🟢 Starting Calibration Pipeline

=== Processing MDC101_W036_2025-12-31 ===

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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 2 las0.zip files to process

Processing Rigs:   0%|          | 0/2 [00:00<?, ?it/s][INFO] Filtered 1303 stationary frames, 213 remain


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→ 1000 Phase 2: corners:  86%|████████▋ | 184/213 [02:44<00:26,  1.08it/s]

→ 1000 Phase 2: corners:  87%|████████▋ | 185/213 [02:45<00:25,  1.09it/s]

→ 1000 Phase 2: corners:  87%|████████▋ | 186/213 [02:46<00:25,  1.08it/s]

→ 1000 Phase 2: corners:  88%|████████▊ | 187/213 [02:47<00:24,  1.08it/s]

→ 1000 Phase 2: corners:  88%|████████▊ | 188/213 [02:48<00:23,  1.07it/s]

→ 1000 Phase 2: corners:  89%|████████▊ | 189/213 [02:49<00:21,  1.09it/s]

→ 1000 Phase 2: corners:  89%|████████▉ | 190/213 [02:50<00:20,  1.10it/s]

→ 1000 Phase 2: corners:  90%|████████▉ | 191/213 [02:51<00:19,  1.11it/s]

→ 1000 Phase 2: corners:  90%|█████████ | 192/213 [02:52<00:18,  1.13it/s]

→ 1000 Phase 2: corners:  91%|█████████ | 193/213 [02:53<00:17,  1.14it/s]

→ 1000 Phase 2: corners:  91%|█████████ | 194/213 [02:53<00:16,  1.14it/s]

→ 1000 Phase 2: corners:  92%|█████████▏| 195/213 [02:54<00:15,  1.15it/s]

→ 1000 Phase 2: corners:  92%|█████████▏| 196/213 [02:55<00:14,  1.16it/s]

→ 1000 Phase 2: corners:  92%|█████████▏| 197/213 [02:56<00:13,  1.16it/s]

→ 1000 Phase 2: corners:  93%|█████████▎| 198/213 [02:57<00:13,  1.14it/s]

→ 1000 Phase 2: corners:  93%|█████████▎| 199/213 [02:58<00:12,  1.16it/s]

→ 1000 Phase 2: corners:  94%|█████████▍| 200/213 [02:59<00:11,  1.15it/s]

→ 1000 Phase 2: corners:  94%|█████████▍| 201/213 [02:59<00:10,  1.15it/s]

→ 1000 Phase 2: corners:  95%|█████████▍| 202/213 [03:00<00:09,  1.15it/s]

→ 1000 Phase 2: corners:  95%|█████████▌| 203/213 [03:01<00:08,  1.14it/s]

→ 1000 Phase 2: corners:  96%|█████████▌| 204/213 [03:02<00:07,  1.15it/s]

→ 1000 Phase 2: corners:  96%|█████████▌| 205/213 [03:03<00:06,  1.15it/s]

→ 1000 Phase 2: corners:  97%|█████████▋| 206/213 [03:04<00:06,  1.15it/s]

→ 1000 Phase 2: corners:  97%|█████████▋| 207/213 [03:05<00:05,  1.15it/s]

→ 1000 Phase 2: corners:  98%|█████████▊| 208/213 [03:06<00:04,  1.14it/s]

→ 1000 Phase 2: corners:  98%|█████████▊| 209/213 [03:06<00:03,  1.14it/s]

→ 1000 Phase 2: corners:  99%|█████████▊| 210/213 [03:07<00:02,  1.15it/s]

→ 1000 Phase 2: corners:  99%|█████████▉| 211/213 [03:08<00:01,  1.15it/s]

→ 1000 Phase 2: corners: 100%|█████████▉| 212/213 [03:09<00:00,  1.16it/s]

→ 1000 Phase 2: corners: 100%|██████████| 213/213 [03:10<00:00,  1.16it/s]

                                                                          [PASS2] Frame 0000684: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000685: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000686: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000687: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001308: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001309: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001310: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001311: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000686: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001310: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 4 frames fixed, 4 untrusted, 213 total


→ 1000 Phase 3: finalize:   0%|          | 0/213 [00:00<?, ?it/s]

→ 1000 Phase 3: finalize:   1%|          | 2/213 [00:00<00:17, 11.97it/s]

→ 1000 Phase 3: finalize:   2%|▏         | 4/213 [00:00<00:16, 12.35it/s]

→ 1000 Phase 3: finalize:   3%|▎         | 6/213 [00:00<00:16, 12.48it/s]

→ 1000 Phase 3: finalize:   4%|▍         | 8/213 [00:00<00:16, 12.56it/s]

→ 1000 Phase 3: finalize:   5%|▍         | 10/213 [00:00<00:16, 12.59it/s]

→ 1000 Phase 3: finalize:   6%|▌         | 12/213 [00:00<00:15, 12.63it/s]

→ 1000 Phase 3: finalize:   7%|▋         | 14/213 [00:01<00:15, 12.67it/s]

→ 1000 Phase 3: finalize:   8%|▊         | 16/213 [00:01<00:15, 12.69it/s]

→ 1000 Phase 3: finalize:   8%|▊         | 18/213 [00:01<00:15, 12.70it/s]

→ 1000 Phase 3: finalize:   9%|▉         | 20/213 [00:01<00:15, 12.68it/s]

→ 1000 Phase 3: finalize:  10%|█         | 22/213 [00:01<00:15, 12.70it/s]

→ 1000 Phase 3: finalize:  11%|█▏        | 24/213 [00:01<00:14, 12.71it/s]

→ 1000 Phase 3: finalize:  12%|█▏        | 26/213 [00:02<00:14, 12.74it/s]

→ 1000 Phase 3: finalize:  13%|█▎        | 28/213 [00:02<00:14, 12.73it/s]

→ 1000 Phase 3: finalize:  14%|█▍        | 30/213 [00:02<00:14, 12.71it/s]

→ 1000 Phase 3: finalize:  15%|█▌        | 32/213 [00:02<00:14, 12.70it/s]

→ 1000 Phase 3: finalize:  16%|█▌        | 34/213 [00:02<00:14, 12.69it/s]

→ 1000 Phase 3: finalize:  17%|█▋        | 36/213 [00:02<00:13, 12.67it/s]

→ 1000 Phase 3: finalize:  18%|█▊        | 38/213 [00:03<00:13, 12.64it/s]

→ 1000 Phase 3: finalize:  19%|█▉        | 40/213 [00:03<00:13, 12.65it/s]

→ 1000 Phase 3: finalize:  20%|█▉        | 42/213 [00:03<00:13, 12.61it/s]

→ 1000 Phase 3: finalize:  21%|██        | 44/213 [00:03<00:13, 12.59it/s]

→ 1000 Phase 3: finalize:  22%|██▏       | 46/213 [00:03<00:13, 12.57it/s]

→ 1000 Phase 3: finalize:  23%|██▎       | 48/213 [00:03<00:13, 12.55it/s]

→ 1000 Phase 3: finalize:  23%|██▎       | 50/213 [00:03<00:13, 12.52it/s]

→ 1000 Phase 3: finalize:  24%|██▍       | 52/213 [00:04<00:12, 12.53it/s]

→ 1000 Phase 3: finalize:  25%|██▌       | 54/213 [00:04<00:12, 12.50it/s]

→ 1000 Phase 3: finalize:  26%|██▋       | 56/213 [00:04<00:12, 12.48it/s]

→ 1000 Phase 3: finalize:  27%|██▋       | 58/213 [00:04<00:12, 12.48it/s]

→ 1000 Phase 3: finalize:  28%|██▊       | 60/213 [00:04<00:12, 12.50it/s]

→ 1000 Phase 3: finalize:  29%|██▉       | 62/213 [00:04<00:12, 12.47it/s]

→ 1000 Phase 3: finalize:  30%|███       | 64/213 [00:05<00:11, 12.49it/s]

→ 1000 Phase 3: finalize:  31%|███       | 66/213 [00:05<00:11, 12.49it/s]

→ 1000 Phase 3: finalize:  32%|███▏      | 68/213 [00:05<00:11, 12.49it/s]

→ 1000 Phase 3: finalize:  33%|███▎      | 70/213 [00:05<00:11, 12.45it/s]

→ 1000 Phase 3: finalize:  34%|███▍      | 72/213 [00:05<00:11, 12.41it/s]

→ 1000 Phase 3: finalize:  35%|███▍      | 74/213 [00:05<00:11, 12.37it/s]

→ 1000 Phase 3: finalize:  36%|███▌      | 76/213 [00:06<00:11, 12.36it/s]

→ 1000 Phase 3: finalize:  37%|███▋      | 78/213 [00:06<00:10, 12.36it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 80/213 [00:06<00:10, 12.32it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 82/213 [00:06<00:10, 12.29it/s]

→ 1000 Phase 3: finalize:  39%|███▉      | 84/213 [00:06<00:10, 12.27it/s]

→ 1000 Phase 3: finalize:  40%|████      | 86/213 [00:06<00:10, 12.26it/s]

→ 1000 Phase 3: finalize:  41%|████▏     | 88/213 [00:07<00:10, 12.25it/s]

→ 1000 Phase 3: finalize:  42%|████▏     | 90/213 [00:07<00:10, 12.25it/s]

→ 1000 Phase 3: finalize:  43%|████▎     | 92/213 [00:07<00:09, 12.28it/s]

→ 1000 Phase 3: finalize:  44%|████▍     | 94/213 [00:07<00:09, 12.29it/s]

→ 1000 Phase 3: finalize:  45%|████▌     | 96/213 [00:07<00:09, 12.34it/s]

→ 1000 Phase 3: finalize:  46%|████▌     | 98/213 [00:07<00:09, 12.37it/s]

→ 1000 Phase 3: finalize:  47%|████▋     | 100/213 [00:08<00:09, 12.40it/s]

→ 1000 Phase 3: finalize:  48%|████▊     | 102/213 [00:08<00:08, 12.43it/s]

→ 1000 Phase 3: finalize:  49%|████▉     | 104/213 [00:08<00:08, 12.45it/s]

→ 1000 Phase 3: finalize:  50%|████▉     | 106/213 [00:08<00:08, 12.47it/s]

→ 1000 Phase 3: finalize:  51%|█████     | 108/213 [00:08<00:08, 12.48it/s]

→ 1000 Phase 3: finalize:  52%|█████▏    | 110/213 [00:08<00:08, 12.55it/s]

→ 1000 Phase 3: finalize:  53%|█████▎    | 112/213 [00:08<00:08, 12.59it/s]

→ 1000 Phase 3: finalize:  54%|█████▎    | 114/213 [00:09<00:07, 12.71it/s]

→ 1000 Phase 3: finalize:  54%|█████▍    | 116/213 [00:09<00:07, 12.70it/s]

→ 1000 Phase 3: finalize:  55%|█████▌    | 118/213 [00:09<00:07, 12.79it/s]

→ 1000 Phase 3: finalize:  56%|█████▋    | 120/213 [00:09<00:07, 12.74it/s]

→ 1000 Phase 3: finalize:  57%|█████▋    | 122/213 [00:09<00:07, 12.71it/s]

→ 1000 Phase 3: finalize:  58%|█████▊    | 124/213 [00:09<00:07, 12.69it/s]

→ 1000 Phase 3: finalize:  59%|█████▉    | 126/213 [00:10<00:06, 12.71it/s]

→ 1000 Phase 3: finalize:  60%|██████    | 128/213 [00:10<00:06, 12.69it/s]

→ 1000 Phase 3: finalize:  61%|██████    | 130/213 [00:10<00:06, 12.68it/s]

→ 1000 Phase 3: finalize:  62%|██████▏   | 132/213 [00:10<00:06, 12.70it/s]

→ 1000 Phase 3: finalize:  63%|██████▎   | 134/213 [00:10<00:06, 12.71it/s]

→ 1000 Phase 3: finalize:  64%|██████▍   | 136/213 [00:10<00:06, 12.78it/s]

→ 1000 Phase 3: finalize:  65%|██████▍   | 138/213 [00:10<00:05, 12.81it/s]

→ 1000 Phase 3: finalize:  66%|██████▌   | 140/213 [00:11<00:05, 12.85it/s]

→ 1000 Phase 3: finalize:  67%|██████▋   | 142/213 [00:11<00:05, 12.88it/s]

→ 1000 Phase 3: finalize:  68%|██████▊   | 144/213 [00:11<00:05, 12.90it/s]

→ 1000 Phase 3: finalize:  69%|██████▊   | 146/213 [00:11<00:05, 12.90it/s]

→ 1000 Phase 3: finalize:  69%|██████▉   | 148/213 [00:11<00:05, 12.92it/s]

→ 1000 Phase 3: finalize:  70%|███████   | 150/213 [00:11<00:04, 12.95it/s]

→ 1000 Phase 3: finalize:  71%|███████▏  | 152/213 [00:12<00:04, 12.94it/s]

→ 1000 Phase 3: finalize:  72%|███████▏  | 154/213 [00:12<00:04, 12.95it/s]

