2026-09-03T04:50:54 - INFO: Slick 0.0.8a13

🟢 Starting Calibration Pipeline

=== Processing MDCP3D-SL-013_W046(6)_2026-09-02 ===
2026-09-03T04:50:54 - INFO: Camera ID: 0F7YM
2026-09-03T04:50:54 - INFO: Wand ID: 00001f0c51aa
2026-09-03T04:50:54 - INFO: Recorded At: 2026-09-02T01:41:02Z

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                        Step 1: Digitization                       
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[🔄] 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 236 stationary frames, 328 remain


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→ 2000L (328 images) Phase 1:  88%|████████▊ | 289/328 [00:04<00:00, 75.94it/s]

→ 2000L (328 images) Phase 1:  91%|█████████ | 298/328 [00:04<00:00, 64.89it/s]

→ 2000L (328 images) Phase 1:  94%|█████████▎| 307/328 [00:04<00:00, 68.96it/s]

→ 2000L (328 images) Phase 1:  98%|█████████▊| 321/328 [00:05<00:00, 84.17it/s]

                                                                               

→ 2000L Phase 2: corners:   0%|          | 0/327 [00:00<?, ?it/s]

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→ 2000L Phase 2: corners:  91%|█████████▏| 299/327 [00:02<00:00, 159.00it/s]

→ 2000L Phase 2: corners:  96%|█████████▋| 315/327 [00:02<00:00, 153.19it/s]

                                                                            [PASS2] Frame 0000153: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000627: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000635: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000636: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000637: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000638: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000678: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000679: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000681: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000682: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000684: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000685: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001042: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001043: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001044: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001045: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001050: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001051: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001052: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001053: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001054: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001060: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001061: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001062: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001066: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000627: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000681: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000684: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001061: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001062: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001066: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000627: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000681: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001053: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001054: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001060: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001062: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001066: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Summary: 15 frames fixed, 28 untrusted, 327 total


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→ 2000L Phase 3: finalize:  96%|█████████▌| 313/327 [00:06<00:00, 49.09it/s]

→ 2000L Phase 3: finalize:  97%|█████████▋| 318/327 [00:06<00:00, 49.01it/s]

→ 2000L Phase 3: finalize:  99%|█████████▉| 323/327 [00:06<00:00, 49.03it/s]

                                                                            
[TIMING] 2000L — 328 frames
  Phase 1  radial detect   (parallel)  :   5.18s  (15.8 ms/frame)
  Phase 2a corner detect   (parallel)  :   2.55s  (7.8 ms/frame)
  Phase 2b corner fix      (sequential):   0.81s
  Phase 3  finalize        (sequential):   6.57s  (20.0 ms/frame)
    decode + undistort                 :   3.60s  (11.0 ms/frame)
    corner apply + refinement          :   1.35s  (4.1 ms/frame)
    segment                            :   1.32s  (4.0 ms/frame)
    smooth                             :   0.19s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  15.11s


Processing Rigs:  25%|██▌       | 1/4 [00:17<00:53, 17.98s/it][INFO] Filtered 400 stationary frames, 474 remain


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→ 1500 (474 images) Phase 1:  94%|█████████▎| 444/474 [00:06<00:00, 77.42it/s]

→ 1500 (474 images) Phase 1:  96%|█████████▌| 455/474 [00:07<00:00, 69.13it/s]

→ 1500 (474 images) Phase 1:  99%|█████████▊| 468/474 [00:07<00:00, 77.45it/s]

                                                                              

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→ 1500 Phase 2: corners:  40%|████      | 191/473 [00:01<00:02, 135.40it/s]

→ 1500 Phase 2: corners:  43%|████▎     | 205/473 [00:01<00:02, 132.83it/s]

→ 1500 Phase 2: corners:  46%|████▋     | 219/473 [00:01<00:01, 130.36it/s]

→ 1500 Phase 2: corners:  49%|████▉     | 234/473 [00:02<00:01, 133.33it/s]

→ 1500 Phase 2: corners:  53%|█████▎    | 250/473 [00:02<00:01, 140.21it/s]

→ 1500 Phase 2: corners:  56%|█████▌    | 265/473 [00:02<00:01, 140.73it/s]

→ 1500 Phase 2: corners:  59%|█████▉    | 280/473 [00:02<00:01, 140.00it/s]

→ 1500 Phase 2: corners:  63%|██████▎   | 298/473 [00:02<00:01, 149.97it/s]

→ 1500 Phase 2: corners:  66%|██████▋   | 314/473 [00:02<00:01, 148.59it/s]

→ 1500 Phase 2: corners:  70%|██████▉   | 330/473 [00:02<00:00, 151.69it/s]

→ 1500 Phase 2: corners:  73%|███████▎  | 346/473 [00:02<00:00, 152.83it/s]

→ 1500 Phase 2: corners:  77%|███████▋  | 362/473 [00:02<00:00, 144.32it/s]

→ 1500 Phase 2: corners:  81%|████████  | 381/473 [00:02<00:00, 155.96it/s]

→ 1500 Phase 2: corners:  84%|████████▍ | 397/473 [00:03<00:00, 151.30it/s]

→ 1500 Phase 2: corners:  87%|████████▋ | 413/473 [00:03<00:00, 140.49it/s]

→ 1500 Phase 2: corners:  91%|█████████▏| 432/473 [00:03<00:00, 153.19it/s]

→ 1500 Phase 2: corners:  95%|█████████▍| 448/473 [00:03<00:00, 150.65it/s]

→ 1500 Phase 2: corners:  99%|█████████▉| 468/473 [00:03<00:00, 160.68it/s]

                                                                           [PASS2] Frame 0000543: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000544: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000545: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000546: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 2 frames fixed, 21 untrusted, 473 total


→ 1500 Phase 3: finalize:   0%|          | 0/473 [00:00<?, ?it/s]

→ 1500 Phase 3: finalize:   1%|▏         | 7/473 [00:00<00:07, 64.84it/s]

→ 1500 Phase 3: finalize:   3%|▎         | 14/473 [00:00<00:08, 57.00it/s]

→ 1500 Phase 3: finalize:   4%|▍         | 20/473 [00:00<00:08, 52.15it/s]

→ 1500 Phase 3: finalize:   5%|▌         | 26/473 [00:00<00:08, 49.91it/s]

→ 1500 Phase 3: finalize:   7%|▋         | 32/473 [00:00<00:09, 48.85it/s]

→ 1500 Phase 3: finalize:   8%|▊         | 37/473 [00:00<00:08, 48.48it/s]

→ 1500 Phase 3: finalize:   9%|▉         | 42/473 [00:00<00:08, 48.03it/s]

→ 1500 Phase 3: finalize:  10%|▉         | 47/473 [00:00<00:08, 47.85it/s]

→ 1500 Phase 3: finalize:  11%|█         | 52/473 [00:01<00:08, 47.68it/s]

→ 1500 Phase 3: finalize:  12%|█▏        | 57/473 [00:01<00:08, 47.54it/s]

→ 1500 Phase 3: finalize:  13%|█▎        | 62/473 [00:01<00:08, 47.37it/s]

→ 1500 Phase 3: finalize:  14%|█▍        | 67/473 [00:01<00:08, 47.25it/s]

→ 1500 Phase 3: finalize:  15%|█▌        | 72/473 [00:01<00:08, 47.21it/s]

→ 1500 Phase 3: finalize:  16%|█▋        | 77/473 [00:01<00:08, 47.25it/s]

→ 1500 Phase 3: finalize:  17%|█▋        | 82/473 [00:01<00:08, 47.34it/s]

→ 1500 Phase 3: finalize:  18%|█▊        | 87/473 [00:01<00:08, 47.38it/s]

→ 1500 Phase 3: finalize:  19%|█▉        | 92/473 [00:01<00:08, 47.35it/s]

→ 1500 Phase 3: finalize:  21%|██        | 97/473 [00:02<00:07, 47.33it/s]

→ 1500 Phase 3: finalize:  22%|██▏       | 102/473 [00:02<00:07, 47.28it/s]

→ 1500 Phase 3: finalize:  23%|██▎       | 107/473 [00:02<00:07, 47.32it/s]

→ 1500 Phase 3: finalize:  24%|██▎       | 112/473 [00:02<00:07, 47.38it/s]

→ 1500 Phase 3: finalize:  25%|██▍       | 117/473 [00:02<00:07, 47.70it/s]

→ 1500 Phase 3: finalize:  26%|██▌       | 122/473 [00:02<00:07, 47.93it/s]

→ 1500 Phase 3: finalize:  27%|██▋       | 127/473 [00:02<00:07, 47.98it/s]

→ 1500 Phase 3: finalize:  28%|██▊       | 132/473 [00:02<00:07, 48.23it/s]

→ 1500 Phase 3: finalize:  29%|██▉       | 137/473 [00:02<00:06, 48.33it/s]

→ 1500 Phase 3: finalize:  30%|███       | 142/473 [00:02<00:06, 48.29it/s]

→ 1500 Phase 3: finalize:  31%|███       | 147/473 [00:03<00:06, 48.56it/s]

→ 1500 Phase 3: finalize:  32%|███▏      | 152/473 [00:03<00:06, 48.27it/s]

→ 1500 Phase 3: finalize:  33%|███▎      | 157/473 [00:03<00:06, 48.28it/s]

→ 1500 Phase 3: finalize:  34%|███▍      | 162/473 [00:03<00:06, 48.43it/s]

→ 1500 Phase 3: finalize:  35%|███▌      | 167/473 [00:03<00:06, 48.61it/s]

→ 1500 Phase 3: finalize:  36%|███▋      | 172/473 [00:03<00:06, 48.81it/s]

→ 1500 Phase 3: finalize:  37%|███▋      | 177/473 [00:03<00:06, 49.15it/s]

→ 1500 Phase 3: finalize:  38%|███▊      | 182/473 [00:03<00:05, 48.95it/s]

→ 1500 Phase 3: finalize:  40%|███▉      | 187/473 [00:03<00:05, 48.97it/s]

→ 1500 Phase 3: finalize:  41%|████      | 192/473 [00:03<00:05, 49.10it/s]

→ 1500 Phase 3: finalize:  42%|████▏     | 197/473 [00:04<00:05, 49.22it/s]

→ 1500 Phase 3: finalize:  43%|████▎     | 202/473 [00:04<00:05, 48.77it/s]

→ 1500 Phase 3: finalize:  44%|████▍     | 207/473 [00:04<00:05, 47.57it/s]

→ 1500 Phase 3: finalize:  45%|████▍     | 212/473 [00:04<00:05, 47.85it/s]

→ 1500 Phase 3: finalize:  46%|████▌     | 217/473 [00:04<00:05, 48.02it/s]

→ 1500 Phase 3: finalize:  47%|████▋     | 222/473 [00:04<00:05, 48.16it/s]

→ 1500 Phase 3: finalize:  48%|████▊     | 227/473 [00:04<00:05, 48.32it/s]

→ 1500 Phase 3: finalize:  49%|████▉     | 232/473 [00:04<00:04, 48.45it/s]

→ 1500 Phase 3: finalize:  50%|█████     | 237/473 [00:04<00:04, 48.45it/s]

→ 1500 Phase 3: finalize:  51%|█████     | 242/473 [00:04<00:04, 48.40it/s]

→ 1500 Phase 3: finalize:  52%|█████▏    | 247/473 [00:05<00:04, 48.28it/s]

→ 1500 Phase 3: finalize:  53%|█████▎    | 252/473 [00:05<00:04, 48.77it/s]

→ 1500 Phase 3: finalize:  54%|█████▍    | 257/473 [00:05<00:04, 48.40it/s]

→ 1500 Phase 3: finalize:  55%|█████▌    | 262/473 [00:05<00:04, 48.32it/s]

→ 1500 Phase 3: finalize:  56%|█████▋    | 267/473 [00:05<00:04, 48.71it/s]

→ 1500 Phase 3: finalize:  58%|█████▊    | 272/473 [00:05<00:04, 48.96it/s]

→ 1500 Phase 3: finalize:  59%|█████▊    | 277/473 [00:05<00:04, 49.00it/s]

→ 1500 Phase 3: finalize:  60%|█████▉    | 282/473 [00:05<00:03, 49.22it/s]

→ 1500 Phase 3: finalize:  61%|██████    | 287/473 [00:05<00:03, 49.41it/s]

→ 1500 Phase 3: finalize:  62%|██████▏   | 292/473 [00:06<00:03, 49.47it/s]

→ 1500 Phase 3: finalize:  63%|██████▎   | 297/473 [00:06<00:03, 49.54it/s]

→ 1500 Phase 3: finalize:  64%|██████▍   | 302/473 [00:06<00:03, 49.58it/s]

→ 1500 Phase 3: finalize:  65%|██████▍   | 307/473 [00:06<00:03, 49.49it/s]

→ 1500 Phase 3: finalize:  66%|██████▌   | 312/473 [00:06<00:03, 49.39it/s]

→ 1500 Phase 3: finalize:  67%|██████▋   | 317/473 [00:06<00:03, 49.36it/s]

→ 1500 Phase 3: finalize:  68%|██████▊   | 322/473 [00:06<00:03, 49.26it/s]

→ 1500 Phase 3: finalize:  69%|██████▉   | 327/473 [00:06<00:02, 49.05it/s]

→ 1500 Phase 3: finalize:  70%|███████   | 332/473 [00:06<00:02, 48.81it/s]

→ 1500 Phase 3: finalize:  71%|███████   | 337/473 [00:06<00:02, 48.61it/s]

→ 1500 Phase 3: finalize:  72%|███████▏  | 342/473 [00:07<00:02, 48.50it/s]

→ 1500 Phase 3: finalize:  73%|███████▎  | 347/473 [00:07<00:02, 48.46it/s]

→ 1500 Phase 3: finalize:  74%|███████▍  | 352/473 [00:07<00:02, 48.58it/s]

→ 1500 Phase 3: finalize:  75%|███████▌  | 357/473 [00:07<00:02, 48.73it/s]

→ 1500 Phase 3: finalize:  77%|███████▋  | 362/473 [00:07<00:02, 48.87it/s]

→ 1500 Phase 3: finalize:  78%|███████▊  | 367/473 [00:07<00:02, 48.86it/s]

→ 1500 Phase 3: finalize:  79%|███████▊  | 372/473 [00:07<00:02, 48.76it/s]

→ 1500 Phase 3: finalize:  80%|███████▉  | 377/473 [00:07<00:01, 48.55it/s]

→ 1500 Phase 3: finalize:  81%|████████  | 382/473 [00:07<00:01, 48.53it/s]

→ 1500 Phase 3: finalize:  82%|████████▏ | 387/473 [00:07<00:01, 48.50it/s]

→ 1500 Phase 3: finalize:  83%|████████▎ | 392/473 [00:08<00:01, 48.45it/s]

→ 1500 Phase 3: finalize:  84%|████████▍ | 397/473 [00:08<00:01, 48.16it/s]

→ 1500 Phase 3: finalize:  85%|████████▍ | 402/473 [00:08<00:01, 48.30it/s]

→ 1500 Phase 3: finalize:  86%|████████▌ | 407/473 [00:08<00:01, 48.37it/s]

→ 1500 Phase 3: finalize:  87%|████████▋ | 412/473 [00:08<00:01, 48.36it/s]

→ 1500 Phase 3: finalize:  88%|████████▊ | 417/473 [00:08<00:01, 48.43it/s]

→ 1500 Phase 3: finalize:  89%|████████▉ | 422/473 [00:08<00:01, 48.31it/s]

→ 1500 Phase 3: finalize:  90%|█████████ | 427/473 [00:08<00:00, 47.83it/s]

→ 1500 Phase 3: finalize:  91%|█████████▏| 432/473 [00:08<00:00, 47.63it/s]

→ 1500 Phase 3: finalize:  92%|█████████▏| 437/473 [00:09<00:00, 47.88it/s]

→ 1500 Phase 3: finalize:  93%|█████████▎| 442/473 [00:09<00:00, 48.04it/s]

→ 1500 Phase 3: finalize:  95%|█████████▍| 447/473 [00:09<00:00, 48.00it/s]

→ 1500 Phase 3: finalize:  96%|█████████▌| 452/473 [00:09<00:00, 47.85it/s]

→ 1500 Phase 3: finalize:  97%|█████████▋| 457/473 [00:09<00:00, 47.43it/s]

→ 1500 Phase 3: finalize:  98%|█████████▊| 462/473 [00:09<00:00, 47.41it/s]

→ 1500 Phase 3: finalize:  99%|█████████▊| 467/473 [00:09<00:00, 47.25it/s]

→ 1500 Phase 3: finalize: 100%|██████████| 473/473 [00:09<00:00, 48.63it/s]

                                                                           
[TIMING] 1500 — 474 frames
  Phase 1  radial detect   (parallel)  :   7.37s  (15.6 ms/frame)
  Phase 2a corner detect   (parallel)  :   3.64s  (7.7 ms/frame)
  Phase 2b corner fix      (sequential):   0.24s
  Phase 3  finalize        (sequential):   9.75s  (20.6 ms/frame)
    decode + undistort                 :   5.37s  (11.3 ms/frame)
    corner apply + refinement          :   1.99s  (4.2 ms/frame)
    segment                            :   1.92s  (4.0 ms/frame)
    smooth                             :   0.32s  (0.7 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  21.01s


Processing Rigs:  50%|█████     | 2/4 [00:43<00:44, 22.44s/it][INFO] Filtered 161 stationary frames, 296 remain


→ 2000R (296 images) Phase 1:   0%|          | 0/296 [00:00<?, ?it/s]

→ 2000R (296 images) Phase 1:   0%|          | 1/296 [00:00<02:32,  1.93it/s]

→ 2000R (296 images) Phase 1:   1%|          | 2/296 [00:00<01:36,  3.04it/s]

→ 2000R (296 images) Phase 1:  11%|█         | 33/296 [00:00<00:05, 48.87it/s]

→ 2000R (296 images) Phase 1:  13%|█▎        | 39/296 [00:01<00:07, 36.65it/s]

→ 2000R (296 images) Phase 1:  22%|██▏       | 65/296 [00:01<00:03, 60.59it/s]

→ 2000R (296 images) Phase 1:  24%|██▍       | 72/296 [00:01<00:04, 50.79it/s]

→ 2000R (296 images) Phase 1:  33%|███▎      | 97/296 [00:01<00:02, 70.59it/s]

→ 2000R (296 images) Phase 1:  35%|███▌      | 105/296 [00:02<00:03, 57.21it/s]

→ 2000R (296 images) Phase 1:  44%|████▎     | 129/296 [00:02<00:02, 75.28it/s]

→ 2000R (296 images) Phase 1:  47%|████▋     | 138/296 [00:02<00:02, 60.48it/s]

→ 2000R (296 images) Phase 1:  54%|█████▍    | 161/296 [00:02<00:01, 75.14it/s]

→ 2000R (296 images) Phase 1:  57%|█████▋    | 170/296 [00:03<00:02, 61.56it/s]

→ 2000R (296 images) Phase 1:  62%|██████▏   | 183/296 [00:03<00:01, 69.29it/s]

→ 2000R (296 images) Phase 1:  66%|██████▌   | 194/296 [00:03<00:01, 70.55it/s]

→ 2000R (296 images) Phase 1:  68%|██████▊   | 202/296 [00:03<00:01, 63.76it/s]

→ 2000R (296 images) Phase 1:  73%|███████▎  | 216/296 [00:03<00:01, 73.11it/s]

→ 2000R (296 images) Phase 1:  76%|███████▋  | 226/296 [00:03<00:01, 69.67it/s]

→ 2000R (296 images) Phase 1:  79%|███████▉  | 234/296 [00:04<00:00, 62.91it/s]

→ 2000R (296 images) Phase 1:  84%|████████▍ | 248/296 [00:04<00:00, 76.69it/s]

→ 2000R (296 images) Phase 1:  87%|████████▋ | 258/296 [00:04<00:00, 69.87it/s]

→ 2000R (296 images) Phase 1:  90%|████████▉ | 266/296 [00:04<00:00, 62.60it/s]

→ 2000R (296 images) Phase 1:  96%|█████████▋| 285/296 [00:04<00:00, 85.98it/s]

→ 2000R (296 images) Phase 1: 100%|█████████▉| 295/296 [00:04<00:00, 81.66it/s]

                                                                               

→ 2000R Phase 2: corners:   0%|          | 0/295 [00:00<?, ?it/s]

→ 2000R Phase 2: corners:   0%|          | 1/295 [00:00<01:22,  3.58it/s]

→ 2000R Phase 2: corners:   4%|▍         | 13/295 [00:00<00:06, 41.68it/s]

→ 2000R Phase 2: corners:   9%|▉         | 26/295 [00:00<00:04, 66.36it/s]

→ 2000R Phase 2: corners:  14%|█▎        | 40/295 [00:00<00:02, 87.84it/s]

→ 2000R Phase 2: corners:  19%|█▉        | 56/295 [00:00<00:02, 106.31it/s]

→ 2000R Phase 2: corners:  24%|██▎       | 70/295 [00:00<00:01, 114.61it/s]

→ 2000R Phase 2: corners:  28%|██▊       | 83/295 [00:00<00:01, 118.34it/s]

→ 2000R Phase 2: corners:  34%|███▎      | 99/295 [00:01<00:01, 128.94it/s]

→ 2000R Phase 2: corners:  39%|███▊      | 114/295 [00:01<00:01, 134.85it/s]

→ 2000R Phase 2: corners:  43%|████▎     | 128/295 [00:01<00:01, 131.46it/s]

→ 2000R Phase 2: corners:  49%|████▉     | 146/295 [00:01<00:01, 144.67it/s]

→ 2000R Phase 2: corners:  55%|█████▌    | 163/295 [00:01<00:00, 146.41it/s]

→ 2000R Phase 2: corners:  61%|██████    | 180/295 [00:01<00:00, 151.74it/s]

→ 2000R Phase 2: corners:  66%|██████▋   | 196/295 [00:01<00:00, 150.73it/s]

→ 2000R Phase 2: corners:  73%|███████▎  | 214/295 [00:01<00:00, 156.68it/s]

→ 2000R Phase 2: corners:  79%|███████▊  | 232/295 [00:01<00:00, 160.36it/s]

→ 2000R Phase 2: corners:  84%|████████▍ | 249/295 [00:01<00:00, 157.94it/s]

→ 2000R Phase 2: corners:  90%|█████████ | 266/295 [00:02<00:00, 157.06it/s]

→ 2000R Phase 2: corners:  96%|█████████▌| 282/295 [00:02<00:00, 146.58it/s]

                                                                            [PASS2] Frame 0000542: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000543: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000544: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000599: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000600: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000601: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000602: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000610: fixed corners {0, 2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000183: fixed corners {1, 2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000543: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000183: fixed corners {1, 2} (was_fixed=False, trusted=False)
[PASS2] Summary: 3 frames fixed, 11 untrusted, 295 total


→ 2000R Phase 3: finalize:   0%|          | 0/295 [00:00<?, ?it/s]

→ 2000R Phase 3: finalize:   2%|▏         | 5/295 [00:00<00:05, 49.16it/s]

→ 2000R Phase 3: finalize:   4%|▎         | 11/295 [00:00<00:05, 53.82it/s]

→ 2000R Phase 3: finalize:   6%|▌         | 17/295 [00:00<00:05, 50.59it/s]

→ 2000R Phase 3: finalize:   8%|▊         | 23/295 [00:00<00:05, 49.20it/s]

→ 2000R Phase 3: finalize:   9%|▉         | 28/295 [00:00<00:05, 48.93it/s]

→ 2000R Phase 3: finalize:  11%|█         | 33/295 [00:00<00:05, 48.68it/s]

→ 2000R Phase 3: finalize:  13%|█▎        | 38/295 [00:00<00:05, 48.63it/s]

→ 2000R Phase 3: finalize:  15%|█▍        | 43/295 [00:00<00:05, 48.47it/s]

→ 2000R Phase 3: finalize:  16%|█▋        | 48/295 [00:00<00:05, 48.56it/s]

→ 2000R Phase 3: finalize:  18%|█▊        | 53/295 [00:01<00:04, 48.66it/s]

→ 2000R Phase 3: finalize:  20%|█▉        | 58/295 [00:01<00:04, 48.81it/s]

→ 2000R Phase 3: finalize:  21%|██▏       | 63/295 [00:01<00:04, 48.85it/s]

→ 2000R Phase 3: finalize:  23%|██▎       | 68/295 [00:01<00:04, 48.78it/s]

→ 2000R Phase 3: finalize:  25%|██▍       | 73/295 [00:01<00:04, 47.58it/s]

→ 2000R Phase 3: finalize:  26%|██▋       | 78/295 [00:01<00:04, 47.60it/s]

→ 2000R Phase 3: finalize:  28%|██▊       | 83/295 [00:01<00:04, 47.60it/s]

→ 2000R Phase 3: finalize:  30%|██▉       | 88/295 [00:01<00:04, 47.64it/s]

→ 2000R Phase 3: finalize:  32%|███▏      | 93/295 [00:01<00:04, 47.76it/s]

→ 2000R Phase 3: finalize:  33%|███▎      | 98/295 [00:02<00:04, 47.97it/s]

→ 2000R Phase 3: finalize:  35%|███▍      | 103/295 [00:02<00:04, 47.65it/s]

→ 2000R Phase 3: finalize:  37%|███▋      | 108/295 [00:02<00:03, 47.56it/s]

→ 2000R Phase 3: finalize:  38%|███▊      | 113/295 [00:02<00:03, 47.59it/s]

→ 2000R Phase 3: finalize:  40%|████      | 118/295 [00:02<00:03, 47.75it/s]

→ 2000R Phase 3: finalize:  42%|████▏     | 123/295 [00:02<00:03, 47.72it/s]

→ 2000R Phase 3: finalize:  43%|████▎     | 128/295 [00:02<00:03, 48.01it/s]

→ 2000R Phase 3: finalize:  45%|████▌     | 133/295 [00:02<00:03, 48.22it/s]

→ 2000R Phase 3: finalize:  47%|████▋     | 138/295 [00:02<00:03, 48.28it/s]

→ 2000R Phase 3: finalize:  48%|████▊     | 143/295 [00:02<00:03, 48.66it/s]

→ 2000R Phase 3: finalize:  51%|█████     | 149/295 [00:03<00:02, 49.31it/s]

→ 2000R Phase 3: finalize:  53%|█████▎    | 155/295 [00:03<00:02, 49.85it/s]

→ 2000R Phase 3: finalize:  55%|█████▍    | 161/295 [00:03<00:02, 50.24it/s]

→ 2000R Phase 3: finalize:  57%|█████▋    | 167/295 [00:03<00:02, 50.57it/s]

→ 2000R Phase 3: finalize:  59%|█████▊    | 173/295 [00:03<00:02, 50.11it/s]

→ 2000R Phase 3: finalize:  61%|██████    | 179/295 [00:03<00:02, 49.99it/s]

→ 2000R Phase 3: finalize:  62%|██████▏   | 184/295 [00:03<00:02, 49.82it/s]

→ 2000R Phase 3: finalize:  64%|██████▍   | 189/295 [00:03<00:02, 49.59it/s]

→ 2000R Phase 3: finalize:  66%|██████▌   | 194/295 [00:03<00:02, 49.59it/s]

→ 2000R Phase 3: finalize:  67%|██████▋   | 199/295 [00:04<00:01, 49.64it/s]

→ 2000R Phase 3: finalize:  69%|██████▉   | 205/295 [00:04<00:01, 49.88it/s]

→ 2000R Phase 3: finalize:  72%|███████▏  | 211/295 [00:04<00:01, 50.65it/s]

→ 2000R Phase 3: finalize:  74%|███████▎  | 217/295 [00:04<00:01, 50.90it/s]

→ 2000R Phase 3: finalize:  76%|███████▌  | 223/295 [00:04<00:01, 51.23it/s]

