
Best score: 0.2005: : 979iter [01:48, 11.95iter/s]
Best score: 0.2005: : 980iter [01:48, 11.95iter/s]
Best score: 0.2005: : 981iter [01:48, 11.79iter/s]
Best score: 0.2005: : 981iter [01:48, 11.79iter/s]
Best score: 0.2005: : 982iter [01:48, 11.79iter/s]
Best score: 0.2005: : 983iter [01:48, 11.78iter/s]
Best score: 0.2005: : 983iter [01:48, 11.78iter/s]
Best score: 0.2005: : 984iter [01:49, 11.78iter/s]
Best score: 0.2005: : 985iter [01:49, 11.85iter/s]
Best score: 0.2005: : 985iter [01:49, 11.85iter/s]
Best score: 0.2005: : 986iter [01:49, 11.85iter/s]
Best score: 0.2005: : 987iter [01:49, 11.87iter/s]
Best score: 0.2005: : 987iter [01:49, 11.87iter/s]
Best score: 0.2005: : 988iter [01:49, 11.87iter/s]
Best score: 0.2005: : 989iter [01:49, 11.93iter/s]
Best score: 0.2005: : 989iter [01:49, 11.93iter/s]
Best score: 0.2005: : 990iter [01:49, 11.93iter/s]
Best score: 0.2005: : 991iter [01:49, 11.74iter/s]
Best score: 0.2005: : 991iter [01:49, 11.74iter/s]
Best score: 0.2005: : 992iter [01:49, 11.74iter/s]
Best score: 0.2005: : 993iter [01:49, 11.80iter/s]
Best score: 0.2005: : 993iter [01:49, 11.80iter/s]
Best score: 0.2005: : 994iter [01:49, 11.80iter/s]
Best score: 0.2005: : 995iter [01:49, 11.83iter/s]
Best score: 0.2005: : 995iter [01:49, 11.83iter/s]
Best score: 0.2005: : 996iter [01:50, 11.83iter/s]
Best score: 0.2005: : 997iter [01:50, 11.92iter/s]
Best score: 0.2005: : 997iter [01:50, 11.92iter/s]
Best score: 0.2005: : 998iter [01:50, 11.92iter/s]
Best score: 0.2005: : 999iter [01:50, 11.92iter/s]
[ITER 1000] Best: 0.2005
[PARAMS] Current best parameters:
  fx: 558.9806
  fy: 559.1498
  px: 984.1386
  py: 767.3000
  k1: -0.04448211
  k2: 0.02838510
  k3: -0.01622262
  k4: 0.00339012
  p1: -0.00188464
  p2: 0.00167843
  p3: 0.01176100
  p4: -0.01384134
  s1: -0.0139
  s2: 0.0132
  s3: -0.0202
  s4: 0.0153
  tilt_x: -0.0583
  tilt_y: 0.0016
  scale: 2.9900
  rotation: 0.2502