→ 1000 Phase 3: finalize:  73%|███████▎  | 156/213 [00:12<00:04, 12.95it/s]

→ 1000 Phase 3: finalize:  74%|███████▍  | 158/213 [00:12<00:04, 12.94it/s]

→ 1000 Phase 3: finalize:  75%|███████▌  | 160/213 [00:12<00:04, 12.95it/s]

→ 1000 Phase 3: finalize:  76%|███████▌  | 162/213 [00:12<00:03, 12.95it/s]

→ 1000 Phase 3: finalize:  77%|███████▋  | 164/213 [00:13<00:03, 12.93it/s]

→ 1000 Phase 3: finalize:  78%|███████▊  | 166/213 [00:13<00:03, 12.93it/s]

→ 1000 Phase 3: finalize:  79%|███████▉  | 168/213 [00:13<00:03, 12.94it/s]

→ 1000 Phase 3: finalize:  80%|███████▉  | 170/213 [00:13<00:03, 12.93it/s]

→ 1000 Phase 3: finalize:  81%|████████  | 172/213 [00:13<00:03, 12.88it/s]

→ 1000 Phase 3: finalize:  82%|████████▏ | 174/213 [00:13<00:03, 12.87it/s]

→ 1000 Phase 3: finalize:  83%|████████▎ | 176/213 [00:13<00:02, 12.85it/s]

→ 1000 Phase 3: finalize:  84%|████████▎ | 178/213 [00:14<00:02, 12.82it/s]

→ 1000 Phase 3: finalize:  85%|████████▍ | 180/213 [00:14<00:02, 12.79it/s]

→ 1000 Phase 3: finalize:  85%|████████▌ | 182/213 [00:14<00:02, 12.77it/s]

→ 1000 Phase 3: finalize:  86%|████████▋ | 184/213 [00:14<00:02, 12.76it/s]

→ 1000 Phase 3: finalize:  87%|████████▋ | 186/213 [00:14<00:02, 12.69it/s]

→ 1000 Phase 3: finalize:  88%|████████▊ | 188/213 [00:14<00:01, 12.66it/s]

→ 1000 Phase 3: finalize:  89%|████████▉ | 190/213 [00:15<00:01, 12.68it/s]

→ 1000 Phase 3: finalize:  90%|█████████ | 192/213 [00:15<00:01, 12.71it/s]

→ 1000 Phase 3: finalize:  91%|█████████ | 194/213 [00:15<00:01, 12.72it/s]

→ 1000 Phase 3: finalize:  92%|█████████▏| 196/213 [00:15<00:01, 12.75it/s]

→ 1000 Phase 3: finalize:  93%|█████████▎| 198/213 [00:15<00:01, 12.73it/s]

→ 1000 Phase 3: finalize:  94%|█████████▍| 200/213 [00:15<00:01, 12.72it/s]

→ 1000 Phase 3: finalize:  95%|█████████▍| 202/213 [00:15<00:00, 12.71it/s]

→ 1000 Phase 3: finalize:  96%|█████████▌| 204/213 [00:16<00:00, 12.69it/s]

→ 1000 Phase 3: finalize:  97%|█████████▋| 206/213 [00:16<00:00, 12.67it/s]

→ 1000 Phase 3: finalize:  98%|█████████▊| 208/213 [00:16<00:00, 12.69it/s]

→ 1000 Phase 3: finalize:  99%|█████████▊| 210/213 [00:16<00:00, 12.71it/s]

→ 1000 Phase 3: finalize: 100%|█████████▉| 212/213 [00:16<00:00, 12.72it/s]

                                                                           
Processing Rigs:  50%|█████     | 1/2 [03:52<03:52, 232.97s/it][INFO] Filtered 1045 stationary frames, 204 remain


→ 500 (204 images) Phase 1:   0%|          | 0/204 [00:00<?, ?it/s]

→ 500 (204 images) Phase 1:   0%|          | 1/204 [00:02<09:42,  2.87s/it]

→ 500 (204 images) Phase 1:  16%|█▌        | 33/204 [00:05<00:24,  6.98it/s]

→ 500 (204 images) Phase 1:  28%|██▊       | 57/204 [00:05<00:10, 13.88it/s]

→ 500 (204 images) Phase 1:  34%|███▍      | 69/204 [00:08<00:15,  8.89it/s]

→ 500 (204 images) Phase 1:  46%|████▌     | 93/204 [00:08<00:07, 15.26it/s]

→ 500 (204 images) Phase 1:  52%|█████▏    | 107/204 [00:11<00:09, 10.20it/s]

→ 500 (204 images) Phase 1:  62%|██████▏   | 126/204 [00:11<00:05, 14.84it/s]

→ 500 (204 images) Phase 1:  67%|██████▋   | 137/204 [00:13<00:06,  9.64it/s]

→ 500 (204 images) Phase 1:  77%|███████▋  | 158/204 [00:13<00:03, 14.85it/s]

→ 500 (204 images) Phase 1:  82%|████████▏ | 168/204 [00:16<00:03,  9.42it/s]

→ 500 (204 images) Phase 1:  92%|█████████▏| 188/204 [00:16<00:01, 14.46it/s]

→ 500 (204 images) Phase 1:  98%|█████████▊| 199/204 [00:18<00:00, 11.76it/s]

                                                                             

→ 500 Phase 2: corners:   0%|          | 0/204 [00:00<?, ?it/s]

→ 500 Phase 2: corners:   0%|          | 1/204 [00:00<03:01,  1.12it/s]

→ 500 Phase 2: corners:   1%|          | 2/204 [00:01<03:19,  1.01it/s]

→ 500 Phase 2: corners:   1%|▏         | 3/204 [00:02<03:22,  1.01s/it]

→ 500 Phase 2: corners:   2%|▏         | 4/204 [00:04<03:23,  1.02s/it]

→ 500 Phase 2: corners:   2%|▏         | 5/204 [00:04<03:18,  1.00it/s]

→ 500 Phase 2: corners:   3%|▎         | 6/204 [00:05<03:16,  1.01it/s]

→ 500 Phase 2: corners:   3%|▎         | 7/204 [00:06<03:12,  1.02it/s]

→ 500 Phase 2: corners:   4%|▍         | 8/204 [00:07<03:02,  1.08it/s]

→ 500 Phase 2: corners:   4%|▍         | 9/204 [00:08<03:07,  1.04it/s]

→ 500 Phase 2: corners:   5%|▍         | 10/204 [00:09<03:12,  1.01it/s]

→ 500 Phase 2: corners:   5%|▌         | 11/204 [00:10<03:05,  1.04it/s]

→ 500 Phase 2: corners:   6%|▌         | 12/204 [00:11<03:03,  1.05it/s]

→ 500 Phase 2: corners:   6%|▋         | 13/204 [00:12<02:57,  1.08it/s]

→ 500 Phase 2: corners:   7%|▋         | 14/204 [00:13<03:03,  1.04it/s]

→ 500 Phase 2: corners:   7%|▋         | 15/204 [00:14<03:02,  1.03it/s]

→ 500 Phase 2: corners:   8%|▊         | 16/204 [00:15<02:58,  1.05it/s]

→ 500 Phase 2: corners:   8%|▊         | 17/204 [00:16<03:05,  1.01it/s]

→ 500 Phase 2: corners:   9%|▉         | 18/204 [00:17<02:57,  1.05it/s]

→ 500 Phase 2: corners:   9%|▉         | 19/204 [00:18<02:50,  1.09it/s]

→ 500 Phase 2: corners:  10%|▉         | 20/204 [00:19<02:46,  1.11it/s]

→ 500 Phase 2: corners:  10%|█         | 21/204 [00:20<02:46,  1.10it/s]

→ 500 Phase 2: corners:  11%|█         | 22/204 [00:20<02:42,  1.12it/s]

→ 500 Phase 2: corners:  11%|█▏        | 23/204 [00:21<02:38,  1.14it/s]

→ 500 Phase 2: corners:  12%|█▏        | 24/204 [00:22<02:42,  1.11it/s]

→ 500 Phase 2: corners:  12%|█▏        | 25/204 [00:23<02:37,  1.14it/s]

→ 500 Phase 2: corners:  13%|█▎        | 26/204 [00:24<02:42,  1.09it/s]

→ 500 Phase 2: corners:  13%|█▎        | 27/204 [00:25<02:36,  1.13it/s]

→ 500 Phase 2: corners:  14%|█▎        | 28/204 [00:26<02:33,  1.15it/s]

→ 500 Phase 2: corners:  14%|█▍        | 29/204 [00:27<02:45,  1.06it/s]

→ 500 Phase 2: corners:  15%|█▍        | 30/204 [00:27<02:27,  1.18it/s]

→ 500 Phase 2: corners:  15%|█▌        | 31/204 [00:28<02:38,  1.09it/s]

→ 500 Phase 2: corners:  16%|█▌        | 32/204 [00:29<02:40,  1.07it/s]

→ 500 Phase 2: corners:  16%|█▌        | 33/204 [00:30<02:39,  1.07it/s]

→ 500 Phase 2: corners:  17%|█▋        | 34/204 [00:31<02:40,  1.06it/s]

→ 500 Phase 2: corners:  17%|█▋        | 35/204 [00:32<02:45,  1.02it/s]

→ 500 Phase 2: corners:  18%|█▊        | 36/204 [00:33<02:44,  1.02it/s]

→ 500 Phase 2: corners:  18%|█▊        | 37/204 [00:34<02:44,  1.02it/s]

→ 500 Phase 2: corners:  19%|█▊        | 38/204 [00:35<02:47,  1.01s/it]

→ 500 Phase 2: corners:  19%|█▉        | 39/204 [00:37<02:50,  1.03s/it]

→ 500 Phase 2: corners:  20%|█▉        | 40/204 [00:38<02:46,  1.02s/it]

→ 500 Phase 2: corners:  20%|██        | 41/204 [00:39<02:43,  1.00s/it]

→ 500 Phase 2: corners:  21%|██        | 42/204 [00:40<02:44,  1.01s/it]

→ 500 Phase 2: corners:  21%|██        | 43/204 [00:41<02:46,  1.03s/it]

→ 500 Phase 2: corners:  22%|██▏       | 44/204 [00:42<02:42,  1.01s/it]

→ 500 Phase 2: corners:  22%|██▏       | 45/204 [00:43<02:46,  1.05s/it]

→ 500 Phase 2: corners:  23%|██▎       | 46/204 [00:44<02:43,  1.04s/it]

→ 500 Phase 2: corners:  23%|██▎       | 47/204 [00:45<02:45,  1.06s/it]

→ 500 Phase 2: corners:  24%|██▎       | 48/204 [00:46<02:48,  1.08s/it]

→ 500 Phase 2: corners:  24%|██▍       | 49/204 [00:47<02:50,  1.10s/it]

→ 500 Phase 2: corners:  25%|██▍       | 50/204 [00:48<02:44,  1.07s/it]

→ 500 Phase 2: corners:  25%|██▌       | 51/204 [00:49<02:44,  1.07s/it]

→ 500 Phase 2: corners:  25%|██▌       | 52/204 [00:50<02:37,  1.03s/it]

→ 500 Phase 2: corners:  26%|██▌       | 53/204 [00:51<02:34,  1.02s/it]

→ 500 Phase 2: corners:  26%|██▋       | 54/204 [00:52<02:28,  1.01it/s]

→ 500 Phase 2: corners:  27%|██▋       | 55/204 [00:53<02:30,  1.01s/it]

→ 500 Phase 2: corners:  27%|██▋       | 56/204 [00:54<02:34,  1.04s/it]

→ 500 Phase 2: corners:  28%|██▊       | 57/204 [00:55<02:28,  1.01s/it]

→ 500 Phase 2: corners:  28%|██▊       | 58/204 [00:56<02:25,  1.00it/s]

→ 500 Phase 2: corners:  29%|██▉       | 59/204 [00:57<02:26,  1.01s/it]

→ 500 Phase 2: corners:  29%|██▉       | 60/204 [00:58<02:19,  1.03it/s]

→ 500 Phase 2: corners:  30%|██▉       | 61/204 [00:59<02:14,  1.06it/s]

→ 500 Phase 2: corners:  30%|███       | 62/204 [01:00<02:13,  1.06it/s]

→ 500 Phase 2: corners:  31%|███       | 63/204 [01:01<02:10,  1.08it/s]

→ 500 Phase 2: corners:  31%|███▏      | 64/204 [01:02<02:09,  1.08it/s]

→ 500 Phase 2: corners:  32%|███▏      | 65/204 [01:03<02:08,  1.08it/s]

→ 500 Phase 2: corners:  32%|███▏      | 66/204 [01:03<02:06,  1.09it/s]

→ 500 Phase 2: corners:  33%|███▎      | 67/204 [01:04<02:05,  1.09it/s]

→ 500 Phase 2: corners:  33%|███▎      | 68/204 [01:05<02:06,  1.08it/s]

→ 500 Phase 2: corners:  34%|███▍      | 69/204 [01:06<02:06,  1.07it/s]