→ 2000R Phase 3: finalize:  78%|███████▊  | 229/295 [00:04<00:01, 51.59it/s]

→ 2000R Phase 3: finalize:  80%|███████▉  | 235/295 [00:04<00:01, 51.54it/s]

→ 2000R Phase 3: finalize:  82%|████████▏ | 241/295 [00:04<00:01, 51.51it/s]

→ 2000R Phase 3: finalize:  84%|████████▎ | 247/295 [00:05<00:00, 51.39it/s]

→ 2000R Phase 3: finalize:  86%|████████▌ | 253/295 [00:05<00:00, 51.16it/s]

→ 2000R Phase 3: finalize:  88%|████████▊ | 259/295 [00:05<00:00, 50.57it/s]

→ 2000R Phase 3: finalize:  90%|████████▉ | 265/295 [00:05<00:00, 50.15it/s]

→ 2000R Phase 3: finalize:  92%|█████████▏| 271/295 [00:05<00:00, 50.07it/s]

→ 2000R Phase 3: finalize:  94%|█████████▍| 277/295 [00:05<00:00, 49.16it/s]

→ 2000R Phase 3: finalize:  96%|█████████▌| 282/295 [00:05<00:00, 48.45it/s]

→ 2000R Phase 3: finalize:  97%|█████████▋| 287/295 [00:05<00:00, 48.09it/s]

→ 2000R Phase 3: finalize:  99%|█████████▉| 292/295 [00:05<00:00, 48.06it/s]

                                                                            
[TIMING] 2000R — 296 frames
  Phase 1  radial detect   (parallel)  :   4.91s  (16.6 ms/frame)
  Phase 2a corner detect   (parallel)  :   2.35s  (8.0 ms/frame)
  Phase 2b corner fix      (sequential):   0.32s
  Phase 3  finalize        (sequential):   5.99s  (20.2 ms/frame)
    decode + undistort                 :   3.27s  (11.0 ms/frame)
    corner apply + refinement          :   1.26s  (4.3 ms/frame)
    segment                            :   1.20s  (4.0 ms/frame)
    smooth                             :   0.17s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  13.57s


Processing Rigs:  75%|███████▌  | 3/4 [00:59<00:19, 19.52s/it][INFO] Filtered 294 stationary frames, 303 remain


→ 1000 (303 images) Phase 1:   0%|          | 0/303 [00:00<?, ?it/s]

→ 1000 (303 images) Phase 1:   0%|          | 1/303 [00:00<03:09,  1.60it/s]

→ 1000 (303 images) Phase 1:   3%|▎         | 9/303 [00:00<00:18, 16.08it/s]

→ 1000 (303 images) Phase 1:  11%|█         | 33/303 [00:01<00:06, 40.84it/s]

→ 1000 (303 images) Phase 1:  15%|█▍        | 45/303 [00:01<00:04, 53.32it/s]

→ 1000 (303 images) Phase 1:  21%|██▏       | 65/303 [00:01<00:04, 54.94it/s]

→ 1000 (303 images) Phase 1:  24%|██▍       | 73/303 [00:01<00:03, 58.75it/s]

→ 1000 (303 images) Phase 1:  32%|███▏      | 97/303 [00:01<00:03, 62.93it/s]

→ 1000 (303 images) Phase 1:  35%|███▍      | 105/303 [00:02<00:03, 65.02it/s]

→ 1000 (303 images) Phase 1:  43%|████▎     | 129/303 [00:02<00:02, 65.47it/s]

→ 1000 (303 images) Phase 1:  46%|████▌     | 140/303 [00:02<00:02, 71.69it/s]

→ 1000 (303 images) Phase 1:  53%|█████▎    | 161/303 [00:02<00:02, 65.18it/s]

→ 1000 (303 images) Phase 1:  58%|█████▊    | 175/303 [00:03<00:01, 75.24it/s]

→ 1000 (303 images) Phase 1:  64%|██████▎   | 193/303 [00:03<00:01, 63.66it/s]

→ 1000 (303 images) Phase 1:  70%|██████▉   | 212/303 [00:03<00:01, 81.59it/s]

→ 1000 (303 images) Phase 1:  74%|███████▍  | 225/303 [00:03<00:01, 63.18it/s]

→ 1000 (303 images) Phase 1:  80%|████████  | 243/303 [00:03<00:00, 79.80it/s]

→ 1000 (303 images) Phase 1:  85%|████████▍ | 257/303 [00:04<00:00, 62.95it/s]

→ 1000 (303 images) Phase 1:  90%|█████████ | 274/303 [00:04<00:00, 78.26it/s]

→ 1000 (303 images) Phase 1:  95%|█████████▌| 289/303 [00:04<00:00, 75.73it/s]

                                                                              

→ 1000 Phase 2: corners:   0%|          | 0/302 [00:00<?, ?it/s]

→ 1000 Phase 2: corners:   0%|          | 1/302 [00:00<01:30,  3.31it/s]

→ 1000 Phase 2: corners:   6%|▌         | 17/302 [00:00<00:05, 53.10it/s]

→ 1000 Phase 2: corners:   9%|▉         | 28/302 [00:00<00:03, 70.62it/s]

→ 1000 Phase 2: corners:  13%|█▎        | 38/302 [00:00<00:03, 77.71it/s]

→ 1000 Phase 2: corners:  18%|█▊        | 54/302 [00:00<00:02, 99.32it/s]

→ 1000 Phase 2: corners:  22%|██▏       | 66/302 [00:00<00:02, 103.08it/s]

→ 1000 Phase 2: corners:  27%|██▋       | 82/302 [00:00<00:01, 116.93it/s]

→ 1000 Phase 2: corners:  32%|███▏      | 96/302 [00:01<00:01, 120.54it/s]

→ 1000 Phase 2: corners:  36%|███▌      | 109/302 [00:01<00:01, 121.07it/s]

→ 1000 Phase 2: corners:  40%|████      | 122/302 [00:01<00:01, 123.16it/s]

→ 1000 Phase 2: corners:  45%|████▍     | 135/302 [00:01<00:01, 120.20it/s]

→ 1000 Phase 2: corners:  50%|█████     | 152/302 [00:01<00:01, 133.92it/s]

→ 1000 Phase 2: corners:  55%|█████▌    | 167/302 [00:01<00:00, 138.06it/s]

→ 1000 Phase 2: corners:  61%|██████▏   | 185/302 [00:01<00:00, 149.49it/s]

→ 1000 Phase 2: corners:  67%|██████▋   | 201/302 [00:01<00:00, 134.75it/s]

→ 1000 Phase 2: corners:  71%|███████   | 215/302 [00:01<00:00, 135.95it/s]

→ 1000 Phase 2: corners:  76%|███████▋  | 231/302 [00:02<00:00, 142.50it/s]

→ 1000 Phase 2: corners:  82%|████████▏ | 248/302 [00:02<00:00, 149.34it/s]

→ 1000 Phase 2: corners:  88%|████████▊ | 267/302 [00:02<00:00, 155.36it/s]

→ 1000 Phase 2: corners:  94%|█████████▍| 284/302 [00:02<00:00, 157.57it/s]

                                                                           [PASS2] Frame 0000506: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000529: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000530: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000531: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000532: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 3 frames fixed, 4 untrusted, 302 total


→ 1000 Phase 3: finalize:   0%|          | 0/302 [00:00<?, ?it/s]

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→ 1000 Phase 3: finalize:   6%|▋         | 19/302 [00:00<00:05, 54.81it/s]

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→ 1000 Phase 3: finalize:  10%|█         | 31/302 [00:00<00:05, 53.17it/s]

→ 1000 Phase 3: finalize:  12%|█▏        | 37/302 [00:00<00:05, 52.44it/s]

→ 1000 Phase 3: finalize:  14%|█▍        | 43/302 [00:00<00:05, 51.78it/s]

→ 1000 Phase 3: finalize:  16%|█▌        | 49/302 [00:00<00:04, 51.39it/s]

→ 1000 Phase 3: finalize:  18%|█▊        | 55/302 [00:01<00:04, 50.99it/s]

→ 1000 Phase 3: finalize:  20%|██        | 61/302 [00:01<00:04, 50.55it/s]

→ 1000 Phase 3: finalize:  22%|██▏       | 67/302 [00:01<00:04, 50.59it/s]

→ 1000 Phase 3: finalize:  24%|██▍       | 73/302 [00:01<00:04, 50.72it/s]

→ 1000 Phase 3: finalize:  26%|██▌       | 79/302 [00:01<00:04, 50.90it/s]

→ 1000 Phase 3: finalize:  28%|██▊       | 85/302 [00:01<00:04, 51.09it/s]

→ 1000 Phase 3: finalize:  30%|███       | 91/302 [00:01<00:04, 51.50it/s]

→ 1000 Phase 3: finalize:  32%|███▏      | 97/302 [00:01<00:03, 51.75it/s]

→ 1000 Phase 3: finalize:  34%|███▍      | 103/302 [00:01<00:03, 51.60it/s]

→ 1000 Phase 3: finalize:  36%|███▌      | 109/302 [00:02<00:03, 51.48it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 115/302 [00:02<00:03, 51.42it/s]

→ 1000 Phase 3: finalize:  40%|████      | 121/302 [00:02<00:03, 51.41it/s]

→ 1000 Phase 3: finalize:  42%|████▏     | 127/302 [00:02<00:03, 51.49it/s]

→ 1000 Phase 3: finalize:  44%|████▍     | 133/302 [00:02<00:03, 51.35it/s]

→ 1000 Phase 3: finalize:  46%|████▌     | 139/302 [00:02<00:03, 51.58it/s]

→ 1000 Phase 3: finalize:  48%|████▊     | 145/302 [00:02<00:03, 51.65it/s]

→ 1000 Phase 3: finalize:  50%|█████     | 151/302 [00:02<00:02, 51.70it/s]

→ 1000 Phase 3: finalize:  52%|█████▏    | 157/302 [00:03<00:02, 51.60it/s]

→ 1000 Phase 3: finalize:  54%|█████▍    | 163/302 [00:03<00:02, 51.50it/s]

→ 1000 Phase 3: finalize:  56%|█████▌    | 169/302 [00:03<00:02, 51.56it/s]

→ 1000 Phase 3: finalize:  58%|█████▊    | 175/302 [00:03<00:02, 51.60it/s]

→ 1000 Phase 3: finalize:  60%|█████▉    | 181/302 [00:03<00:02, 51.54it/s]

→ 1000 Phase 3: finalize:  62%|██████▏   | 187/302 [00:03<00:02, 51.46it/s]

→ 1000 Phase 3: finalize:  64%|██████▍   | 193/302 [00:03<00:02, 51.32it/s]

→ 1000 Phase 3: finalize:  66%|██████▌   | 199/302 [00:03<00:02, 51.49it/s]

→ 1000 Phase 3: finalize:  68%|██████▊   | 205/302 [00:03<00:01, 51.77it/s]

→ 1000 Phase 3: finalize:  70%|██████▉   | 211/302 [00:04<00:01, 52.01it/s]

→ 1000 Phase 3: finalize:  72%|███████▏  | 217/302 [00:04<00:01, 52.13it/s]

→ 1000 Phase 3: finalize:  74%|███████▍  | 223/302 [00:04<00:01, 52.13it/s]

→ 1000 Phase 3: finalize:  76%|███████▌  | 229/302 [00:04<00:01, 51.83it/s]

→ 1000 Phase 3: finalize:  78%|███████▊  | 235/302 [00:04<00:01, 51.43it/s]

→ 1000 Phase 3: finalize:  80%|███████▉  | 241/302 [00:04<00:01, 51.05it/s]

→ 1000 Phase 3: finalize:  82%|████████▏ | 247/302 [00:04<00:01, 51.04it/s]

→ 1000 Phase 3: finalize:  84%|████████▍ | 253/302 [00:04<00:00, 51.28it/s]

→ 1000 Phase 3: finalize:  86%|████████▌ | 259/302 [00:05<00:00, 51.26it/s]

→ 1000 Phase 3: finalize:  88%|████████▊ | 265/302 [00:05<00:00, 51.24it/s]

→ 1000 Phase 3: finalize:  90%|████████▉ | 271/302 [00:05<00:00, 51.29it/s]

→ 1000 Phase 3: finalize:  92%|█████████▏| 277/302 [00:05<00:00, 51.46it/s]

→ 1000 Phase 3: finalize:  94%|█████████▎| 283/302 [00:05<00:00, 51.83it/s]

→ 1000 Phase 3: finalize:  96%|█████████▌| 289/302 [00:05<00:00, 52.02it/s]

→ 1000 Phase 3: finalize:  98%|█████████▊| 295/302 [00:05<00:00, 52.15it/s]

→ 1000 Phase 3: finalize: 100%|█████████▉| 301/302 [00:05<00:00, 52.28it/s]

                                                                           
[TIMING] 1000 — 303 frames
  Phase 1  radial detect   (parallel)  :   4.80s  (15.8 ms/frame)
  Phase 2a corner detect   (parallel)  :   2.50s  (8.3 ms/frame)
  Phase 2b corner fix      (sequential):   0.18s
  Phase 3  finalize        (sequential):   5.84s  (19.3 ms/frame)
    decode + undistort                 :   3.29s  (10.9 ms/frame)
    corner apply + refinement          :   1.09s  (3.6 ms/frame)
    segment                            :   1.19s  (3.9 ms/frame)
    smooth                             :   0.17s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  13.32s


Processing Rigs: 100%|██████████| 4/4 [01:15<00:00, 18.18s/it]
Processing Rigs: 100%|██████████| 4/4 [01:15<00:00, 18.93s/it]
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 1397 frames from 4 rigs to /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 2000L: 100 frames selected from 327
[📋] 1500: 100 frames selected from 473
[📋] 2000R: 100 frames selected from 295
[📋] 1000: 100 frames selected from 302
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDCP3D-SL-013_W046(6)_2026-09-02/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<04:50,  3.68s/it]
Computing max image from bright frames:   2%|▎         | 2/80 [00:03<02:02,  1.57s/it]
Computing max image from bright frames:   4%|▍         | 3/80 [00:04<01:16,  1.01it/s]
Computing max image from bright frames:   5%|▌         | 4/80 [00:04<00:51,  1.48it/s]
Computing max image from bright frames:   6%|▋         | 5/80 [00:04<00:36,  2.05it/s]
Computing max image from bright frames:   8%|▊         | 6/80 [00:04<00:26,  2.79it/s]
Computing max image from bright frames:   9%|▉         | 7/80 [00:04<00:20,  3.57it/s]
Computing max image from bright frames:  10%|█         | 8/80 [00:04<00:16,  4.29it/s]
Computing max image from bright frames:  11%|█▏        | 9/80 [00:04<00:15,  4.46it/s]
Computing max image from bright frames:  14%|█▍        | 11/80 [00:05<00:11,  6.24it/s]
Computing max image from bright frames:  16%|█▋        | 13/80 [00:05<00:08,  7.89it/s]
Computing max image from bright frames:  18%|█▊        | 14/80 [00:05<00:08,  7.77it/s]
Computing max image from bright frames:  19%|█▉        | 15/80 [00:05<00:07,  8.14it/s]
Computing max image from bright frames:  20%|██        | 16/80 [00:05<00:11,  5.55it/s]
Computing max image from bright frames:  22%|██▎       | 18/80 [00:06<00:09,  6.77it/s]
Computing max image from bright frames:  25%|██▌       | 20/80 [00:06<00:07,  8.06it/s]
Computing max image from bright frames:  28%|██▊       | 22/80 [00:06<00:06,  9.37it/s]
Computing max image from bright frames:  30%|███       | 24/80 [00:06<00:05,  9.78it/s]
Computing max image from bright frames:  32%|███▎      | 26/80 [00:06<00:05, 10.53it/s]
Computing max image from bright frames:  35%|███▌      | 28/80 [00:07<00:05,  9.44it/s]
Computing max image from bright frames:  38%|███▊      | 30/80 [00:07<00:05,  9.86it/s]
Computing max image from bright frames:  40%|████      | 32/80 [00:07<00:05,  8.69it/s]
Computing max image from bright frames:  41%|████▏     | 33/80 [00:08<00:13,  3.39it/s]
Computing max image from bright frames:  44%|████▍     | 35/80 [00:08<00:11,  3.93it/s]
Computing max image from bright frames:  46%|████▋     | 37/80 [00:09<00:09,  4.69it/s]
Computing max image from bright frames:  49%|████▉     | 39/80 [00:09<00:06,  6.03it/s]
Computing max image from bright frames:  51%|█████▏    | 41/80 [00:09<00:07,  5.38it/s]
Computing max image from bright frames:  54%|█████▍    | 43/80 [00:09<00:05,  6.48it/s]
Computing max image from bright frames:  55%|█████▌    | 44/80 [00:10<00:05,  6.50it/s]
Computing max image from bright frames:  56%|█████▋    | 45/80 [00:10<00:05,  6.74it/s]
Computing max image from bright frames:  57%|█████▊    | 46/80 [00:10<00:04,  7.18it/s]
Computing max image from bright frames:  59%|█████▉    | 47/80 [00:10<00:04,  6.84it/s]
Computing max image from bright frames:  60%|██████    | 48/80 [00:10<00:04,  7.27it/s]
Computing max image from bright frames:  61%|██████▏   | 49/80 [00:10<00:04,  7.27it/s]
Computing max image from bright frames:  64%|██████▍   | 51/80 [00:11<00:03,  7.47it/s]
Computing max image from bright frames:  65%|██████▌   | 52/80 [00:11<00:03,  7.39it/s]
Computing max image from bright frames:  66%|██████▋   | 53/80 [00:11<00:03,  7.50it/s]
Computing max image from bright frames:  69%|██████▉   | 55/80 [00:11<00:02, 10.09it/s]
Computing max image from bright frames:  72%|███████▎  | 58/80 [00:11<00:01, 14.22it/s]
Computing max image from bright frames:  76%|███████▋  | 61/80 [00:11<00:01, 17.49it/s]
Computing max image from bright frames:  79%|███████▉  | 63/80 [00:11<00:01, 13.29it/s]
Computing max image from bright frames:  81%|████████▏ | 65/80 [00:12<00:02,  5.19it/s]
Computing max image from bright frames:  86%|████████▋ | 69/80 [00:13<00:01,  8.16it/s]
Computing max image from bright frames:  90%|█████████ | 72/80 [00:13<00:00,  9.80it/s]
Computing max image from bright frames:  92%|█████████▎| 74/80 [00:13<00:00, 10.25it/s]
Computing max image from bright frames:  96%|█████████▋| 77/80 [00:13<00:00, 12.18it/s]
                                                                                       
[✅] Casing detection complete: cx=863.0, cy=995.0

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


  0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:25,  3.86it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   1%|          | 1/100 [00:00<00:25,  3.86it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   2%|▏         | 2/100 [00:00<00:25,  3.86it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 321.212} (0.001):   3%|▎         | 3/100 [00:00<00:25,  3.86it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 328.283} (0.001):   4%|▍         | 4/100 [00:00<00:24,  3.86it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 328.283} (0.001):   5%|▌         | 5/100 [00:00<00:06, 15.66it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 335.354} (0.001):   5%|▌         | 5/100 [00:00<00:06, 15.66it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 342.424} (0.001):   6%|▌         | 6/100 [00:00<00:06, 15.66it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 349.495} (0.001):   7%|▋         | 7/100 [00:00<00:05, 15.66it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   8%|▊         | 8/100 [00:00<00:05, 15.66it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   9%|▉         | 9/100 [00:00<00:04, 22.46it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.002 | Best: {'fx': 363.636} (0.002):   9%|▉         | 9/100 [00:00<00:04, 22.46it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.002 | Best: {'fx': 370.707} (0.002):  10%|█         | 10/100 [00:00<00:04, 22.46it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.003 | Best: {'fx': 377.778} (0.003):  11%|█         | 11/100 [00:00<00:03, 22.46it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.003 | Best: {'fx': 377.778} (0.003):  12%|█▏        | 12/100 [00:00<00:03, 23.50it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.003 | Best: {'fx': 384.848} (0.003):  12%|█▏        | 12/100 [00:00<00:03, 23.50it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.004 | Best: {'fx': 391.919} (0.004):  13%|█▎        | 13/100 [00:00<00:03, 23.50it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  14%|█▍        | 14/100 [00:00<00:03, 23.50it/s] 
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  15%|█▌        | 15/100 [00:00<00:03, 23.50it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  16%|█▌        | 16/100 [00:00<00:03, 26.64it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  16%|█▌        | 16/100 [00:00<00:03, 26.64it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  17%|█▋        | 17/100 [00:00<00:03, 26.64it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  18%|█▊        | 18/100 [00:00<00:03, 26.64it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.008 | Best: {'fx': 434.343} (0.008):  19%|█▉        | 19/100 [00:00<00:03, 26.64it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.008 | Best: {'fx': 434.343} (0.008):  20%|██        | 20/100 [00:00<00:02, 28.00it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.012 | Best: {'fx': 455.556} (0.012):  20%|██        | 20/100 [00:00<00:02, 28.00it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.018 | Best: {'fx': 469.697} (0.018):  21%|██        | 21/100 [00:00<00:02, 28.00it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.010 | Best: {'fx': 469.697} (0.018):  22%|██▏       | 22/100 [00:00<00:02, 28.00it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.010 | Best: {'fx': 469.697} (0.018):  23%|██▎       | 23/100 [00:00<00:02, 26.16it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.009 | Best: {'fx': 469.697} (0.018):  23%|██▎       | 23/100 [00:00<00:02, 26.16it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.015 | Best: {'fx': 469.697} (0.018):  24%|██▍       | 24/100 [00:01<00:02, 26.16it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.024 | Best: {'fx': 483.838} (0.024):  25%|██▌       | 25/100 [00:01<00:02, 26.16it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.024 | Best: {'fx': 483.838} (0.024):  26%|██▌       | 26/100 [00:01<00:02, 26.56it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 483.838} (0.024):  26%|██▌       | 26/100 [00:01<00:02, 26.56it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.038 | Best: {'fx': 497.98} (0.038):  27%|██▋       | 27/100 [00:01<00:02, 26.56it/s] 
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.030 | Best: {'fx': 497.98} (0.038):  28%|██▊       | 28/100 [00:01<00:02, 26.56it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.047 | Best: {'fx': 505.051} (0.047):  29%|██▉       | 29/100 [00:01<00:02, 26.56it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.056 | Best: {'fx': 512.121} (0.056):  30%|███       | 30/100 [00:01<00:02, 26.56it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.064 | Best: {'fx': 547.475} (0.064):  31%|███       | 31/100 [00:01<00:02, 26.56it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.064 | Best: {'fx': 547.475} (0.064):  32%|███▏      | 32/100 [00:01<00:03, 19.99it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.082 | Best: {'fx': 533.333} (0.082):  32%|███▏      | 32/100 [00:01<00:03, 19.99it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.078 | Best: {'fx': 533.333} (0.082):  33%|███▎      | 33/100 [00:01<00:03, 19.99it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.049 | Best: {'fx': 533.333} (0.082):  34%|███▍      | 34/100 [00:01<00:03, 19.99it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.049 | Best: {'fx': 533.333} (0.082):  35%|███▌      | 35/100 [00:01<00:03, 20.54it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.056 | Best: {'fx': 533.333} (0.082):  35%|███▌      | 35/100 [00:01<00:03, 20.54it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.066 | Best: {'fx': 533.333} (0.082):  36%|███▌      | 36/100 [00:01<00:03, 20.54it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.045 | Best: {'fx': 533.333} (0.082):  37%|███▋      | 37/100 [00:01<00:03, 20.54it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.040 | Best: {'fx': 533.333} (0.082):  38%|███▊      | 38/100 [00:01<00:03, 20.54it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.073 | Best: {'fx': 533.333} (0.082):  39%|███▉      | 39/100 [00:01<00:02, 20.54it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.035 | Best: {'fx': 533.333} (0.082):  40%|████      | 40/100 [00:01<00:02, 20.54it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.042 | Best: {'fx': 533.333} (0.082):  41%|████      | 41/100 [00:01<00:02, 20.54it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.042 | Best: {'fx': 533.333} (0.082):  42%|████▏     | 42/100 [00:01<00:02, 26.65it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.037 | Best: {'fx': 533.333} (0.082):  42%|████▏     | 42/100 [00:01<00:02, 26.65it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.033 | Best: {'fx': 533.333} (0.082):  43%|████▎     | 43/100 [00:01<00:02, 26.65it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.031 | Best: {'fx': 533.333} (0.082):  44%|████▍     | 44/100 [00:01<00:02, 26.65it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.029 | Best: {'fx': 533.333} (0.082):  45%|████▌     | 45/100 [00:01<00:02, 26.65it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.029 | Best: {'fx': 533.333} (0.082):  46%|████▌     | 46/100 [00:01<00:01, 28.79it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.032 | Best: {'fx': 533.333} (0.082):  46%|████▌     | 46/100 [00:01<00:01, 28.79it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.028 | Best: {'fx': 533.333} (0.082):  47%|████▋     | 47/100 [00:01<00:01, 28.79it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.030 | Best: {'fx': 533.333} (0.082):  48%|████▊     | 48/100 [00:01<00:01, 28.79it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.027 | Best: {'fx': 533.333} (0.082):  49%|████▉     | 49/100 [00:02<00:01, 28.79it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.027 | Best: {'fx': 533.333} (0.082):  50%|█████     | 50/100 [00:02<00:01, 29.36it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.027 | Best: {'fx': 533.333} (0.082):  50%|█████     | 50/100 [00:02<00:01, 29.36it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.026 | Best: {'fx': 533.333} (0.082):  51%|█████     | 51/100 [00:02<00:01, 29.36it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.026 | Best: {'fx': 533.333} (0.082):  52%|█████▏    | 52/100 [00:02<00:01, 29.36it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.023 | Best: {'fx': 533.333} (0.082):  53%|█████▎    | 53/100 [00:02<00:01, 29.36it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.023 | Best: {'fx': 533.333} (0.082):  54%|█████▍    | 54/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.082):  54%|█████▍    | 54/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 533.333} (0.082):  55%|█████▌    | 55/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.024 | Best: {'fx': 533.333} (0.082):  56%|█████▌    | 56/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.025 | Best: {'fx': 533.333} (0.082):  57%|█████▋    | 57/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.023 | Best: {'fx': 533.333} (0.082):  58%|█████▊    | 58/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 533.333} (0.082):  59%|█████▉    | 59/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.024 | Best: {'fx': 533.333} (0.082):  60%|██████    | 60/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.025 | Best: {'fx': 533.333} (0.082):  61%|██████    | 61/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.023 | Best: {'fx': 533.333} (0.082):  62%|██████▏   | 62/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.082):  63%|██████▎   | 63/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.082):  64%|██████▍   | 64/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 533.333} (0.082):  65%|██████▌   | 65/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 533.333} (0.082):  66%|██████▌   | 66/100 [00:02<00:01, 27.58it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.022 | Best: {'fx': 533.333} (0.082):  67%|██████▋   | 67/100 [00:02<00:00, 47.09it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.082):  67%|██████▋   | 67/100 [00:02<00:00, 47.09it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.023 | Best: {'fx': 533.333} (0.082):  68%|██████▊   | 68/100 [00:02<00:00, 47.09it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.082):  69%|██████▉   | 69/100 [00:02<00:00, 47.09it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.082):  70%|███████   | 70/100 [00:02<00:00, 47.09it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.082):  71%|███████   | 71/100 [00:02<00:00, 47.09it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.082):  72%|███████▏  | 72/100 [00:02<00:00, 47.09it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.021 | Best: {'fx': 533.333} (0.082):  73%|███████▎  | 73/100 [00:02<00:00, 46.00it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.082):  73%|███████▎  | 73/100 [00:02<00:00, 46.00it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.082):  74%|███████▍  | 74/100 [00:02<00:00, 46.00it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.082):  75%|███████▌  | 75/100 [00:02<00:00, 46.00it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.082):  76%|███████▌  | 76/100 [00:02<00:00, 46.00it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.082):  77%|███████▋  | 77/100 [00:02<00:00, 46.00it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.082):  78%|███████▊  | 78/100 [00:02<00:00, 42.33it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.082):  78%|███████▊  | 78/100 [00:02<00:00, 42.33it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.082):  79%|███████▉  | 79/100 [00:02<00:00, 42.33it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.020 | Best: {'fx': 533.333} (0.082):  80%|████████  | 80/100 [00:02<00:00, 42.33it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  81%|████████  | 81/100 [00:02<00:00, 42.33it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  82%|████████▏ | 82/100 [00:02<00:00, 42.33it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  83%|████████▎ | 83/100 [00:02<00:00, 38.96it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  83%|████████▎ | 83/100 [00:02<00:00, 38.96it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  84%|████████▍ | 84/100 [00:02<00:00, 38.96it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  85%|████████▌ | 85/100 [00:02<00:00, 38.96it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  86%|████████▌ | 86/100 [00:02<00:00, 38.96it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  87%|████████▋ | 87/100 [00:02<00:00, 38.96it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  88%|████████▊ | 88/100 [00:02<00:00, 40.51it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  88%|████████▊ | 88/100 [00:02<00:00, 40.51it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  89%|████████▉ | 89/100 [00:02<00:00, 40.51it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  90%|█████████ | 90/100 [00:02<00:00, 40.51it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  91%|█████████ | 91/100 [00:02<00:00, 40.51it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  92%|█████████▏| 92/100 [00:02<00:00, 40.51it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  93%|█████████▎| 93/100 [00:03<00:00, 40.51it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  94%|█████████▍| 94/100 [00:03<00:00, 39.48it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.018 | Best: {'fx': 533.333} (0.082):  94%|█████████▍| 94/100 [00:03<00:00, 39.48it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.018 | Best: {'fx': 533.333} (0.082):  95%|█████████▌| 95/100 [00:03<00:00, 39.48it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  96%|█████████▌| 96/100 [00:03<00:00, 39.48it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.019 | Best: {'fx': 533.333} (0.082):  97%|█████████▋| 97/100 [00:03<00:00, 39.48it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.018 | Best: {'fx': 533.333} (0.082):  98%|█████████▊| 98/100 [00:03<00:00, 39.48it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.018 | Best: {'fx': 533.333} (0.082):  99%|█████████▉| 99/100 [00:03<00:00, 34.53it/s]
Brute | Start: {'fx': 500.0} (0.040) | Current: 0.018 | Best: {'fx': 533.333} (0.082):  99%|█████████▉| 99/100 [00:03<00:00, 34.53it/s]
                                                                                                                                       