Best score: 0.2005: : 999iter [01:50, 11.92iter/s]
Best score: 0.2005: : 1000iter [01:50, 11.92iter/s]
Best score: 0.2005: : 1001iter [01:50,  7.67iter/s]
Best score: 0.2005: : 1001iter [01:50,  7.67iter/s]
Best score: 0.2005: : 1002iter [01:50,  7.67iter/s]
Best score: 0.2005: : 1003iter [01:50,  8.59iter/s]
Best score: 0.2005: : 1003iter [01:50,  8.59iter/s]
Best score: 0.2005: : 1004iter [01:51,  8.59iter/s]
Best score: 0.2005: : 1005iter [01:51,  9.42iter/s]
Best score: 0.2005: : 1005iter [01:51,  9.42iter/s]
Best score: 0.2005: : 1006iter [01:51,  9.42iter/s]
Best score: 0.2005: : 1007iter [01:51, 10.10iter/s]
Best score: 0.2005: : 1007iter [01:51, 10.10iter/s]
Best score: 0.2005: : 1008iter [01:51, 10.10iter/s]
Best score: 0.2005: : 1009iter [01:51, 10.63iter/s]
Best score: 0.2005: : 1009iter [01:51, 10.63iter/s]
Best score: 0.2005: : 1010iter [01:51, 10.63iter/s]
Best score: 0.2005: : 1011iter [01:51, 10.87iter/s]
Best score: 0.2005: : 1011iter [01:51, 10.87iter/s]
Best score: 0.2005: : 1012iter [01:51, 10.87iter/s]
Best score: 0.2005: : 1013iter [01:51, 11.22iter/s]
Best score: 0.2005: : 1013iter [01:51, 11.22iter/s]
Best score: 0.2005: : 1014iter [01:51, 11.22iter/s]
Best score: 0.2005: : 1015iter [01:51, 11.46iter/s]
Best score: 0.2005: : 1015iter [01:51, 11.46iter/s]
Best score: 0.2005: : 1016iter [01:52, 11.46iter/s]
Best score: 0.2005: : 1017iter [01:52, 11.65iter/s]
Best score: 0.2005: : 1017iter [01:52, 11.65iter/s]
Best score: 0.2005: : 1018iter [01:52, 11.65iter/s]
Best score: 0.2005: : 1019iter [01:52, 11.80iter/s]
Best score: 0.2005: : 1019iter [01:52, 11.80iter/s]
Best score: 0.2005: : 1020iter [01:52, 11.80iter/s]
Best score: 0.2005: : 1021iter [01:52, 11.69iter/s]
Best score: 0.2005: : 1021iter [01:52, 11.69iter/s]
Best score: 0.2005: : 1022iter [01:52, 11.69iter/s]
Best score: 0.2005: : 1023iter [01:52, 11.81iter/s]
Best score: 0.2005: : 1023iter [01:52, 11.81iter/s]
Best score: 0.2005: : 1024iter [01:52, 11.81iter/s]
Best score: 0.2005: : 1025iter [01:52, 11.89iter/s]
Best score: 0.2005: : 1025iter [01:52, 11.89iter/s]
Best score: 0.2005: : 1026iter [01:52, 11.89iter/s]
Best score: 0.2005: : 1027iter [01:52, 11.97iter/s]
Best score: 0.2005: : 1027iter [01:52, 11.97iter/s]
Best score: 0.2005: : 1028iter [01:53, 11.97iter/s]
Best score: 0.2005: : 1029iter [01:53, 12.00iter/s]
Best score: 0.2004: : 1029iter [01:53, 12.00iter/s]
Best score: 0.2004: : 1030iter [01:53, 12.00iter/s]
Best score: 0.2004: : 1031iter [01:53, 11.80iter/s]
Best score: 0.2004: : 1031iter [01:53, 11.80iter/s]
Best score: 0.2004: : 1032iter [01:53, 11.80iter/s]
Best score: 0.2004: : 1033iter [01:53, 11.88iter/s]
Best score: 0.2004: : 1033iter [01:53, 11.88iter/s]
Best score: 0.2004: : 1034iter [01:53, 11.88iter/s]
Best score: 0.2004: : 1035iter [01:53, 11.92iter/s]
Best score: 0.2004: : 1035iter [01:53, 11.92iter/s]
Best score: 0.2004: : 1036iter [01:53, 11.92iter/s]
Best score: 0.2004: : 1037iter [01:53, 11.98iter/s]
Best score: 0.2004: : 1037iter [01:53, 11.98iter/s]
Best score: 0.2004: : 1038iter [01:53, 11.98iter/s]
Best score: 0.2004: : 1039iter [01:53, 11.97iter/s]
Best score: 0.2004: : 1039iter [01:53, 11.97iter/s]
Best score: 0.2004: : 1040iter [01:54, 11.97iter/s]
Best score: 0.2004: : 1041iter [01:54, 11.81iter/s]
Best score: 0.2004: : 1041iter [01:54, 11.81iter/s]
Best score: 0.2004: : 1042iter [01:54, 11.81iter/s]
Best score: 0.2004: : 1043iter [01:54, 11.91iter/s]
Best score: 0.2004: : 1043iter [01:54, 11.91iter/s]
Best score: 0.2004: : 1044iter [01:54, 11.91iter/s]
Best score: 0.2004: : 1045iter [01:54, 11.98iter/s]
Best score: 0.2004: : 1045iter [01:54, 11.98iter/s]
Best score: 0.2004: : 1046iter [01:54, 11.98iter/s]
Best score: 0.2004: : 1047iter [01:54, 12.02iter/s]
Best score: 0.2004: : 1047iter [01:54, 12.02iter/s]
Best score: 0.2004: : 1048iter [01:54, 12.02iter/s]
Best score: 0.2004: : 1049iter [01:54, 12.05iter/s]
[ITER 1050] Best: 0.2004
[PARAMS] Current best parameters:
  fx: 558.8617
  fy: 559.0429
  px: 984.1409
  py: 767.1866
  k1: -0.04488127
  k2: 0.02923260
  k3: -0.01673244
  k4: 0.00349354
  p1: -0.00174508
  p2: 0.00150035
  p3: 0.01197331
  p4: -0.01407567
  s1: -0.0140
  s2: 0.0135
  s3: -0.0206
  s4: 0.0155
  tilt_x: -0.0592
  tilt_y: 0.0012
  scale: 2.9908
  rotation: 0.2526