→ 500 Phase 2: corners:  34%|███▍      | 70/204 [01:07<02:09,  1.03it/s]

→ 500 Phase 2: corners:  35%|███▍      | 71/204 [01:08<02:06,  1.05it/s]

→ 500 Phase 2: corners:  35%|███▌      | 72/204 [01:09<02:05,  1.05it/s]

→ 500 Phase 2: corners:  36%|███▌      | 73/204 [01:10<02:08,  1.02it/s]

→ 500 Phase 2: corners:  36%|███▋      | 74/204 [01:11<02:09,  1.01it/s]

→ 500 Phase 2: corners:  37%|███▋      | 75/204 [01:12<02:05,  1.03it/s]

→ 500 Phase 2: corners:  37%|███▋      | 76/204 [01:13<02:04,  1.03it/s]

→ 500 Phase 2: corners:  38%|███▊      | 77/204 [01:14<02:06,  1.00it/s]

→ 500 Phase 2: corners:  38%|███▊      | 78/204 [01:15<02:05,  1.00it/s]

→ 500 Phase 2: corners:  39%|███▊      | 79/204 [01:16<02:03,  1.01it/s]

→ 500 Phase 2: corners:  39%|███▉      | 80/204 [01:17<02:04,  1.00s/it]

→ 500 Phase 2: corners:  40%|███▉      | 81/204 [01:18<02:02,  1.00it/s]

→ 500 Phase 2: corners:  40%|████      | 82/204 [01:19<02:00,  1.01it/s]

→ 500 Phase 2: corners:  41%|████      | 83/204 [01:20<02:01,  1.01s/it]

→ 500 Phase 2: corners:  41%|████      | 84/204 [01:21<02:01,  1.01s/it]

→ 500 Phase 2: corners:  42%|████▏     | 85/204 [01:22<01:59,  1.00s/it]

→ 500 Phase 2: corners:  42%|████▏     | 86/204 [01:23<01:58,  1.00s/it]

→ 500 Phase 2: corners:  43%|████▎     | 87/204 [01:24<01:59,  1.02s/it]

→ 500 Phase 2: corners:  43%|████▎     | 88/204 [01:25<01:58,  1.03s/it]

→ 500 Phase 2: corners:  44%|████▎     | 89/204 [01:26<01:55,  1.01s/it]

→ 500 Phase 2: corners:  44%|████▍     | 90/204 [01:27<01:57,  1.03s/it]

→ 500 Phase 2: corners:  45%|████▍     | 91/204 [01:28<01:56,  1.03s/it]

→ 500 Phase 2: corners:  45%|████▌     | 92/204 [01:29<01:52,  1.00s/it]

→ 500 Phase 2: corners:  46%|████▌     | 93/204 [01:30<01:53,  1.02s/it]

→ 500 Phase 2: corners:  46%|████▌     | 94/204 [01:31<01:47,  1.02it/s]

→ 500 Phase 2: corners:  47%|████▋     | 95/204 [01:32<01:44,  1.04it/s]

→ 500 Phase 2: corners:  47%|████▋     | 96/204 [01:33<01:43,  1.05it/s]

→ 500 Phase 2: corners:  48%|████▊     | 97/204 [01:34<01:40,  1.07it/s]

→ 500 Phase 2: corners:  48%|████▊     | 98/204 [01:35<01:36,  1.09it/s]

→ 500 Phase 2: corners:  49%|████▊     | 99/204 [01:36<01:33,  1.12it/s]

→ 500 Phase 2: corners:  49%|████▉     | 100/204 [01:37<01:30,  1.14it/s]

→ 500 Phase 2: corners:  50%|████▉     | 101/204 [01:37<01:28,  1.17it/s]

→ 500 Phase 2: corners:  50%|█████     | 102/204 [01:38<01:27,  1.16it/s]

→ 500 Phase 2: corners:  50%|█████     | 103/204 [01:39<01:27,  1.15it/s]

→ 500 Phase 2: corners:  51%|█████     | 104/204 [01:40<01:26,  1.16it/s]

→ 500 Phase 2: corners:  51%|█████▏    | 105/204 [01:41<01:25,  1.16it/s]

→ 500 Phase 2: corners:  52%|█████▏    | 106/204 [01:42<01:24,  1.15it/s]

→ 500 Phase 2: corners:  52%|█████▏    | 107/204 [01:43<01:24,  1.15it/s]

→ 500 Phase 2: corners:  53%|█████▎    | 108/204 [01:44<01:23,  1.15it/s]

→ 500 Phase 2: corners:  53%|█████▎    | 109/204 [01:44<01:24,  1.12it/s]

→ 500 Phase 2: corners:  54%|█████▍    | 110/204 [01:45<01:23,  1.12it/s]

→ 500 Phase 2: corners:  54%|█████▍    | 111/204 [01:46<01:24,  1.10it/s]

→ 500 Phase 2: corners:  55%|█████▍    | 112/204 [01:47<01:23,  1.10it/s]

→ 500 Phase 2: corners:  55%|█████▌    | 113/204 [01:48<01:24,  1.08it/s]

→ 500 Phase 2: corners:  56%|█████▌    | 114/204 [01:49<01:23,  1.08it/s]

→ 500 Phase 2: corners:  56%|█████▋    | 115/204 [01:50<01:24,  1.06it/s]

→ 500 Phase 2: corners:  57%|█████▋    | 116/204 [01:51<01:24,  1.04it/s]

→ 500 Phase 2: corners:  57%|█████▋    | 117/204 [01:52<01:23,  1.04it/s]

→ 500 Phase 2: corners:  58%|█████▊    | 118/204 [01:53<01:22,  1.04it/s]

→ 500 Phase 2: corners:  58%|█████▊    | 119/204 [01:54<01:23,  1.02it/s]

→ 500 Phase 2: corners:  59%|█████▉    | 120/204 [01:55<01:21,  1.03it/s]

→ 500 Phase 2: corners:  59%|█████▉    | 121/204 [01:56<01:21,  1.02it/s]

→ 500 Phase 2: corners:  60%|█████▉    | 122/204 [01:57<01:23,  1.02s/it]

→ 500 Phase 2: corners:  60%|██████    | 123/204 [01:58<01:21,  1.00s/it]

→ 500 Phase 2: corners:  61%|██████    | 124/204 [01:59<01:19,  1.01it/s]

→ 500 Phase 2: corners:  61%|██████▏   | 125/204 [02:00<01:17,  1.02it/s]

→ 500 Phase 2: corners:  62%|██████▏   | 126/204 [02:01<01:15,  1.03it/s]

→ 500 Phase 2: corners:  62%|██████▏   | 127/204 [02:02<01:14,  1.04it/s]

→ 500 Phase 2: corners:  63%|██████▎   | 128/204 [02:03<01:12,  1.05it/s]

→ 500 Phase 2: corners:  63%|██████▎   | 129/204 [02:04<01:10,  1.07it/s]

→ 500 Phase 2: corners:  64%|██████▎   | 130/204 [02:05<01:08,  1.09it/s]

→ 500 Phase 2: corners:  64%|██████▍   | 131/204 [02:05<01:05,  1.12it/s]

→ 500 Phase 2: corners:  65%|██████▍   | 132/204 [02:06<01:04,  1.11it/s]

→ 500 Phase 2: corners:  65%|██████▌   | 133/204 [02:07<01:03,  1.11it/s]

→ 500 Phase 2: corners:  66%|██████▌   | 134/204 [02:08<01:01,  1.14it/s]

→ 500 Phase 2: corners:  66%|██████▌   | 135/204 [02:09<01:01,  1.13it/s]

→ 500 Phase 2: corners:  67%|██████▋   | 136/204 [02:10<00:59,  1.14it/s]

→ 500 Phase 2: corners:  67%|██████▋   | 137/204 [02:11<00:58,  1.14it/s]

→ 500 Phase 2: corners:  68%|██████▊   | 138/204 [02:12<00:57,  1.15it/s]

→ 500 Phase 2: corners:  68%|██████▊   | 139/204 [02:12<00:57,  1.14it/s]

→ 500 Phase 2: corners:  69%|██████▊   | 140/204 [02:13<00:56,  1.12it/s]

→ 500 Phase 2: corners:  69%|██████▉   | 141/204 [02:14<00:57,  1.09it/s]

→ 500 Phase 2: corners:  70%|██████▉   | 142/204 [02:15<00:57,  1.08it/s]

→ 500 Phase 2: corners:  70%|███████   | 143/204 [02:16<00:58,  1.05it/s]

→ 500 Phase 2: corners:  71%|███████   | 144/204 [02:17<00:57,  1.05it/s]

→ 500 Phase 2: corners:  71%|███████   | 145/204 [02:18<00:56,  1.04it/s]

→ 500 Phase 2: corners:  72%|███████▏  | 146/204 [02:19<00:57,  1.02it/s]

→ 500 Phase 2: corners:  72%|███████▏  | 147/204 [02:20<00:57,  1.01s/it]

→ 500 Phase 2: corners:  73%|███████▎  | 148/204 [02:21<00:58,  1.04s/it]

→ 500 Phase 2: corners:  73%|███████▎  | 149/204 [02:23<00:57,  1.05s/it]

→ 500 Phase 2: corners:  74%|███████▎  | 150/204 [02:24<00:57,  1.07s/it]

→ 500 Phase 2: corners:  74%|███████▍  | 151/204 [02:25<00:56,  1.06s/it]

→ 500 Phase 2: corners:  75%|███████▍  | 152/204 [02:26<00:56,  1.09s/it]

→ 500 Phase 2: corners:  75%|███████▌  | 153/204 [02:27<00:54,  1.07s/it]

→ 500 Phase 2: corners:  75%|███████▌  | 154/204 [02:28<00:54,  1.09s/it]

→ 500 Phase 2: corners:  76%|███████▌  | 155/204 [02:29<00:53,  1.10s/it]

→ 500 Phase 2: corners:  76%|███████▋  | 156/204 [02:30<00:52,  1.09s/it]

→ 500 Phase 2: corners:  77%|███████▋  | 157/204 [02:31<00:50,  1.08s/it]

→ 500 Phase 2: corners:  77%|███████▋  | 158/204 [02:32<00:50,  1.10s/it]

→ 500 Phase 2: corners:  78%|███████▊  | 159/204 [02:33<00:49,  1.10s/it]

→ 500 Phase 2: corners:  78%|███████▊  | 160/204 [02:35<00:47,  1.09s/it]

→ 500 Phase 2: corners:  79%|███████▉  | 161/204 [02:36<00:46,  1.08s/it]

→ 500 Phase 2: corners:  79%|███████▉  | 162/204 [02:37<00:44,  1.07s/it]

→ 500 Phase 2: corners:  80%|███████▉  | 163/204 [02:38<00:42,  1.05s/it]

→ 500 Phase 2: corners:  80%|████████  | 164/204 [02:39<00:41,  1.03s/it]

→ 500 Phase 2: corners:  81%|████████  | 165/204 [02:40<00:40,  1.03s/it]

→ 500 Phase 2: corners:  81%|████████▏ | 166/204 [02:41<00:38,  1.01s/it]

→ 500 Phase 2: corners:  82%|████████▏ | 167/204 [02:42<00:36,  1.01it/s]

→ 500 Phase 2: corners:  82%|████████▏ | 168/204 [02:43<00:35,  1.01it/s]

→ 500 Phase 2: corners:  83%|████████▎ | 169/204 [02:44<00:34,  1.01it/s]

→ 500 Phase 2: corners:  83%|████████▎ | 170/204 [02:45<00:33,  1.02it/s]

→ 500 Phase 2: corners:  84%|████████▍ | 171/204 [02:45<00:32,  1.03it/s]

→ 500 Phase 2: corners:  84%|████████▍ | 172/204 [02:46<00:31,  1.02it/s]

→ 500 Phase 2: corners:  85%|████████▍ | 173/204 [02:47<00:30,  1.02it/s]

→ 500 Phase 2: corners:  85%|████████▌ | 174/204 [02:48<00:29,  1.01it/s]

→ 500 Phase 2: corners:  86%|████████▌ | 175/204 [02:49<00:28,  1.02it/s]

→ 500 Phase 2: corners:  86%|████████▋ | 176/204 [02:50<00:27,  1.02it/s]

→ 500 Phase 2: corners:  87%|████████▋ | 177/204 [02:51<00:26,  1.01it/s]

→ 500 Phase 2: corners:  87%|████████▋ | 178/204 [02:52<00:25,  1.00it/s]

→ 500 Phase 2: corners:  88%|████████▊ | 179/204 [02:54<00:25,  1.02s/it]

→ 500 Phase 2: corners:  88%|████████▊ | 180/204 [02:55<00:24,  1.04s/it]

→ 500 Phase 2: corners:  89%|████████▊ | 181/204 [02:56<00:23,  1.04s/it]

→ 500 Phase 2: corners:  89%|████████▉ | 182/204 [02:57<00:22,  1.02s/it]

→ 500 Phase 2: corners:  90%|████████▉ | 183/204 [02:58<00:21,  1.00s/it]