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.051 | Best: {'fx': 508.333} (0.051):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.051 | Best: {'fx': 508.333} (0.051):   2%|▏         | 1/50 [00:00<00:25,  1.96it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.052 | Best: {'fx': 509.354} (0.052):   2%|▏         | 1/50 [00:00<00:25,  1.96it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.054 | Best: {'fx': 510.374} (0.054):   4%|▍         | 2/50 [00:00<00:24,  1.96it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.059 | Best: {'fx': 513.435} (0.059):   6%|▌         | 3/50 [00:00<00:24,  1.96it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.059 | Best: {'fx': 513.435} (0.059):   8%|▊         | 4/50 [00:00<00:06,  6.62it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.055 | Best: {'fx': 513.435} (0.059):   8%|▊         | 4/50 [00:00<00:06,  6.62it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.057 | Best: {'fx': 513.435} (0.059):  10%|█         | 5/50 [00:00<00:06,  6.62it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.062 | Best: {'fx': 515.476} (0.062):  12%|█▏        | 6/50 [00:00<00:06,  6.62it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.063 | Best: {'fx': 516.497} (0.063):  14%|█▍        | 7/50 [00:00<00:06,  6.62it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.060 | Best: {'fx': 516.497} (0.063):  16%|█▌        | 8/50 [00:00<00:06,  6.62it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.060 | Best: {'fx': 516.497} (0.063):  18%|█▊        | 9/50 [00:00<00:02, 15.01it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.068 | Best: {'fx': 521.599} (0.068):  18%|█▊        | 9/50 [00:00<00:02, 15.01it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.070 | Best: {'fx': 522.619} (0.070):  20%|██        | 10/50 [00:01<00:02, 15.01it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.064 | Best: {'fx': 522.619} (0.070):  22%|██▏       | 11/50 [00:01<00:02, 15.01it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.064 | Best: {'fx': 522.619} (0.070):  24%|██▍       | 12/50 [00:01<00:02, 14.64it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.072 | Best: {'fx': 523.639} (0.072):  24%|██▍       | 12/50 [00:01<00:02, 14.64it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.065 | Best: {'fx': 523.639} (0.072):  26%|██▌       | 13/50 [00:01<00:02, 14.64it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.068 | Best: {'fx': 523.639} (0.072):  28%|██▊       | 14/50 [00:01<00:02, 14.64it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.067 | Best: {'fx': 523.639} (0.072):  30%|███       | 15/50 [00:01<00:02, 14.64it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.075 | Best: {'fx': 524.66} (0.075):  32%|███▏      | 16/50 [00:01<00:02, 14.64it/s] 
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.078 | Best: {'fx': 526.701} (0.078):  34%|███▍      | 17/50 [00:01<00:02, 14.64it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.078 | Best: {'fx': 526.701} (0.078):  36%|███▌      | 18/50 [00:01<00:01, 21.58it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.078 | Best: {'fx': 526.701} (0.078):  36%|███▌      | 18/50 [00:01<00:01, 21.58it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.077 | Best: {'fx': 526.701} (0.078):  38%|███▊      | 19/50 [00:01<00:01, 21.58it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.071 | Best: {'fx': 526.701} (0.078):  40%|████      | 20/50 [00:01<00:01, 21.58it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.071 | Best: {'fx': 526.701} (0.078):  42%|████▏     | 21/50 [00:01<00:01, 19.33it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.082 | Best: {'fx': 532.823} (0.082):  42%|████▏     | 21/50 [00:01<00:01, 19.33it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.074 | Best: {'fx': 532.823} (0.082):  44%|████▍     | 22/50 [00:01<00:01, 19.33it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.081 | Best: {'fx': 532.823} (0.082):  46%|████▌     | 23/50 [00:01<00:01, 19.33it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.083 | Best: {'fx': 531.803} (0.083):  48%|████▊     | 24/50 [00:01<00:01, 19.33it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.079 | Best: {'fx': 531.803} (0.083):  50%|█████     | 25/50 [00:01<00:01, 19.33it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.081 | Best: {'fx': 531.803} (0.083):  52%|█████▏    | 26/50 [00:01<00:01, 19.33it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.081 | Best: {'fx': 531.803} (0.083):  54%|█████▍    | 27/50 [00:01<00:00, 26.16it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.069 | Best: {'fx': 531.803} (0.083):  54%|█████▍    | 27/50 [00:01<00:00, 26.16it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.070 | Best: {'fx': 531.803} (0.083):  56%|█████▌    | 28/50 [00:01<00:00, 26.16it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.081 | Best: {'fx': 531.803} (0.083):  58%|█████▊    | 29/50 [00:01<00:00, 26.16it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.069 | Best: {'fx': 531.803} (0.083):  60%|██████    | 30/50 [00:01<00:00, 26.16it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.078 | Best: {'fx': 531.803} (0.083):  62%|██████▏   | 31/50 [00:01<00:00, 26.16it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.079 | Best: {'fx': 531.803} (0.083):  64%|██████▍   | 32/50 [00:01<00:00, 26.16it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.081 | Best: {'fx': 531.803} (0.083):  66%|██████▌   | 33/50 [00:01<00:00, 26.16it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.067 | Best: {'fx': 531.803} (0.083):  68%|██████▊   | 34/50 [00:01<00:00, 26.16it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.077 | Best: {'fx': 531.803} (0.083):  70%|███████   | 35/50 [00:01<00:00, 26.16it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.064 | Best: {'fx': 531.803} (0.083):  72%|███████▏  | 36/50 [00:01<00:00, 26.16it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.064 | Best: {'fx': 531.803} (0.083):  74%|███████▍  | 37/50 [00:01<00:00, 39.31it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.068 | Best: {'fx': 531.803} (0.083):  74%|███████▍  | 37/50 [00:01<00:00, 39.31it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.065 | Best: {'fx': 531.803} (0.083):  76%|███████▌  | 38/50 [00:01<00:00, 39.31it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.076 | Best: {'fx': 531.803} (0.083):  78%|███████▊  | 39/50 [00:01<00:00, 39.31it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.063 | Best: {'fx': 531.803} (0.083):  80%|████████  | 40/50 [00:01<00:00, 39.31it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.059 | Best: {'fx': 531.803} (0.083):  82%|████████▏ | 41/50 [00:01<00:00, 39.31it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.059 | Best: {'fx': 531.803} (0.083):  84%|████████▍ | 42/50 [00:01<00:00, 41.27it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.060 | Best: {'fx': 531.803} (0.083):  84%|████████▍ | 42/50 [00:01<00:00, 41.27it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.061 | Best: {'fx': 531.803} (0.083):  86%|████████▌ | 43/50 [00:01<00:00, 41.27it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.055 | Best: {'fx': 531.803} (0.083):  88%|████████▊ | 44/50 [00:01<00:00, 41.27it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.058 | Best: {'fx': 531.803} (0.083):  90%|█████████ | 45/50 [00:01<00:00, 41.27it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.057 | Best: {'fx': 531.803} (0.083):  92%|█████████▏| 46/50 [00:01<00:00, 41.27it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.054 | Best: {'fx': 531.803} (0.083):  94%|█████████▍| 47/50 [00:01<00:00, 41.27it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.054 | Best: {'fx': 531.803} (0.083):  96%|█████████▌| 48/50 [00:01<00:00, 45.70it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.053 | Best: {'fx': 531.803} (0.083):  96%|█████████▌| 48/50 [00:01<00:00, 45.70it/s]
Brute | Start: {'fx': 533.333} (0.082) | Current: 0.053 | Best: {'fx': 531.803} (0.083):  98%|█████████▊| 49/50 [00:01<00:00, 45.70it/s]
                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 531.8027210884354
    px: 863.0
    py: 995.0
    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 1 incomplete frames): 79 frames will be used for optimization
  Rigs: 2000L(2000mm):20/20, 1500(1500mm):19/20, 2000R(2000mm):20/20, 1000(1000mm):20/20
  Total: 79/80 frames used for optimization

Initial score: 52.5972: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 52.5972, picklable_objective(x0) = 52.6182

Best score: 52.6182: : 0iter [00:01, ?iter/s] 
Best score: 52.6182: : 1iter [00:01,  2.00s/iter]
Best score: 52.6182: : 1iter [00:02,  2.00s/iter]
Best score: 52.6182: : 2iter [00:02,  2.00s/iter]
Best score: 52.6182: : 3iter [00:02,  1.72iter/s]
Best score: 52.6182: : 3iter [00:02,  1.72iter/s]
Best score: 52.6182: : 4iter [00:02,  1.72iter/s]
Best score: 52.6182: : 5iter [00:02,  3.06iter/s]
Best score: 52.6182: : 5iter [00:02,  3.06iter/s]
Best score: 52.6182: : 6iter [00:02,  3.06iter/s]
Best score: 52.6182: : 7iter [00:02,  4.44iter/s]
Best score: 52.6182: : 7iter [00:02,  4.44iter/s]
Best score: 52.6182: : 8iter [00:02,  4.44iter/s]
Best score: 52.6182: : 9iter [00:02,  5.79iter/s]
Best score: 52.6182: : 9iter [00:02,  5.79iter/s]
Best score: 52.6182: : 10iter [00:02,  5.79iter/s]
Best score: 52.6182: : 11iter [00:02,  6.96iter/s]
Best score: 52.6182: : 11iter [00:02,  6.96iter/s]
Best score: 52.6182: : 12iter [00:03,  6.96iter/s]
Best score: 52.6182: : 13iter [00:03,  8.02iter/s]
Best score: 52.6182: : 13iter [00:03,  8.02iter/s]
Best score: 52.6182: : 14iter [00:03,  8.02iter/s]
Best score: 52.6182: : 15iter [00:03,  8.90iter/s]
Best score: 52.6182: : 15iter [00:03,  8.90iter/s]
Best score: 52.6182: : 16iter [00:03,  8.90iter/s]
Best score: 52.6182: : 17iter [00:03,  9.60iter/s]
Best score: 52.6182: : 17iter [00:03,  9.60iter/s]
Best score: 52.6182: : 18iter [00:03,  9.60iter/s]
Best score: 52.6182: : 19iter [00:03, 10.16iter/s]
Best score: 52.6182: : 19iter [00:03, 10.16iter/s]
Best score: 52.6182: : 20iter [00:03, 10.16iter/s]
Best score: 52.6182: : 21iter [00:03, 10.42iter/s]
Best score: 52.6182: : 21iter [00:03, 10.42iter/s]
Best score: 52.6182: : 22iter [00:03, 10.42iter/s]
Best score: 52.6182: : 23iter [00:03, 10.72iter/s]
Best score: 52.6182: : 23iter [00:03, 10.72iter/s]
Best score: 52.6182: : 24iter [00:04, 10.72iter/s]
Best score: 52.6182: : 25iter [00:04, 10.99iter/s]
Best score: 52.6182: : 25iter [00:04, 10.99iter/s]
Best score: 52.6182: : 26iter [00:04, 10.99iter/s]
Best score: 52.6182: : 27iter [00:04, 11.19iter/s]
Best score: 52.6182: : 27iter [00:04, 11.19iter/s]
Best score: 52.6182: : 28iter [00:04, 11.19iter/s]
Best score: 52.6182: : 29iter [00:04, 11.34iter/s]
Best score: 52.6182: : 29iter [00:04, 11.34iter/s]
Best score: 52.6182: : 30iter [00:04, 11.34iter/s]
Best score: 52.6182: : 31iter [00:04, 11.27iter/s]
Best score: 52.6182: : 31iter [00:04, 11.27iter/s]
Best score: 52.6182: : 32iter [00:04, 11.27iter/s]
Best score: 52.6182: : 33iter [00:04, 11.43iter/s]
Best score: 52.6182: : 33iter [00:04, 11.43iter/s]
Best score: 52.6182: : 34iter [00:04, 11.43iter/s]
Best score: 52.6182: : 35iter [00:04, 11.54iter/s]
Best score: 52.6182: : 35iter [00:05, 11.54iter/s]
Best score: 52.6182: : 36iter [00:05, 11.54iter/s]
Best score: 52.6182: : 37iter [00:05, 11.63iter/s]
Best score: 52.6182: : 37iter [00:05, 11.63iter/s]
Best score: 52.6182: : 38iter [00:05, 11.63iter/s]
Best score: 52.6182: : 39iter [00:05, 11.58iter/s]
Best score: 27.9635: : 39iter [00:05, 11.58iter/s]
Best score: 27.9635: : 40iter [00:05, 11.58iter/s]
Best score: 27.9635: : 41iter [00:05, 11.46iter/s]
Best score: 27.9635: : 41iter [00:05, 11.46iter/s]
Best score: 27.9635: : 42iter [00:05, 11.46iter/s]
Best score: 27.9635: : 43iter [00:05, 11.56iter/s]
Best score: 27.9635: : 43iter [00:05, 11.56iter/s]
Best score: 27.9635: : 44iter [00:05, 11.56iter/s]
Best score: 27.9635: : 45iter [00:05, 11.66iter/s]
Best score: 27.9635: : 45iter [00:05, 11.66iter/s]
Best score: 27.9635: : 46iter [00:05, 11.66iter/s]
Best score: 27.9635: : 47iter [00:05, 11.67iter/s]
Best score: 27.9635: : 47iter [00:06, 11.67iter/s]
Best score: 27.9635: : 48iter [00:06, 11.67iter/s]
Best score: 27.9635: : 49iter [00:06, 11.72iter/s]
[ITER 50] Best: 23.3743
[PARAMS] Current best parameters:
  fx: 528.9495
  fy: 520.8987
  px: 847.1861
  py: 1002.8176
  k1: 0.02818447
  k2: 0.01145361
  k3: -0.03269657
  k4: 0.01203845
  p1: 0.00351183
  p2: 0.00969871
  p3: 0.01478921
  p4: 0.01931233
  s1: -0.0120
  s2: -0.0064
  s3: -0.0083
  s4: -0.0045
  tilt_x: -0.0023
  tilt_y: 0.0214
  scale: 2.9773
  rotation: -0.7715

Best score: 23.3743: : 49iter [00:06, 11.72iter/s]
Best score: 23.3743: : 50iter [00:06, 11.72iter/s]
Best score: 23.3743: : 51iter [00:06, 11.51iter/s]
Best score: 23.3743: : 51iter [00:06, 11.51iter/s]
Best score: 23.3743: : 52iter [00:06, 11.51iter/s]
Best score: 23.3743: : 53iter [00:06, 11.57iter/s]
Best score: 23.3743: : 53iter [00:06, 11.57iter/s]
Best score: 23.3743: : 54iter [00:06, 11.57iter/s]
Best score: 23.3743: : 55iter [00:06, 11.66iter/s]
Best score: 23.3743: : 55iter [00:06, 11.66iter/s]
Best score: 23.3743: : 56iter [00:06, 11.66iter/s]
Best score: 23.3743: : 57iter [00:06, 11.74iter/s]
Best score: 23.3743: : 57iter [00:06, 11.74iter/s]
Best score: 23.3743: : 58iter [00:07, 11.74iter/s]
Best score: 23.3743: : 59iter [00:07, 11.69iter/s]
Best score: 18.8948: : 59iter [00:07, 11.69iter/s]
Best score: 18.8948: : 60iter [00:07, 11.69iter/s]
Best score: 18.8948: : 61iter [00:07, 11.47iter/s]
Best score: 18.8948: : 61iter [00:07, 11.47iter/s]
Best score: 18.8948: : 62iter [00:07, 11.47iter/s]
Best score: 18.8948: : 63iter [00:07, 11.57iter/s]
Best score: 18.8948: : 63iter [00:07, 11.57iter/s]
Best score: 18.8948: : 64iter [00:07, 11.57iter/s]
Best score: 18.8948: : 65iter [00:07, 11.61iter/s]
Best score: 18.8948: : 65iter [00:07, 11.61iter/s]
Best score: 18.8948: : 66iter [00:07, 11.61iter/s]
Best score: 18.8948: : 67iter [00:07, 11.68iter/s]
Best score: 18.8948: : 67iter [00:07, 11.68iter/s]
Best score: 18.8948: : 68iter [00:07, 11.68iter/s]
Best score: 18.8948: : 69iter [00:07, 11.68iter/s]
Best score: 7.8336: : 69iter [00:07, 11.68iter/s] 
Best score: 7.8336: : 70iter [00:08, 11.68iter/s]
Best score: 7.8336: : 71iter [00:08, 11.47iter/s]
Best score: 7.8336: : 71iter [00:08, 11.47iter/s]
Best score: 7.8336: : 72iter [00:08, 11.47iter/s]
Best score: 7.8336: : 73iter [00:08, 11.56iter/s]
Best score: 7.8336: : 73iter [00:08, 11.56iter/s]
Best score: 7.8336: : 74iter [00:08, 11.56iter/s]
Best score: 7.8336: : 75iter [00:08, 11.62iter/s]
Best score: 7.8336: : 75iter [00:08, 11.62iter/s]
Best score: 7.8336: : 76iter [00:08, 11.62iter/s]
Best score: 7.8336: : 77iter [00:08, 11.65iter/s]
Best score: 7.8336: : 77iter [00:08, 11.65iter/s]
Best score: 7.8336: : 78iter [00:08, 11.65iter/s]
Best score: 7.8336: : 79iter [00:08, 11.67iter/s]
Best score: 5.6566: : 79iter [00:08, 11.67iter/s]
Best score: 5.6566: : 80iter [00:08, 11.67iter/s]
Best score: 5.6566: : 81iter [00:08, 11.48iter/s]
Best score: 5.6566: : 81iter [00:08, 11.48iter/s]
Best score: 5.6566: : 82iter [00:09, 11.48iter/s]
Best score: 5.6566: : 83iter [00:09, 11.56iter/s]
Best score: 5.6566: : 83iter [00:09, 11.56iter/s]
Best score: 5.6566: : 84iter [00:09, 11.56iter/s]
Best score: 5.6566: : 85iter [00:09, 11.63iter/s]
Best score: 5.6566: : 85iter [00:09, 11.63iter/s]
Best score: 5.6566: : 86iter [00:09, 11.63iter/s]
Best score: 5.6566: : 87iter [00:09, 11.72iter/s]
Best score: 5.6566: : 87iter [00:09, 11.72iter/s]
Best score: 5.6566: : 88iter [00:09, 11.72iter/s]
Best score: 5.6566: : 89iter [00:09, 11.77iter/s]
Best score: 4.1301: : 89iter [00:09, 11.77iter/s]
Best score: 4.1301: : 90iter [00:09, 11.77iter/s]
Best score: 4.1301: : 91iter [00:09, 11.62iter/s]
Best score: 4.1301: : 91iter [00:09, 11.62iter/s]
Best score: 4.1301: : 92iter [00:09, 11.62iter/s]
Best score: 4.1301: : 93iter [00:09, 11.66iter/s]
Best score: 4.1301: : 93iter [00:10, 11.66iter/s]
Best score: 4.1301: : 94iter [00:10, 11.66iter/s]
Best score: 4.1301: : 95iter [00:10, 11.70iter/s]
Best score: 4.1301: : 95iter [00:10, 11.70iter/s]
Best score: 4.1301: : 96iter [00:10, 11.70iter/s]
Best score: 4.1301: : 97iter [00:10, 11.75iter/s]
Best score: 4.1301: : 97iter [00:10, 11.75iter/s]
Best score: 4.1301: : 98iter [00:10, 11.75iter/s]
Best score: 4.1301: : 99iter [00:10, 11.69iter/s]
Best score: 4.0611: : 99iter [00:10, 11.69iter/s]
[ITER 100] Best: 4.0611
[PARAMS] Current best parameters:
  fx: 580.3165
  fy: 581.4296
  px: 863.0760
  py: 1004.1360
  k1: -0.04500530
  k2: -0.00104154
  k3: -0.00437838
  k4: 0.00348168
  p1: -0.00349511
  p2: 0.01215986
  p3: -0.00209786
  p4: 0.01167960
  s1: 0.0034
  s2: -0.0122
  s3: -0.0044
  s4: -0.0001
  tilt_x: 0.0095
  tilt_y: -0.0272
  scale: 3.0310
  rotation: 0.0840

Best score: 4.0611: : 100iter [00:10, 11.69iter/s]
Best score: 4.0611: : 101iter [00:10, 10.03iter/s]
Best score: 4.0611: : 101iter [00:10, 10.03iter/s]
Best score: 4.0611: : 102iter [00:10, 10.03iter/s]
Best score: 4.0611: : 103iter [00:10, 10.43iter/s]
Best score: 4.0611: : 103iter [00:10, 10.43iter/s]
Best score: 4.0611: : 104iter [00:11, 10.43iter/s]
Best score: 4.0611: : 105iter [00:11, 10.73iter/s]
Best score: 4.0611: : 105iter [00:11, 10.73iter/s]
Best score: 4.0611: : 106iter [00:11, 10.73iter/s]
Best score: 4.0611: : 107iter [00:11, 10.96iter/s]
Best score: 4.0611: : 107iter [00:11, 10.96iter/s]
Best score: 4.0611: : 108iter [00:11, 10.96iter/s]
Best score: 4.0611: : 109iter [00:11, 11.12iter/s]
Best score: 4.0611: : 109iter [00:11, 11.12iter/s]
Best score: 4.0611: : 110iter [00:11, 11.12iter/s]
Best score: 4.0611: : 111iter [00:11, 11.05iter/s]
Best score: 4.0611: : 111iter [00:11, 11.05iter/s]
Best score: 4.0611: : 112iter [00:11, 11.05iter/s]
Best score: 4.0611: : 113iter [00:11, 11.17iter/s]
Best score: 4.0611: : 113iter [00:11, 11.17iter/s]
Best score: 4.0611: : 114iter [00:11, 11.17iter/s]
Best score: 4.0611: : 115iter [00:11, 11.25iter/s]
Best score: 4.0611: : 115iter [00:12, 11.25iter/s]
Best score: 4.0611: : 116iter [00:12, 11.25iter/s]
Best score: 4.0611: : 117iter [00:12, 11.41iter/s]
Best score: 4.0611: : 117iter [00:12, 11.41iter/s]
Best score: 4.0611: : 118iter [00:12, 11.41iter/s]
Best score: 4.0611: : 119iter [00:12, 11.47iter/s]
Best score: 4.0611: : 119iter [00:12, 11.47iter/s]
Best score: 4.0611: : 120iter [00:12, 11.47iter/s]
Best score: 4.0611: : 121iter [00:12, 11.37iter/s]
Best score: 4.0611: : 121iter [00:12, 11.37iter/s]
Best score: 4.0611: : 122iter [00:12, 11.37iter/s]
Best score: 4.0611: : 123iter [00:12, 11.47iter/s]
Best score: 4.0611: : 123iter [00:12, 11.47iter/s]
Best score: 4.0611: : 124iter [00:12, 11.47iter/s]
Best score: 4.0611: : 125iter [00:12, 11.51iter/s]
Best score: 4.0611: : 125iter [00:12, 11.51iter/s]
Best score: 4.0611: : 126iter [00:12, 11.51iter/s]
Best score: 4.0611: : 127iter [00:12, 11.59iter/s]
Best score: 4.0611: : 127iter [00:13, 11.59iter/s]
Best score: 4.0611: : 128iter [00:13, 11.59iter/s]
Best score: 4.0611: : 129iter [00:13, 11.64iter/s]
Best score: 4.0611: : 129iter [00:13, 11.64iter/s]
Best score: 4.0611: : 130iter [00:13, 11.64iter/s]
Best score: 4.0611: : 131iter [00:13, 11.50iter/s]
Best score: 4.0611: : 131iter [00:13, 11.50iter/s]
Best score: 4.0611: : 132iter [00:13, 11.50iter/s]
Best score: 4.0611: : 133iter [00:13, 11.61iter/s]
Best score: 4.0611: : 133iter [00:13, 11.61iter/s]
Best score: 4.0611: : 134iter [00:13, 11.61iter/s]
Best score: 4.0611: : 135iter [00:13, 11.65iter/s]
Best score: 4.0611: : 135iter [00:13, 11.65iter/s]
Best score: 4.0611: : 136iter [00:13, 11.65iter/s]
Best score: 4.0611: : 137iter [00:13, 11.75iter/s]
Best score: 4.0611: : 137iter [00:13, 11.75iter/s]
Best score: 4.0611: : 138iter [00:13, 11.75iter/s]
Best score: 4.0611: : 139iter [00:13, 11.77iter/s]
Best score: 4.0611: : 139iter [00:14, 11.77iter/s]
Best score: 4.0611: : 140iter [00:14, 11.77iter/s]
Best score: 4.0611: : 141iter [00:14, 11.60iter/s]
Best score: 4.0611: : 141iter [00:14, 11.60iter/s]
Best score: 4.0611: : 142iter [00:14, 11.60iter/s]
Best score: 4.0611: : 143iter [00:14, 11.69iter/s]
Best score: 4.0611: : 143iter [00:14, 11.69iter/s]
Best score: 4.0611: : 144iter [00:14, 11.69iter/s]
Best score: 4.0611: : 145iter [00:14, 11.70iter/s]
Best score: 4.0611: : 145iter [00:14, 11.70iter/s]
Best score: 4.0611: : 146iter [00:14, 11.70iter/s]
Best score: 4.0611: : 147iter [00:14, 11.71iter/s]
Best score: 4.0611: : 147iter [00:14, 11.71iter/s]
Best score: 4.0611: : 148iter [00:14, 11.71iter/s]
Best score: 4.0611: : 149iter [00:14, 11.71iter/s]
[ITER 150] Best: 4.0611
[PARAMS] Current best parameters:
  fx: 580.3165
  fy: 581.4296
  px: 863.0760
  py: 1004.1360
  k1: -0.04500530
  k2: -0.00104154
  k3: -0.00437838
  k4: 0.00348168
  p1: -0.00349511
  p2: 0.01215986
  p3: -0.00209786
  p4: 0.01167960
  s1: 0.0034
  s2: -0.0122
  s3: -0.0044
  s4: -0.0001
  tilt_x: 0.0095
  tilt_y: -0.0272
  scale: 3.0310
  rotation: 0.0840