Best score: 0.2004: : 1049iter [01:54, 12.05iter/s]
Best score: 0.2004: : 1050iter [01:55, 12.05iter/s]
Best score: 0.2004: : 1051iter [01:55,  7.69iter/s]
Best score: 0.2004: : 1051iter [01:55,  7.69iter/s]
Best score: 0.2004: : 1052iter [01:55,  7.69iter/s]
Best score: 0.2004: : 1053iter [01:55,  8.64iter/s]
Best score: 0.2004: : 1053iter [01:55,  8.64iter/s]
Best score: 0.2004: : 1054iter [01:55,  8.64iter/s]
Best score: 0.2004: : 1055iter [01:55,  9.45iter/s]
Best score: 0.2004: : 1055iter [01:55,  9.45iter/s]
Best score: 0.2004: : 1056iter [01:55,  9.45iter/s]
Best score: 0.2004: : 1057iter [01:55, 10.07iter/s]
Best score: 0.2004: : 1057iter [01:55, 10.07iter/s]
Best score: 0.2004: : 1058iter [01:55, 10.07iter/s]
Best score: 0.2004: : 1059iter [01:55, 10.62iter/s]
Best score: 0.2004: : 1059iter [01:55, 10.62iter/s]
Best score: 0.2004: : 1060iter [01:55, 10.62iter/s]
Best score: 0.2004: : 1061iter [01:55, 10.86iter/s]
Best score: 0.2004: : 1061iter [01:56, 10.86iter/s]
Best score: 0.2004: : 1062iter [01:56, 10.86iter/s]
Best score: 0.2004: : 1063iter [01:56, 11.22iter/s]
Best score: 0.2004: : 1063iter [01:56, 11.22iter/s]
Best score: 0.2004: : 1064iter [01:56, 11.22iter/s]
Best score: 0.2004: : 1065iter [01:56, 11.46iter/s]
Best score: 0.2004: : 1065iter [01:56, 11.46iter/s]
Best score: 0.2004: : 1066iter [01:56, 11.46iter/s]
Best score: 0.2004: : 1067iter [01:56, 11.55iter/s]
Best score: 0.2004: : 1067iter [01:56, 11.55iter/s]
Best score: 0.2004: : 1068iter [01:56, 11.55iter/s]
Best score: 0.2004: : 1069iter [01:56, 11.65iter/s]
Best score: 0.2004: : 1069iter [01:56, 11.65iter/s]
Best score: 0.2004: : 1070iter [01:56, 11.65iter/s]
Best score: 0.2004: : 1071iter [01:56, 11.49iter/s]
Best score: 0.2004: : 1071iter [01:56, 11.49iter/s]
Best score: 0.2004: : 1072iter [01:57, 11.49iter/s]
Best score: 0.2004: : 1073iter [01:57, 11.62iter/s]
Best score: 0.2004: : 1073iter [01:57, 11.62iter/s]
Best score: 0.2004: : 1074iter [01:57, 11.62iter/s]
Best score: 0.2004: : 1075iter [01:57, 11.75iter/s]
Best score: 0.2004: : 1075iter [01:57, 11.75iter/s]
Best score: 0.2004: : 1076iter [01:57, 11.75iter/s]
Best score: 0.2004: : 1077iter [01:57, 11.81iter/s]
Best score: 0.2004: : 1077iter [01:57, 11.81iter/s]
Best score: 0.2004: : 1078iter [01:57, 11.81iter/s]
Best score: 0.2004: : 1079iter [01:57, 11.80iter/s]
Best score: 0.2004: : 1079iter [01:57, 11.80iter/s]
Best score: 0.2004: : 1080iter [01:57, 11.80iter/s]
Best score: 0.2004: : 1081iter [01:57, 11.65iter/s]
Best score: 0.2004: : 1081iter [01:57, 11.65iter/s]
Best score: 0.2004: : 1082iter [01:57, 11.65iter/s]
Best score: 0.2004: : 1083iter [01:57, 11.78iter/s]
Best score: 0.2004: : 1083iter [01:57, 11.78iter/s]
Best score: 0.2004: : 1084iter [01:58, 11.78iter/s]
Best score: 0.2004: : 1085iter [01:58, 11.88iter/s]
Best score: 0.2004: : 1085iter [01:58, 11.88iter/s]
Best score: 0.2004: : 1086iter [01:58, 11.88iter/s]
Best score: 0.2004: : 1087iter [01:58, 11.89iter/s]
Best score: 0.2004: : 1087iter [01:58, 11.89iter/s]
Best score: 0.2004: : 1088iter [01:58, 11.89iter/s]
Best score: 0.2004: : 1089iter [01:58, 11.91iter/s]
Best score: 0.2004: : 1089iter [01:58, 11.91iter/s]
Best score: 0.2004: : 1090iter [01:58, 11.91iter/s]
Best score: 0.2004: : 1091iter [01:58, 11.77iter/s]
Best score: 0.2004: : 1091iter [01:58, 11.77iter/s]
Best score: 0.2004: : 1092iter [01:58, 11.77iter/s]
Best score: 0.2004: : 1093iter [01:58, 11.87iter/s]
Best score: 0.2004: : 1093iter [01:58, 11.87iter/s]
Best score: 0.2004: : 1094iter [01:58, 11.87iter/s]
Best score: 0.2004: : 1095iter [01:58, 11.94iter/s]
Best score: 0.2004: : 1095iter [01:58, 11.94iter/s]
Best score: 0.2004: : 1096iter [01:59, 11.94iter/s]
Best score: 0.2004: : 1097iter [01:59, 11.99iter/s]
Best score: 0.2004: : 1097iter [01:59, 11.99iter/s]
Best score: 0.2004: : 1098iter [01:59, 11.99iter/s]
Best score: 0.2004: : 1099iter [01:59, 12.02iter/s]
[ITER 1100] Best: 0.2003
[PARAMS] Current best parameters:
  fx: 558.5025
  fy: 558.6756
  px: 984.1807
  py: 767.0374
  k1: -0.04516790
  k2: 0.03069165
  k3: -0.01788480
  k4: 0.00378472
  p1: -0.00186318
  p2: 0.00160291
  p3: 0.01064863
  p4: -0.01345273
  s1: -0.0128
  s2: 0.0129
  s3: -0.0194
  s4: 0.0150
  tilt_x: -0.0596
  tilt_y: 0.0012
  scale: 2.9912
  rotation: 0.2525