→ 500 Phase 2: corners:  90%|█████████ | 184/204 [02:58<00:19,  1.03it/s]

→ 500 Phase 2: corners:  91%|█████████ | 185/204 [02:59<00:18,  1.02it/s]

→ 500 Phase 2: corners:  91%|█████████ | 186/204 [03:00<00:16,  1.06it/s]

→ 500 Phase 2: corners:  92%|█████████▏| 187/204 [03:01<00:15,  1.09it/s]

→ 500 Phase 2: corners:  92%|█████████▏| 188/204 [03:02<00:14,  1.10it/s]

→ 500 Phase 2: corners:  93%|█████████▎| 189/204 [03:03<00:13,  1.10it/s]

→ 500 Phase 2: corners:  93%|█████████▎| 190/204 [03:04<00:12,  1.12it/s]

→ 500 Phase 2: corners:  94%|█████████▎| 191/204 [03:05<00:11,  1.13it/s]

→ 500 Phase 2: corners:  94%|█████████▍| 192/204 [03:06<00:10,  1.15it/s]

→ 500 Phase 2: corners:  95%|█████████▍| 193/204 [03:06<00:09,  1.15it/s]

→ 500 Phase 2: corners:  95%|█████████▌| 194/204 [03:07<00:08,  1.14it/s]

→ 500 Phase 2: corners:  96%|█████████▌| 195/204 [03:08<00:07,  1.13it/s]

→ 500 Phase 2: corners:  96%|█████████▌| 196/204 [03:09<00:07,  1.13it/s]

→ 500 Phase 2: corners:  97%|█████████▋| 197/204 [03:10<00:06,  1.14it/s]

→ 500 Phase 2: corners:  97%|█████████▋| 198/204 [03:11<00:05,  1.12it/s]

→ 500 Phase 2: corners:  98%|█████████▊| 199/204 [03:12<00:04,  1.11it/s]

→ 500 Phase 2: corners:  98%|█████████▊| 200/204 [03:13<00:03,  1.11it/s]

→ 500 Phase 2: corners:  99%|█████████▊| 201/204 [03:14<00:02,  1.11it/s]

→ 500 Phase 2: corners:  99%|█████████▉| 202/204 [03:15<00:01,  1.08it/s]

→ 500 Phase 2: corners: 100%|█████████▉| 203/204 [03:16<00:00,  1.09it/s]

→ 500 Phase 2: corners: 100%|██████████| 204/204 [03:16<00:00,  1.09it/s]

                                                                         [PASS2] Frame 0000647: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000653: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 2 frames fixed, 1 untrusted, 204 total


→ 500 Phase 3: finalize:   0%|          | 0/204 [00:00<?, ?it/s]

→ 500 Phase 3: finalize:   1%|          | 2/204 [00:00<00:16, 12.27it/s]

→ 500 Phase 3: finalize:   2%|▏         | 4/204 [00:00<00:16, 12.45it/s]

→ 500 Phase 3: finalize:   3%|▎         | 6/204 [00:00<00:15, 12.57it/s]

→ 500 Phase 3: finalize:   4%|▍         | 8/204 [00:00<00:15, 12.60it/s]

→ 500 Phase 3: finalize:   5%|▍         | 10/204 [00:00<00:15, 12.60it/s]

→ 500 Phase 3: finalize:   6%|▌         | 12/204 [00:00<00:15, 12.63it/s]

→ 500 Phase 3: finalize:   7%|▋         | 14/204 [00:01<00:14, 12.67it/s]

→ 500 Phase 3: finalize:   8%|▊         | 16/204 [00:01<00:14, 12.68it/s]

→ 500 Phase 3: finalize:   9%|▉         | 18/204 [00:01<00:14, 12.61it/s]

→ 500 Phase 3: finalize:  10%|▉         | 20/204 [00:01<00:14, 12.67it/s]

→ 500 Phase 3: finalize:  11%|█         | 22/204 [00:01<00:14, 12.69it/s]

→ 500 Phase 3: finalize:  12%|█▏        | 24/204 [00:01<00:14, 12.84it/s]

→ 500 Phase 3: finalize:  13%|█▎        | 26/204 [00:02<00:13, 12.95it/s]

→ 500 Phase 3: finalize:  14%|█▎        | 28/204 [00:02<00:13, 13.06it/s]

→ 500 Phase 3: finalize:  15%|█▍        | 30/204 [00:02<00:12, 14.05it/s]

→ 500 Phase 3: finalize:  16%|█▌        | 32/204 [00:02<00:12, 13.77it/s]

→ 500 Phase 3: finalize:  17%|█▋        | 34/204 [00:02<00:12, 13.54it/s]

→ 500 Phase 3: finalize:  18%|█▊        | 36/204 [00:02<00:12, 13.31it/s]

→ 500 Phase 3: finalize:  19%|█▊        | 38/204 [00:02<00:12, 13.09it/s]

→ 500 Phase 3: finalize:  20%|█▉        | 40/204 [00:03<00:12, 12.95it/s]

→ 500 Phase 3: finalize:  21%|██        | 42/204 [00:03<00:12, 12.91it/s]

→ 500 Phase 3: finalize:  22%|██▏       | 44/204 [00:03<00:12, 12.86it/s]

→ 500 Phase 3: finalize:  23%|██▎       | 46/204 [00:03<00:12, 12.78it/s]

→ 500 Phase 3: finalize:  24%|██▎       | 48/204 [00:03<00:12, 12.68it/s]

→ 500 Phase 3: finalize:  25%|██▍       | 50/204 [00:03<00:12, 12.61it/s]

→ 500 Phase 3: finalize:  25%|██▌       | 52/204 [00:04<00:12, 12.60it/s]

→ 500 Phase 3: finalize:  26%|██▋       | 54/204 [00:04<00:11, 12.59it/s]

→ 500 Phase 3: finalize:  27%|██▋       | 56/204 [00:04<00:11, 12.53it/s]

→ 500 Phase 3: finalize:  28%|██▊       | 58/204 [00:04<00:11, 12.55it/s]

→ 500 Phase 3: finalize:  29%|██▉       | 60/204 [00:04<00:11, 12.56it/s]

→ 500 Phase 3: finalize:  30%|███       | 62/204 [00:04<00:11, 12.56it/s]

→ 500 Phase 3: finalize:  31%|███▏      | 64/204 [00:04<00:11, 12.56it/s]

→ 500 Phase 3: finalize:  32%|███▏      | 66/204 [00:05<00:11, 12.53it/s]

→ 500 Phase 3: finalize:  33%|███▎      | 68/204 [00:05<00:10, 12.52it/s]

→ 500 Phase 3: finalize:  34%|███▍      | 70/204 [00:05<00:10, 12.49it/s]

→ 500 Phase 3: finalize:  35%|███▌      | 72/204 [00:05<00:10, 12.48it/s]

→ 500 Phase 3: finalize:  36%|███▋      | 74/204 [00:05<00:10, 12.90it/s]

→ 500 Phase 3: finalize:  37%|███▋      | 76/204 [00:05<00:10, 12.76it/s]

→ 500 Phase 3: finalize:  38%|███▊      | 78/204 [00:06<00:09, 12.68it/s]

→ 500 Phase 3: finalize:  39%|███▉      | 80/204 [00:06<00:09, 12.62it/s]

→ 500 Phase 3: finalize:  40%|████      | 82/204 [00:06<00:09, 12.57it/s]

→ 500 Phase 3: finalize:  41%|████      | 84/204 [00:06<00:09, 12.54it/s]

→ 500 Phase 3: finalize:  42%|████▏     | 86/204 [00:06<00:09, 12.53it/s]

→ 500 Phase 3: finalize:  43%|████▎     | 88/204 [00:06<00:09, 12.88it/s]

→ 500 Phase 3: finalize:  44%|████▍     | 90/204 [00:07<00:08, 12.81it/s]

→ 500 Phase 3: finalize:  45%|████▌     | 92/204 [00:07<00:08, 13.13it/s]

→ 500 Phase 3: finalize:  46%|████▌     | 94/204 [00:07<00:08, 13.40it/s]

→ 500 Phase 3: finalize:  47%|████▋     | 96/204 [00:07<00:07, 14.04it/s]

→ 500 Phase 3: finalize:  48%|████▊     | 98/204 [00:07<00:07, 13.78it/s]

→ 500 Phase 3: finalize:  49%|████▉     | 100/204 [00:07<00:07, 13.76it/s]

→ 500 Phase 3: finalize:  50%|█████     | 102/204 [00:07<00:07, 13.65it/s]

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→ 500 Phase 3: finalize:  89%|████████▉ | 182/204 [00:13<00:01, 13.25it/s]

→ 500 Phase 3: finalize:  90%|█████████ | 184/204 [00:13<00:01, 13.25it/s]

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→ 500 Phase 3: finalize:  92%|█████████▏| 188/204 [00:14<00:01, 13.25it/s]

→ 500 Phase 3: finalize:  93%|█████████▎| 190/204 [00:14<00:01, 13.26it/s]

→ 500 Phase 3: finalize:  94%|█████████▍| 192/204 [00:14<00:00, 13.27it/s]

→ 500 Phase 3: finalize:  95%|█████████▌| 194/204 [00:14<00:00, 13.19it/s]

→ 500 Phase 3: finalize:  96%|█████████▌| 196/204 [00:14<00:00, 13.19it/s]

→ 500 Phase 3: finalize:  97%|█████████▋| 198/204 [00:14<00:00, 13.18it/s]

→ 500 Phase 3: finalize:  98%|█████████▊| 200/204 [00:15<00:00, 13.19it/s]

→ 500 Phase 3: finalize:  99%|█████████▉| 202/204 [00:15<00:00, 13.18it/s]

→ 500 Phase 3: finalize: 100%|██████████| 204/204 [00:15<00:00, 13.19it/s]

                                                                          
Processing Rigs: 100%|██████████| 2/2 [07:47<00:00, 233.73s/it]
Processing Rigs: 100%|██████████| 2/2 [07:47<00:00, 233.62s/it]
[💾] Saved RigFrameDataset to /working/MDC101_W036_2025-12-31/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 417 frames from 2 rigs to /working/MDC101_W036_2025-12-31/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC101_W036_2025-12-31/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 1000: 100 frames selected from 213
[📋] 500: 100 frames selected from 204
[💾] Saved RigFrameDataset to /working/MDC101_W036_2025-12-31/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC101_W036_2025-12-31/calibration/debug/1_digitized/rig_frames.json

-------------------------------------------------------------------
                        Step 2: Calibration                        
-------------------------------------------------------------------

-> Calculating the casing center ...
[INFO] Using 40 total sampled bright frames

Computing max image from bright frames:   0%|          | 0/40 [00:00<?, ?it/s]
Computing max image from bright frames:   2%|▎         | 1/40 [00:03<02:01,  3.11s/it]
Computing max image from bright frames:   5%|▌         | 2/40 [00:06<01:57,  3.10s/it]
Computing max image from bright frames:   8%|▊         | 3/40 [00:09<01:54,  3.09s/it]
Computing max image from bright frames:  10%|█         | 4/40 [00:12<01:51,  3.08s/it]
Computing max image from bright frames:  12%|█▎        | 5/40 [00:15<01:47,  3.07s/it]
Computing max image from bright frames:  15%|█▌        | 6/40 [00:18<01:43,  3.05s/it]
Computing max image from bright frames:  18%|█▊        | 7/40 [00:21<01:41,  3.07s/it]
Computing max image from bright frames:  20%|██        | 8/40 [00:24<01:38,  3.08s/it]
Computing max image from bright frames:  22%|██▎       | 9/40 [00:27<01:35,  3.08s/it]
Computing max image from bright frames:  25%|██▌       | 10/40 [00:30<01:31,  3.06s/it]
Computing max image from bright frames:  28%|██▊       | 11/40 [00:33<01:27,  3.01s/it]
Computing max image from bright frames:  30%|███       | 12/40 [00:36<01:22,  2.93s/it]
Computing max image from bright frames:  32%|███▎      | 13/40 [00:39<01:17,  2.88s/it]
Computing max image from bright frames:  35%|███▌      | 14/40 [00:41<01:14,  2.87s/it]
Computing max image from bright frames:  38%|███▊      | 15/40 [00:45<01:14,  2.96s/it]
Computing max image from bright frames:  40%|████      | 16/40 [00:48<01:11,  2.99s/it]
Computing max image from bright frames:  42%|████▎     | 17/40 [00:51<01:09,  3.02s/it]
Computing max image from bright frames:  45%|████▌     | 18/40 [00:54<01:06,  3.05s/it]
Computing max image from bright frames:  48%|████▊     | 19/40 [00:57<01:03,  3.04s/it]
Computing max image from bright frames:  50%|█████     | 20/40 [00:59<00:56,  2.83s/it]
Computing max image from bright frames:  52%|█████▎    | 21/40 [01:02<00:54,  2.88s/it]
Computing max image from bright frames:  55%|█████▌    | 22/40 [01:05<00:52,  2.94s/it]
Computing max image from bright frames:  57%|█████▊    | 23/40 [01:08<00:50,  2.98s/it]
Computing max image from bright frames:  60%|██████    | 24/40 [01:11<00:48,  3.00s/it]
Computing max image from bright frames:  62%|██████▎   | 25/40 [01:15<00:45,  3.03s/it]
Computing max image from bright frames:  65%|██████▌   | 26/40 [01:18<00:42,  3.05s/it]
Computing max image from bright frames:  68%|██████▊   | 27/40 [01:21<00:39,  3.07s/it]
Computing max image from bright frames:  70%|███████   | 28/40 [01:24<00:36,  3.08s/it]
Computing max image from bright frames:  72%|███████▎  | 29/40 [01:27<00:33,  3.05s/it]
Computing max image from bright frames:  75%|███████▌  | 30/40 [01:30<00:30,  3.04s/it]
Computing max image from bright frames:  78%|███████▊  | 31/40 [01:33<00:26,  2.99s/it]
Computing max image from bright frames:  80%|████████  | 32/40 [01:36<00:23,  2.94s/it]
Computing max image from bright frames:  82%|████████▎ | 33/40 [01:38<00:20,  2.92s/it]
Computing max image from bright frames:  85%|████████▌ | 34/40 [01:41<00:17,  2.89s/it]
Computing max image from bright frames:  88%|████████▊ | 35/40 [01:44<00:14,  2.92s/it]
Computing max image from bright frames:  90%|█████████ | 36/40 [01:47<00:11,  2.95s/it]
Computing max image from bright frames:  92%|█████████▎| 37/40 [01:50<00:08,  2.98s/it]
Computing max image from bright frames:  95%|█████████▌| 38/40 [01:53<00:06,  3.01s/it]
Computing max image from bright frames:  98%|█████████▊| 39/40 [01:56<00:03,  3.02s/it]
Computing max image from bright frames: 100%|██████████| 40/40 [01:59<00:00,  3.01s/it]
                                                                                       