Best score: 4.0611: : 149iter [00:14, 11.71iter/s]
Best score: 4.0611: : 150iter [00:15, 11.71iter/s]
Best score: 4.0611: : 151iter [00:15,  7.56iter/s]
Best score: 4.0611: : 151iter [00:15,  7.56iter/s]
Best score: 4.0611: : 152iter [00:15,  7.56iter/s]
Best score: 4.0611: : 153iter [00:15,  8.51iter/s]
Best score: 4.0611: : 153iter [00:15,  8.51iter/s]
Best score: 4.0611: : 154iter [00:15,  8.51iter/s]
Best score: 4.0611: : 155iter [00:15,  9.33iter/s]
Best score: 4.0611: : 155iter [00:15,  9.33iter/s]
Best score: 4.0611: : 156iter [00:15,  9.33iter/s]
Best score: 4.0611: : 157iter [00:15,  9.96iter/s]
Best score: 4.0611: : 157iter [00:15,  9.96iter/s]
Best score: 4.0611: : 158iter [00:16,  9.96iter/s]
Best score: 4.0611: : 159iter [00:16, 10.50iter/s]
Best score: 4.0611: : 159iter [00:16, 10.50iter/s]
Best score: 4.0611: : 160iter [00:16, 10.50iter/s]
Best score: 4.0611: : 161iter [00:16, 10.73iter/s]
Best score: 4.0611: : 161iter [00:16, 10.73iter/s]
Best score: 4.0611: : 162iter [00:16, 10.73iter/s]
Best score: 4.0611: : 163iter [00:16, 11.09iter/s]
Best score: 4.0611: : 163iter [00:16, 11.09iter/s]
Best score: 4.0611: : 164iter [00:16, 11.09iter/s]
Best score: 4.0611: : 165iter [00:16, 11.32iter/s]
Best score: 4.0611: : 165iter [00:16, 11.32iter/s]
Best score: 4.0611: : 166iter [00:16, 11.32iter/s]
Best score: 4.0611: : 167iter [00:16, 11.52iter/s]
Best score: 4.0611: : 167iter [00:16, 11.52iter/s]
Best score: 4.0611: : 168iter [00:16, 11.52iter/s]
Best score: 4.0611: : 169iter [00:16, 11.64iter/s]
Best score: 3.1476: : 169iter [00:16, 11.64iter/s]
Best score: 3.1476: : 170iter [00:17, 11.64iter/s]
Best score: 3.1476: : 171iter [00:17, 11.49iter/s]
Best score: 3.1476: : 171iter [00:17, 11.49iter/s]
Best score: 3.1476: : 172iter [00:17, 11.49iter/s]
Best score: 3.1476: : 173iter [00:17, 11.64iter/s]
Best score: 3.1476: : 173iter [00:17, 11.64iter/s]
Best score: 3.1476: : 174iter [00:17, 11.64iter/s]
Best score: 3.1476: : 175iter [00:17, 11.74iter/s]
Best score: 3.1476: : 175iter [00:17, 11.74iter/s]
Best score: 3.1476: : 176iter [00:17, 11.74iter/s]
Best score: 3.1476: : 177iter [00:17, 11.80iter/s]
Best score: 3.1476: : 177iter [00:17, 11.80iter/s]
Best score: 3.1476: : 178iter [00:17, 11.80iter/s]
Best score: 3.1476: : 179iter [00:17, 11.83iter/s]
Best score: 1.9847: : 179iter [00:17, 11.83iter/s]
Best score: 1.9847: : 180iter [00:17, 11.83iter/s]
Best score: 1.9847: : 181iter [00:17, 11.64iter/s]
Best score: 1.9847: : 181iter [00:17, 11.64iter/s]
Best score: 1.9847: : 182iter [00:18, 11.64iter/s]
Best score: 1.9847: : 183iter [00:18, 11.63iter/s]
Best score: 1.9847: : 183iter [00:18, 11.63iter/s]
Best score: 1.9847: : 184iter [00:18, 11.63iter/s]
Best score: 1.9847: : 185iter [00:18, 11.68iter/s]
Best score: 1.9847: : 185iter [00:18, 11.68iter/s]
Best score: 1.9847: : 186iter [00:18, 11.68iter/s]
Best score: 1.9847: : 187iter [00:18, 11.74iter/s]
Best score: 1.9847: : 187iter [00:18, 11.74iter/s]
Best score: 1.9847: : 188iter [00:18, 11.74iter/s]
Best score: 1.9847: : 189iter [00:18, 11.80iter/s]
Best score: 1.3216: : 189iter [00:18, 11.80iter/s]
Best score: 1.3216: : 190iter [00:18, 11.80iter/s]
Best score: 1.3216: : 191iter [00:18, 11.65iter/s]
Best score: 1.3216: : 191iter [00:18, 11.65iter/s]
Best score: 1.3216: : 192iter [00:18, 11.65iter/s]
Best score: 1.3216: : 193iter [00:18, 11.74iter/s]
Best score: 1.3216: : 193iter [00:18, 11.74iter/s]
Best score: 1.3216: : 194iter [00:19, 11.74iter/s]
Best score: 1.3216: : 195iter [00:19, 11.80iter/s]
Best score: 1.3216: : 195iter [00:19, 11.80iter/s]
Best score: 1.3216: : 196iter [00:19, 11.80iter/s]
Best score: 1.3216: : 197iter [00:19, 11.80iter/s]
Best score: 1.3216: : 197iter [00:19, 11.80iter/s]
Best score: 1.3216: : 198iter [00:19, 11.80iter/s]
Best score: 1.3216: : 199iter [00:19, 11.81iter/s]
[ITER 200] Best: 0.8875
[PARAMS] Current best parameters:
  fx: 558.4960
  fy: 559.3032
  px: 850.7805
  py: 1005.3420
  k1: -0.01706884
  k2: -0.00861092
  k3: 0.00224284
  k4: 0.00014860
  p1: -0.00016545
  p2: -0.01460275
  p3: 0.00002884
  p4: 0.01693641
  s1: -0.0013
  s2: -0.0068
  s3: 0.0019
  s4: -0.0036
  tilt_x: 0.0040
  tilt_y: -0.0145
  scale: 3.0033
  rotation: -0.3724

Best score: 0.8875: : 199iter [00:19, 11.81iter/s]
Best score: 0.8875: : 200iter [00:19, 11.81iter/s]
Best score: 0.8875: : 201iter [00:19,  7.64iter/s]
Best score: 0.8875: : 201iter [00:19,  7.64iter/s]
Best score: 0.8875: : 202iter [00:20,  7.64iter/s]
Best score: 0.8875: : 203iter [00:20,  8.54iter/s]
Best score: 0.8875: : 203iter [00:20,  8.54iter/s]
Best score: 0.8875: : 204iter [00:20,  8.54iter/s]
Best score: 0.8875: : 205iter [00:20,  9.30iter/s]
Best score: 0.8875: : 205iter [00:20,  9.30iter/s]
Best score: 0.8875: : 206iter [00:20,  9.30iter/s]
Best score: 0.8875: : 207iter [00:20,  9.97iter/s]
Best score: 0.8875: : 207iter [00:20,  9.97iter/s]
Best score: 0.8875: : 208iter [00:20,  9.97iter/s]
Best score: 0.8875: : 209iter [00:20, 10.49iter/s]
Best score: 0.7901: : 209iter [00:20, 10.49iter/s]
Best score: 0.7901: : 210iter [00:20, 10.49iter/s]
Best score: 0.7901: : 211iter [00:20, 10.67iter/s]
Best score: 0.7901: : 211iter [00:20, 10.67iter/s]
Best score: 0.7901: : 212iter [00:20, 10.67iter/s]
Best score: 0.7901: : 213iter [00:20, 10.99iter/s]
Best score: 0.7901: : 213iter [00:20, 10.99iter/s]
Best score: 0.7901: : 214iter [00:21, 10.99iter/s]
Best score: 0.7901: : 215iter [00:21, 11.24iter/s]
Best score: 0.7901: : 215iter [00:21, 11.24iter/s]
Best score: 0.7901: : 216iter [00:21, 11.24iter/s]
Best score: 0.7901: : 217iter [00:21, 11.44iter/s]
Best score: 0.7901: : 217iter [00:21, 11.44iter/s]
Best score: 0.7901: : 218iter [00:21, 11.44iter/s]
Best score: 0.7901: : 219iter [00:21, 11.58iter/s]
Best score: 0.7901: : 219iter [00:21, 11.58iter/s]
Best score: 0.7901: : 220iter [00:21, 11.58iter/s]
Best score: 0.7901: : 221iter [00:21, 11.49iter/s]
Best score: 0.7901: : 221iter [00:21, 11.49iter/s]
Best score: 0.7901: : 222iter [00:21, 11.49iter/s]
Best score: 0.7901: : 223iter [00:21, 11.55iter/s]
Best score: 0.7901: : 223iter [00:21, 11.55iter/s]
Best score: 0.7901: : 224iter [00:21, 11.55iter/s]
Best score: 0.7901: : 225iter [00:21, 11.66iter/s]
Best score: 0.7901: : 225iter [00:22, 11.66iter/s]
Best score: 0.7901: : 226iter [00:22, 11.66iter/s]
Best score: 0.7901: : 227iter [00:22, 11.73iter/s]
Best score: 0.7901: : 227iter [00:22, 11.73iter/s]
Best score: 0.7901: : 228iter [00:22, 11.73iter/s]
Best score: 0.7901: : 229iter [00:22, 11.79iter/s]
Best score: 0.7901: : 229iter [00:22, 11.79iter/s]
Best score: 0.7901: : 230iter [00:22, 11.79iter/s]
Best score: 0.7901: : 231iter [00:22, 11.64iter/s]
Best score: 0.7901: : 231iter [00:22, 11.64iter/s]
Best score: 0.7901: : 232iter [00:22, 11.64iter/s]
Best score: 0.7901: : 233iter [00:22, 11.73iter/s]
Best score: 0.7901: : 233iter [00:22, 11.73iter/s]
Best score: 0.7901: : 234iter [00:22, 11.73iter/s]
Best score: 0.7901: : 235iter [00:22, 11.79iter/s]
Best score: 0.7901: : 235iter [00:22, 11.79iter/s]
Best score: 0.7901: : 236iter [00:22, 11.79iter/s]
Best score: 0.7901: : 237iter [00:22, 11.83iter/s]
Best score: 0.7901: : 237iter [00:23, 11.83iter/s]
Best score: 0.7901: : 238iter [00:23, 11.83iter/s]
Best score: 0.7901: : 239iter [00:23, 11.86iter/s]
Best score: 0.7845: : 239iter [00:23, 11.86iter/s]
Best score: 0.7845: : 240iter [00:23, 11.86iter/s]
Best score: 0.7845: : 241iter [00:23, 11.67iter/s]
Best score: 0.7845: : 241iter [00:23, 11.67iter/s]
Best score: 0.7845: : 242iter [00:23, 11.67iter/s]
Best score: 0.7845: : 243iter [00:23, 11.75iter/s]
Best score: 0.7845: : 243iter [00:23, 11.75iter/s]
Best score: 0.7845: : 244iter [00:23, 11.75iter/s]
Best score: 0.7845: : 245iter [00:23, 11.80iter/s]
Best score: 0.7845: : 245iter [00:23, 11.80iter/s]
Best score: 0.7845: : 246iter [00:23, 11.80iter/s]
Best score: 0.7845: : 247iter [00:23, 11.86iter/s]
Best score: 0.7845: : 247iter [00:23, 11.86iter/s]
Best score: 0.7845: : 248iter [00:23, 11.86iter/s]
Best score: 0.7845: : 249iter [00:23, 11.89iter/s]
[ITER 250] Best: 0.4719
[PARAMS] Current best parameters:
  fx: 559.6080
  fy: 559.9426
  px: 856.3545
  py: 996.2587
  k1: -0.02912924
  k2: 0.01490964
  k3: -0.01559898
  k4: 0.00484186
  p1: -0.00904110
  p2: -0.00468586
  p3: -0.00050956
  p4: 0.01232713
  s1: -0.0023
  s2: -0.0056
  s3: 0.0049
  s4: -0.0053
  tilt_x: -0.0206
  tilt_y: -0.0264
  scale: 3.0105
  rotation: -0.5048

Best score: 0.4719: : 249iter [00:24, 11.89iter/s]
Best score: 0.4719: : 250iter [00:24, 11.89iter/s]
Best score: 0.4719: : 251iter [00:24,  7.64iter/s]
Best score: 0.4719: : 251iter [00:24,  7.64iter/s]
Best score: 0.4719: : 252iter [00:24,  7.64iter/s]
Best score: 0.4719: : 253iter [00:24,  8.55iter/s]
Best score: 0.4719: : 253iter [00:24,  8.55iter/s]
Best score: 0.4719: : 254iter [00:24,  8.55iter/s]
Best score: 0.4719: : 255iter [00:24,  9.35iter/s]
Best score: 0.4719: : 255iter [00:24,  9.35iter/s]
Best score: 0.4719: : 256iter [00:24,  9.35iter/s]
Best score: 0.4719: : 257iter [00:24,  9.95iter/s]
Best score: 0.4719: : 257iter [00:25,  9.95iter/s]
Best score: 0.4719: : 258iter [00:25,  9.95iter/s]
Best score: 0.4719: : 259iter [00:25, 10.48iter/s]
Best score: 0.4112: : 259iter [00:25, 10.48iter/s]
Best score: 0.4112: : 260iter [00:25, 10.48iter/s]
Best score: 0.4112: : 261iter [00:25, 10.72iter/s]
Best score: 0.4112: : 261iter [00:25, 10.72iter/s]
Best score: 0.4112: : 262iter [00:25, 10.72iter/s]
Best score: 0.4112: : 263iter [00:25, 11.05iter/s]
Best score: 0.4112: : 263iter [00:25, 11.05iter/s]
Best score: 0.4112: : 264iter [00:25, 11.05iter/s]
Best score: 0.4112: : 265iter [00:25, 11.31iter/s]
Best score: 0.4112: : 265iter [00:25, 11.31iter/s]
Best score: 0.4112: : 266iter [00:25, 11.31iter/s]
Best score: 0.4112: : 267iter [00:25, 11.42iter/s]
Best score: 0.4112: : 267iter [00:25, 11.42iter/s]
Best score: 0.4112: : 268iter [00:25, 11.42iter/s]
Best score: 0.4112: : 269iter [00:25, 11.59iter/s]
Best score: 0.4112: : 269iter [00:26, 11.59iter/s]
Best score: 0.4112: : 270iter [00:26, 11.59iter/s]
Best score: 0.4112: : 271iter [00:26, 11.45iter/s]
Best score: 0.4112: : 271iter [00:26, 11.45iter/s]
Best score: 0.4112: : 272iter [00:26, 11.45iter/s]
Best score: 0.4112: : 273iter [00:26, 11.58iter/s]
Best score: 0.4112: : 273iter [00:26, 11.58iter/s]
Best score: 0.4112: : 274iter [00:26, 11.58iter/s]
Best score: 0.4112: : 275iter [00:26, 11.71iter/s]
Best score: 0.4112: : 275iter [00:26, 11.71iter/s]
Best score: 0.4112: : 276iter [00:26, 11.71iter/s]
Best score: 0.4112: : 277iter [00:26, 11.75iter/s]
Best score: 0.4112: : 277iter [00:26, 11.75iter/s]
Best score: 0.4112: : 278iter [00:26, 11.75iter/s]
Best score: 0.4112: : 279iter [00:26, 11.82iter/s]
Best score: 0.4112: : 279iter [00:26, 11.82iter/s]
Best score: 0.4112: : 280iter [00:26, 11.82iter/s]
Best score: 0.4112: : 281iter [00:26, 11.65iter/s]
Best score: 0.4112: : 281iter [00:27, 11.65iter/s]
Best score: 0.4112: : 282iter [00:27, 11.65iter/s]
Best score: 0.4112: : 283iter [00:27, 11.73iter/s]
Best score: 0.4112: : 283iter [00:27, 11.73iter/s]
Best score: 0.4112: : 284iter [00:27, 11.73iter/s]
Best score: 0.4112: : 285iter [00:27, 11.79iter/s]
Best score: 0.4112: : 285iter [00:27, 11.79iter/s]
Best score: 0.4112: : 286iter [00:27, 11.79iter/s]
Best score: 0.4112: : 287iter [00:27, 11.83iter/s]
Best score: 0.4112: : 287iter [00:27, 11.83iter/s]
Best score: 0.4112: : 288iter [00:27, 11.83iter/s]
Best score: 0.4112: : 289iter [00:27, 11.83iter/s]
Best score: 0.4112: : 289iter [00:27, 11.83iter/s]
Best score: 0.4112: : 290iter [00:27, 11.83iter/s]
Best score: 0.4112: : 291iter [00:27, 11.66iter/s]
Best score: 0.4112: : 291iter [00:27, 11.66iter/s]
Best score: 0.4112: : 292iter [00:28, 11.66iter/s]
Best score: 0.4112: : 293iter [00:28, 11.68iter/s]
Best score: 0.4112: : 293iter [00:28, 11.68iter/s]
Best score: 0.4112: : 294iter [00:28, 11.68iter/s]
Best score: 0.4112: : 295iter [00:28, 11.75iter/s]
Best score: 0.4112: : 295iter [00:28, 11.75iter/s]
Best score: 0.4112: : 296iter [00:28, 11.75iter/s]
Best score: 0.4112: : 297iter [00:28, 11.83iter/s]
Best score: 0.4112: : 297iter [00:28, 11.83iter/s]
Best score: 0.4112: : 298iter [00:28, 11.83iter/s]
Best score: 0.4112: : 299iter [00:28, 11.82iter/s]
[ITER 300] Best: 0.3906
[PARAMS] Current best parameters:
  fx: 559.9200
  fy: 559.5141
  px: 853.9085
  py: 996.0441
  k1: -0.04090834
  k2: 0.02622832
  k3: -0.01917036
  k4: 0.00538724
  p1: -0.00814433
  p2: -0.01137338
  p3: -0.00051218
  p4: 0.01832028
  s1: 0.0011
  s2: -0.0102
  s3: -0.0005
  s4: -0.0089
  tilt_x: -0.0218
  tilt_y: -0.0262
  scale: 3.0311
  rotation: -0.4204

Best score: 0.3906: : 299iter [00:28, 11.82iter/s]
Best score: 0.3906: : 300iter [00:28, 11.82iter/s]
Best score: 0.3906: : 301iter [00:28,  7.62iter/s]
Best score: 0.3906: : 301iter [00:29,  7.62iter/s]
Best score: 0.3906: : 302iter [00:29,  6.57iter/s]
Best score: 0.3906: : 302iter [00:29,  6.57iter/s]
Best score: 0.3906: : 303iter [00:29,  6.57iter/s]
Best score: 0.3906: : 304iter [00:29,  7.74iter/s]
Best score: 0.3906: : 304iter [00:29,  7.74iter/s]
Best score: 0.3906: : 305iter [00:29,  7.74iter/s]
Best score: 0.3906: : 306iter [00:29,  8.72iter/s]
Best score: 0.3906: : 306iter [00:29,  8.72iter/s]
Best score: 0.3906: : 307iter [00:29,  8.72iter/s]
Best score: 0.3906: : 308iter [00:29,  9.53iter/s]
Best score: 0.3906: : 308iter [00:29,  9.53iter/s]
Best score: 0.3253: : 309iter [00:29,  9.53iter/s]
Best score: 0.3253: : 310iter [00:29, 10.02iter/s]
Best score: 0.3253: : 310iter [00:30, 10.02iter/s]
Best score: 0.3253: : 311iter [00:30, 10.02iter/s]
Best score: 0.3253: : 312iter [00:30, 10.55iter/s]
Best score: 0.3253: : 312iter [00:30, 10.55iter/s]
Best score: 0.3253: : 313iter [00:30, 10.55iter/s]
Best score: 0.3253: : 314iter [00:30, 10.93iter/s]
Best score: 0.3253: : 314iter [00:30, 10.93iter/s]
Best score: 0.3253: : 315iter [00:30, 10.93iter/s]
Best score: 0.3253: : 316iter [00:30, 11.14iter/s]
Best score: 0.3253: : 316iter [00:30, 11.14iter/s]
Best score: 0.3253: : 317iter [00:30, 11.14iter/s]
Best score: 0.3253: : 318iter [00:30, 11.37iter/s]
Best score: 0.3253: : 318iter [00:30, 11.37iter/s]
Best score: 0.2914: : 319iter [00:30, 11.37iter/s]
Best score: 0.2914: : 320iter [00:30, 11.35iter/s]
Best score: 0.2914: : 320iter [00:30, 11.35iter/s]
Best score: 0.2914: : 321iter [00:30, 11.35iter/s]
Best score: 0.2914: : 322iter [00:30, 11.52iter/s]
Best score: 0.2914: : 322iter [00:31, 11.52iter/s]
Best score: 0.2914: : 323iter [00:31, 11.52iter/s]
Best score: 0.2914: : 324iter [00:31, 11.65iter/s]
Best score: 0.2914: : 324iter [00:31, 11.65iter/s]
Best score: 0.2914: : 325iter [00:31, 11.65iter/s]
Best score: 0.2914: : 326iter [00:31, 11.73iter/s]
Best score: 0.2914: : 326iter [00:31, 11.73iter/s]
Best score: 0.2914: : 327iter [00:31, 11.73iter/s]
Best score: 0.2914: : 328iter [00:31, 11.76iter/s]
Best score: 0.2914: : 328iter [00:31, 11.76iter/s]
Best score: 0.2914: : 329iter [00:31, 11.76iter/s]
Best score: 0.2914: : 330iter [00:31, 11.60iter/s]
Best score: 0.2914: : 330iter [00:31, 11.60iter/s]
Best score: 0.2914: : 331iter [00:31, 11.60iter/s]
Best score: 0.2914: : 332iter [00:31, 11.69iter/s]
Best score: 0.2914: : 332iter [00:31, 11.69iter/s]
Best score: 0.2914: : 333iter [00:31, 11.69iter/s]
Best score: 0.2914: : 334iter [00:31, 11.75iter/s]
Best score: 0.2914: : 334iter [00:32, 11.75iter/s]
Best score: 0.2914: : 335iter [00:32, 11.75iter/s]
Best score: 0.2914: : 336iter [00:32, 11.79iter/s]
Best score: 0.2914: : 336iter [00:32, 11.79iter/s]
Best score: 0.2914: : 337iter [00:32, 11.79iter/s]
Best score: 0.2914: : 338iter [00:32, 11.82iter/s]
Best score: 0.2914: : 338iter [00:32, 11.82iter/s]
Best score: 0.2750: : 339iter [00:32, 11.82iter/s]
Best score: 0.2750: : 340iter [00:32, 11.67iter/s]
Best score: 0.2750: : 340iter [00:32, 11.67iter/s]
Best score: 0.2750: : 341iter [00:32, 11.67iter/s]
Best score: 0.2750: : 342iter [00:32, 11.76iter/s]
Best score: 0.2750: : 342iter [00:32, 11.76iter/s]
Best score: 0.2750: : 343iter [00:32, 11.76iter/s]
Best score: 0.2750: : 344iter [00:32, 11.79iter/s]
Best score: 0.2750: : 344iter [00:32, 11.79iter/s]
Best score: 0.2750: : 345iter [00:32, 11.79iter/s]
Best score: 0.2750: : 346iter [00:32, 11.84iter/s]
Best score: 0.2750: : 346iter [00:33, 11.84iter/s]
Best score: 0.2750: : 347iter [00:33, 11.84iter/s]
Best score: 0.2750: : 348iter [00:33, 11.87iter/s]
Best score: 0.2750: : 348iter [00:33, 11.87iter/s]
[ITER 350] Best: 0.2750
[PARAMS] Current best parameters:
  fx: 552.6367
  fy: 552.4175
  px: 853.2052
  py: 996.0994
  k1: -0.03400777
  k2: 0.02330263
  k3: -0.01417995
  k4: 0.00316051
  p1: -0.00722716
  p2: -0.00682332
  p3: 0.00290848
  p4: 0.01589406
  s1: -0.0036
  s2: -0.0119
  s3: -0.0009
  s4: -0.0106
  tilt_x: -0.0225
  tilt_y: -0.0140
  scale: 3.0339
  rotation: -0.4300