Best score: 0.2003: : 1099iter [01:59, 12.02iter/s]
[📈] Running L-BFGS-B polish after 1100 DE iterations...

Best score: 0.2003: : 1100iter [01:59,  9.20iter/s]
  Polish improved score: 0.200332 -> 0.200322

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 100,413 → 91,333 within 3500mm ring
  Ring polish did not improve score: 0.200322
  Success: True
  Tangential distortion: p1=-0.001863, p2=0.001601, p3=0.010650, p4=-0.013446
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.2003
[✅] Parameters copied to: /working/MDC045_W022(6)_2023-10-25/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 558.502454431133
    fy: 558.6756301422233
    px: 984.1806698973099
    py: 767.0374106380934
    k1: -0.04516793925116658
    k2: 0.030692613847816734
    k3: -0.017883402775968785
    k4: 0.0037836662768401396
    p1: -0.0018633184518703607
    p2: 0.0016010099354661603
    p3: 0.010650223392596667
    p4: -0.01344648685967332
    scale: 2.99123831034809
    rotation: 0.25254673001003414
    mmpp: 3.4150384830027787

[🔄] Converting 728 frames to PTD, creating debug images for 400 calibration frames...

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

   🔄 2000L:   0%|          | 0/182 [00:00<?, ?frame/s]

   🔄 2000L:  10%|▉         | 18/182 [00:00<00:00, 176.04frame/s]

   🔄 2000L:  20%|██        | 37/182 [00:00<00:00, 178.83frame/s]

   🔄 2000L:  31%|███       | 56/182 [00:00<00:00, 181.50frame/s]

   🔄 2000L:  41%|████      | 75/182 [00:00<00:00, 183.44frame/s]

   🔄 2000L:  52%|█████▏    | 94/182 [00:00<00:00, 182.28frame/s]

   🔄 2000L:  62%|██████▏   | 113/182 [00:00<00:00, 181.44frame/s]

   🔄 2000L:  73%|███████▎  | 132/182 [00:00<00:00, 181.41frame/s]

   🔄 2000L:  83%|████████▎ | 151/182 [00:00<00:00, 181.24frame/s]

   🔄 2000L:  93%|█████████▎| 170/182 [00:00<00:00, 180.69frame/s]

                                                                  
📁 Rigs:  25%|██▌       | 1/4 [00:01<00:05,  1.80s/rig]

   🔄 1500:   0%|          | 0/217 [00:00<?, ?frame/s]

   🔄 1500:   9%|▉         | 20/217 [00:00<00:01, 191.49frame/s]

   🔄 1500:  18%|█▊        | 40/217 [00:00<00:00, 186.66frame/s]

   🔄 1500:  27%|██▋       | 59/217 [00:00<00:00, 184.48frame/s]

   🔄 1500:  36%|███▌      | 78/217 [00:00<00:00, 183.28frame/s]

   🔄 1500:  45%|████▍     | 97/217 [00:00<00:00, 183.94frame/s]

   🔄 1500:  53%|█████▎    | 116/217 [00:00<00:00, 184.87frame/s]

   🔄 1500:  62%|██████▏   | 135/217 [00:00<00:00, 184.90frame/s]

   🔄 1500:  71%|███████   | 154/217 [00:00<00:00, 183.76frame/s]

   🔄 1500:  80%|███████▉  | 173/217 [00:00<00:00, 183.12frame/s]

   🔄 1500:  88%|████████▊ | 192/217 [00:01<00:00, 182.82frame/s]

   🔄 1500:  97%|█████████▋| 211/217 [00:01<00:00, 181.81frame/s]