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Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   1%|          | 1/100 [00:00<00:12,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   1%|          | 1/100 [00:00<00:12,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   2%|▏         | 2/100 [00:00<00:12,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   3%|▎         | 3/100 [00:00<00:12,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   4%|▍         | 4/100 [00:00<00:12,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   5%|▌         | 5/100 [00:00<00:12,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   6%|▌         | 6/100 [00:00<00:12,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   7%|▋         | 7/100 [00:00<00:11,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   8%|▊         | 8/100 [00:00<00:11,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   9%|▉         | 9/100 [00:00<00:11,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  10%|█         | 10/100 [00:00<00:11,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  11%|█         | 11/100 [00:00<00:11,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  12%|█▏        | 12/100 [00:00<00:11,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  13%|█▎        | 13/100 [00:00<00:11,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  14%|█▍        | 14/100 [00:00<00:11,  7.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  15%|█▌        | 15/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  15%|█▌        | 15/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  16%|█▌        | 16/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  17%|█▋        | 17/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  18%|█▊        | 18/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  19%|█▉        | 19/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  20%|██        | 20/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  21%|██        | 21/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  22%|██▏       | 22/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 483.838} (0.000):  23%|██▎       | 23/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 483.838} (0.000):  24%|██▍       | 24/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 483.838} (0.000):  25%|██▌       | 25/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.003 | Best: {'fx': 497.98} (0.003):  26%|██▌       | 26/100 [00:00<00:01, 70.72it/s] 
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 497.98} (0.003):  27%|██▋       | 27/100 [00:00<00:01, 70.72it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 497.98} (0.003):  28%|██▊       | 28/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.001 | Best: {'fx': 497.98} (0.003):  28%|██▊       | 28/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.018 | Best: {'fx': 519.192} (0.018):  29%|██▉       | 29/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.030 | Best: {'fx': 547.475} (0.030):  30%|███       | 30/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.038 | Best: {'fx': 540.404} (0.038):  31%|███       | 31/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.005 | Best: {'fx': 540.404} (0.038):  32%|███▏      | 32/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.025 | Best: {'fx': 540.404} (0.038):  33%|███▎      | 33/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.043 | Best: {'fx': 526.263} (0.043):  34%|███▍      | 34/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 526.263} (0.043):  35%|███▌      | 35/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.069 | Best: {'fx': 533.333} (0.069):  36%|███▌      | 36/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.022 | Best: {'fx': 533.333} (0.069):  37%|███▋      | 37/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.020 | Best: {'fx': 533.333} (0.069):  38%|███▊      | 38/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.018 | Best: {'fx': 533.333} (0.069):  39%|███▉      | 39/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.014 | Best: {'fx': 533.333} (0.069):  40%|████      | 40/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.016 | Best: {'fx': 533.333} (0.069):  41%|████      | 41/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.016 | Best: {'fx': 533.333} (0.069):  42%|████▏     | 42/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.015 | Best: {'fx': 533.333} (0.069):  43%|████▎     | 43/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.013 | Best: {'fx': 533.333} (0.069):  44%|████▍     | 44/100 [00:00<00:00, 89.77it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.013 | Best: {'fx': 533.333} (0.069):  45%|████▌     | 45/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.011 | Best: {'fx': 533.333} (0.069):  45%|████▌     | 45/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.013 | Best: {'fx': 533.333} (0.069):  46%|████▌     | 46/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.011 | Best: {'fx': 533.333} (0.069):  47%|████▋     | 47/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.012 | Best: {'fx': 533.333} (0.069):  48%|████▊     | 48/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.012 | Best: {'fx': 533.333} (0.069):  49%|████▉     | 49/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.012 | Best: {'fx': 533.333} (0.069):  50%|█████     | 50/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  51%|█████     | 51/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.011 | Best: {'fx': 533.333} (0.069):  52%|█████▏    | 52/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  53%|█████▎    | 53/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.011 | Best: {'fx': 533.333} (0.069):  54%|█████▍    | 54/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  55%|█████▌    | 55/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.011 | Best: {'fx': 533.333} (0.069):  56%|█████▌    | 56/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  57%|█████▋    | 57/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  58%|█████▊    | 58/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  59%|█████▉    | 59/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  60%|██████    | 60/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  61%|██████    | 61/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  62%|██████▏   | 62/100 [00:00<00:00, 114.24it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  63%|██████▎   | 63/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  63%|██████▎   | 63/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  64%|██████▍   | 64/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  65%|██████▌   | 65/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  66%|██████▌   | 66/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.069):  67%|██████▋   | 67/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  68%|██████▊   | 68/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  69%|██████▉   | 69/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  70%|███████   | 70/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  71%|███████   | 71/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  72%|███████▏  | 72/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  73%|███████▎  | 73/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  74%|███████▍  | 74/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  75%|███████▌  | 75/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  76%|███████▌  | 76/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  77%|███████▋  | 77/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  78%|███████▊  | 78/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  79%|███████▉  | 79/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  80%|████████  | 80/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  81%|████████  | 81/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  82%|████████▏ | 82/100 [00:00<00:00, 131.04it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  83%|████████▎ | 83/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  83%|████████▎ | 83/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  84%|████████▍ | 84/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  85%|████████▌ | 85/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  86%|████████▌ | 86/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  87%|████████▋ | 87/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  88%|████████▊ | 88/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  89%|████████▉ | 89/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  90%|█████████ | 90/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  91%|█████████ | 91/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  92%|█████████▏| 92/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  93%|█████████▎| 93/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  94%|█████████▍| 94/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  95%|█████████▌| 95/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  96%|█████████▌| 96/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  97%|█████████▋| 97/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  98%|█████████▊| 98/100 [00:00<00:00, 136.10it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.069):  99%|█████████▉| 99/100 [00:00<00:00, 136.10it/s]
                                                                                                                                        

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.008 | Best: {'fx': 509.354} (0.008):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.008 | Best: {'fx': 509.354} (0.008):   2%|▏         | 1/50 [00:00<00:05,  9.50it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.007 | Best: {'fx': 509.354} (0.008):   2%|▏         | 1/50 [00:00<00:05,  9.50it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.009 | Best: {'fx': 510.374} (0.009):   4%|▍         | 2/50 [00:00<00:05,  9.50it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.010 | Best: {'fx': 511.395} (0.010):   6%|▌         | 3/50 [00:00<00:04,  9.50it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.010 | Best: {'fx': 513.435} (0.010):   8%|▊         | 4/50 [00:00<00:04,  9.50it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.010 | Best: {'fx': 513.435} (0.010):  10%|█         | 5/50 [00:00<00:04,  9.50it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.011 | Best: {'fx': 514.456} (0.011):  12%|█▏        | 6/50 [00:00<00:04,  9.50it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.015 | Best: {'fx': 517.517} (0.015):  14%|█▍        | 7/50 [00:00<00:04,  9.50it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.011 | Best: {'fx': 517.517} (0.015):  16%|█▌        | 8/50 [00:00<00:04,  9.50it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.013 | Best: {'fx': 517.517} (0.015):  18%|█▊        | 9/50 [00:00<00:04,  9.50it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.021 | Best: {'fx': 520.578} (0.021):  20%|██        | 10/50 [00:00<00:04,  9.50it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.021 | Best: {'fx': 520.578} (0.021):  22%|██▏       | 11/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.016 | Best: {'fx': 520.578} (0.021):  22%|██▏       | 11/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.020 | Best: {'fx': 520.578} (0.021):  24%|██▍       | 12/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.031 | Best: {'fx': 523.639} (0.031):  26%|██▌       | 13/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.026 | Best: {'fx': 523.639} (0.031):  28%|██▊       | 14/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.028 | Best: {'fx': 523.639} (0.031):  30%|███       | 15/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.034 | Best: {'fx': 524.66} (0.034):  32%|███▏      | 16/50 [00:00<00:00, 60.27it/s] 
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.038 | Best: {'fx': 525.68} (0.038):  34%|███▍      | 17/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.041 | Best: {'fx': 527.721} (0.041):  36%|███▌      | 18/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.053 | Best: {'fx': 528.741} (0.053):  38%|███▊      | 19/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.042 | Best: {'fx': 528.741} (0.053):  40%|████      | 20/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.067 | Best: {'fx': 531.803} (0.067):  42%|████▏     | 21/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.057 | Best: {'fx': 531.803} (0.067):  44%|████▍     | 22/50 [00:00<00:00, 60.27it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.057 | Best: {'fx': 531.803} (0.067):  46%|████▌     | 23/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.072 | Best: {'fx': 533.844} (0.072):  46%|████▌     | 23/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.063 | Best: {'fx': 533.844} (0.072):  48%|████▊     | 24/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.070 | Best: {'fx': 533.844} (0.072):  50%|█████     | 25/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.051 | Best: {'fx': 533.844} (0.072):  52%|█████▏    | 26/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.052 | Best: {'fx': 533.844} (0.072):  54%|█████▍    | 27/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.061 | Best: {'fx': 533.844} (0.072):  56%|█████▌    | 28/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.047 | Best: {'fx': 533.844} (0.072):  58%|█████▊    | 29/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.035 | Best: {'fx': 533.844} (0.072):  60%|██████    | 30/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.039 | Best: {'fx': 533.844} (0.072):  62%|██████▏   | 31/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.033 | Best: {'fx': 533.844} (0.072):  64%|██████▍   | 32/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.043 | Best: {'fx': 533.844} (0.072):  66%|██████▌   | 33/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.030 | Best: {'fx': 533.844} (0.072):  68%|██████▊   | 34/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.037 | Best: {'fx': 533.844} (0.072):  70%|███████   | 35/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.035 | Best: {'fx': 533.844} (0.072):  72%|███████▏  | 36/50 [00:00<00:00, 86.34it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.035 | Best: {'fx': 533.844} (0.072):  74%|███████▍  | 37/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.032 | Best: {'fx': 533.844} (0.072):  74%|███████▍  | 37/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.026 | Best: {'fx': 533.844} (0.072):  76%|███████▌  | 38/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.027 | Best: {'fx': 533.844} (0.072):  78%|███████▊  | 39/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.030 | Best: {'fx': 533.844} (0.072):  80%|████████  | 40/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.029 | Best: {'fx': 533.844} (0.072):  82%|████████▏ | 41/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.030 | Best: {'fx': 533.844} (0.072):  84%|████████▍ | 42/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.028 | Best: {'fx': 533.844} (0.072):  86%|████████▌ | 43/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.026 | Best: {'fx': 533.844} (0.072):  88%|████████▊ | 44/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.024 | Best: {'fx': 533.844} (0.072):  90%|█████████ | 45/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.026 | Best: {'fx': 533.844} (0.072):  92%|█████████▏| 46/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.024 | Best: {'fx': 533.844} (0.072):  94%|█████████▍| 47/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.024 | Best: {'fx': 533.844} (0.072):  96%|█████████▌| 48/50 [00:00<00:00, 107.04it/s]
Brute | Start: {'fx': 533.333} (0.069) | Current: 0.023 | Best: {'fx': 533.844} (0.072):  98%|█████████▊| 49/50 [00:00<00:00, 107.04it/s]
                                                                                                                                         