Best score: 0.2750: : 349iter [00:33, 11.87iter/s]
Best score: 0.2750: : 350iter [00:33, 11.69iter/s]
Best score: 0.2750: : 350iter [00:33, 11.69iter/s]
Best score: 0.2750: : 351iter [00:33, 11.69iter/s]
Best score: 0.2750: : 352iter [00:33,  7.68iter/s]
Best score: 0.2750: : 352iter [00:33,  7.68iter/s]
Best score: 0.2750: : 353iter [00:33,  7.68iter/s]
Best score: 0.2750: : 354iter [00:33,  8.60iter/s]
Best score: 0.2750: : 354iter [00:34,  8.60iter/s]
Best score: 0.2750: : 355iter [00:34,  8.60iter/s]
Best score: 0.2750: : 356iter [00:34,  9.38iter/s]
Best score: 0.2750: : 356iter [00:34,  9.38iter/s]
Best score: 0.2750: : 357iter [00:34,  9.38iter/s]
Best score: 0.2750: : 358iter [00:34, 10.03iter/s]
Best score: 0.2750: : 358iter [00:34, 10.03iter/s]
Best score: 0.2620: : 359iter [00:34, 10.03iter/s]
Best score: 0.2620: : 360iter [00:34, 10.38iter/s]
Best score: 0.2620: : 360iter [00:34, 10.38iter/s]
Best score: 0.2620: : 361iter [00:34, 10.38iter/s]
Best score: 0.2620: : 362iter [00:34, 10.81iter/s]
Best score: 0.2620: : 362iter [00:34, 10.81iter/s]
Best score: 0.2620: : 363iter [00:34, 10.81iter/s]
Best score: 0.2620: : 364iter [00:34, 11.09iter/s]
Best score: 0.2620: : 364iter [00:34, 11.09iter/s]
Best score: 0.2620: : 365iter [00:34, 11.09iter/s]
Best score: 0.2620: : 366iter [00:34, 11.29iter/s]
Best score: 0.2620: : 366iter [00:35, 11.29iter/s]
Best score: 0.2620: : 367iter [00:35, 11.29iter/s]
Best score: 0.2620: : 368iter [00:35, 11.46iter/s]
Best score: 0.2620: : 368iter [00:35, 11.46iter/s]
Best score: 0.2579: : 369iter [00:35, 11.46iter/s]
Best score: 0.2579: : 370iter [00:35, 11.36iter/s]
Best score: 0.2579: : 370iter [00:35, 11.36iter/s]
Best score: 0.2579: : 371iter [00:35, 11.36iter/s]
Best score: 0.2579: : 372iter [00:35, 11.53iter/s]
Best score: 0.2579: : 372iter [00:35, 11.53iter/s]
Best score: 0.2579: : 373iter [00:35, 11.53iter/s]
Best score: 0.2579: : 374iter [00:35, 11.66iter/s]
Best score: 0.2579: : 374iter [00:35, 11.66iter/s]
Best score: 0.2579: : 375iter [00:35, 11.66iter/s]
Best score: 0.2579: : 376iter [00:35, 11.70iter/s]
Best score: 0.2579: : 376iter [00:35, 11.70iter/s]
Best score: 0.2579: : 377iter [00:35, 11.70iter/s]
Best score: 0.2579: : 378iter [00:35, 11.74iter/s]
Best score: 0.2579: : 378iter [00:36, 11.74iter/s]
Best score: 0.2568: : 379iter [00:36, 11.74iter/s]
Best score: 0.2568: : 380iter [00:36, 11.60iter/s]
Best score: 0.2568: : 380iter [00:36, 11.60iter/s]
Best score: 0.2568: : 381iter [00:36, 11.60iter/s]
Best score: 0.2568: : 382iter [00:36, 11.71iter/s]
Best score: 0.2568: : 382iter [00:36, 11.71iter/s]
Best score: 0.2568: : 383iter [00:36, 11.71iter/s]
Best score: 0.2568: : 384iter [00:36, 11.77iter/s]
Best score: 0.2568: : 384iter [00:36, 11.77iter/s]
Best score: 0.2568: : 385iter [00:36, 11.77iter/s]
Best score: 0.2568: : 386iter [00:36, 11.81iter/s]
Best score: 0.2568: : 386iter [00:36, 11.81iter/s]
Best score: 0.2568: : 387iter [00:36, 11.81iter/s]
Best score: 0.2568: : 388iter [00:36, 11.85iter/s]
Best score: 0.2568: : 388iter [00:36, 11.85iter/s]
Best score: 0.2489: : 389iter [00:37, 11.85iter/s]
Best score: 0.2489: : 390iter [00:37, 11.67iter/s]
Best score: 0.2489: : 390iter [00:37, 11.67iter/s]
Best score: 0.2489: : 391iter [00:37, 11.67iter/s]
Best score: 0.2489: : 392iter [00:37, 11.73iter/s]
Best score: 0.2489: : 392iter [00:37, 11.73iter/s]
Best score: 0.2489: : 393iter [00:37, 11.73iter/s]
Best score: 0.2489: : 394iter [00:37, 11.79iter/s]
Best score: 0.2489: : 394iter [00:37, 11.79iter/s]
Best score: 0.2489: : 395iter [00:37, 11.79iter/s]
Best score: 0.2489: : 396iter [00:37, 11.83iter/s]
Best score: 0.2489: : 396iter [00:37, 11.83iter/s]
Best score: 0.2489: : 397iter [00:37, 11.83iter/s]
Best score: 0.2489: : 398iter [00:37, 11.86iter/s]
Best score: 0.2489: : 398iter [00:37, 11.86iter/s]
[ITER 400] Best: 0.2489
[PARAMS] Current best parameters:
  fx: 546.1052
  fy: 546.1113
  px: 851.5389
  py: 997.3616
  k1: -0.03812211
  k2: 0.03668207
  k3: -0.01963465
  k4: 0.00350686
  p1: -0.00266950
  p2: -0.00994919
  p3: 0.00169535
  p4: 0.01759863
  s1: 0.0000
  s2: -0.0154
  s3: -0.0027
  s4: -0.0141
  tilt_x: -0.0249
  tilt_y: -0.0124
  scale: 3.0491
  rotation: -0.3750

Best score: 0.2489: : 399iter [00:37, 11.86iter/s]
Best score: 0.2489: : 400iter [00:37, 11.63iter/s]
Best score: 0.2489: : 400iter [00:38, 11.63iter/s]
Best score: 0.2489: : 401iter [00:38, 11.63iter/s]
Best score: 0.2489: : 402iter [00:38,  7.64iter/s]
Best score: 0.2489: : 402iter [00:38,  7.64iter/s]
Best score: 0.2489: : 403iter [00:38,  7.64iter/s]
Best score: 0.2489: : 404iter [00:38,  8.56iter/s]
Best score: 0.2489: : 404iter [00:38,  8.56iter/s]
Best score: 0.2489: : 405iter [00:38,  8.56iter/s]
Best score: 0.2489: : 406iter [00:38,  9.36iter/s]
Best score: 0.2489: : 406iter [00:38,  9.36iter/s]
Best score: 0.2489: : 407iter [00:38,  9.36iter/s]
Best score: 0.2489: : 408iter [00:38, 10.00iter/s]
Best score: 0.2489: : 408iter [00:38, 10.00iter/s]
Best score: 0.2456: : 409iter [00:39, 10.00iter/s]
Best score: 0.2456: : 410iter [00:39, 10.33iter/s]
Best score: 0.2456: : 410iter [00:39, 10.33iter/s]
Best score: 0.2456: : 411iter [00:39, 10.33iter/s]
Best score: 0.2456: : 412iter [00:39, 10.76iter/s]
Best score: 0.2456: : 412iter [00:39, 10.76iter/s]
Best score: 0.2456: : 413iter [00:39, 10.76iter/s]
Best score: 0.2456: : 414iter [00:39, 11.09iter/s]
Best score: 0.2456: : 414iter [00:39, 11.09iter/s]
Best score: 0.2456: : 415iter [00:39, 11.09iter/s]
Best score: 0.2456: : 416iter [00:39, 11.33iter/s]
Best score: 0.2456: : 416iter [00:39, 11.33iter/s]
Best score: 0.2456: : 417iter [00:39, 11.33iter/s]
Best score: 0.2456: : 418iter [00:39, 11.51iter/s]
Best score: 0.2456: : 418iter [00:39, 11.51iter/s]
Best score: 0.2440: : 419iter [00:39, 11.51iter/s]
Best score: 0.2440: : 420iter [00:39, 11.44iter/s]
Best score: 0.2440: : 420iter [00:39, 11.44iter/s]
Best score: 0.2440: : 421iter [00:40, 11.44iter/s]
Best score: 0.2440: : 422iter [00:40, 11.54iter/s]
Best score: 0.2440: : 422iter [00:40, 11.54iter/s]
Best score: 0.2440: : 423iter [00:40, 11.54iter/s]
Best score: 0.2440: : 424iter [00:40, 11.65iter/s]
Best score: 0.2440: : 424iter [00:40, 11.65iter/s]
Best score: 0.2440: : 425iter [00:40, 11.65iter/s]
Best score: 0.2440: : 426iter [00:40, 11.75iter/s]
Best score: 0.2440: : 426iter [00:40, 11.75iter/s]
Best score: 0.2440: : 427iter [00:40, 11.75iter/s]
Best score: 0.2440: : 428iter [00:40, 11.81iter/s]
Best score: 0.2440: : 428iter [00:40, 11.81iter/s]
Best score: 0.2440: : 429iter [00:40, 11.81iter/s]
Best score: 0.2440: : 430iter [00:40, 11.64iter/s]
Best score: 0.2440: : 430iter [00:40, 11.64iter/s]
Best score: 0.2440: : 431iter [00:40, 11.64iter/s]
Best score: 0.2440: : 432iter [00:40, 11.74iter/s]
Best score: 0.2440: : 432iter [00:40, 11.74iter/s]
Best score: 0.2440: : 433iter [00:41, 11.74iter/s]
Best score: 0.2440: : 434iter [00:41, 11.78iter/s]
Best score: 0.2440: : 434iter [00:41, 11.78iter/s]
Best score: 0.2440: : 435iter [00:41, 11.78iter/s]
Best score: 0.2440: : 436iter [00:41, 11.83iter/s]
Best score: 0.2440: : 436iter [00:41, 11.83iter/s]
Best score: 0.2440: : 437iter [00:41, 11.83iter/s]
Best score: 0.2440: : 438iter [00:41, 11.86iter/s]
Best score: 0.2440: : 438iter [00:41, 11.86iter/s]
Best score: 0.2440: : 439iter [00:41, 11.86iter/s]
Best score: 0.2440: : 440iter [00:41, 11.69iter/s]
Best score: 0.2440: : 440iter [00:41, 11.69iter/s]
Best score: 0.2440: : 441iter [00:41, 11.69iter/s]
Best score: 0.2440: : 442iter [00:41, 11.78iter/s]
Best score: 0.2440: : 442iter [00:41, 11.78iter/s]
Best score: 0.2440: : 443iter [00:41, 11.78iter/s]
Best score: 0.2440: : 444iter [00:41, 11.79iter/s]
Best score: 0.2440: : 444iter [00:41, 11.79iter/s]
Best score: 0.2440: : 445iter [00:42, 11.79iter/s]
Best score: 0.2440: : 446iter [00:42, 11.83iter/s]
Best score: 0.2440: : 446iter [00:42, 11.83iter/s]
Best score: 0.2440: : 447iter [00:42, 11.83iter/s]
Best score: 0.2440: : 448iter [00:42, 11.86iter/s]
Best score: 0.2440: : 448iter [00:42, 11.86iter/s]
[ITER 450] Best: 0.2416
[PARAMS] Current best parameters:
  fx: 548.5125
  fy: 548.3710
  px: 851.5096
  py: 997.5473
  k1: -0.04056791
  k2: 0.03985041
  k3: -0.02315392
  k4: 0.00462636
  p1: -0.00249573
  p2: -0.01237336
  p3: 0.00339806
  p4: 0.01707205
  s1: 0.0015
  s2: -0.0152
  s3: -0.0033
  s4: -0.0142
  tilt_x: -0.0238
  tilt_y: -0.0168
  scale: 3.0453
  rotation: -0.3782

Best score: 0.2416: : 449iter [00:42, 11.86iter/s]
Best score: 0.2416: : 450iter [00:42, 11.68iter/s]
Best score: 0.2416: : 450iter [00:42, 11.68iter/s]
Best score: 0.2416: : 451iter [00:42, 11.68iter/s]
Best score: 0.2416: : 452iter [00:42,  7.67iter/s]
Best score: 0.2416: : 452iter [00:42,  7.67iter/s]
Best score: 0.2416: : 453iter [00:43,  7.67iter/s]
Best score: 0.2416: : 454iter [00:43,  8.59iter/s]
Best score: 0.2416: : 454iter [00:43,  8.59iter/s]
Best score: 0.2416: : 455iter [00:43,  8.59iter/s]
Best score: 0.2416: : 456iter [00:43,  9.38iter/s]
Best score: 0.2416: : 456iter [00:43,  9.38iter/s]
Best score: 0.2416: : 457iter [00:43,  9.38iter/s]
Best score: 0.2416: : 458iter [00:43, 10.00iter/s]
Best score: 0.2416: : 458iter [00:43, 10.00iter/s]
Best score: 0.2409: : 459iter [00:43, 10.00iter/s]
Best score: 0.2409: : 460iter [00:43, 10.35iter/s]
Best score: 0.2409: : 460iter [00:43, 10.35iter/s]
Best score: 0.2409: : 461iter [00:43, 10.35iter/s]
Best score: 0.2409: : 462iter [00:43, 10.74iter/s]
Best score: 0.2409: : 462iter [00:43, 10.74iter/s]
Best score: 0.2409: : 463iter [00:43, 10.74iter/s]
Best score: 0.2409: : 464iter [00:43, 11.08iter/s]
Best score: 0.2409: : 464iter [00:43, 11.08iter/s]
Best score: 0.2409: : 465iter [00:44, 11.08iter/s]
Best score: 0.2409: : 466iter [00:44, 11.28iter/s]
Best score: 0.2409: : 466iter [00:44, 11.28iter/s]
Best score: 0.2409: : 467iter [00:44, 11.28iter/s]
Best score: 0.2409: : 468iter [00:44, 11.40iter/s]
Best score: 0.2409: : 468iter [00:44, 11.40iter/s]
Best score: 0.2385: : 469iter [00:44, 11.40iter/s]
Best score: 0.2385: : 470iter [00:44, 11.37iter/s]
Best score: 0.2385: : 470iter [00:44, 11.37iter/s]
Best score: 0.2385: : 471iter [00:44, 11.37iter/s]
Best score: 0.2385: : 472iter [00:44, 11.53iter/s]
Best score: 0.2385: : 472iter [00:44, 11.53iter/s]
Best score: 0.2385: : 473iter [00:44, 11.53iter/s]
Best score: 0.2385: : 474iter [00:44, 11.62iter/s]
Best score: 0.2385: : 474iter [00:44, 11.62iter/s]
Best score: 0.2385: : 475iter [00:44, 11.62iter/s]
Best score: 0.2385: : 476iter [00:44, 11.68iter/s]
Best score: 0.2385: : 476iter [00:45, 11.68iter/s]
Best score: 0.2385: : 477iter [00:45, 11.68iter/s]
Best score: 0.2385: : 478iter [00:45, 11.69iter/s]
Best score: 0.2385: : 478iter [00:45, 11.69iter/s]
Best score: 0.2385: : 479iter [00:45, 11.69iter/s]
Best score: 0.2385: : 480iter [00:45, 11.52iter/s]
Best score: 0.2385: : 480iter [00:45, 11.52iter/s]
Best score: 0.2385: : 481iter [00:45, 11.52iter/s]
Best score: 0.2385: : 482iter [00:45, 11.61iter/s]
Best score: 0.2385: : 482iter [00:45, 11.61iter/s]
Best score: 0.2385: : 483iter [00:45, 11.61iter/s]
Best score: 0.2385: : 484iter [00:45, 11.70iter/s]
Best score: 0.2385: : 484iter [00:45, 11.70iter/s]
Best score: 0.2385: : 485iter [00:45, 11.70iter/s]
Best score: 0.2385: : 486iter [00:45, 11.78iter/s]
Best score: 0.2385: : 486iter [00:45, 11.78iter/s]
Best score: 0.2385: : 487iter [00:45, 11.78iter/s]
Best score: 0.2385: : 488iter [00:45, 11.84iter/s]
Best score: 0.2385: : 488iter [00:46, 11.84iter/s]
Best score: 0.2366: : 489iter [00:46, 11.84iter/s]
Best score: 0.2366: : 490iter [00:46, 11.67iter/s]
Best score: 0.2366: : 490iter [00:46, 11.67iter/s]
Best score: 0.2366: : 491iter [00:46, 11.67iter/s]
Best score: 0.2366: : 492iter [00:46, 11.76iter/s]
Best score: 0.2366: : 492iter [00:46, 11.76iter/s]
Best score: 0.2366: : 493iter [00:46, 11.76iter/s]
Best score: 0.2366: : 494iter [00:46, 11.76iter/s]
Best score: 0.2366: : 494iter [00:46, 11.76iter/s]
Best score: 0.2366: : 495iter [00:46, 11.76iter/s]
Best score: 0.2366: : 496iter [00:46, 11.78iter/s]
Best score: 0.2366: : 496iter [00:46, 11.78iter/s]
Best score: 0.2366: : 497iter [00:46, 11.78iter/s]
Best score: 0.2366: : 498iter [00:46, 11.68iter/s]
Best score: 0.2366: : 498iter [00:46, 11.68iter/s]
[ITER 500] Best: 0.2362
[PARAMS] Current best parameters:
  fx: 551.8854
  fy: 551.7319
  px: 851.4472
  py: 998.6500
  k1: -0.03942736
  k2: 0.03376524
  k3: -0.02018861
  k4: 0.00421428
  p1: -0.00129084
  p2: -0.01364787
  p3: 0.00389048
  p4: 0.01552996
  s1: 0.0019
  s2: -0.0141
  s3: -0.0038
  s4: -0.0129
  tilt_x: -0.0212
  tilt_y: -0.0192
  scale: 3.0390
  rotation: -0.3906

Best score: 0.2362: : 499iter [00:46, 11.68iter/s]
Best score: 0.2362: : 500iter [00:46, 11.46iter/s]
Best score: 0.2362: : 500iter [00:47, 11.46iter/s]
Best score: 0.2362: : 501iter [00:47, 11.46iter/s]
Best score: 0.2362: : 502iter [00:47,  7.55iter/s]
Best score: 0.2362: : 502iter [00:47,  7.55iter/s]
Best score: 0.2362: : 503iter [00:47,  7.55iter/s]
Best score: 0.2362: : 504iter [00:47,  8.46iter/s]
Best score: 0.2362: : 504iter [00:47,  8.46iter/s]
Best score: 0.2362: : 505iter [00:47,  8.46iter/s]
Best score: 0.2362: : 506iter [00:47,  9.27iter/s]
Best score: 0.2362: : 506iter [00:47,  9.27iter/s]
Best score: 0.2362: : 507iter [00:47,  9.27iter/s]
Best score: 0.2362: : 508iter [00:47,  9.90iter/s]
Best score: 0.2362: : 508iter [00:48,  9.90iter/s]
Best score: 0.2359: : 509iter [00:48,  9.90iter/s]
Best score: 0.2359: : 510iter [00:48, 10.20iter/s]
Best score: 0.2359: : 510iter [00:48, 10.20iter/s]
Best score: 0.2359: : 511iter [00:48, 10.20iter/s]
Best score: 0.2359: : 512iter [00:48, 10.66iter/s]
Best score: 0.2359: : 512iter [00:48, 10.66iter/s]
Best score: 0.2359: : 513iter [00:48, 10.66iter/s]
Best score: 0.2359: : 514iter [00:48, 11.01iter/s]
Best score: 0.2359: : 514iter [00:48, 11.01iter/s]
Best score: 0.2359: : 515iter [00:48, 11.01iter/s]
Best score: 0.2359: : 516iter [00:48, 11.20iter/s]
Best score: 0.2359: : 516iter [00:48, 11.20iter/s]
Best score: 0.2359: : 517iter [00:48, 11.20iter/s]
Best score: 0.2359: : 518iter [00:48, 11.40iter/s]
Best score: 0.2359: : 518iter [00:48, 11.40iter/s]
Best score: 0.2339: : 519iter [00:49, 11.40iter/s]
Best score: 0.2339: : 520iter [00:49, 11.36iter/s]
Best score: 0.2339: : 520iter [00:49, 11.36iter/s]
Best score: 0.2339: : 521iter [00:49, 11.36iter/s]
Best score: 0.2339: : 522iter [00:49, 11.54iter/s]
Best score: 0.2339: : 522iter [00:49, 11.54iter/s]
Best score: 0.2339: : 523iter [00:49, 11.54iter/s]
Best score: 0.2339: : 524iter [00:49, 11.66iter/s]
Best score: 0.2339: : 524iter [00:49, 11.66iter/s]
Best score: 0.2339: : 525iter [00:49, 11.66iter/s]
Best score: 0.2339: : 526iter [00:49, 11.69iter/s]
Best score: 0.2339: : 526iter [00:49, 11.69iter/s]
Best score: 0.2339: : 527iter [00:49, 11.69iter/s]
Best score: 0.2339: : 528iter [00:49, 11.68iter/s]
Best score: 0.2339: : 528iter [00:49, 11.68iter/s]
Best score: 0.2339: : 529iter [00:49, 11.68iter/s]
Best score: 0.2339: : 530iter [00:49, 11.56iter/s]
Best score: 0.2339: : 530iter [00:49, 11.56iter/s]
Best score: 0.2339: : 531iter [00:50, 11.56iter/s]
Best score: 0.2339: : 532iter [00:50, 11.67iter/s]
Best score: 0.2339: : 532iter [00:50, 11.67iter/s]
Best score: 0.2339: : 533iter [00:50, 11.67iter/s]
Best score: 0.2339: : 534iter [00:50, 11.75iter/s]
Best score: 0.2339: : 534iter [00:50, 11.75iter/s]
Best score: 0.2339: : 535iter [00:50, 11.75iter/s]
Best score: 0.2339: : 536iter [00:50, 11.80iter/s]
Best score: 0.2339: : 536iter [00:50, 11.80iter/s]
Best score: 0.2339: : 537iter [00:50, 11.80iter/s]
Best score: 0.2339: : 538iter [00:50, 11.84iter/s]
Best score: 0.2339: : 538iter [00:50, 11.84iter/s]
Best score: 0.2337: : 539iter [00:50, 11.84iter/s]
Best score: 0.2337: : 540iter [00:50, 11.68iter/s]
Best score: 0.2337: : 540iter [00:50, 11.68iter/s]
Best score: 0.2337: : 541iter [00:50, 11.68iter/s]
Best score: 0.2337: : 542iter [00:50, 11.66iter/s]
Best score: 0.2337: : 542iter [00:50, 11.66iter/s]
Best score: 0.2337: : 543iter [00:51, 11.66iter/s]
Best score: 0.2337: : 544iter [00:51, 11.74iter/s]
Best score: 0.2337: : 544iter [00:51, 11.74iter/s]
Best score: 0.2337: : 545iter [00:51, 11.74iter/s]
Best score: 0.2337: : 546iter [00:51, 11.80iter/s]
Best score: 0.2337: : 546iter [00:51, 11.80iter/s]
Best score: 0.2337: : 547iter [00:51, 11.80iter/s]
Best score: 0.2337: : 548iter [00:51, 11.85iter/s]
Best score: 0.2337: : 548iter [00:51, 11.85iter/s]
[ITER 550] Best: 0.2327
[PARAMS] Current best parameters:
  fx: 555.2127
  fy: 555.0372
  px: 851.2599
  py: 998.1573
  k1: -0.04322471
  k2: 0.03231919
  k3: -0.01782392
  k4: 0.00351310
  p1: -0.00292134
  p2: -0.01821783
  p3: 0.00651286
  p4: 0.01589256
  s1: 0.0034
  s2: -0.0141
  s3: -0.0058
  s4: -0.0128
  tilt_x: -0.0208
  tilt_y: -0.0275
  scale: 3.0410
  rotation: -0.3797

Best score: 0.2327: : 549iter [00:51, 11.85iter/s]
Best score: 0.2327: : 550iter [00:51, 11.62iter/s]
Best score: 0.2327: : 550iter [00:51, 11.62iter/s]
Best score: 0.2327: : 551iter [00:52, 11.62iter/s]
Best score: 0.2327: : 552iter [00:52,  7.62iter/s]
Best score: 0.2327: : 552iter [00:52,  7.62iter/s]
Best score: 0.2327: : 553iter [00:52,  7.62iter/s]
Best score: 0.2327: : 554iter [00:52,  8.55iter/s]
Best score: 0.2327: : 554iter [00:52,  8.55iter/s]
Best score: 0.2327: : 555iter [00:52,  8.55iter/s]
Best score: 0.2327: : 556iter [00:52,  9.35iter/s]
Best score: 0.2327: : 556iter [00:52,  9.35iter/s]
Best score: 0.2327: : 557iter [00:52,  9.35iter/s]
Best score: 0.2327: : 558iter [00:52,  9.96iter/s]
Best score: 0.2327: : 558iter [00:52,  9.96iter/s]
Best score: 0.2327: : 559iter [00:52,  9.96iter/s]
Best score: 0.2327: : 560iter [00:52, 10.30iter/s]
Best score: 0.2327: : 560iter [00:52, 10.30iter/s]
Best score: 0.2327: : 561iter [00:52, 10.30iter/s]
Best score: 0.2327: : 562iter [00:52, 10.67iter/s]
Best score: 0.2327: : 562iter [00:52, 10.67iter/s]
Best score: 0.2327: : 563iter [00:53, 10.67iter/s]
Best score: 0.2327: : 564iter [00:53, 10.99iter/s]
Best score: 0.2327: : 564iter [00:53, 10.99iter/s]
Best score: 0.2327: : 565iter [00:53, 10.99iter/s]
Best score: 0.2327: : 566iter [00:53, 11.20iter/s]
Best score: 0.2327: : 566iter [00:53, 11.20iter/s]
Best score: 0.2327: : 567iter [00:53, 11.20iter/s]
Best score: 0.2327: : 568iter [00:53, 11.40iter/s]
Best score: 0.2327: : 568iter [00:53, 11.40iter/s]
Best score: 0.2321: : 569iter [00:53, 11.40iter/s]
Best score: 0.2321: : 570iter [00:53, 11.35iter/s]
Best score: 0.2321: : 570iter [00:53, 11.35iter/s]
Best score: 0.2321: : 571iter [00:53, 11.35iter/s]
Best score: 0.2321: : 572iter [00:53, 11.46iter/s]
Best score: 0.2321: : 572iter [00:53, 11.46iter/s]
Best score: 0.2321: : 573iter [00:53, 11.46iter/s]
Best score: 0.2321: : 574iter [00:53, 11.58iter/s]
Best score: 0.2321: : 574iter [00:54, 11.58iter/s]
Best score: 0.2321: : 575iter [00:54, 11.58iter/s]
Best score: 0.2321: : 576iter [00:54, 11.62iter/s]
Best score: 0.2321: : 576iter [00:54, 11.62iter/s]
Best score: 0.2321: : 577iter [00:54, 11.62iter/s]
Best score: 0.2321: : 578iter [00:54, 11.67iter/s]
Best score: 0.2321: : 578iter [00:54, 11.67iter/s]
Best score: 0.2307: : 579iter [00:54, 11.67iter/s]
Best score: 0.2307: : 580iter [00:54, 11.55iter/s]
Best score: 0.2307: : 580iter [00:54, 11.55iter/s]
Best score: 0.2307: : 581iter [00:54, 11.55iter/s]
Best score: 0.2307: : 582iter [00:54, 11.64iter/s]
Best score: 0.2307: : 582iter [00:54, 11.64iter/s]
Best score: 0.2307: : 583iter [00:54, 11.64iter/s]
Best score: 0.2307: : 584iter [00:54, 11.67iter/s]
Best score: 0.2307: : 584iter [00:54, 11.67iter/s]
Best score: 0.2307: : 585iter [00:54, 11.67iter/s]
Best score: 0.2307: : 586iter [00:54, 11.76iter/s]
Best score: 0.2307: : 586iter [00:55, 11.76iter/s]
Best score: 0.2307: : 587iter [00:55, 11.76iter/s]
Best score: 0.2307: : 588iter [00:55, 11.80iter/s]
Best score: 0.2307: : 588iter [00:55, 11.80iter/s]
Best score: 0.2297: : 589iter [00:55, 11.80iter/s]
Best score: 0.2297: : 590iter [00:55, 11.64iter/s]
Best score: 0.2297: : 590iter [00:55, 11.64iter/s]
Best score: 0.2297: : 591iter [00:55, 11.64iter/s]
Best score: 0.2297: : 592iter [00:55, 11.74iter/s]
Best score: 0.2297: : 592iter [00:55, 11.74iter/s]
Best score: 0.2297: : 593iter [00:55, 11.74iter/s]
Best score: 0.2297: : 594iter [00:55, 11.75iter/s]
Best score: 0.2297: : 594iter [00:55, 11.75iter/s]
Best score: 0.2297: : 595iter [00:55, 11.75iter/s]
Best score: 0.2297: : 596iter [00:55, 11.82iter/s]
Best score: 0.2297: : 596iter [00:55, 11.82iter/s]
Best score: 0.2297: : 597iter [00:55, 11.82iter/s]
Best score: 0.2297: : 598iter [00:55, 11.87iter/s]
Best score: 0.2297: : 598iter [00:56, 11.87iter/s]
[ITER 600] Best: 0.2294
[PARAMS] Current best parameters:
  fx: 557.4459
  fy: 557.3165
  px: 852.1721
  py: 998.0579
  k1: -0.04201548
  k2: 0.02624207
  k3: -0.01372104
  k4: 0.00258540
  p1: -0.00038418
  p2: -0.01851595
  p3: 0.00490799
  p4: 0.01426548
  s1: 0.0062
  s2: -0.0125
  s3: -0.0059
  s4: -0.0119
  tilt_x: -0.0268
  tilt_y: -0.0323
  scale: 3.0385
  rotation: -0.3671