                                                                 
📁 Rigs:  50%|█████     | 2/4 [00:04<00:04,  2.08s/rig]

   🔄 2000R:   0%|          | 0/177 [00:00<?, ?frame/s]

   🔄 2000R:  10%|█         | 18/177 [00:00<00:00, 176.63frame/s]

   🔄 2000R:  21%|██        | 37/177 [00:00<00:00, 179.14frame/s]

   🔄 2000R:  32%|███▏      | 56/177 [00:00<00:00, 180.92frame/s]

   🔄 2000R:  42%|████▏     | 75/177 [00:00<00:00, 180.12frame/s]

   🔄 2000R:  53%|█████▎    | 94/177 [00:00<00:00, 180.53frame/s]

   🔄 2000R:  64%|██████▍   | 113/177 [00:00<00:00, 181.05frame/s]

   🔄 2000R:  75%|███████▍  | 132/177 [00:00<00:00, 182.14frame/s]

   🔄 2000R:  85%|████████▌ | 151/177 [00:00<00:00, 182.84frame/s]

   🔄 2000R:  96%|█████████▌| 170/177 [00:00<00:00, 182.40frame/s]

                                                                  
📁 Rigs:  75%|███████▌  | 3/4 [00:05<00:01,  1.86s/rig]

   🔄 1000:   0%|          | 0/152 [00:00<?, ?frame/s]

   🔄 1000:  12%|█▎        | 19/152 [00:00<00:00, 185.97frame/s]

   🔄 1000:  25%|██▌       | 38/152 [00:00<00:00, 187.07frame/s]

   🔄 1000:  38%|███▊      | 57/152 [00:00<00:00, 186.72frame/s]

   🔄 1000:  50%|█████     | 76/152 [00:00<00:00, 187.56frame/s]

   🔄 1000:  62%|██████▎   | 95/152 [00:00<00:00, 188.15frame/s]

   🔄 1000:  75%|███████▌  | 114/152 [00:00<00:00, 188.11frame/s]

   🔄 1000:  88%|████████▊ | 134/152 [00:00<00:00, 188.82frame/s]

                                                                 
📁 Rigs: 100%|██████████| 4/4 [00:07<00:00,  1.71s/rig]
📁 Rigs: 100%|██████████| 4/4 [00:07<00:00,  1.79s/rig]
[✅] Saved PTDs: /working/MDC045_W022(6)_2023-10-25/calibration/debug/4_undistorted/output/ptd

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

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

   🔄 2000L:  18%|█▊        | 18/100 [00:00<00:00, 178.24frame/s]

   🔄 2000L:  37%|███▋      | 37/100 [00:00<00:00, 181.15frame/s]

   🔄 2000L:  56%|█████▌    | 56/100 [00:00<00:00, 178.71frame/s]

   🔄 2000L:  75%|███████▌  | 75/100 [00:00<00:00, 179.58frame/s]

   🔄 2000L:  93%|█████████▎| 93/100 [00:00<00:00, 179.31frame/s]

                                                                 
📁 Rigs:  25%|██▌       | 1/4 [00:01<00:03,  1.03s/rig]

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

   🔄 1500:  19%|█▉        | 19/100 [00:00<00:00, 186.32frame/s]

   🔄 1500:  38%|███▊      | 38/100 [00:00<00:00, 182.31frame/s]

   🔄 1500:  57%|█████▋    | 57/100 [00:00<00:00, 183.37frame/s]

   🔄 1500:  76%|███████▌  | 76/100 [00:00<00:00, 182.65frame/s]

   🔄 1500:  95%|█████████▌| 95/100 [00:00<00:00, 182.43frame/s]

                                                                
📁 Rigs:  50%|█████     | 2/4 [00:01<00:01,  1.06rig/s]

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

   🔄 2000R:  18%|█▊        | 18/100 [00:00<00:00, 177.90frame/s]

   🔄 2000R:  36%|███▌      | 36/100 [00:00<00:00, 178.12frame/s]

   🔄 2000R:  54%|█████▍    | 54/100 [00:00<00:00, 178.20frame/s]

   🔄 2000R:  73%|███████▎  | 73/100 [00:00<00:00, 179.96frame/s]

   🔄 2000R:  92%|█████████▏| 92/100 [00:00<00:00, 181.25frame/s]

                                                                 
📁 Rigs:  75%|███████▌  | 3/4 [00:02<00:00,  1.01rig/s]

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

   🔄 1000:  19%|█▉        | 19/100 [00:00<00:00, 188.35frame/s]

   🔄 1000:  38%|███▊      | 38/100 [00:00<00:00, 188.04frame/s]

   🔄 1000:  58%|█████▊    | 58/100 [00:00<00:00, 189.05frame/s]

   🔄 1000:  77%|███████▋  | 77/100 [00:00<00:00, 188.47frame/s]