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 533.843537414966
    px: 993.0
    py: 767.0
    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

  [Ring preference] diameter=3500 mm  →  radius=1373.8 px

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

Initial score: 325.3011: 0iter [00:00, ?iter/s]  [Ring mask] 25,748/25,748 points within ring radius 1373.8 px
[DEBUG] objective(x0) = 325.3011, picklable_objective(x0) = 325.4546

Best score: 325.4546: : 0iter [00:01, ?iter/s] 
Best score: 325.4546: : 1iter [00:01,  1.89s/iter]
Best score: 325.4546: : 1iter [00:01,  1.89s/iter]
Best score: 325.4546: : 2iter [00:01,  1.89s/iter]
Best score: 325.4546: : 3iter [00:02,  1.89s/iter]
Best score: 325.4546: : 4iter [00:02,  2.54iter/s]
Best score: 325.4546: : 4iter [00:02,  2.54iter/s]
Best score: 325.4546: : 5iter [00:02,  2.54iter/s]
Best score: 325.4546: : 6iter [00:02,  2.54iter/s]
Best score: 325.4546: : 7iter [00:02,  4.83iter/s]
Best score: 325.4546: : 7iter [00:02,  4.83iter/s]
Best score: 325.4546: : 8iter [00:02,  4.83iter/s]
Best score: 223.2920: : 9iter [00:02,  4.83iter/s]
Best score: 223.2920: : 10iter [00:02,  7.30iter/s]
Best score: 223.2920: : 10iter [00:02,  7.30iter/s]
Best score: 223.2920: : 11iter [00:02,  7.30iter/s]
Best score: 223.2920: : 12iter [00:02,  7.30iter/s]
Best score: 223.2920: : 13iter [00:02,  9.86iter/s]
Best score: 223.2920: : 13iter [00:02,  9.86iter/s]
Best score: 223.2920: : 14iter [00:02,  9.86iter/s]
Best score: 223.2920: : 15iter [00:02,  9.86iter/s]
Best score: 223.2920: : 16iter [00:02, 12.30iter/s]
Best score: 223.2920: : 16iter [00:02, 12.30iter/s]
Best score: 223.2920: : 17iter [00:02, 12.30iter/s]
Best score: 223.2920: : 18iter [00:02, 12.30iter/s]
Best score: 223.2920: : 19iter [00:02, 14.53iter/s]
Best score: 184.2134: : 19iter [00:02, 14.53iter/s]
Best score: 184.2134: : 20iter [00:02, 14.53iter/s]
Best score: 184.2134: : 21iter [00:02, 14.53iter/s]
Best score: 184.2134: : 22iter [00:02, 16.30iter/s]
Best score: 184.2134: : 22iter [00:02, 16.30iter/s]
Best score: 184.2134: : 23iter [00:02, 16.30iter/s]
Best score: 184.2134: : 24iter [00:02, 16.30iter/s]
Best score: 184.2134: : 25iter [00:02, 17.83iter/s]
Best score: 184.2134: : 25iter [00:03, 17.83iter/s]
Best score: 184.2134: : 26iter [00:03, 17.83iter/s]
Best score: 184.2134: : 27iter [00:03, 17.83iter/s]
Best score: 184.2134: : 28iter [00:03, 19.05iter/s]
Best score: 184.2134: : 28iter [00:03, 19.05iter/s]
Best score: 184.2134: : 29iter [00:03, 19.05iter/s]
Best score: 184.2134: : 30iter [00:03, 19.05iter/s]
Best score: 184.2134: : 31iter [00:03, 19.74iter/s]
Best score: 184.2134: : 31iter [00:03, 19.74iter/s]
Best score: 184.2134: : 32iter [00:03, 19.74iter/s]
Best score: 184.2134: : 33iter [00:03, 19.74iter/s]
Best score: 184.2134: : 34iter [00:03, 20.56iter/s]
Best score: 184.2134: : 34iter [00:03, 20.56iter/s]
Best score: 184.2134: : 35iter [00:03, 20.56iter/s]
Best score: 184.2134: : 36iter [00:03, 20.56iter/s]
Best score: 184.2134: : 37iter [00:03, 21.01iter/s]
Best score: 184.2134: : 37iter [00:03, 21.01iter/s]
Best score: 184.2134: : 38iter [00:03, 21.01iter/s]
Best score: 50.9207: : 39iter [00:03, 21.01iter/s] 
Best score: 50.9207: : 40iter [00:03, 21.25iter/s]
Best score: 50.9207: : 40iter [00:03, 21.25iter/s]
Best score: 50.9207: : 41iter [00:03, 21.25iter/s]
Best score: 50.9207: : 42iter [00:03, 21.25iter/s]
Best score: 50.9207: : 43iter [00:03, 21.59iter/s]
Best score: 50.9207: : 43iter [00:03, 21.59iter/s]
Best score: 50.9207: : 44iter [00:03, 21.59iter/s]
Best score: 50.9207: : 45iter [00:03, 21.59iter/s]
Best score: 50.9207: : 46iter [00:03, 21.89iter/s]
Best score: 50.9207: : 46iter [00:03, 21.89iter/s]
Best score: 50.9207: : 47iter [00:04, 21.89iter/s]
Best score: 50.9207: : 48iter [00:04, 21.89iter/s]
Best score: 50.9207: : 49iter [00:04, 22.11iter/s]
[ITER 50] Best: 50.9207
[PARAMS] Current best parameters:
  fx: 540.0429
  fy: 534.0863
  px: 971.2486
  py: 774.1984
  k1: -0.06941958
  k2: 0.03474113
  k3: 0.02710290
  k4: -0.01488125
  p1: 0.00018551
  p2: -0.00418885
  p3: -0.00315502
  p4: -0.00614214
  scale: 3.0331
  rotation: -0.0156

Best score: 50.9207: : 49iter [00:04, 22.11iter/s]
Best score: 50.9207: : 50iter [00:04, 22.11iter/s]
Best score: 50.9207: : 51iter [00:04, 22.11iter/s]
Best score: 50.9207: : 52iter [00:04, 22.10iter/s]
Best score: 50.9207: : 52iter [00:04, 22.10iter/s]
Best score: 50.9207: : 53iter [00:04, 22.10iter/s]
Best score: 50.9207: : 54iter [00:04, 22.10iter/s]
Best score: 50.9207: : 55iter [00:04, 22.29iter/s]
Best score: 50.9207: : 55iter [00:04, 22.29iter/s]
Best score: 50.9207: : 56iter [00:04, 22.29iter/s]
Best score: 50.9207: : 57iter [00:04, 22.29iter/s]
Best score: 50.9207: : 58iter [00:04, 22.40iter/s]
Best score: 50.9207: : 58iter [00:04, 22.40iter/s]
Best score: 41.6288: : 59iter [00:04, 22.40iter/s]
Best score: 41.6288: : 60iter [00:04, 22.40iter/s]
Best score: 41.6288: : 61iter [00:04, 22.22iter/s]
Best score: 41.6288: : 61iter [00:04, 22.22iter/s]
Best score: 41.6288: : 62iter [00:04, 22.22iter/s]
Best score: 41.6288: : 63iter [00:04, 22.22iter/s]
Best score: 41.6288: : 64iter [00:04, 22.38iter/s]
Best score: 41.6288: : 64iter [00:04, 22.38iter/s]
Best score: 41.6288: : 65iter [00:04, 22.38iter/s]
Best score: 41.6288: : 66iter [00:04, 22.38iter/s]
Best score: 41.6288: : 67iter [00:04, 22.51iter/s]
Best score: 41.6288: : 67iter [00:04, 22.51iter/s]
Best score: 41.6288: : 68iter [00:04, 22.51iter/s]
Best score: 11.9090: : 69iter [00:04, 22.51iter/s]
Best score: 11.9090: : 70iter [00:04, 22.35iter/s]
Best score: 11.9090: : 70iter [00:05, 22.35iter/s]
Best score: 11.9090: : 71iter [00:05, 22.35iter/s]
Best score: 11.9090: : 72iter [00:05, 22.35iter/s]
Best score: 11.9090: : 73iter [00:05, 22.47iter/s]
Best score: 11.9090: : 73iter [00:05, 22.47iter/s]
Best score: 11.9090: : 74iter [00:05, 22.47iter/s]
Best score: 11.9090: : 75iter [00:05, 22.47iter/s]
Best score: 11.9090: : 76iter [00:05, 22.65iter/s]
Best score: 11.9090: : 76iter [00:05, 22.65iter/s]
Best score: 11.9090: : 77iter [00:05, 22.65iter/s]
Best score: 11.9090: : 78iter [00:05, 22.65iter/s]
Best score: 11.9090: : 79iter [00:05, 22.65iter/s]
Best score: 8.7711: : 79iter [00:05, 22.65iter/s] 
Best score: 8.7711: : 80iter [00:05, 22.65iter/s]
Best score: 8.7711: : 81iter [00:05, 22.65iter/s]
Best score: 8.7711: : 82iter [00:05, 22.37iter/s]
Best score: 8.7711: : 82iter [00:05, 22.37iter/s]
Best score: 8.7711: : 83iter [00:05, 22.37iter/s]
Best score: 8.7711: : 84iter [00:05, 22.37iter/s]
Best score: 8.7711: : 85iter [00:05, 22.50iter/s]
Best score: 8.7711: : 85iter [00:05, 22.50iter/s]
Best score: 8.7711: : 86iter [00:05, 22.50iter/s]
Best score: 8.7711: : 87iter [00:05, 22.50iter/s]
Best score: 8.7711: : 88iter [00:05, 22.61iter/s]
Best score: 8.7711: : 88iter [00:05, 22.61iter/s]
Best score: 8.0253: : 89iter [00:05, 22.61iter/s]
Best score: 8.0253: : 90iter [00:05, 22.61iter/s]
Best score: 8.0253: : 91iter [00:05, 22.49iter/s]
Best score: 8.0253: : 91iter [00:05, 22.49iter/s]
Best score: 8.0253: : 92iter [00:06, 22.49iter/s]
Best score: 8.0253: : 93iter [00:06, 22.49iter/s]
Best score: 8.0253: : 94iter [00:06, 22.58iter/s]
Best score: 8.0253: : 94iter [00:06, 22.58iter/s]
Best score: 8.0253: : 95iter [00:06, 22.58iter/s]
Best score: 8.0253: : 96iter [00:06, 22.58iter/s]
Best score: 8.0253: : 97iter [00:06, 22.65iter/s]
Best score: 8.0253: : 97iter [00:06, 22.65iter/s]
Best score: 8.0253: : 98iter [00:06, 22.65iter/s]
[ITER 100] Best: 7.9290
[PARAMS] Current best parameters:
  fx: 532.0384
  fy: 529.6881
  px: 977.7166
  py: 775.9865
  k1: -0.03015281
  k2: -0.00259378
  k3: 0.03055199
  k4: -0.01181598
  p1: -0.00320056
  p2: -0.00267903
  p3: -0.00221526
  p4: 0.00117029
  scale: 3.0751
  rotation: -0.2664