Best score: 0.2294: : 599iter [00:56, 11.87iter/s]
Best score: 0.2294: : 600iter [00:56, 11.67iter/s]
Best score: 0.2294: : 600iter [00:56, 11.67iter/s]
Best score: 0.2294: : 601iter [00:56, 11.67iter/s]
Best score: 0.2294: : 602iter [00:56,  7.67iter/s]
Best score: 0.2294: : 602iter [00:56,  7.67iter/s]
Best score: 0.2294: : 603iter [00:56,  7.67iter/s]
Best score: 0.2294: : 604iter [00:56,  8.60iter/s]
Best score: 0.2294: : 604iter [00:56,  8.60iter/s]
Best score: 0.2294: : 605iter [00:56,  8.60iter/s]
Best score: 0.2294: : 606iter [00:56,  9.38iter/s]
Best score: 0.2294: : 606iter [00:57,  9.38iter/s]
Best score: 0.2294: : 607iter [00:57,  9.38iter/s]
Best score: 0.2294: : 608iter [00:57, 10.02iter/s]
Best score: 0.2294: : 608iter [00:57, 10.02iter/s]
Best score: 0.2280: : 609iter [00:57, 10.02iter/s]
Best score: 0.2280: : 610iter [00:57, 10.37iter/s]
Best score: 0.2280: : 610iter [00:57, 10.37iter/s]
Best score: 0.2280: : 611iter [00:57, 10.37iter/s]
Best score: 0.2280: : 612iter [00:57, 10.80iter/s]
Best score: 0.2280: : 612iter [00:57, 10.80iter/s]
Best score: 0.2280: : 613iter [00:57, 10.80iter/s]
Best score: 0.2280: : 614iter [00:57, 11.13iter/s]
Best score: 0.2280: : 614iter [00:57, 11.13iter/s]
Best score: 0.2280: : 615iter [00:57, 11.13iter/s]
Best score: 0.2280: : 616iter [00:57, 11.36iter/s]
Best score: 0.2280: : 616iter [00:57, 11.36iter/s]
Best score: 0.2280: : 617iter [00:57, 11.36iter/s]
Best score: 0.2280: : 618iter [00:57, 11.52iter/s]
Best score: 0.2280: : 618iter [00:58, 11.52iter/s]
Best score: 0.2275: : 619iter [00:58, 11.52iter/s]
Best score: 0.2275: : 620iter [00:58, 11.39iter/s]
Best score: 0.2275: : 620iter [00:58, 11.39iter/s]
Best score: 0.2275: : 621iter [00:58, 11.39iter/s]
Best score: 0.2275: : 622iter [00:58, 11.51iter/s]
Best score: 0.2275: : 622iter [00:58, 11.51iter/s]
Best score: 0.2275: : 623iter [00:58, 11.51iter/s]
Best score: 0.2275: : 624iter [00:58, 11.64iter/s]
Best score: 0.2275: : 624iter [00:58, 11.64iter/s]
Best score: 0.2275: : 625iter [00:58, 11.64iter/s]
Best score: 0.2275: : 626iter [00:58, 11.69iter/s]
Best score: 0.2275: : 626iter [00:58, 11.69iter/s]
Best score: 0.2275: : 627iter [00:58, 11.69iter/s]
Best score: 0.2275: : 628iter [00:58, 11.67iter/s]
Best score: 0.2275: : 628iter [00:58, 11.67iter/s]
Best score: 0.2274: : 629iter [00:58, 11.67iter/s]
Best score: 0.2274: : 630iter [00:58, 11.50iter/s]
Best score: 0.2274: : 630iter [00:59, 11.50iter/s]
Best score: 0.2274: : 631iter [00:59, 11.50iter/s]
Best score: 0.2274: : 632iter [00:59, 11.63iter/s]
Best score: 0.2274: : 632iter [00:59, 11.63iter/s]
Best score: 0.2274: : 633iter [00:59, 11.63iter/s]
Best score: 0.2274: : 634iter [00:59, 11.73iter/s]
Best score: 0.2274: : 634iter [00:59, 11.73iter/s]
Best score: 0.2274: : 635iter [00:59, 11.73iter/s]
Best score: 0.2274: : 636iter [00:59, 11.69iter/s]
Best score: 0.2274: : 636iter [00:59, 11.69iter/s]
Best score: 0.2274: : 637iter [00:59, 11.69iter/s]
Best score: 0.2274: : 638iter [00:59, 11.71iter/s]
Best score: 0.2274: : 638iter [00:59, 11.71iter/s]
Best score: 0.2274: : 639iter [00:59, 11.71iter/s]
Best score: 0.2274: : 640iter [00:59, 11.59iter/s]
Best score: 0.2274: : 640iter [00:59, 11.59iter/s]
Best score: 0.2274: : 641iter [01:00, 11.59iter/s]
Best score: 0.2274: : 642iter [01:00, 11.64iter/s]
Best score: 0.2274: : 642iter [01:00, 11.64iter/s]
Best score: 0.2274: : 643iter [01:00, 11.64iter/s]
Best score: 0.2274: : 644iter [01:00, 11.74iter/s]
Best score: 0.2274: : 644iter [01:00, 11.74iter/s]
Best score: 0.2274: : 645iter [01:00, 11.74iter/s]
Best score: 0.2274: : 646iter [01:00, 11.80iter/s]
Best score: 0.2274: : 646iter [01:00, 11.80iter/s]
Best score: 0.2274: : 647iter [01:00, 11.80iter/s]
Best score: 0.2274: : 648iter [01:00, 11.84iter/s]
Best score: 0.2274: : 648iter [01:00, 11.84iter/s]
[ITER 650] Best: 0.2270
[PARAMS] Current best parameters:
  fx: 561.8198
  fy: 561.6948
  px: 853.6347
  py: 999.0413
  k1: -0.04541767
  k2: 0.02358964
  k3: -0.01102663
  k4: 0.00184932
  p1: 0.00505566
  p2: -0.01812838
  p3: 0.00077349
  p4: 0.01157848
  s1: 0.0126
  s2: -0.0111
  s3: -0.0051
  s4: -0.0103
  tilt_x: -0.0334
  tilt_y: -0.0385
  scale: 3.0385
  rotation: -0.3636

Best score: 0.2270: : 649iter [01:00, 11.84iter/s]
Best score: 0.2270: : 650iter [01:00, 11.66iter/s]
Best score: 0.2270: : 650iter [01:01, 11.66iter/s]
Best score: 0.2270: : 651iter [01:01, 11.66iter/s]
Best score: 0.2270: : 652iter [01:01,  7.66iter/s]
Best score: 0.2270: : 652iter [01:01,  7.66iter/s]
Best score: 0.2270: : 653iter [01:01,  7.66iter/s]
Best score: 0.2270: : 654iter [01:01,  8.56iter/s]
Best score: 0.2270: : 654iter [01:01,  8.56iter/s]
Best score: 0.2270: : 655iter [01:01,  8.56iter/s]
Best score: 0.2270: : 656iter [01:01,  9.35iter/s]
Best score: 0.2270: : 656iter [01:01,  9.35iter/s]
Best score: 0.2270: : 657iter [01:01,  9.35iter/s]
Best score: 0.2270: : 658iter [01:01, 10.01iter/s]
Best score: 0.2270: : 658iter [01:01, 10.01iter/s]
Best score: 0.2267: : 659iter [01:01, 10.01iter/s]
Best score: 0.2267: : 660iter [01:01, 10.37iter/s]
Best score: 0.2267: : 660iter [01:01, 10.37iter/s]
Best score: 0.2267: : 661iter [01:02, 10.37iter/s]
Best score: 0.2267: : 662iter [01:02, 10.79iter/s]
Best score: 0.2267: : 662iter [01:02, 10.79iter/s]
Best score: 0.2267: : 663iter [01:02, 10.79iter/s]
Best score: 0.2267: : 664iter [01:02, 11.10iter/s]
Best score: 0.2267: : 664iter [01:02, 11.10iter/s]
Best score: 0.2267: : 665iter [01:02, 11.10iter/s]
Best score: 0.2267: : 666iter [01:02, 11.33iter/s]
Best score: 0.2267: : 666iter [01:02, 11.33iter/s]
Best score: 0.2267: : 667iter [01:02, 11.33iter/s]
Best score: 0.2267: : 668iter [01:02, 11.51iter/s]
Best score: 0.2267: : 668iter [01:02, 11.51iter/s]
Best score: 0.2264: : 669iter [01:02, 11.51iter/s]
Best score: 0.2264: : 670iter [01:02, 11.45iter/s]
Best score: 0.2264: : 670iter [01:02, 11.45iter/s]
Best score: 0.2264: : 671iter [01:02, 11.45iter/s]
Best score: 0.2264: : 672iter [01:02, 11.60iter/s]
Best score: 0.2264: : 672iter [01:02, 11.60iter/s]
Best score: 0.2264: : 673iter [01:03, 11.60iter/s]
Best score: 0.2264: : 674iter [01:03, 11.67iter/s]
Best score: 0.2264: : 674iter [01:03, 11.67iter/s]
Best score: 0.2264: : 675iter [01:03, 11.67iter/s]
Best score: 0.2264: : 676iter [01:03, 11.66iter/s]
Best score: 0.2264: : 676iter [01:03, 11.66iter/s]
Best score: 0.2264: : 677iter [01:03, 11.66iter/s]
Best score: 0.2264: : 678iter [01:03, 11.65iter/s]
Best score: 0.2264: : 678iter [01:03, 11.65iter/s]
Best score: 0.2264: : 679iter [01:03, 11.65iter/s]
Best score: 0.2264: : 680iter [01:03, 11.49iter/s]
Best score: 0.2264: : 680iter [01:03, 11.49iter/s]
Best score: 0.2264: : 681iter [01:03, 11.49iter/s]
Best score: 0.2264: : 682iter [01:03, 11.63iter/s]
Best score: 0.2264: : 682iter [01:03, 11.63iter/s]
Best score: 0.2264: : 683iter [01:03, 11.63iter/s]
Best score: 0.2264: : 684iter [01:03, 11.74iter/s]
Best score: 0.2264: : 684iter [01:03, 11.74iter/s]
Best score: 0.2264: : 685iter [01:04, 11.74iter/s]
Best score: 0.2264: : 686iter [01:04, 11.80iter/s]
Best score: 0.2264: : 686iter [01:04, 11.80iter/s]
Best score: 0.2264: : 687iter [01:04, 11.80iter/s]
Best score: 0.2264: : 688iter [01:04, 11.81iter/s]
Best score: 0.2264: : 688iter [01:04, 11.81iter/s]
Best score: 0.2258: : 689iter [01:04, 11.81iter/s]
Best score: 0.2258: : 690iter [01:04, 11.66iter/s]
Best score: 0.2258: : 690iter [01:04, 11.66iter/s]
Best score: 0.2258: : 691iter [01:04, 11.66iter/s]
Best score: 0.2258: : 692iter [01:04, 11.73iter/s]
Best score: 0.2258: : 692iter [01:04, 11.73iter/s]
Best score: 0.2258: : 693iter [01:04, 11.73iter/s]
Best score: 0.2258: : 694iter [01:04, 11.78iter/s]
Best score: 0.2258: : 694iter [01:04, 11.78iter/s]
Best score: 0.2258: : 695iter [01:04, 11.78iter/s]
Best score: 0.2258: : 696iter [01:04, 11.78iter/s]
Best score: 0.2258: : 696iter [01:04, 11.78iter/s]
Best score: 0.2258: : 697iter [01:05, 11.78iter/s]
Best score: 0.2258: : 698iter [01:05, 11.72iter/s]
Best score: 0.2258: : 698iter [01:05, 11.72iter/s]
[ITER 700] Best: 0.2255
[PARAMS] Current best parameters:
  fx: 565.4780
  fy: 565.3317
  px: 854.1917
  py: 1000.5400
  k1: -0.05078066
  k2: 0.02649090
  k3: -0.01265161
  k4: 0.00226925
  p1: 0.00844251
  p2: -0.01925801
  p3: 0.00032221
  p4: 0.00925958
  s1: 0.0153
  s2: -0.0093
  s3: -0.0061
  s4: -0.0082
  tilt_x: -0.0329
  tilt_y: -0.0436
  scale: 3.0401
  rotation: -0.3582

Best score: 0.2255: : 699iter [01:05, 11.72iter/s]
Best score: 0.2255: : 700iter [01:05, 11.50iter/s]
Best score: 0.2255: : 700iter [01:05, 11.50iter/s]
Best score: 0.2255: : 701iter [01:05, 11.50iter/s]
Best score: 0.2255: : 702iter [01:05,  7.56iter/s]
Best score: 0.2255: : 702iter [01:05,  7.56iter/s]
Best score: 0.2255: : 703iter [01:05,  7.56iter/s]
Best score: 0.2255: : 704iter [01:05,  8.50iter/s]
Best score: 0.2255: : 704iter [01:05,  8.50iter/s]
Best score: 0.2255: : 705iter [01:06,  8.50iter/s]
Best score: 0.2255: : 706iter [01:06,  9.30iter/s]
Best score: 0.2255: : 706iter [01:06,  9.30iter/s]
Best score: 0.2255: : 707iter [01:06,  9.30iter/s]
Best score: 0.2255: : 708iter [01:06,  9.96iter/s]
Best score: 0.2255: : 708iter [01:06,  9.96iter/s]
Best score: 0.2255: : 709iter [01:06,  9.96iter/s]
Best score: 0.2255: : 710iter [01:06, 10.33iter/s]
Best score: 0.2255: : 710iter [01:06, 10.33iter/s]
Best score: 0.2255: : 711iter [01:06, 10.33iter/s]
Best score: 0.2255: : 712iter [01:06, 10.77iter/s]
Best score: 0.2255: : 712iter [01:06, 10.77iter/s]
Best score: 0.2255: : 713iter [01:06, 10.77iter/s]
Best score: 0.2255: : 714iter [01:06, 11.10iter/s]
Best score: 0.2255: : 714iter [01:06, 11.10iter/s]
Best score: 0.2255: : 715iter [01:06, 11.10iter/s]
Best score: 0.2255: : 716iter [01:06, 11.34iter/s]
Best score: 0.2255: : 716iter [01:07, 11.34iter/s]
Best score: 0.2255: : 717iter [01:07, 11.34iter/s]
Best score: 0.2255: : 718iter [01:07, 11.42iter/s]
Best score: 0.2255: : 718iter [01:07, 11.42iter/s]
Best score: 0.2255: : 719iter [01:07, 11.42iter/s]
Best score: 0.2255: : 720iter [01:07, 11.33iter/s]
Best score: 0.2255: : 720iter [01:07, 11.33iter/s]
Best score: 0.2255: : 721iter [01:07, 11.33iter/s]
Best score: 0.2255: : 722iter [01:07, 11.47iter/s]
Best score: 0.2255: : 722iter [01:07, 11.47iter/s]
Best score: 0.2255: : 723iter [01:07, 11.47iter/s]
Best score: 0.2255: : 724iter [01:07, 11.60iter/s]
Best score: 0.2255: : 724iter [01:07, 11.60iter/s]
Best score: 0.2255: : 725iter [01:07, 11.60iter/s]
Best score: 0.2255: : 726iter [01:07, 11.71iter/s]
Best score: 0.2255: : 726iter [01:07, 11.71iter/s]
Best score: 0.2255: : 727iter [01:07, 11.71iter/s]
Best score: 0.2255: : 728iter [01:07, 11.77iter/s]
Best score: 0.2255: : 728iter [01:08, 11.77iter/s]
Best score: 0.2255: : 729iter [01:08, 11.77iter/s]
Best score: 0.2255: : 730iter [01:08, 11.56iter/s]
Best score: 0.2255: : 730iter [01:08, 11.56iter/s]
Best score: 0.2255: : 731iter [01:08, 11.56iter/s]
Best score: 0.2255: : 732iter [01:08, 11.63iter/s]
Best score: 0.2255: : 732iter [01:08, 11.63iter/s]
Best score: 0.2255: : 733iter [01:08, 11.63iter/s]
Best score: 0.2255: : 734iter [01:08, 11.73iter/s]
Best score: 0.2255: : 734iter [01:08, 11.73iter/s]
Best score: 0.2255: : 735iter [01:08, 11.73iter/s]
Best score: 0.2255: : 736iter [01:08, 11.75iter/s]
Best score: 0.2255: : 736iter [01:08, 11.75iter/s]
Best score: 0.2255: : 737iter [01:08, 11.75iter/s]
Best score: 0.2255: : 738iter [01:08, 11.82iter/s]
Best score: 0.2255: : 738iter [01:08, 11.82iter/s]
Best score: 0.2255: : 739iter [01:08, 11.82iter/s]
Best score: 0.2255: : 740iter [01:08, 11.67iter/s]
Best score: 0.2255: : 740iter [01:09, 11.67iter/s]
Best score: 0.2255: : 741iter [01:09, 11.67iter/s]
Best score: 0.2255: : 742iter [01:09, 11.76iter/s]
Best score: 0.2255: : 742iter [01:09, 11.76iter/s]
Best score: 0.2255: : 743iter [01:09, 11.76iter/s]
Best score: 0.2255: : 744iter [01:09, 11.82iter/s]
Best score: 0.2255: : 744iter [01:09, 11.82iter/s]
Best score: 0.2255: : 745iter [01:09, 11.82iter/s]
Best score: 0.2255: : 746iter [01:09, 11.86iter/s]
Best score: 0.2255: : 746iter [01:09, 11.86iter/s]
Best score: 0.2255: : 747iter [01:09, 11.86iter/s]
Best score: 0.2255: : 748iter [01:09, 11.88iter/s]
Best score: 0.2255: : 748iter [01:09, 11.88iter/s]
[ITER 750] Best: 0.2252
[PARAMS] Current best parameters:
  fx: 565.4486
  fy: 565.2840
  px: 854.0624
  py: 1000.5657
  k1: -0.05212082
  k2: 0.02927682
  k3: -0.01468022
  k4: 0.00277292
  p1: 0.00792118
  p2: -0.02072403
  p3: 0.00087642
  p4: 0.00929712
  s1: 0.0164
  s2: -0.0098
  s3: -0.0060
  s4: -0.0087
  tilt_x: -0.0315
  tilt_y: -0.0458
  scale: 3.0412
  rotation: -0.3548

Best score: 0.2252: : 749iter [01:09, 11.88iter/s]
Best score: 0.2252: : 750iter [01:09, 11.64iter/s]
Best score: 0.2252: : 750iter [01:10, 11.64iter/s]
Best score: 0.2252: : 751iter [01:10, 11.64iter/s]
Best score: 0.2252: : 752iter [01:10,  7.64iter/s]
Best score: 0.2252: : 752iter [01:10,  7.64iter/s]
Best score: 0.2252: : 753iter [01:10,  7.64iter/s]
Best score: 0.2252: : 754iter [01:10,  8.57iter/s]
Best score: 0.2252: : 754iter [01:10,  8.57iter/s]
Best score: 0.2252: : 755iter [01:10,  8.57iter/s]
Best score: 0.2252: : 756iter [01:10,  9.34iter/s]
Best score: 0.2252: : 756iter [01:10,  9.34iter/s]
Best score: 0.2252: : 757iter [01:10,  9.34iter/s]
Best score: 0.2252: : 758iter [01:10,  9.95iter/s]
Best score: 0.2252: : 758iter [01:10,  9.95iter/s]
Best score: 0.2251: : 759iter [01:10,  9.95iter/s]
Best score: 0.2251: : 760iter [01:10, 10.32iter/s]
Best score: 0.2251: : 760iter [01:11, 10.32iter/s]
Best score: 0.2251: : 761iter [01:11, 10.32iter/s]
Best score: 0.2251: : 762iter [01:11, 10.74iter/s]
Best score: 0.2251: : 762iter [01:11, 10.74iter/s]
Best score: 0.2251: : 763iter [01:11, 10.74iter/s]
Best score: 0.2251: : 764iter [01:11, 11.09iter/s]
Best score: 0.2251: : 764iter [01:11, 11.09iter/s]
Best score: 0.2251: : 765iter [01:11, 11.09iter/s]
Best score: 0.2251: : 766iter [01:11, 11.33iter/s]
Best score: 0.2251: : 766iter [01:11, 11.33iter/s]
Best score: 0.2251: : 767iter [01:11, 11.33iter/s]
Best score: 0.2251: : 768iter [01:11, 11.52iter/s]
Best score: 0.2251: : 768iter [01:11, 11.52iter/s]
Best score: 0.2251: : 769iter [01:11, 11.52iter/s]
Best score: 0.2251: : 770iter [01:11, 11.38iter/s]
Best score: 0.2251: : 770iter [01:11, 11.38iter/s]
Best score: 0.2251: : 771iter [01:12, 11.38iter/s]
Best score: 0.2251: : 772iter [01:12, 11.44iter/s]
Best score: 0.2251: : 772iter [01:12, 11.44iter/s]
Best score: 0.2251: : 773iter [01:12, 11.44iter/s]
Best score: 0.2251: : 774iter [01:12, 11.50iter/s]
Best score: 0.2251: : 774iter [01:12, 11.50iter/s]
Best score: 0.2251: : 775iter [01:12, 11.50iter/s]
Best score: 0.2251: : 776iter [01:12, 11.52iter/s]
Best score: 0.2251: : 776iter [01:12, 11.52iter/s]
Best score: 0.2251: : 777iter [01:12, 11.52iter/s]
Best score: 0.2251: : 778iter [01:12,  9.20iter/s]
Best score: 0.2251: : 778iter [01:12,  9.20iter/s]
Best score: 0.2249: : 779iter [01:12,  9.20iter/s]
Best score: 0.2249: : 780iter [01:12,  9.71iter/s]
Best score: 0.2249: : 780iter [01:12,  9.71iter/s]
Best score: 0.2249: : 781iter [01:13,  9.71iter/s]
Best score: 0.2249: : 782iter [01:13, 10.30iter/s]
Best score: 0.2249: : 782iter [01:13, 10.30iter/s]
Best score: 0.2249: : 783iter [01:13, 10.30iter/s]
Best score: 0.2249: : 784iter [01:13, 10.74iter/s]
Best score: 0.2249: : 784iter [01:13, 10.74iter/s]
Best score: 0.2249: : 785iter [01:13, 10.74iter/s]
Best score: 0.2249: : 786iter [01:13, 11.09iter/s]
Best score: 0.2249: : 786iter [01:13, 11.09iter/s]
Best score: 0.2249: : 787iter [01:13, 11.09iter/s]
Best score: 0.2249: : 788iter [01:13, 11.34iter/s]
Best score: 0.2249: : 788iter [01:13, 11.34iter/s]
Best score: 0.2249: : 789iter [01:13, 11.34iter/s]
Best score: 0.2249: : 790iter [01:13, 11.28iter/s]
Best score: 0.2249: : 790iter [01:13, 11.28iter/s]
Best score: 0.2249: : 791iter [01:13, 11.28iter/s]
Best score: 0.2249: : 792iter [01:13, 11.42iter/s]
Best score: 0.2249: : 792iter [01:13, 11.42iter/s]
Best score: 0.2249: : 793iter [01:14, 11.42iter/s]
Best score: 0.2249: : 794iter [01:14, 11.53iter/s]
Best score: 0.2249: : 794iter [01:14, 11.53iter/s]
Best score: 0.2249: : 795iter [01:14, 11.53iter/s]
Best score: 0.2249: : 796iter [01:14, 11.65iter/s]
Best score: 0.2249: : 796iter [01:14, 11.65iter/s]
Best score: 0.2249: : 797iter [01:14, 11.65iter/s]
Best score: 0.2249: : 798iter [01:14, 11.68iter/s]
Best score: 0.2249: : 798iter [01:14, 11.68iter/s]
[ITER 800] Best: 0.2249
[PARAMS] Current best parameters:
  fx: 567.2299
  fy: 567.0063
  px: 854.1924
  py: 1000.5935
  k1: -0.05304606
  k2: 0.02721457
  k3: -0.01284776
  k4: 0.00231238
  p1: 0.00817445
  p2: -0.02023924
  p3: 0.00217401
  p4: 0.00881594
  s1: 0.0145
  s2: -0.0090
  s3: -0.0076
  s4: -0.0080
  tilt_x: -0.0319
  tilt_y: -0.0456
  scale: 3.0405
  rotation: -0.3556

Best score: 0.2249: : 799iter [01:14, 11.68iter/s]
Best score: 0.2249: : 800iter [01:14, 11.47iter/s]
Best score: 0.2249: : 800iter [01:14, 11.47iter/s]
Best score: 0.2249: : 801iter [01:15, 11.47iter/s]
Best score: 0.2249: : 802iter [01:15,  7.53iter/s]
Best score: 0.2249: : 802iter [01:15,  7.53iter/s]
Best score: 0.2249: : 803iter [01:15,  7.53iter/s]
Best score: 0.2249: : 804iter [01:15,  8.44iter/s]
Best score: 0.2249: : 804iter [01:15,  8.44iter/s]
Best score: 0.2249: : 805iter [01:15,  8.44iter/s]
Best score: 0.2249: : 806iter [01:15,  9.23iter/s]
Best score: 0.2249: : 806iter [01:15,  9.23iter/s]
Best score: 0.2249: : 807iter [01:15,  9.23iter/s]
Best score: 0.2249: : 808iter [01:15,  9.88iter/s]
Best score: 0.2249: : 808iter [01:15,  9.88iter/s]
Best score: 0.2247: : 809iter [01:15,  9.88iter/s]
Best score: 0.2247: : 810iter [01:15, 10.23iter/s]
Best score: 0.2247: : 810iter [01:15, 10.23iter/s]
Best score: 0.2247: : 811iter [01:15, 10.23iter/s]
Best score: 0.2247: : 812iter [01:15, 10.61iter/s]
Best score: 0.2247: : 812iter [01:15, 10.61iter/s]
Best score: 0.2247: : 813iter [01:16, 10.61iter/s]
Best score: 0.2247: : 814iter [01:16, 10.88iter/s]
Best score: 0.2247: : 814iter [01:16, 10.88iter/s]
Best score: 0.2247: : 815iter [01:16, 10.88iter/s]
Best score: 0.2247: : 816iter [01:16, 11.18iter/s]
Best score: 0.2247: : 816iter [01:16, 11.18iter/s]
Best score: 0.2247: : 817iter [01:16, 11.18iter/s]
Best score: 0.2247: : 818iter [01:16, 11.31iter/s]
Best score: 0.2247: : 818iter [01:16, 11.31iter/s]
Best score: 0.2247: : 819iter [01:16, 11.31iter/s]
Best score: 0.2247: : 820iter [01:16, 11.27iter/s]
Best score: 0.2247: : 820iter [01:16, 11.27iter/s]
Best score: 0.2247: : 821iter [01:16, 11.27iter/s]
Best score: 0.2247: : 822iter [01:16, 11.46iter/s]
Best score: 0.2247: : 822iter [01:16, 11.46iter/s]
Best score: 0.2247: : 823iter [01:16, 11.46iter/s]
Best score: 0.2247: : 824iter [01:16, 11.60iter/s]
Best score: 0.2247: : 824iter [01:17, 11.60iter/s]
Best score: 0.2247: : 825iter [01:17, 11.60iter/s]
Best score: 0.2247: : 826iter [01:17, 11.62iter/s]
Best score: 0.2247: : 826iter [01:17, 11.62iter/s]
Best score: 0.2247: : 827iter [01:17, 11.62iter/s]
Best score: 0.2247: : 828iter [01:17, 11.67iter/s]
Best score: 0.2247: : 828iter [01:17, 11.67iter/s]
Best score: 0.2247: : 829iter [01:17, 11.67iter/s]
Best score: 0.2247: : 830iter [01:17, 11.50iter/s]
Best score: 0.2247: : 830iter [01:17, 11.50iter/s]
Best score: 0.2247: : 831iter [01:17, 11.50iter/s]
Best score: 0.2247: : 832iter [01:17, 11.54iter/s]
Best score: 0.2247: : 832iter [01:17, 11.54iter/s]
Best score: 0.2247: : 833iter [01:17, 11.54iter/s]
Best score: 0.2247: : 834iter [01:17, 11.60iter/s]
Best score: 0.2247: : 834iter [01:17, 11.60iter/s]
Best score: 0.2247: : 835iter [01:17, 11.60iter/s]
Best score: 0.2247: : 836iter [01:17, 11.68iter/s]
Best score: 0.2247: : 836iter [01:18, 11.68iter/s]
Best score: 0.2247: : 837iter [01:18, 11.68iter/s]
Best score: 0.2247: : 838iter [01:18, 11.71iter/s]
Best score: 0.2247: : 838iter [01:18, 11.71iter/s]
Best score: 0.2247: : 839iter [01:18, 11.71iter/s]
Best score: 0.2247: : 840iter [01:18, 11.55iter/s]
Best score: 0.2247: : 840iter [01:18, 11.55iter/s]
Best score: 0.2247: : 841iter [01:18, 11.55iter/s]
Best score: 0.2247: : 842iter [01:18, 11.67iter/s]
Best score: 0.2247: : 842iter [01:18, 11.67iter/s]
Best score: 0.2247: : 843iter [01:18, 11.67iter/s]
Best score: 0.2247: : 844iter [01:18, 11.76iter/s]
Best score: 0.2247: : 844iter [01:18, 11.76iter/s]
Best score: 0.2247: : 845iter [01:18, 11.76iter/s]
Best score: 0.2247: : 846iter [01:18, 11.77iter/s]
Best score: 0.2247: : 846iter [01:18, 11.77iter/s]
Best score: 0.2247: : 847iter [01:18, 11.77iter/s]
Best score: 0.2247: : 848iter [01:18, 11.75iter/s]
Best score: 0.2247: : 848iter [01:19, 11.75iter/s]
[ITER 850] Best: 0.2247
[PARAMS] Current best parameters:
  fx: 567.3642
  fy: 567.1382
  px: 854.4833
  py: 1000.7274
  k1: -0.05505048
  k2: 0.03053564
  k3: -0.01499696
  k4: 0.00280018
  p1: 0.00846940
  p2: -0.02070340
  p3: 0.00213664
  p4: 0.00854336
  s1: 0.0156
  s2: -0.0090
  s3: -0.0074
  s4: -0.0080
  tilt_x: -0.0319
  tilt_y: -0.0480
  scale: 3.0426
  rotation: -0.3529