   🔄 1000:  96%|█████████▌| 96/100 [00:00<00:00, 188.63frame/s]

                                                                
📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.06rig/s]
📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.04rig/s]
[✅] Saved PTDs: /working/MDC045_W022(6)_2023-10-25/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%|▎         | 95886/3080448 [00:00<00:03, 958854.06px/s]
📤 Writing LUT:   6%|▋         | 196479/3080448 [00:00<00:02, 986544.89px/s]
📤 Writing LUT:  10%|▉         | 295134/3080448 [00:00<00:02, 982851.87px/s]
📤 Writing LUT:  13%|█▎        | 393421/3080448 [00:00<00:02, 959855.35px/s]
📤 Writing LUT:  16%|█▌        | 489483/3080448 [00:00<00:02, 925389.88px/s]
📤 Writing LUT:  19%|█▉        | 582230/3080448 [00:00<00:02, 903314.23px/s]
📤 Writing LUT:  22%|██▏       | 672728/3080448 [00:00<00:02, 890103.82px/s]
📤 Writing LUT:  25%|██▍       | 763580/3080448 [00:00<00:02, 895740.39px/s]
📤 Writing LUT:  28%|██▊       | 853245/3080448 [00:00<00:02, 887131.96px/s]
📤 Writing LUT:  31%|███       | 944432/3080448 [00:01<00:02, 894575.73px/s]
📤 Writing LUT:  34%|███▎      | 1033950/3080448 [00:01<00:02, 893929.16px/s]
📤 Writing LUT:  36%|███▋      | 1123384/3080448 [00:01<00:02, 888746.05px/s]
📤 Writing LUT:  39%|███▉      | 1212288/3080448 [00:01<00:02, 884940.86px/s]
📤 Writing LUT:  42%|████▏     | 1300890/3080448 [00:01<00:02, 885261.79px/s]
📤 Writing LUT:  45%|████▌     | 1389430/3080448 [00:01<00:01, 884734.78px/s]
📤 Writing LUT:  48%|████▊     | 1477913/3080448 [00:01<00:01, 883101.90px/s]
📤 Writing LUT:  51%|█████     | 1566230/3080448 [00:01<00:01, 882171.23px/s]
📤 Writing LUT:  54%|█████▍    | 1655767/3080448 [00:01<00:01, 886115.77px/s]
📤 Writing LUT:  57%|█████▋    | 1744384/3080448 [00:01<00:01, 883438.34px/s]
📤 Writing LUT:  60%|█████▉    | 1834128/3080448 [00:02<00:01, 887622.21px/s]
📤 Writing LUT:  62%|██████▏   | 1922896/3080448 [00:02<00:01, 883641.87px/s]
📤 Writing LUT:  65%|██████▌   | 2011267/3080448 [00:02<00:01, 878752.41px/s]
📤 Writing LUT:  68%|██████▊   | 2099151/3080448 [00:02<00:01, 875574.82px/s]
📤 Writing LUT:  71%|███████   | 2188286/3080448 [00:02<00:01, 880270.45px/s]
📤 Writing LUT:  74%|███████▍  | 2278928/3080448 [00:02<00:00, 888070.52px/s]
📤 Writing LUT:  77%|███████▋  | 2370081/3080448 [00:02<00:00, 895078.68px/s]
📤 Writing LUT:  80%|███████▉  | 2459599/3080448 [00:02<00:00, 886780.65px/s]
📤 Writing LUT:  83%|████████▎ | 2548300/3080448 [00:02<00:00, 881831.21px/s]
📤 Writing LUT:  86%|████████▌ | 2636502/3080448 [00:02<00:00, 877780.87px/s]
📤 Writing LUT:  88%|████████▊ | 2724294/3080448 [00:03<00:00, 875998.43px/s]
📤 Writing LUT:  91%|█████████▏| 2813246/3080448 [00:03<00:00, 880017.84px/s]
📤 Writing LUT:  94%|█████████▍| 2901257/3080448 [00:03<00:00, 879397.23px/s]
📤 Writing LUT:  97%|█████████▋| 2989203/3080448 [00:03<00:00, 879005.74px/s]
📤 Writing LUT: 100%|█████████▉| 3077108/3080448 [00:03<00:00, 877613.26px/s]
📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 891279.20px/s]
[✅] LUT written to: /working/MDC045_W022(6)_2023-10-25/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDC045_W022(6)_2023-10-25' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC045_W022(6)_2023-10-25/calibration/MDC045_W022(6)_2023-10-25_unknown.lut

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

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

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

   🔥 2000L:   0%|          | 0/182 [00:00<?, ?frame/s]

   🔥 2000L:   4%|▍         | 8/182 [00:00<00:02, 75.97frame/s]

   🔥 2000L:   9%|▉         | 17/182 [00:00<00:02, 79.11frame/s]

   🔥 2000L:  14%|█▍        | 26/182 [00:00<00:01, 83.73frame/s]