Best score: 7.9290: : 99iter [00:06, 22.65iter/s]
Best score: 7.9290: : 100iter [00:06, 22.48iter/s]
Best score: 7.9290: : 100iter [00:06, 22.48iter/s]
Best score: 7.9290: : 101iter [00:06, 22.48iter/s]
Best score: 7.9290: : 102iter [00:06, 22.48iter/s]
Best score: 7.9290: : 103iter [00:06, 22.62iter/s]
Best score: 7.9290: : 103iter [00:06, 22.62iter/s]
Best score: 7.9290: : 104iter [00:06, 22.62iter/s]
Best score: 7.9290: : 105iter [00:06, 22.62iter/s]
Best score: 7.9290: : 106iter [00:06, 22.62iter/s]
Best score: 7.9290: : 106iter [00:06, 22.62iter/s]
Best score: 7.9290: : 107iter [00:06, 22.62iter/s]
Best score: 7.9290: : 108iter [00:06, 22.62iter/s]
Best score: 7.9290: : 109iter [00:06, 22.62iter/s]
Best score: 5.0843: : 109iter [00:06, 22.62iter/s]
Best score: 5.0843: : 110iter [00:06, 22.62iter/s]
Best score: 5.0843: : 111iter [00:06, 22.62iter/s]
Best score: 5.0843: : 112iter [00:06, 22.41iter/s]
Best score: 5.0843: : 112iter [00:06, 22.41iter/s]
Best score: 5.0843: : 113iter [00:06, 22.41iter/s]
Best score: 5.0843: : 114iter [00:06, 22.41iter/s]
Best score: 5.0843: : 115iter [00:06, 22.51iter/s]
Best score: 5.0843: : 115iter [00:07, 22.51iter/s]
Best score: 5.0843: : 116iter [00:07, 22.51iter/s]
Best score: 5.0843: : 117iter [00:07, 22.51iter/s]
Best score: 5.0843: : 118iter [00:07, 22.54iter/s]
Best score: 5.0843: : 118iter [00:07, 22.54iter/s]
Best score: 5.0843: : 119iter [00:07, 22.54iter/s]
Best score: 5.0843: : 120iter [00:07, 22.54iter/s]
Best score: 5.0843: : 121iter [00:07, 22.37iter/s]
Best score: 5.0843: : 121iter [00:07, 22.37iter/s]
Best score: 5.0843: : 122iter [00:07, 22.37iter/s]
Best score: 5.0843: : 123iter [00:07, 22.37iter/s]
Best score: 5.0843: : 124iter [00:07, 22.47iter/s]
Best score: 5.0843: : 124iter [00:07, 22.47iter/s]
Best score: 5.0843: : 125iter [00:07, 22.47iter/s]
Best score: 5.0843: : 126iter [00:07, 22.47iter/s]
Best score: 5.0843: : 127iter [00:07, 22.54iter/s]
Best score: 5.0843: : 127iter [00:07, 22.54iter/s]
Best score: 5.0843: : 128iter [00:07, 22.54iter/s]
Best score: 4.4977: : 129iter [00:07, 22.54iter/s]
Best score: 4.4977: : 130iter [00:07, 22.46iter/s]
Best score: 4.4977: : 130iter [00:07, 22.46iter/s]
Best score: 4.4977: : 131iter [00:07, 22.46iter/s]
Best score: 4.4977: : 132iter [00:07, 22.46iter/s]
Best score: 4.4977: : 133iter [00:07, 22.54iter/s]
Best score: 4.4977: : 133iter [00:07, 22.54iter/s]
Best score: 4.4977: : 134iter [00:07, 22.54iter/s]
Best score: 4.4977: : 135iter [00:07, 22.54iter/s]
Best score: 4.4977: : 136iter [00:07, 22.64iter/s]
Best score: 4.4977: : 136iter [00:07, 22.64iter/s]
Best score: 4.4977: : 137iter [00:07, 22.64iter/s]
Best score: 4.4977: : 138iter [00:08, 22.64iter/s]
Best score: 4.4977: : 139iter [00:08, 22.68iter/s]
Best score: 3.1703: : 139iter [00:08, 22.68iter/s]
Best score: 3.1703: : 140iter [00:08, 22.68iter/s]
Best score: 3.1703: : 141iter [00:08, 22.68iter/s]
Best score: 3.1703: : 142iter [00:08, 22.53iter/s]
Best score: 3.1703: : 142iter [00:08, 22.53iter/s]
Best score: 3.1703: : 143iter [00:08, 22.53iter/s]
Best score: 3.1703: : 144iter [00:08, 22.53iter/s]
Best score: 3.1703: : 145iter [00:08, 22.53iter/s]
Best score: 3.1703: : 145iter [00:08, 22.53iter/s]
Best score: 3.1703: : 146iter [00:08, 22.53iter/s]
Best score: 3.1703: : 147iter [00:08, 22.53iter/s]
Best score: 3.1703: : 148iter [00:08, 22.62iter/s]
Best score: 3.1703: : 148iter [00:08, 22.62iter/s]
[ITER 150] Best: 3.1576
[PARAMS] Current best parameters:
  fx: 507.0394
  fy: 506.1031
  px: 975.6344
  py: 781.7092
  k1: 0.01018048
  k2: -0.01816403
  k3: 0.02989301
  k4: -0.00974648
  p1: 0.00954682
  p2: -0.00638873
  p3: -0.00521502
  p4: 0.00110190
  scale: 3.0791
  rotation: -0.1583

Best score: 3.1576: : 149iter [00:08, 22.62iter/s]
Best score: 3.1576: : 150iter [00:08, 22.62iter/s]
Best score: 3.1576: : 151iter [00:08, 22.44iter/s]
Best score: 3.1576: : 151iter [00:08, 22.44iter/s]
Best score: 3.1576: : 152iter [00:08, 22.44iter/s]
Best score: 3.1576: : 153iter [00:08, 22.44iter/s]
Best score: 3.1576: : 154iter [00:08, 22.49iter/s]
Best score: 3.1576: : 154iter [00:08, 22.49iter/s]
Best score: 3.1576: : 155iter [00:08, 22.49iter/s]
Best score: 3.1576: : 156iter [00:08, 22.49iter/s]
Best score: 3.1576: : 157iter [00:08, 22.52iter/s]
Best score: 3.1576: : 157iter [00:08, 22.52iter/s]
Best score: 3.1576: : 158iter [00:08, 22.52iter/s]
Best score: 2.8144: : 159iter [00:08, 22.52iter/s]
Best score: 2.8144: : 160iter [00:08, 22.33iter/s]
Best score: 2.8144: : 160iter [00:09, 22.33iter/s]
Best score: 2.8144: : 161iter [00:09, 22.33iter/s]
Best score: 2.8144: : 162iter [00:09, 22.33iter/s]
Best score: 2.8144: : 163iter [00:09, 22.45iter/s]
Best score: 2.8144: : 163iter [00:09, 22.45iter/s]
Best score: 2.8144: : 164iter [00:09, 22.45iter/s]
Best score: 2.8144: : 165iter [00:09, 22.45iter/s]
Best score: 2.8144: : 166iter [00:09, 22.57iter/s]
Best score: 2.8144: : 166iter [00:09, 22.57iter/s]
Best score: 2.8144: : 167iter [00:09, 22.57iter/s]
Best score: 2.8144: : 168iter [00:09, 22.57iter/s]
Best score: 2.8144: : 169iter [00:09, 22.64iter/s]
Best score: 2.2096: : 169iter [00:09, 22.64iter/s]
Best score: 2.2096: : 170iter [00:09, 22.64iter/s]
Best score: 2.2096: : 171iter [00:09, 22.64iter/s]
Best score: 2.2096: : 172iter [00:09, 22.43iter/s]
Best score: 2.2096: : 172iter [00:09, 22.43iter/s]
Best score: 2.2096: : 173iter [00:09, 22.43iter/s]
Best score: 2.2096: : 174iter [00:09, 22.43iter/s]
Best score: 2.2096: : 175iter [00:09, 22.52iter/s]
Best score: 2.2096: : 175iter [00:09, 22.52iter/s]
Best score: 2.2096: : 176iter [00:09, 22.52iter/s]
Best score: 2.2096: : 177iter [00:09, 22.52iter/s]
Best score: 2.2096: : 178iter [00:09, 22.56iter/s]
Best score: 2.2096: : 178iter [00:09, 22.56iter/s]
Best score: 2.2096: : 179iter [00:09, 22.56iter/s]
Best score: 2.2096: : 180iter [00:09, 22.56iter/s]
Best score: 2.2096: : 181iter [00:09, 22.35iter/s]
Best score: 2.2096: : 181iter [00:09, 22.35iter/s]
Best score: 2.2096: : 182iter [00:09, 22.35iter/s]
Best score: 2.2096: : 183iter [00:10, 22.35iter/s]
Best score: 2.2096: : 184iter [00:10, 22.47iter/s]
Best score: 2.2096: : 184iter [00:10, 22.47iter/s]
Best score: 2.2096: : 185iter [00:10, 22.47iter/s]
Best score: 2.2096: : 186iter [00:10, 22.47iter/s]
Best score: 2.2096: : 187iter [00:10, 22.50iter/s]
Best score: 2.2096: : 187iter [00:10, 22.50iter/s]
Best score: 2.2096: : 188iter [00:10, 22.50iter/s]
Best score: 2.0925: : 189iter [00:10, 22.50iter/s]
Best score: 2.0925: : 190iter [00:10, 22.27iter/s]
Best score: 2.0925: : 190iter [00:10, 22.27iter/s]
Best score: 2.0925: : 191iter [00:10, 22.27iter/s]
Best score: 2.0925: : 192iter [00:10, 22.27iter/s]
Best score: 2.0925: : 193iter [00:10, 22.38iter/s]
Best score: 2.0925: : 193iter [00:10, 22.38iter/s]
Best score: 2.0925: : 194iter [00:10, 22.38iter/s]
Best score: 2.0925: : 195iter [00:10, 22.38iter/s]
Best score: 2.0925: : 196iter [00:10, 22.48iter/s]
Best score: 2.0925: : 196iter [00:10, 22.48iter/s]
Best score: 2.0925: : 197iter [00:10, 22.48iter/s]
Best score: 2.0925: : 198iter [00:10, 22.48iter/s]
Best score: 2.0925: : 199iter [00:10, 22.56iter/s]
[ITER 200] Best: 2.0925
[PARAMS] Current best parameters:
  fx: 506.8904
  fy: 506.2421
  px: 974.1626
  py: 781.8443
  k1: 0.03379763
  k2: -0.01829907
  k3: 0.01538683
  k4: -0.00510599
  p1: 0.00929039
  p2: -0.00981645
  p3: -0.00398215
  p4: 0.00104715
  scale: 2.9754
  rotation: -0.1434

Best score: 2.0925: : 199iter [00:10, 22.56iter/s]
Best score: 2.0925: : 200iter [00:10, 22.56iter/s]
Best score: 2.0925: : 201iter [00:10, 22.56iter/s]
Best score: 2.0925: : 202iter [00:10, 22.45iter/s]
Best score: 2.0925: : 202iter [00:10, 22.45iter/s]
Best score: 2.0925: : 203iter [00:10, 22.45iter/s]
Best score: 2.0925: : 204iter [00:10, 22.45iter/s]
Best score: 2.0925: : 205iter [00:10, 22.56iter/s]
Best score: 2.0925: : 205iter [00:11, 22.56iter/s]
Best score: 2.0925: : 206iter [00:11, 22.56iter/s]
Best score: 2.0925: : 207iter [00:11, 22.56iter/s]
Best score: 2.0925: : 208iter [00:11, 22.62iter/s]
Best score: 2.0925: : 208iter [00:11, 22.62iter/s]
Best score: 1.9746: : 209iter [00:11, 22.62iter/s]
Best score: 1.9746: : 210iter [00:11, 22.62iter/s]
Best score: 1.9746: : 211iter [00:11, 22.44iter/s]
Best score: 1.9746: : 211iter [00:11, 22.44iter/s]
Best score: 1.9746: : 212iter [00:11, 22.44iter/s]
Best score: 1.9746: : 213iter [00:11, 22.44iter/s]
Best score: 1.9746: : 214iter [00:11, 22.53iter/s]
Best score: 1.9746: : 214iter [00:11, 22.53iter/s]
Best score: 1.9746: : 215iter [00:11, 22.53iter/s]
Best score: 1.9746: : 216iter [00:11, 22.53iter/s]
Best score: 1.9746: : 217iter [00:11, 22.58iter/s]
Best score: 1.9746: : 217iter [00:11, 22.58iter/s]
Best score: 1.9746: : 218iter [00:11, 22.58iter/s]
Best score: 1.8216: : 219iter [00:11, 22.58iter/s]
Best score: 1.8216: : 220iter [00:11, 22.37iter/s]
Best score: 1.8216: : 220iter [00:11, 22.37iter/s]
Best score: 1.8216: : 221iter [00:11, 22.37iter/s]
Best score: 1.8216: : 222iter [00:11, 22.37iter/s]
Best score: 1.8216: : 223iter [00:11, 22.47iter/s]
Best score: 1.8216: : 223iter [00:11, 22.47iter/s]
Best score: 1.8216: : 224iter [00:11, 22.47iter/s]
Best score: 1.8216: : 225iter [00:11, 22.47iter/s]
Best score: 1.8216: : 226iter [00:11, 22.57iter/s]
Best score: 1.8216: : 226iter [00:11, 22.57iter/s]
Best score: 1.8216: : 227iter [00:11, 22.57iter/s]
Best score: 1.8216: : 228iter [00:12, 22.57iter/s]
Best score: 1.8216: : 229iter [00:12, 22.62iter/s]
Best score: 1.7454: : 229iter [00:12, 22.62iter/s]
Best score: 1.7454: : 230iter [00:12, 22.62iter/s]
Best score: 1.7454: : 231iter [00:12, 22.62iter/s]
Best score: 1.7454: : 232iter [00:12, 22.47iter/s]
Best score: 1.7454: : 232iter [00:12, 22.47iter/s]
Best score: 1.7454: : 233iter [00:12, 22.47iter/s]
Best score: 1.7454: : 234iter [00:12, 22.47iter/s]
Best score: 1.7454: : 235iter [00:12, 22.56iter/s]
Best score: 1.7454: : 235iter [00:12, 22.56iter/s]
Best score: 1.7454: : 236iter [00:12, 22.56iter/s]
Best score: 1.7454: : 237iter [00:12, 22.56iter/s]
Best score: 1.7454: : 238iter [00:12, 22.61iter/s]
Best score: 1.7454: : 238iter [00:12, 22.61iter/s]
Best score: 1.7454: : 239iter [00:12, 22.61iter/s]
Best score: 1.7454: : 240iter [00:12, 22.61iter/s]
Best score: 1.7454: : 241iter [00:12, 22.44iter/s]
Best score: 1.7454: : 241iter [00:12, 22.44iter/s]
Best score: 1.7454: : 242iter [00:12, 22.44iter/s]
Best score: 1.7454: : 243iter [00:12, 22.44iter/s]
Best score: 1.7454: : 244iter [00:12, 22.46iter/s]
Best score: 1.7454: : 244iter [00:12, 22.46iter/s]
Best score: 1.7454: : 245iter [00:12, 22.46iter/s]
Best score: 1.7454: : 246iter [00:12, 22.46iter/s]
Best score: 1.7454: : 247iter [00:12, 22.61iter/s]
Best score: 1.7454: : 247iter [00:12, 22.61iter/s]
Best score: 1.7454: : 248iter [00:12, 22.61iter/s]
[ITER 250] Best: 1.7141
[PARAMS] Current best parameters:
  fx: 510.2444
  fy: 509.8387
  px: 974.3790
  py: 781.8109
  k1: 0.03814500
  k2: -0.01985325
  k3: 0.01030585
  k4: -0.00302566
  p1: 0.00965854
  p2: -0.00974794
  p3: -0.00219848
  p4: 0.00057588
  scale: 2.9603
  rotation: -0.1613