Best score: 0.2247: : 849iter [01:19, 11.75iter/s]
Best score: 0.2247: : 850iter [01:19, 11.52iter/s]
Best score: 0.2247: : 850iter [01:19, 11.52iter/s]
Best score: 0.2247: : 851iter [01:19, 11.52iter/s]
Best score: 0.2247: : 852iter [01:19,  7.58iter/s]
Best score: 0.2247: : 852iter [01:19,  7.58iter/s]
Best score: 0.2247: : 853iter [01:19,  7.58iter/s]
Best score: 0.2247: : 854iter [01:19,  8.51iter/s]
Best score: 0.2247: : 854iter [01:19,  8.51iter/s]
Best score: 0.2247: : 855iter [01:19,  8.51iter/s]
Best score: 0.2247: : 856iter [01:19,  9.29iter/s]
Best score: 0.2247: : 856iter [01:20,  9.29iter/s]
Best score: 0.2247: : 857iter [01:20,  9.29iter/s]
Best score: 0.2247: : 858iter [01:20,  9.89iter/s]
Best score: 0.2247: : 858iter [01:20,  9.89iter/s]
Best score: 0.2246: : 859iter [01:20,  9.89iter/s]
Best score: 0.2246: : 860iter [01:20, 10.21iter/s]
Best score: 0.2246: : 860iter [01:20, 10.21iter/s]
Best score: 0.2246: : 861iter [01:20, 10.21iter/s]
Best score: 0.2246: : 862iter [01:20, 10.68iter/s]
Best score: 0.2246: : 862iter [01:20, 10.68iter/s]
Best score: 0.2246: : 863iter [01:20, 10.68iter/s]
Best score: 0.2246: : 864iter [01:20, 11.03iter/s]
Best score: 0.2246: : 864iter [01:20, 11.03iter/s]
Best score: 0.2246: : 865iter [01:20, 11.03iter/s]
Best score: 0.2246: : 866iter [01:20, 11.28iter/s]
Best score: 0.2246: : 866iter [01:20, 11.28iter/s]
Best score: 0.2246: : 867iter [01:20, 11.28iter/s]
Best score: 0.2246: : 868iter [01:20, 11.42iter/s]
Best score: 0.2246: : 868iter [01:21, 11.42iter/s]
Best score: 0.2246: : 869iter [01:21, 11.42iter/s]
Best score: 0.2246: : 870iter [01:21, 11.38iter/s]
Best score: 0.2246: : 870iter [01:21, 11.38iter/s]
Best score: 0.2246: : 871iter [01:21, 11.38iter/s]
Best score: 0.2246: : 872iter [01:21, 11.50iter/s]
Best score: 0.2246: : 872iter [01:21, 11.50iter/s]
Best score: 0.2246: : 873iter [01:21, 11.50iter/s]
Best score: 0.2246: : 874iter [01:21, 11.63iter/s]
Best score: 0.2246: : 874iter [01:21, 11.63iter/s]
Best score: 0.2246: : 875iter [01:21, 11.63iter/s]
Best score: 0.2246: : 876iter [01:21, 11.64iter/s]
Best score: 0.2246: : 876iter [01:21, 11.64iter/s]
Best score: 0.2246: : 877iter [01:21, 11.64iter/s]
Best score: 0.2246: : 878iter [01:21, 11.63iter/s]
Best score: 0.2246: : 878iter [01:21, 11.63iter/s]
Best score: 0.2246: : 879iter [01:22, 11.63iter/s]
Best score: 0.2246: : 880iter [01:22, 11.46iter/s]
Best score: 0.2246: : 880iter [01:22, 11.46iter/s]
Best score: 0.2246: : 881iter [01:22, 11.46iter/s]
Best score: 0.2246: : 882iter [01:22, 11.54iter/s]
Best score: 0.2246: : 882iter [01:22, 11.54iter/s]
Best score: 0.2246: : 883iter [01:22, 11.54iter/s]
Best score: 0.2246: : 884iter [01:22, 11.65iter/s]
Best score: 0.2246: : 884iter [01:22, 11.65iter/s]
Best score: 0.2246: : 885iter [01:22, 11.65iter/s]
Best score: 0.2246: : 886iter [01:22, 11.74iter/s]
Best score: 0.2246: : 886iter [01:22, 11.74iter/s]
Best score: 0.2246: : 887iter [01:22, 11.74iter/s]
Best score: 0.2246: : 888iter [01:22, 11.72iter/s]
Best score: 0.2246: : 888iter [01:22, 11.72iter/s]
Best score: 0.2246: : 889iter [01:22, 11.72iter/s]
Best score: 0.2246: : 890iter [01:22, 11.50iter/s]
Best score: 0.2246: : 890iter [01:22, 11.50iter/s]
Best score: 0.2246: : 891iter [01:23, 11.50iter/s]
Best score: 0.2246: : 892iter [01:23, 11.58iter/s]
Best score: 0.2246: : 892iter [01:23, 11.58iter/s]
Best score: 0.2246: : 893iter [01:23, 11.58iter/s]
Best score: 0.2246: : 894iter [01:23, 11.59iter/s]
Best score: 0.2246: : 894iter [01:23, 11.59iter/s]
Best score: 0.2246: : 895iter [01:23, 11.59iter/s]
Best score: 0.2246: : 896iter [01:23, 11.69iter/s]
Best score: 0.2246: : 896iter [01:23, 11.69iter/s]
Best score: 0.2246: : 897iter [01:23, 11.69iter/s]
Best score: 0.2246: : 898iter [01:23, 11.72iter/s]
Best score: 0.2246: : 898iter [01:23, 11.72iter/s]
[ITER 900] Best: 0.2245
[PARAMS] Current best parameters:
  fx: 566.6689
  fy: 566.4815
  px: 854.8479
  py: 1000.7350
  k1: -0.05597813
  k2: 0.03343489
  k3: -0.01695420
  k4: 0.00323285
  p1: 0.00901393
  p2: -0.02116941
  p3: 0.00068247
  p4: 0.00838154
  s1: 0.0180
  s2: -0.0090
  s3: -0.0062
  s4: -0.0081
  tilt_x: -0.0330
  tilt_y: -0.0507
  scale: 3.0448
  rotation: -0.3524

Best score: 0.2245: : 899iter [01:23, 11.72iter/s]
Best score: 0.2245: : 900iter [01:23, 11.50iter/s]
Best score: 0.2245: : 900iter [01:24, 11.50iter/s]
Best score: 0.2245: : 901iter [01:24, 11.50iter/s]
Best score: 0.2245: : 902iter [01:24,  7.57iter/s]
Best score: 0.2245: : 902iter [01:24,  7.57iter/s]
Best score: 0.2245: : 903iter [01:24,  7.57iter/s]
Best score: 0.2245: : 904iter [01:24,  8.46iter/s]
Best score: 0.2245: : 904iter [01:24,  8.46iter/s]
Best score: 0.2245: : 905iter [01:24,  8.46iter/s]
Best score: 0.2245: : 906iter [01:24,  9.25iter/s]
Best score: 0.2245: : 906iter [01:24,  9.25iter/s]
Best score: 0.2245: : 907iter [01:24,  9.25iter/s]
Best score: 0.2245: : 908iter [01:24,  9.88iter/s]
Best score: 0.2245: : 908iter [01:24,  9.88iter/s]
Best score: 0.2245: : 909iter [01:24,  9.88iter/s]
Best score: 0.2245: : 910iter [01:24, 10.23iter/s]
Best score: 0.2245: : 910iter [01:24, 10.23iter/s]
Best score: 0.2245: : 911iter [01:25, 10.23iter/s]
Best score: 0.2245: : 912iter [01:25, 10.61iter/s]
Best score: 0.2245: : 912iter [01:25, 10.61iter/s]
Best score: 0.2245: : 913iter [01:25, 10.61iter/s]
Best score: 0.2245: : 914iter [01:25, 10.89iter/s]
Best score: 0.2245: : 914iter [01:25, 10.89iter/s]
Best score: 0.2245: : 915iter [01:25, 10.89iter/s]
Best score: 0.2245: : 916iter [01:25, 11.09iter/s]
Best score: 0.2245: : 916iter [01:25, 11.09iter/s]
Best score: 0.2245: : 917iter [01:25, 11.09iter/s]
Best score: 0.2245: : 918iter [01:25, 11.23iter/s]
Best score: 0.2245: : 918iter [01:25, 11.23iter/s]
Best score: 0.2245: : 919iter [01:25, 11.23iter/s]
Best score: 0.2245: : 920iter [01:25, 11.17iter/s]
Best score: 0.2245: : 920iter [01:25, 11.17iter/s]
Best score: 0.2245: : 921iter [01:25, 11.17iter/s]
Best score: 0.2245: : 922iter [01:25, 11.31iter/s]
Best score: 0.2245: : 922iter [01:26, 11.31iter/s]
Best score: 0.2245: : 923iter [01:26, 11.31iter/s]
Best score: 0.2245: : 924iter [01:26, 11.44iter/s]
Best score: 0.2245: : 924iter [01:26, 11.44iter/s]
Best score: 0.2245: : 925iter [01:26, 11.44iter/s]
Best score: 0.2245: : 926iter [01:26, 11.60iter/s]
Best score: 0.2245: : 926iter [01:26, 11.60iter/s]
Best score: 0.2245: : 927iter [01:26, 11.60iter/s]
Best score: 0.2245: : 928iter [01:26, 11.70iter/s]
Best score: 0.2245: : 928iter [01:26, 11.70iter/s]
Best score: 0.2245: : 929iter [01:26, 11.70iter/s]
Best score: 0.2245: : 930iter [01:26, 11.49iter/s]
Best score: 0.2245: : 930iter [01:26, 11.49iter/s]
Best score: 0.2245: : 931iter [01:26, 11.49iter/s]
Best score: 0.2245: : 932iter [01:26, 11.57iter/s]
Best score: 0.2245: : 932iter [01:26, 11.57iter/s]
Best score: 0.2245: : 933iter [01:26, 11.57iter/s]
Best score: 0.2245: : 934iter [01:26, 11.62iter/s]
Best score: 0.2245: : 934iter [01:27, 11.62iter/s]
Best score: 0.2245: : 935iter [01:27, 11.62iter/s]
Best score: 0.2245: : 936iter [01:27, 11.61iter/s]
Best score: 0.2245: : 936iter [01:27, 11.61iter/s]
Best score: 0.2245: : 937iter [01:27, 11.61iter/s]
Best score: 0.2245: : 938iter [01:27, 11.61iter/s]
Best score: 0.2245: : 938iter [01:27, 11.61iter/s]
Best score: 0.2244: : 939iter [01:27, 11.61iter/s]
Best score: 0.2244: : 940iter [01:27, 11.41iter/s]
Best score: 0.2244: : 940iter [01:27, 11.41iter/s]
Best score: 0.2244: : 941iter [01:27, 11.41iter/s]
Best score: 0.2244: : 942iter [01:27, 11.48iter/s]
Best score: 0.2244: : 942iter [01:27, 11.48iter/s]
Best score: 0.2244: : 943iter [01:27, 11.48iter/s]
Best score: 0.2244: : 944iter [01:27, 11.61iter/s]
Best score: 0.2244: : 944iter [01:27, 11.61iter/s]
Best score: 0.2244: : 945iter [01:28, 11.61iter/s]
Best score: 0.2244: : 946iter [01:28, 11.70iter/s]
Best score: 0.2244: : 946iter [01:28, 11.70iter/s]
Best score: 0.2244: : 947iter [01:28, 11.70iter/s]
Best score: 0.2244: : 948iter [01:28, 11.78iter/s]
Best score: 0.2244: : 948iter [01:28, 11.78iter/s]
[ITER 950] Best: 0.2242
[PARAMS] Current best parameters:
  fx: 566.4888
  fy: 566.2729
  px: 854.6116
  py: 1000.4509
  k1: -0.05590459
  k2: 0.03360460
  k3: -0.01701014
  k4: 0.00322510
  p1: 0.00906526
  p2: -0.02101555
  p3: 0.00279846
  p4: 0.00761980
  s1: 0.0156
  s2: -0.0083
  s3: -0.0086
  s4: -0.0074
  tilt_x: -0.0345
  tilt_y: -0.0493
  scale: 3.0447
  rotation: -0.3539

Best score: 0.2242: : 949iter [01:28, 11.78iter/s]
Best score: 0.2242: : 950iter [01:28, 11.59iter/s]
Best score: 0.2242: : 950iter [01:28, 11.59iter/s]
Best score: 0.2242: : 951iter [01:28, 11.59iter/s]
Best score: 0.2242: : 952iter [01:28,  7.59iter/s]
Best score: 0.2242: : 952iter [01:28,  7.59iter/s]
Best score: 0.2242: : 953iter [01:29,  7.59iter/s]
Best score: 0.2242: : 954iter [01:29,  8.46iter/s]
Best score: 0.2242: : 954iter [01:29,  8.46iter/s]
Best score: 0.2242: : 955iter [01:29,  8.46iter/s]
Best score: 0.2242: : 956iter [01:29,  9.23iter/s]
Best score: 0.2242: : 956iter [01:29,  9.23iter/s]
Best score: 0.2242: : 957iter [01:29,  9.23iter/s]
Best score: 0.2242: : 958iter [01:29,  9.88iter/s]
Best score: 0.2242: : 958iter [01:29,  9.88iter/s]
Best score: 0.2240: : 959iter [01:29,  9.88iter/s]
Best score: 0.2240: : 960iter [01:29, 10.27iter/s]
Best score: 0.2240: : 960iter [01:29, 10.27iter/s]
Best score: 0.2240: : 961iter [01:29, 10.27iter/s]
Best score: 0.2240: : 962iter [01:29, 10.72iter/s]
Best score: 0.2240: : 962iter [01:29, 10.72iter/s]
Best score: 0.2240: : 963iter [01:29, 10.72iter/s]
Best score: 0.2240: : 964iter [01:29, 11.07iter/s]
Best score: 0.2240: : 964iter [01:29, 11.07iter/s]
Best score: 0.2240: : 965iter [01:30, 11.07iter/s]
Best score: 0.2240: : 966iter [01:30, 11.33iter/s]
Best score: 0.2240: : 966iter [01:30, 11.33iter/s]
Best score: 0.2240: : 967iter [01:30, 11.33iter/s]
Best score: 0.2240: : 968iter [01:30, 11.46iter/s]
Best score: 0.2240: : 968iter [01:30, 11.46iter/s]
Best score: 0.2238: : 969iter [01:30, 11.46iter/s]
Best score: 0.2238: : 970iter [01:30, 11.41iter/s]
Best score: 0.2238: : 970iter [01:30, 11.41iter/s]
Best score: 0.2238: : 971iter [01:30, 11.41iter/s]
Best score: 0.2238: : 972iter [01:30, 11.52iter/s]
Best score: 0.2238: : 972iter [01:30, 11.52iter/s]
Best score: 0.2238: : 973iter [01:30, 11.52iter/s]
Best score: 0.2238: : 974iter [01:30, 11.59iter/s]
Best score: 0.2238: : 974iter [01:30, 11.59iter/s]
Best score: 0.2238: : 975iter [01:30, 11.59iter/s]
Best score: 0.2238: : 976iter [01:30, 11.64iter/s]
Best score: 0.2238: : 976iter [01:30, 11.64iter/s]
Best score: 0.2238: : 977iter [01:31, 11.64iter/s]
Best score: 0.2238: : 978iter [01:31, 11.70iter/s]
Best score: 0.2238: : 978iter [01:31, 11.70iter/s]
Best score: 0.2238: : 979iter [01:31, 11.70iter/s]
Best score: 0.2238: : 980iter [01:31, 11.56iter/s]
Best score: 0.2238: : 980iter [01:31, 11.56iter/s]
Best score: 0.2238: : 981iter [01:31, 11.56iter/s]
Best score: 0.2238: : 982iter [01:31, 11.60iter/s]
Best score: 0.2238: : 982iter [01:31, 11.60iter/s]
Best score: 0.2238: : 983iter [01:31, 11.60iter/s]
Best score: 0.2238: : 984iter [01:31, 11.67iter/s]
Best score: 0.2238: : 984iter [01:31, 11.67iter/s]
Best score: 0.2238: : 985iter [01:31, 11.67iter/s]
Best score: 0.2238: : 986iter [01:31, 11.66iter/s]
Best score: 0.2238: : 986iter [01:31, 11.66iter/s]
Best score: 0.2238: : 987iter [01:31, 11.66iter/s]
Best score: 0.2238: : 988iter [01:31, 11.64iter/s]
Best score: 0.2238: : 988iter [01:32, 11.64iter/s]
Best score: 0.2237: : 989iter [01:32, 11.64iter/s]
Best score: 0.2237: : 990iter [01:32, 11.46iter/s]
Best score: 0.2237: : 990iter [01:32, 11.46iter/s]
Best score: 0.2237: : 991iter [01:32, 11.46iter/s]
Best score: 0.2237: : 992iter [01:32, 11.52iter/s]
Best score: 0.2237: : 992iter [01:32, 11.52iter/s]
Best score: 0.2237: : 993iter [01:32, 11.52iter/s]
Best score: 0.2237: : 994iter [01:32, 11.64iter/s]
Best score: 0.2237: : 994iter [01:32, 11.64iter/s]
Best score: 0.2237: : 995iter [01:32, 11.64iter/s]
Best score: 0.2237: : 996iter [01:32, 11.72iter/s]
Best score: 0.2237: : 996iter [01:32, 11.72iter/s]
Best score: 0.2237: : 997iter [01:32, 11.72iter/s]
Best score: 0.2237: : 998iter [01:32, 11.78iter/s]
Best score: 0.2237: : 998iter [01:32, 11.78iter/s]
[ITER 1000] Best: 0.2237
[PARAMS] Current best parameters:
  fx: 567.2187
  fy: 566.9887
  px: 854.7877
  py: 1000.3588
  k1: -0.05720395
  k2: 0.03481847
  k3: -0.01780907
  k4: 0.00342342
  p1: 0.00888594
  p2: -0.02130224
  p3: 0.00617909
  p4: 0.00548423
  s1: 0.0127
  s2: -0.0061
  s3: -0.0124
  s4: -0.0048
  tilt_x: -0.0346
  tilt_y: -0.0508
  scale: 3.0450
  rotation: -0.3528

Best score: 0.2237: : 999iter [01:32, 11.78iter/s]
Best score: 0.2237: : 1000iter [01:32, 11.60iter/s]
Best score: 0.2237: : 1000iter [01:33, 11.60iter/s]
Best score: 0.2237: : 1001iter [01:33, 11.60iter/s]
Best score: 0.2237: : 1002iter [01:33,  7.61iter/s]
Best score: 0.2237: : 1002iter [01:33,  7.61iter/s]
Best score: 0.2237: : 1003iter [01:33,  7.61iter/s]
Best score: 0.2237: : 1004iter [01:33,  8.53iter/s]
Best score: 0.2237: : 1004iter [01:33,  8.53iter/s]
Best score: 0.2237: : 1005iter [01:33,  8.53iter/s]
Best score: 0.2237: : 1006iter [01:33,  9.26iter/s]
Best score: 0.2237: : 1006iter [01:33,  9.26iter/s]
Best score: 0.2237: : 1007iter [01:33,  9.26iter/s]
Best score: 0.2237: : 1008iter [01:33,  9.87iter/s]
Best score: 0.2237: : 1008iter [01:34,  9.87iter/s]
Best score: 0.2235: : 1009iter [01:34,  9.87iter/s]
Best score: 0.2235: : 1010iter [01:34, 10.25iter/s]
Best score: 0.2235: : 1010iter [01:34, 10.25iter/s]
Best score: 0.2235: : 1011iter [01:34, 10.25iter/s]
Best score: 0.2235: : 1012iter [01:34, 10.71iter/s]
Best score: 0.2235: : 1012iter [01:34, 10.71iter/s]
Best score: 0.2235: : 1013iter [01:34, 10.71iter/s]
Best score: 0.2235: : 1014iter [01:34, 11.00iter/s]
Best score: 0.2235: : 1014iter [01:34, 11.00iter/s]
Best score: 0.2235: : 1015iter [01:34, 11.00iter/s]
Best score: 0.2235: : 1016iter [01:34, 11.18iter/s]
Best score: 0.2235: : 1016iter [01:34, 11.18iter/s]
Best score: 0.2235: : 1017iter [01:34, 11.18iter/s]
Best score: 0.2235: : 1018iter [01:34, 11.30iter/s]
Best score: 0.2235: : 1018iter [01:34, 11.30iter/s]
Best score: 0.2234: : 1019iter [01:34, 11.30iter/s]
Best score: 0.2234: : 1020iter [01:34, 11.21iter/s]
Best score: 0.2234: : 1020iter [01:35, 11.21iter/s]
Best score: 0.2234: : 1021iter [01:35, 11.21iter/s]
Best score: 0.2234: : 1022iter [01:35, 11.32iter/s]
Best score: 0.2234: : 1022iter [01:35, 11.32iter/s]
Best score: 0.2234: : 1023iter [01:35, 11.32iter/s]
Best score: 0.2234: : 1024iter [01:35, 11.40iter/s]
Best score: 0.2234: : 1024iter [01:35, 11.40iter/s]
Best score: 0.2234: : 1025iter [01:35, 11.40iter/s]
Best score: 0.2234: : 1026iter [01:35, 11.46iter/s]
Best score: 0.2234: : 1026iter [01:35, 11.46iter/s]
Best score: 0.2234: : 1027iter [01:35, 11.46iter/s]
Best score: 0.2234: : 1028iter [01:35, 11.49iter/s]
Best score: 0.2234: : 1028iter [01:35, 11.49iter/s]
Best score: 0.2232: : 1029iter [01:35, 11.49iter/s]
Best score: 0.2232: : 1030iter [01:35, 11.33iter/s]
Best score: 0.2232: : 1030iter [01:35, 11.33iter/s]
Best score: 0.2232: : 1031iter [01:36, 11.33iter/s]
Best score: 0.2232: : 1032iter [01:36, 11.44iter/s]
Best score: 0.2232: : 1032iter [01:36, 11.44iter/s]
Best score: 0.2232: : 1033iter [01:36, 11.44iter/s]
Best score: 0.2232: : 1034iter [01:36, 11.49iter/s]
Best score: 0.2232: : 1034iter [01:36, 11.49iter/s]
Best score: 0.2232: : 1035iter [01:36, 11.49iter/s]
Best score: 0.2232: : 1036iter [01:36, 11.57iter/s]
Best score: 0.2232: : 1036iter [01:36, 11.57iter/s]
Best score: 0.2232: : 1037iter [01:36, 11.57iter/s]
Best score: 0.2232: : 1038iter [01:36, 11.59iter/s]
Best score: 0.2232: : 1038iter [01:36, 11.59iter/s]
Best score: 0.2232: : 1039iter [01:36, 11.59iter/s]
Best score: 0.2232: : 1040iter [01:36, 11.40iter/s]
Best score: 0.2232: : 1040iter [01:36, 11.40iter/s]
Best score: 0.2232: : 1041iter [01:36, 11.40iter/s]
Best score: 0.2232: : 1042iter [01:36, 11.46iter/s]
Best score: 0.2232: : 1042iter [01:36, 11.46iter/s]
Best score: 0.2232: : 1043iter [01:37, 11.46iter/s]
Best score: 0.2232: : 1044iter [01:37, 11.50iter/s]
Best score: 0.2232: : 1044iter [01:37, 11.50iter/s]
Best score: 0.2232: : 1045iter [01:37, 11.50iter/s]
Best score: 0.2232: : 1046iter [01:37, 11.60iter/s]
Best score: 0.2232: : 1046iter [01:37, 11.60iter/s]
Best score: 0.2232: : 1047iter [01:37, 11.60iter/s]
Best score: 0.2232: : 1048iter [01:37, 11.70iter/s]
Best score: 0.2232: : 1048iter [01:37, 11.70iter/s]
[ITER 1050] Best: 0.2231
[PARAMS] Current best parameters:
  fx: 565.0995
  fy: 564.8460
  px: 853.7296
  py: 999.9924
  k1: -0.05544363
  k2: 0.03525826
  k3: -0.01826600
  k4: 0.00352065
  p1: 0.00802193
  p2: -0.02212398
  p3: 0.01150788
  p4: 0.00380774
  s1: 0.0070
  s2: -0.0041
  s3: -0.0172
  s4: -0.0033
  tilt_x: -0.0347
  tilt_y: -0.0469
  scale: 3.0458
  rotation: -0.3479