   🔥 2000L:  19%|█▉        | 35/182 [00:00<00:01, 86.00frame/s]

   🔥 2000L:  25%|██▍       | 45/182 [00:00<00:01, 90.04frame/s]

   🔥 2000L:  31%|███       | 56/182 [00:00<00:01, 94.93frame/s]

   🔥 2000L:  37%|███▋      | 67/182 [00:00<00:01, 99.13frame/s]

   🔥 2000L:  42%|████▏     | 77/182 [00:00<00:01, 98.90frame/s]

   🔥 2000L:  48%|████▊     | 87/182 [00:00<00:00, 97.05frame/s]

   🔥 2000L:  53%|█████▎    | 97/182 [00:01<00:00, 94.90frame/s]

   🔥 2000L:  59%|█████▉    | 107/182 [00:01<00:00, 93.82frame/s]

   🔥 2000L:  64%|██████▍   | 117/182 [00:01<00:00, 94.46frame/s]

   🔥 2000L:  70%|███████   | 128/182 [00:01<00:00, 96.70frame/s]

   🔥 2000L:  76%|███████▌  | 138/182 [00:01<00:00, 95.19frame/s]

   🔥 2000L:  81%|████████▏ | 148/182 [00:01<00:00, 90.58frame/s]

   🔥 2000L:  87%|████████▋ | 158/182 [00:01<00:00, 86.39frame/s]

   🔥 2000L:  92%|█████████▏| 167/182 [00:01<00:00, 83.40frame/s]

   🔥 2000L:  97%|█████████▋| 176/182 [00:01<00:00, 81.67frame/s]

                                                                 [✅] 2000L: /working/MDC045_W022(6)_2023-10-25/calibration/debug/5_heatmap/2000L_heatmap.png
[✅] 2000L (fitted): /working/MDC045_W022(6)_2023-10-25/calibration/debug/5_heatmap/2000L_heatmap_fitted.png

📁 Rigs (heatmap):  25%|██▌       | 1/4 [00:03<00:10,  3.60s/rig]

   🔥 1500:   0%|          | 0/217 [00:00<?, ?frame/s]

   🔥 1500:   4%|▎         | 8/217 [00:00<00:02, 77.52frame/s]

   🔥 1500:   8%|▊         | 17/217 [00:00<00:02, 84.58frame/s]

   🔥 1500:  12%|█▏        | 26/217 [00:00<00:02, 84.90frame/s]

   🔥 1500:  16%|█▌        | 35/217 [00:00<00:02, 84.62frame/s]

   🔥 1500:  20%|██        | 44/217 [00:00<00:02, 82.54frame/s]

   🔥 1500:  24%|██▍       | 53/217 [00:00<00:02, 80.71frame/s]

   🔥 1500:  29%|██▊       | 62/217 [00:00<00:01, 80.09frame/s]

   🔥 1500:  33%|███▎      | 71/217 [00:00<00:01, 80.10frame/s]

   🔥 1500:  37%|███▋      | 80/217 [00:00<00:01, 80.71frame/s]

   🔥 1500:  41%|████      | 89/217 [00:01<00:01, 81.13frame/s]

   🔥 1500:  45%|████▌     | 98/217 [00:01<00:01, 81.21frame/s]

   🔥 1500:  49%|████▉     | 107/217 [00:01<00:01, 82.92frame/s]

   🔥 1500:  53%|█████▎    | 116/217 [00:01<00:01, 84.17frame/s]

   🔥 1500:  58%|█████▊    | 125/217 [00:01<00:01, 83.27frame/s]

   🔥 1500:  62%|██████▏   | 134/217 [00:01<00:00, 83.04frame/s]

   🔥 1500:  66%|██████▌   | 143/217 [00:01<00:00, 82.20frame/s]

   🔥 1500:  70%|███████   | 152/217 [00:01<00:00, 81.76frame/s]

   🔥 1500:  74%|███████▍  | 161/217 [00:01<00:00, 81.61frame/s]

   🔥 1500:  78%|███████▊  | 170/217 [00:02<00:00, 82.91frame/s]

   🔥 1500:  83%|████████▎ | 180/217 [00:02<00:00, 85.25frame/s]

   🔥 1500:  88%|████████▊ | 190/217 [00:02<00:00, 87.46frame/s]

   🔥 1500:  92%|█████████▏| 200/217 [00:02<00:00, 89.13frame/s]

   🔥 1500:  97%|█████████▋| 210/217 [00:02<00:00, 90.62frame/s]

                                                                [✅] 1500: /working/MDC045_W022(6)_2023-10-25/calibration/debug/5_heatmap/1500_heatmap.png
[✅] 1500 (fitted): /working/MDC045_W022(6)_2023-10-25/calibration/debug/5_heatmap/1500_heatmap_fitted.png

📁 Rigs (heatmap):  50%|█████     | 2/4 [00:07<00:07,  3.84s/rig]

   🔥 2000R:   0%|          | 0/177 [00:00<?, ?frame/s]

   🔥 2000R:   5%|▍         | 8/177 [00:00<00:02, 75.59frame/s]

   🔥 2000R:   9%|▉         | 16/177 [00:00<00:02, 77.81frame/s]

   🔥 2000R:  14%|█▍        | 25/177 [00:00<00:01, 78.94frame/s]

   🔥 2000R:  19%|█▉        | 34/177 [00:00<00:01, 79.40frame/s]

   🔥 2000R:  24%|██▍       | 43/177 [00:00<00:01, 82.60frame/s]

   🔥 2000R:  30%|██▉       | 53/177 [00:00<00:01, 85.36frame/s]

   🔥 2000R:  36%|███▌      | 63/177 [00:00<00:01, 87.44frame/s]

   🔥 2000R:  41%|████      | 73/177 [00:00<00:01, 88.42frame/s]

   🔥 2000R:  46%|████▋     | 82/177 [00:00<00:01, 88.75frame/s]

   🔥 2000R:  52%|█████▏    | 92/177 [00:01<00:00, 89.93frame/s]

   🔥 2000R:  58%|█████▊    | 102/177 [00:01<00:00, 90.90frame/s]

   🔥 2000R:  64%|██████▍   | 113/177 [00:01<00:00, 94.73frame/s]

   🔥 2000R:  70%|███████   | 124/177 [00:01<00:00, 97.82frame/s]

   🔥 2000R:  76%|███████▌  | 134/177 [00:01<00:00, 98.25frame/s]

   🔥 2000R:  81%|████████▏ | 144/177 [00:01<00:00, 96.39frame/s]

   🔥 2000R:  87%|████████▋ | 154/177 [00:01<00:00, 93.95frame/s]

   🔥 2000R:  93%|█████████▎| 164/177 [00:01<00:00, 89.73frame/s]

   🔥 2000R:  98%|█████████▊| 174/177 [00:01<00:00, 86.52frame/s]

                                                                 [✅] 2000R: /working/MDC045_W022(6)_2023-10-25/calibration/debug/5_heatmap/2000R_heatmap.png
[✅] 2000R (fitted): /working/MDC045_W022(6)_2023-10-25/calibration/debug/5_heatmap/2000R_heatmap_fitted.png

📁 Rigs (heatmap):  75%|███████▌  | 3/4 [00:11<00:03,  3.71s/rig]

   🔥 1000:   0%|          | 0/152 [00:00<?, ?frame/s]

   🔥 1000:   6%|▌         | 9/152 [00:00<00:01, 86.15frame/s]

   🔥 1000:  12%|█▎        | 19/152 [00:00<00:01, 90.04frame/s]

   🔥 1000:  18%|█▊        | 28/152 [00:00<00:01, 89.18frame/s]

   🔥 1000:  24%|██▍       | 37/152 [00:00<00:01, 87.14frame/s]

   🔥 1000:  30%|███       | 46/152 [00:00<00:01, 85.02frame/s]

   🔥 1000:  36%|███▌      | 55/152 [00:00<00:01, 84.23frame/s]

   🔥 1000:  42%|████▏     | 64/152 [00:00<00:01, 84.05frame/s]

   🔥 1000:  48%|████▊     | 73/152 [00:00<00:00, 83.66frame/s]

   🔥 1000:  55%|█████▍    | 83/152 [00:00<00:00, 85.98frame/s]

   🔥 1000:  61%|██████    | 93/152 [00:01<00:00, 88.16frame/s]

   🔥 1000:  67%|██████▋   | 102/152 [00:01<00:00, 87.22frame/s]

   🔥 1000:  73%|███████▎  | 111/152 [00:01<00:00, 87.71frame/s]

   🔥 1000:  80%|███████▉  | 121/152 [00:01<00:00, 90.50frame/s]

   🔥 1000:  86%|████████▌ | 131/152 [00:01<00:00, 91.67frame/s]

   🔥 1000:  93%|█████████▎| 141/152 [00:01<00:00, 92.32frame/s]

   🔥 1000:  99%|█████████▉| 151/152 [00:01<00:00, 93.32frame/s]

                                                                [✅] 1000: /working/MDC045_W022(6)_2023-10-25/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDC045_W022(6)_2023-10-25/calibration/debug/5_heatmap/1000_heatmap_fitted.png

📁 Rigs (heatmap): 100%|██████████| 4/4 [00:13<00:00,  3.20s/rig]
📁 Rigs (heatmap): 100%|██████████| 4/4 [00:13<00:00,  3.40s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDC045_W022(6)_2023-10-25/calibration/debug/5_heatmap
[🏁] Finished processing MDC045_W022(6)_2023-10-25


================================================================================================================================
================================================================================================================================