Best score: 0.2231: : 1049iter [01:37, 11.70iter/s]
Best score: 0.2231: : 1050iter [01:37, 11.55iter/s]
Best score: 0.2231: : 1050iter [01:37, 11.55iter/s]
Best score: 0.2231: : 1051iter [01:38, 11.55iter/s]
Best score: 0.2231: : 1052iter [01:38,  7.60iter/s]
Best score: 0.2231: : 1052iter [01:38,  7.60iter/s]
Best score: 0.2231: : 1053iter [01:38,  7.60iter/s]
Best score: 0.2231: : 1054iter [01:38,  8.51iter/s]
Best score: 0.2231: : 1054iter [01:38,  8.51iter/s]
Best score: 0.2231: : 1055iter [01:38,  8.51iter/s]
Best score: 0.2231: : 1056iter [01:38,  9.26iter/s]
Best score: 0.2231: : 1056iter [01:38,  9.26iter/s]
Best score: 0.2231: : 1057iter [01:38,  9.26iter/s]
Best score: 0.2231: : 1058iter [01:38,  9.89iter/s]
Best score: 0.2231: : 1058iter [01:38,  9.89iter/s]
Best score: 0.2231: : 1059iter [01:38,  9.89iter/s]
Best score: 0.2231: : 1060iter [01:38, 10.27iter/s]
Best score: 0.2231: : 1060iter [01:38, 10.27iter/s]
Best score: 0.2231: : 1061iter [01:38, 10.27iter/s]
Best score: 0.2231: : 1062iter [01:38, 10.64iter/s]
Best score: 0.2231: : 1062iter [01:38, 10.64iter/s]
Best score: 0.2231: : 1063iter [01:39, 10.64iter/s]
Best score: 0.2231: : 1064iter [01:39, 10.96iter/s]
Best score: 0.2231: : 1064iter [01:39, 10.96iter/s]
Best score: 0.2231: : 1065iter [01:39, 10.96iter/s]
Best score: 0.2231: : 1066iter [01:39, 11.23iter/s]
Best score: 0.2231: : 1066iter [01:39, 11.23iter/s]
Best score: 0.2231: : 1067iter [01:39, 11.23iter/s]
Best score: 0.2231: : 1068iter [01:39, 11.43iter/s]
Best score: 0.2231: : 1068iter [01:39, 11.43iter/s]
Best score: 0.2231: : 1069iter [01:39, 11.43iter/s]
Best score: 0.2231: : 1070iter [01:39, 11.33iter/s]
Best score: 0.2231: : 1070iter [01:39, 11.33iter/s]
Best score: 0.2231: : 1071iter [01:39, 11.33iter/s]
Best score: 0.2231: : 1072iter [01:39, 11.52iter/s]
Best score: 0.2231: : 1072iter [01:39, 11.52iter/s]
Best score: 0.2231: : 1073iter [01:39, 11.52iter/s]
Best score: 0.2231: : 1074iter [01:39, 11.64iter/s]
Best score: 0.2231: : 1074iter [01:40, 11.64iter/s]
Best score: 0.2231: : 1075iter [01:40, 11.64iter/s]
Best score: 0.2231: : 1076iter [01:40, 11.68iter/s]
Best score: 0.2231: : 1076iter [01:40, 11.68iter/s]
Best score: 0.2231: : 1077iter [01:40, 11.68iter/s]
Best score: 0.2231: : 1078iter [01:40, 11.75iter/s]
Best score: 0.2231: : 1078iter [01:40, 11.75iter/s]
Best score: 0.2230: : 1079iter [01:40, 11.75iter/s]
Best score: 0.2230: : 1080iter [01:40, 11.56iter/s]
Best score: 0.2230: : 1080iter [01:40, 11.56iter/s]
Best score: 0.2230: : 1081iter [01:40, 11.56iter/s]
Best score: 0.2230: : 1082iter [01:40, 11.68iter/s]
Best score: 0.2230: : 1082iter [01:40, 11.68iter/s]
Best score: 0.2230: : 1083iter [01:40, 11.68iter/s]
Best score: 0.2230: : 1084iter [01:40, 11.75iter/s]
Best score: 0.2230: : 1084iter [01:40, 11.75iter/s]
Best score: 0.2230: : 1085iter [01:40, 11.75iter/s]
Best score: 0.2230: : 1086iter [01:40, 11.80iter/s]
Best score: 0.2230: : 1086iter [01:41, 11.80iter/s]
Best score: 0.2230: : 1087iter [01:41, 11.80iter/s]
Best score: 0.2230: : 1088iter [01:41, 11.79iter/s]
Best score: 0.2230: : 1088iter [01:41, 11.79iter/s]
Best score: 0.2230: : 1089iter [01:41, 11.79iter/s]
Best score: 0.2230: : 1090iter [01:41, 11.55iter/s]
Best score: 0.2230: : 1090iter [01:41, 11.55iter/s]
Best score: 0.2230: : 1091iter [01:41, 11.55iter/s]
Best score: 0.2230: : 1092iter [01:41, 11.62iter/s]
Best score: 0.2230: : 1092iter [01:41, 11.62iter/s]
Best score: 0.2230: : 1093iter [01:41, 11.62iter/s]
Best score: 0.2230: : 1094iter [01:41, 11.67iter/s]
Best score: 0.2230: : 1094iter [01:41, 11.67iter/s]
Best score: 0.2230: : 1095iter [01:41, 11.67iter/s]
Best score: 0.2230: : 1096iter [01:41, 11.67iter/s]
Best score: 0.2230: : 1096iter [01:41, 11.67iter/s]
Best score: 0.2230: : 1097iter [01:41, 11.67iter/s]
Best score: 0.2230: : 1098iter [01:41, 11.67iter/s]
Best score: 0.2230: : 1098iter [01:42, 11.67iter/s]
[ITER 1100] Best: 0.2230
[PARAMS] Current best parameters:
  fx: 564.2276
  fy: 563.9877
  px: 853.8689
  py: 999.7405
  k1: -0.05407329
  k2: 0.03405961
  k3: -0.01736382
  k4: 0.00326203
  p1: 0.00826260
  p2: -0.02204034
  p3: 0.01118333
  p4: 0.00387694
  s1: 0.0076
  s2: -0.0045
  s3: -0.0172
  s4: -0.0034
  tilt_x: -0.0365
  tilt_y: -0.0475
  scale: 3.0463
  rotation: -0.3421

Best score: 0.2230: : 1099iter [01:42, 11.67iter/s]
Best score: 0.2230: : 1100iter [01:42, 11.52iter/s]
Best score: 0.2230: : 1100iter [01:42, 10.74iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.222994 -> 0.222973

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 101,586 → 92,564 within 3500mm ring
  Ring polish did not improve score: 0.222973
  Success: True
  Tangential distortion: p1=0.008265, p2=-0.022049, p3=0.011179, p4=0.003878
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.2230
[✅] Parameters copied to: /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 564.2275870148602
    fy: 563.9877274885896
    px: 853.8688578311674
    py: 999.7405042072684
    k1: -0.0540724691242164
    k2: 0.034061464432284236
    k3: -0.017362950462549247
    k4: 0.003260605916182446
    p1: 0.008265076498521078
    p2: -0.02204924078913697
    p3: 0.011178718317242133
    p4: 0.0038775499219784446
    scale: 3.0463249261052927
    rotation: -0.3420685069993102
    mmpp: 3.4647898186201913

[🔄] Converting 1397 frames to PTD, creating debug images for 400 calibration frames...

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📁 Rigs: 100%|██████████| 4/4 [00:14<00:00,  3.40s/rig]
📁 Rigs: 100%|██████████| 4/4 [00:14<00:00,  3.55s/rig]
[✅] Saved PTDs: /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/4_undistorted/output/ptd

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📁 Rigs:  75%|███████▌  | 3/4 [00:02<00:00,  1.02rig/s]

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📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.01s/rig]
📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.00rig/s]
[✅] Saved PTDs: /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/4_undistorted/temp_ptd
[WARN] No .tfd files found for serial extraction
[WARN] Failed to extract serial number from .tfd file. Check that .tfd files exist and contain 'LASERbidh' or 'LASERbidg' pattern. Using 'unknown' as fallback.

📤 Writing LUT:   0%|          | 0/3240000 [00:00<?, ?px/s]
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📤 Writing LUT:   5%|▌         | 175154/3240000 [00:00<00:03, 885922.90px/s]
📤 Writing LUT:   8%|▊         | 265297/3240000 [00:00<00:03, 893000.25px/s]
📤 Writing LUT:  11%|█         | 357185/3240000 [00:00<00:03, 903215.03px/s]
📤 Writing LUT:  14%|█▍        | 452425/3240000 [00:00<00:03, 920948.56px/s]
📤 Writing LUT:  17%|█▋        | 545180/3240000 [00:00<00:02, 923190.35px/s]
📤 Writing LUT:  20%|█▉        | 637500/3240000 [00:00<00:02, 919236.61px/s]
📤 Writing LUT:  23%|██▎       | 729428/3240000 [00:00<00:02, 911253.75px/s]
📤 Writing LUT:  25%|██▌       | 822697/3240000 [00:00<00:02, 917899.64px/s]
📤 Writing LUT:  28%|██▊       | 914503/3240000 [00:01<00:02, 916149.95px/s]
📤 Writing LUT:  31%|███       | 1006930/3240000 [00:01<00:02, 918619.75px/s]
📤 Writing LUT:  34%|███▍      | 1101418/3240000 [00:01<00:02, 926575.60px/s]
📤 Writing LUT:  37%|███▋      | 1194085/3240000 [00:01<00:02, 918820.03px/s]
📤 Writing LUT:  40%|███▉      | 1286962/3240000 [00:01<00:02, 921798.73px/s]
📤 Writing LUT:  43%|████▎     | 1383299/3240000 [00:01<00:01, 934260.74px/s]
📤 Writing LUT:  46%|████▌     | 1476743/3240000 [00:01<00:01, 932685.72px/s]
📤 Writing LUT:  49%|████▊     | 1572491/3240000 [00:01<00:01, 940110.27px/s]
📤 Writing LUT:  51%|█████▏    | 1666589/3240000 [00:01<00:01, 940369.16px/s]
📤 Writing LUT:  54%|█████▍    | 1760635/3240000 [00:01<00:01, 934924.03px/s]
📤 Writing LUT:  57%|█████▋    | 1854140/3240000 [00:02<00:01, 931878.80px/s]
📤 Writing LUT:  60%|██████    | 1947337/3240000 [00:02<00:01, 928741.28px/s]
📤 Writing LUT:  63%|██████▎   | 2040219/3240000 [00:02<00:01, 927464.36px/s]
📤 Writing LUT:  66%|██████▌   | 2132970/3240000 [00:02<00:01, 922884.31px/s]
📤 Writing LUT:  69%|██████▊   | 2225265/3240000 [00:02<00:01, 921200.77px/s]
📤 Writing LUT:  72%|███████▏  | 2320801/3240000 [00:02<00:00, 931382.33px/s]
📤 Writing LUT:  75%|███████▍  | 2415308/3240000 [00:02<00:00, 935467.92px/s]
📤 Writing LUT:  77%|███████▋  | 2508864/3240000 [00:02<00:00, 925793.45px/s]
📤 Writing LUT:  80%|████████  | 2601470/3240000 [00:02<00:00, 921994.75px/s]
📤 Writing LUT:  83%|████████▎ | 2694140/3240000 [00:02<00:00, 923390.47px/s]
📤 Writing LUT:  86%|████████▌ | 2786522/3240000 [00:03<00:00, 923518.07px/s]
📤 Writing LUT:  89%|████████▉ | 2880191/3240000 [00:03<00:00, 927448.65px/s]
📤 Writing LUT:  92%|█████████▏| 2975261/3240000 [00:03<00:00, 934397.93px/s]
📤 Writing LUT:  95%|█████████▍| 3068710/3240000 [00:03<00:00, 932615.56px/s]
📤 Writing LUT:  98%|█████████▊| 3162604/3240000 [00:03<00:00, 934505.51px/s]
📤 Writing LUT: 100%|██████████| 3240000/3240000 [00:03<00:00, 924971.98px/s]
[✅] LUT written to: /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDCP3D-SL-013_W046(6)_2026-09-02' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/MDCP3D-SL-013_W046(6)_2026-09-02_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%|          | 0/327 [00:00<?, ?frame/s]

   🔥 2000L:   2%|▏         | 8/327 [00:00<00:04, 73.11frame/s]

   🔥 2000L:   6%|▌         | 18/327 [00:00<00:03, 83.33frame/s]

   🔥 2000L:   9%|▊         | 28/327 [00:00<00:03, 87.79frame/s]

   🔥 2000L:  12%|█▏        | 38/327 [00:00<00:03, 92.11frame/s]

   🔥 2000L:  15%|█▍        | 49/327 [00:00<00:02, 97.76frame/s]

   🔥 2000L:  19%|█▊        | 61/327 [00:00<00:02, 102.41frame/s]

   🔥 2000L:  22%|██▏       | 73/327 [00:00<00:02, 105.14frame/s]

   🔥 2000L:  26%|██▌       | 84/327 [00:00<00:02, 105.38frame/s]

   🔥 2000L:  29%|██▉       | 95/327 [00:00<00:02, 105.60frame/s]

   🔥 2000L:  32%|███▏      | 106/327 [00:01<00:02, 105.27frame/s]

   🔥 2000L:  36%|███▌      | 117/327 [00:01<00:01, 105.31frame/s]

   🔥 2000L:  39%|███▉      | 128/327 [00:01<00:01, 104.61frame/s]

   🔥 2000L:  43%|████▎     | 139/327 [00:01<00:01, 104.87frame/s]

   🔥 2000L:  46%|████▌     | 150/327 [00:01<00:01, 105.48frame/s]

   🔥 2000L:  49%|████▉     | 161/327 [00:01<00:01, 106.52frame/s]

   🔥 2000L:  53%|█████▎    | 172/327 [00:01<00:01, 106.39frame/s]

   🔥 2000L:  56%|█████▌    | 183/327 [00:01<00:01, 106.38frame/s]

   🔥 2000L:  60%|█████▉    | 195/327 [00:01<00:01, 107.68frame/s]

   🔥 2000L:  63%|██████▎   | 206/327 [00:01<00:01, 107.97frame/s]

   🔥 2000L:  66%|██████▋   | 217/327 [00:02<00:01, 101.88frame/s]

   🔥 2000L:  70%|██████▉   | 228/327 [00:02<00:01, 95.79frame/s] 

   🔥 2000L:  73%|███████▎  | 238/327 [00:02<00:00, 90.67frame/s]

   🔥 2000L:  76%|███████▌  | 248/327 [00:02<00:00, 87.56frame/s]

   🔥 2000L:  79%|███████▊  | 257/327 [00:02<00:00, 84.48frame/s]

   🔥 2000L:  81%|████████▏ | 266/327 [00:02<00:00, 82.99frame/s]

   🔥 2000L:  84%|████████▍ | 275/327 [00:02<00:00, 82.38frame/s]

   🔥 2000L:  87%|████████▋ | 284/327 [00:02<00:00, 82.81frame/s]

   🔥 2000L:  90%|████████▉ | 293/327 [00:03<00:00, 79.97frame/s]

   🔥 2000L:  92%|█████████▏| 302/327 [00:03<00:00, 78.48frame/s]

   🔥 2000L:  95%|█████████▍| 310/327 [00:03<00:00, 78.12frame/s]

   🔥 2000L:  97%|█████████▋| 318/327 [00:03<00:00, 77.93frame/s]

   🔥 2000L: 100%|█████████▉| 326/327 [00:03<00:00, 77.67frame/s]

                                                                 [✅] 2000L: /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/5_heatmap/2000L_heatmap.png
[✅] 2000L (fitted): /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/5_heatmap/2000L_heatmap_fitted.png

📁 Rigs (heatmap):  25%|██▌       | 1/4 [00:05<00:15,  5.21s/rig]

   🔥 1500:   0%|          | 0/473 [00:00<?, ?frame/s]

   🔥 1500:   2%|▏         | 9/473 [00:00<00:05, 88.88frame/s]

   🔥 1500:   4%|▍         | 18/473 [00:00<00:05, 81.08frame/s]

   🔥 1500:   6%|▌         | 27/473 [00:00<00:05, 77.19frame/s]

   🔥 1500:   7%|▋         | 35/473 [00:00<00:05, 76.94frame/s]

   🔥 1500:   9%|▉         | 43/473 [00:00<00:05, 77.48frame/s]

   🔥 1500:  11%|█         | 51/473 [00:00<00:05, 78.00frame/s]

   🔥 1500:  12%|█▏        | 59/473 [00:00<00:05, 78.50frame/s]

   🔥 1500:  14%|█▍        | 67/473 [00:00<00:05, 78.66frame/s]

   🔥 1500:  16%|█▌        | 75/473 [00:00<00:05, 78.89frame/s]

   🔥 1500:  18%|█▊        | 83/473 [00:01<00:04, 79.15frame/s]

   🔥 1500:  19%|█▉        | 91/473 [00:01<00:04, 79.25frame/s]

   🔥 1500:  21%|██        | 99/473 [00:01<00:04, 78.92frame/s]

   🔥 1500:  23%|██▎       | 107/473 [00:01<00:04, 78.99frame/s]

   🔥 1500:  24%|██▍       | 115/473 [00:01<00:04, 78.95frame/s]

   🔥 1500:  26%|██▌       | 123/473 [00:01<00:04, 78.79frame/s]

   🔥 1500:  28%|██▊       | 131/473 [00:01<00:04, 78.32frame/s]

   🔥 1500:  29%|██▉       | 139/473 [00:01<00:04, 78.16frame/s]

   🔥 1500:  31%|███       | 147/473 [00:01<00:04, 77.42frame/s]

   🔥 1500:  33%|███▎      | 155/473 [00:01<00:04, 76.99frame/s]

   🔥 1500:  34%|███▍      | 163/473 [00:02<00:04, 76.41frame/s]

   🔥 1500:  36%|███▌      | 171/473 [00:02<00:03, 76.57frame/s]

   🔥 1500:  38%|███▊      | 179/473 [00:02<00:03, 76.43frame/s]

   🔥 1500:  40%|███▉      | 187/473 [00:02<00:03, 76.40frame/s]

   🔥 1500:  41%|████      | 195/473 [00:02<00:03, 76.83frame/s]

   🔥 1500:  43%|████▎     | 203/473 [00:02<00:03, 76.98frame/s]

   🔥 1500:  45%|████▍     | 211/473 [00:02<00:03, 77.22frame/s]

   🔥 1500:  46%|████▋     | 219/473 [00:02<00:03, 77.50frame/s]

   🔥 1500:  48%|████▊     | 227/473 [00:02<00:03, 77.94frame/s]

   🔥 1500:  50%|████▉     | 235/473 [00:03<00:03, 77.80frame/s]

   🔥 1500:  51%|█████▏    | 243/473 [00:03<00:02, 77.48frame/s]

   🔥 1500:  53%|█████▎    | 251/473 [00:03<00:02, 78.05frame/s]

   🔥 1500:  55%|█████▍    | 260/473 [00:03<00:02, 79.46frame/s]

   🔥 1500:  57%|█████▋    | 269/473 [00:03<00:02, 81.10frame/s]

   🔥 1500:  59%|█████▉    | 278/473 [00:03<00:02, 81.97frame/s]

   🔥 1500:  61%|██████    | 287/473 [00:03<00:02, 80.93frame/s]

   🔥 1500:  63%|██████▎   | 296/473 [00:03<00:02, 80.56frame/s]

   🔥 1500:  64%|██████▍   | 305/473 [00:03<00:02, 82.88frame/s]

   🔥 1500:  66%|██████▋   | 314/473 [00:03<00:01, 84.37frame/s]

   🔥 1500:  68%|██████▊   | 323/473 [00:04<00:01, 85.94frame/s]

   🔥 1500:  70%|███████   | 333/473 [00:04<00:01, 87.62frame/s]

   🔥 1500:  72%|███████▏  | 342/473 [00:04<00:01, 88.23frame/s]

   🔥 1500:  74%|███████▍  | 352/473 [00:04<00:01, 89.32frame/s]

   🔥 1500:  77%|███████▋  | 362/473 [00:04<00:01, 90.56frame/s]

   🔥 1500:  79%|███████▊  | 372/473 [00:04<00:01, 91.18frame/s]

   🔥 1500:  81%|████████  | 382/473 [00:04<00:01, 88.87frame/s]

   🔥 1500:  83%|████████▎ | 391/473 [00:04<00:00, 86.50frame/s]

   🔥 1500:  85%|████████▍ | 400/473 [00:04<00:00, 87.09frame/s]

   🔥 1500:  86%|████████▋ | 409/473 [00:05<00:00, 87.74frame/s]

   🔥 1500:  88%|████████▊ | 418/473 [00:05<00:00, 86.01frame/s]

   🔥 1500:  90%|█████████ | 427/473 [00:05<00:00, 83.01frame/s]

   🔥 1500:  92%|█████████▏| 436/473 [00:05<00:00, 82.47frame/s]

   🔥 1500:  94%|█████████▍| 445/473 [00:05<00:00, 81.67frame/s]

   🔥 1500:  96%|█████████▌| 454/473 [00:05<00:00, 79.45frame/s]

   🔥 1500:  98%|█████████▊| 462/473 [00:05<00:00, 77.68frame/s]

   🔥 1500:  99%|█████████▉| 470/473 [00:05<00:00, 76.30frame/s]

                                                                [✅] 1500: /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/5_heatmap/1500_heatmap.png
[✅] 1500 (fitted): /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/5_heatmap/1500_heatmap_fitted.png

📁 Rigs (heatmap):  50%|█████     | 2/4 [00:12<00:12,  6.45s/rig]

   🔥 2000R:   0%|          | 0/295 [00:00<?, ?frame/s]

   🔥 2000R:   3%|▎         | 8/295 [00:00<00:03, 73.95frame/s]

   🔥 2000R:   6%|▌         | 17/295 [00:00<00:03, 82.59frame/s]

   🔥 2000R:   9%|▉         | 27/295 [00:00<00:03, 86.89frame/s]

   🔥 2000R:  13%|█▎        | 38/295 [00:00<00:02, 94.53frame/s]

   🔥 2000R:  17%|█▋        | 49/295 [00:00<00:02, 98.15frame/s]

   🔥 2000R:  20%|██        | 60/295 [00:00<00:02, 100.99frame/s]

   🔥 2000R:  24%|██▍       | 71/295 [00:00<00:02, 102.54frame/s]

   🔥 2000R:  28%|██▊       | 82/295 [00:00<00:02, 101.89frame/s]

   🔥 2000R:  32%|███▏      | 93/295 [00:00<00:01, 102.39frame/s]

   🔥 2000R:  35%|███▌      | 104/295 [00:01<00:01, 103.07frame/s]

   🔥 2000R:  39%|███▉      | 115/295 [00:01<00:01, 103.54frame/s]

   🔥 2000R:  43%|████▎     | 126/295 [00:01<00:01, 103.89frame/s]

   🔥 2000R:  46%|████▋     | 137/295 [00:01<00:01, 104.41frame/s]

   🔥 2000R:  50%|█████     | 148/295 [00:01<00:01, 101.79frame/s]

   🔥 2000R:  54%|█████▍    | 159/295 [00:01<00:01, 101.67frame/s]

   🔥 2000R:  58%|█████▊    | 170/295 [00:01<00:01, 101.17frame/s]

   🔥 2000R:  61%|██████▏   | 181/295 [00:01<00:01, 102.22frame/s]

   🔥 2000R:  65%|██████▌   | 192/295 [00:01<00:00, 104.36frame/s]

   🔥 2000R:  69%|██████▉   | 203/295 [00:02<00:00, 103.32frame/s]

   🔥 2000R:  73%|███████▎  | 214/295 [00:02<00:00, 99.35frame/s] 

   🔥 2000R:  76%|███████▌  | 224/295 [00:02<00:00, 95.38frame/s]

   🔥 2000R:  79%|███████▉  | 234/295 [00:02<00:00, 92.31frame/s]

   🔥 2000R:  83%|████████▎ | 244/295 [00:02<00:00, 89.68frame/s]

   🔥 2000R:  86%|████████▌ | 254/295 [00:02<00:00, 87.25frame/s]

   🔥 2000R:  89%|████████▉ | 263/295 [00:02<00:00, 85.09frame/s]

   🔥 2000R:  92%|█████████▏| 272/295 [00:02<00:00, 83.75frame/s]

   🔥 2000R:  95%|█████████▌| 281/295 [00:02<00:00, 82.00frame/s]

   🔥 2000R:  98%|█████████▊| 290/295 [00:03<00:00, 82.09frame/s]

                                                                 [✅] 2000R: /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/5_heatmap/2000R_heatmap.png
[✅] 2000R (fitted): /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/5_heatmap/2000R_heatmap_fitted.png

📁 Rigs (heatmap):  75%|███████▌  | 3/4 [00:17<00:05,  5.70s/rig]

   🔥 1000:   0%|          | 0/302 [00:00<?, ?frame/s]

   🔥 1000:   3%|▎         | 8/302 [00:00<00:03, 75.30frame/s]

   🔥 1000:   6%|▌         | 17/302 [00:00<00:03, 79.60frame/s]

   🔥 1000:   9%|▊         | 26/302 [00:00<00:03, 80.60frame/s]

   🔥 1000:  12%|█▏        | 35/302 [00:00<00:03, 81.14frame/s]

   🔥 1000:  15%|█▍        | 44/302 [00:00<00:03, 80.74frame/s]

   🔥 1000:  18%|█▊        | 53/302 [00:00<00:03, 80.33frame/s]

   🔥 1000:  21%|██        | 62/302 [00:00<00:02, 80.26frame/s]

   🔥 1000:  24%|██▎       | 71/302 [00:00<00:02, 78.83frame/s]

   🔥 1000:  26%|██▌       | 79/302 [00:00<00:02, 78.51frame/s]

   🔥 1000:  29%|██▉       | 87/302 [00:01<00:02, 78.56frame/s]

   🔥 1000:  31%|███▏      | 95/302 [00:01<00:02, 78.45frame/s]

   🔥 1000:  34%|███▍      | 103/302 [00:01<00:02, 78.56frame/s]

   🔥 1000:  37%|███▋      | 111/302 [00:01<00:02, 78.57frame/s]

   🔥 1000:  39%|███▉      | 119/302 [00:01<00:02, 78.63frame/s]

   🔥 1000:  42%|████▏     | 127/302 [00:01<00:02, 78.65frame/s]

   🔥 1000:  45%|████▍     | 135/302 [00:01<00:02, 78.43frame/s]

   🔥 1000:  47%|████▋     | 143/302 [00:01<00:02, 78.71frame/s]

   🔥 1000:  50%|█████     | 151/302 [00:01<00:01, 78.52frame/s]

   🔥 1000:  53%|█████▎    | 160/302 [00:02<00:01, 80.04frame/s]

   🔥 1000:  56%|█████▋    | 170/302 [00:02<00:01, 83.92frame/s]

   🔥 1000:  60%|█████▉    | 180/302 [00:02<00:01, 86.73frame/s]

   🔥 1000:  63%|██████▎   | 189/302 [00:02<00:01, 86.47frame/s]

   🔥 1000:  66%|██████▌   | 198/302 [00:02<00:01, 86.57frame/s]

   🔥 1000:  69%|██████▊   | 207/302 [00:02<00:01, 86.43frame/s]

   🔥 1000:  72%|███████▏  | 216/302 [00:02<00:00, 86.02frame/s]

   🔥 1000:  75%|███████▍  | 225/302 [00:02<00:00, 84.75frame/s]

   🔥 1000:  77%|███████▋  | 234/302 [00:02<00:00, 83.59frame/s]

   🔥 1000:  80%|████████  | 243/302 [00:02<00:00, 83.93frame/s]

   🔥 1000:  83%|████████▎ | 252/302 [00:03<00:00, 83.76frame/s]

   🔥 1000:  86%|████████▋ | 261/302 [00:03<00:00, 82.94frame/s]

   🔥 1000:  89%|████████▉ | 270/302 [00:03<00:00, 81.98frame/s]

   🔥 1000:  92%|█████████▏| 279/302 [00:03<00:00, 81.82frame/s]

   🔥 1000:  95%|█████████▌| 288/302 [00:03<00:00, 82.29frame/s]

   🔥 1000:  98%|█████████▊| 297/302 [00:03<00:00, 81.78frame/s]

                                                                [✅] 1000: /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/5_heatmap/1000_heatmap_fitted.png

📁 Rigs (heatmap): 100%|██████████| 4/4 [00:21<00:00,  5.21s/rig]
📁 Rigs (heatmap): 100%|██████████| 4/4 [00:21<00:00,  5.45s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDCP3D-SL-013_W046(6)_2026-09-02/calibration/debug/5_heatmap
[🏁] Finished processing MDCP3D-SL-013_W046(6)_2026-09-02


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