Best score: 1.7141: : 249iter [00:12, 22.61iter/s]
Best score: 1.7141: : 250iter [00:12, 22.42iter/s]
Best score: 1.7141: : 250iter [00:13, 22.42iter/s]
Best score: 1.7141: : 251iter [00:13, 22.42iter/s]
Best score: 1.7141: : 252iter [00:13, 22.42iter/s]
Best score: 1.7141: : 253iter [00:13, 22.52iter/s]
Best score: 1.7141: : 253iter [00:13, 22.52iter/s]
Best score: 1.7141: : 254iter [00:13, 22.52iter/s]
Best score: 1.7141: : 255iter [00:13, 22.52iter/s]
Best score: 1.7141: : 256iter [00:13, 22.62iter/s]
Best score: 1.7141: : 256iter [00:13, 22.62iter/s]
Best score: 1.7141: : 257iter [00:13, 22.62iter/s]
Best score: 1.7141: : 258iter [00:13, 22.62iter/s]
Best score: 1.7141: : 259iter [00:13, 22.66iter/s]
Best score: 1.7003: : 259iter [00:13, 22.66iter/s]
Best score: 1.7003: : 260iter [00:13, 22.66iter/s]
Best score: 1.7003: : 261iter [00:13, 22.66iter/s]
Best score: 1.7003: : 262iter [00:13, 22.43iter/s]
Best score: 1.7003: : 262iter [00:13, 22.43iter/s]
Best score: 1.7003: : 263iter [00:13, 22.43iter/s]
Best score: 1.7003: : 264iter [00:13, 22.43iter/s]
Best score: 1.7003: : 265iter [00:13, 22.51iter/s]
Best score: 1.7003: : 265iter [00:13, 22.51iter/s]
Best score: 1.7003: : 266iter [00:13, 22.51iter/s]
Best score: 1.7003: : 267iter [00:13, 22.51iter/s]
Best score: 1.7003: : 268iter [00:13, 22.54iter/s]
Best score: 1.7003: : 268iter [00:13, 22.54iter/s]
Best score: 1.6684: : 269iter [00:13, 22.54iter/s]
Best score: 1.6684: : 270iter [00:13, 22.54iter/s]
Best score: 1.6684: : 271iter [00:13, 22.37iter/s]
Best score: 1.6684: : 271iter [00:13, 22.37iter/s]
Best score: 1.6684: : 272iter [00:13, 22.37iter/s]
Best score: 1.6684: : 273iter [00:14, 22.37iter/s]
Best score: 1.6684: : 274iter [00:14, 22.39iter/s]
Best score: 1.6684: : 274iter [00:14, 22.39iter/s]
Best score: 1.6684: : 275iter [00:14, 22.39iter/s]
Best score: 1.6684: : 276iter [00:14, 22.39iter/s]
Best score: 1.6684: : 277iter [00:14, 22.46iter/s]
Best score: 1.6684: : 277iter [00:14, 22.46iter/s]
Best score: 1.6684: : 278iter [00:14, 22.46iter/s]
Best score: 1.6235: : 279iter [00:14, 22.46iter/s]
Best score: 1.6235: : 280iter [00:14, 22.31iter/s]
Best score: 1.6235: : 280iter [00:14, 22.31iter/s]
Best score: 1.6235: : 281iter [00:14, 22.31iter/s]
Best score: 1.6235: : 282iter [00:14, 22.31iter/s]
Best score: 1.6235: : 283iter [00:14, 22.41iter/s]
Best score: 1.6235: : 283iter [00:14, 22.41iter/s]
Best score: 1.6235: : 284iter [00:14, 22.41iter/s]
Best score: 1.6235: : 285iter [00:14, 22.41iter/s]
Best score: 1.6235: : 286iter [00:14, 22.45iter/s]
Best score: 1.6235: : 286iter [00:14, 22.45iter/s]
Best score: 1.6235: : 287iter [00:14, 22.45iter/s]
Best score: 1.6235: : 288iter [00:14, 22.45iter/s]
Best score: 1.6235: : 289iter [00:14, 22.52iter/s]
Best score: 1.6209: : 289iter [00:14, 22.52iter/s]
Best score: 1.6209: : 290iter [00:14, 22.52iter/s]
Best score: 1.6209: : 291iter [00:14, 22.52iter/s]
Best score: 1.6209: : 292iter [00:14, 22.34iter/s]
Best score: 1.6209: : 292iter [00:14, 22.34iter/s]
Best score: 1.6209: : 293iter [00:14, 22.34iter/s]
Best score: 1.6209: : 294iter [00:14, 22.34iter/s]
Best score: 1.6209: : 295iter [00:14, 22.41iter/s]
Best score: 1.6209: : 295iter [00:15, 22.41iter/s]
Best score: 1.6209: : 296iter [00:15, 22.41iter/s]
Best score: 1.6209: : 297iter [00:15, 22.41iter/s]
Best score: 1.6209: : 298iter [00:15, 22.46iter/s]
Best score: 1.6209: : 298iter [00:15, 22.46iter/s]
[ITER 300] Best: 1.6133
[PARAMS] Current best parameters:
  fx: 508.0982
  fy: 507.8849
  px: 974.2024
  py: 781.9424
  k1: 0.04863570
  k2: -0.01942268
  k3: 0.00337592
  k4: -0.00063458
  p1: 0.00992257
  p2: -0.00984817
  p3: -0.00094198
  p4: -0.00019117
  scale: 2.9346
  rotation: -0.1328

Best score: 1.6133: : 299iter [00:15, 22.46iter/s]
Best score: 1.6133: : 300iter [00:15, 22.46iter/s]
Best score: 1.6133: : 301iter [00:15, 22.24iter/s]
Best score: 1.6133: : 301iter [00:15, 22.24iter/s]
Best score: 1.6133: : 302iter [00:15, 22.24iter/s]
Best score: 1.6133: : 303iter [00:15, 22.24iter/s]
Best score: 1.6133: : 304iter [00:15, 22.33iter/s]
Best score: 1.6133: : 304iter [00:15, 22.33iter/s]
Best score: 1.6133: : 305iter [00:15, 22.33iter/s]
Best score: 1.6133: : 306iter [00:15, 22.33iter/s]
Best score: 1.6133: : 307iter [00:15, 22.44iter/s]
Best score: 1.6133: : 307iter [00:15, 22.44iter/s]
Best score: 1.6133: : 308iter [00:15, 22.44iter/s]
Best score: 1.6089: : 309iter [00:15, 22.44iter/s]
Best score: 1.6089: : 310iter [00:15, 22.24iter/s]
Best score: 1.6089: : 310iter [00:15, 22.24iter/s]
Best score: 1.6089: : 311iter [00:15, 22.24iter/s]
Best score: 1.6089: : 312iter [00:15, 22.24iter/s]
Best score: 1.6089: : 313iter [00:15, 22.31iter/s]
Best score: 1.6089: : 313iter [00:15, 22.31iter/s]
Best score: 1.6089: : 314iter [00:15, 22.31iter/s]
Best score: 1.6089: : 315iter [00:15, 22.31iter/s]
Best score: 1.6089: : 316iter [00:15, 22.40iter/s]
Best score: 1.6089: : 316iter [00:15, 22.40iter/s]
Best score: 1.6089: : 317iter [00:16, 22.40iter/s]
Best score: 1.6089: : 318iter [00:16, 22.40iter/s]
Best score: 1.6089: : 319iter [00:16, 22.46iter/s]
Best score: 1.6023: : 319iter [00:16, 22.46iter/s]
Best score: 1.6023: : 320iter [00:16, 22.46iter/s]
Best score: 1.6023: : 321iter [00:16, 22.46iter/s]
Best score: 1.6023: : 322iter [00:16, 22.32iter/s]
Best score: 1.6023: : 322iter [00:16, 22.32iter/s]
Best score: 1.6023: : 323iter [00:16, 22.32iter/s]
Best score: 1.6023: : 324iter [00:16, 22.32iter/s]
Best score: 1.6023: : 325iter [00:16, 22.51iter/s]
Best score: 1.6023: : 325iter [00:16, 22.51iter/s]
Best score: 1.6023: : 326iter [00:16, 22.51iter/s]
Best score: 1.6023: : 327iter [00:16, 22.51iter/s]
Best score: 1.6023: : 328iter [00:16, 22.63iter/s]
Best score: 1.6023: : 328iter [00:16, 22.63iter/s]
Best score: 1.5937: : 329iter [00:16, 22.63iter/s]
Best score: 1.5937: : 330iter [00:16, 22.63iter/s]
Best score: 1.5937: : 331iter [00:16, 22.46iter/s]
Best score: 1.5937: : 331iter [00:16, 22.46iter/s]
Best score: 1.5937: : 332iter [00:16, 22.46iter/s]
Best score: 1.5937: : 333iter [00:16, 22.46iter/s]
Best score: 1.5937: : 334iter [00:16, 22.57iter/s]
Best score: 1.5937: : 334iter [00:16, 22.57iter/s]
Best score: 1.5937: : 335iter [00:16, 22.57iter/s]
Best score: 1.5937: : 336iter [00:16, 22.57iter/s]
Best score: 1.5937: : 337iter [00:16, 22.68iter/s]
Best score: 1.5937: : 337iter [00:16, 22.68iter/s]
Best score: 1.5937: : 338iter [00:16, 22.68iter/s]
Best score: 1.5888: : 339iter [00:16, 22.68iter/s]
Best score: 1.5888: : 340iter [00:16, 22.50iter/s]
Best score: 1.5888: : 340iter [00:17, 22.50iter/s]
Best score: 1.5888: : 341iter [00:17, 22.50iter/s]
Best score: 1.5888: : 342iter [00:17, 22.50iter/s]
Best score: 1.5888: : 343iter [00:17, 22.59iter/s]
Best score: 1.5888: : 343iter [00:17, 22.59iter/s]
Best score: 1.5888: : 344iter [00:17, 22.59iter/s]
Best score: 1.5888: : 345iter [00:17, 22.59iter/s]
Best score: 1.5888: : 346iter [00:17, 22.67iter/s]
Best score: 1.5888: : 346iter [00:17, 22.67iter/s]
Best score: 1.5888: : 347iter [00:17, 22.67iter/s]
Best score: 1.5888: : 348iter [00:17, 22.67iter/s]
Best score: 1.5888: : 349iter [00:17, 22.70iter/s]
[ITER 350] Best: 1.5859
[PARAMS] Current best parameters:
  fx: 508.3447
  fy: 508.0550
  px: 974.0538
  py: 781.9073
  k1: 0.04872468
  k2: -0.01856264
  k3: 0.00256397
  k4: -0.00046359
  p1: 0.00992935
  p2: -0.00996189
  p3: -0.00058616
  p4: -0.00036165
  scale: 2.9300
  rotation: -0.1542

Best score: 1.5859: : 349iter [00:17, 22.70iter/s]
Best score: 1.5859: : 350iter [00:17, 22.70iter/s]
Best score: 1.5859: : 351iter [00:17, 22.70iter/s]
Best score: 1.5859: : 352iter [00:17, 22.49iter/s]
Best score: 1.5859: : 352iter [00:17, 22.49iter/s]
Best score: 1.5859: : 353iter [00:17, 22.49iter/s]
Best score: 1.5859: : 354iter [00:17, 22.49iter/s]
Best score: 1.5859: : 355iter [00:17, 22.56iter/s]
Best score: 1.5859: : 355iter [00:17, 22.56iter/s]
Best score: 1.5859: : 356iter [00:17, 22.56iter/s]
Best score: 1.5859: : 357iter [00:17, 22.56iter/s]
Best score: 1.5859: : 358iter [00:17, 22.60iter/s]
Best score: 1.5859: : 358iter [00:17, 22.60iter/s]
Best score: 1.5712: : 359iter [00:17, 22.60iter/s]
Best score: 1.5712: : 360iter [00:17, 22.60iter/s]
Best score: 1.5712: : 361iter [00:17, 22.39iter/s]
Best score: 1.5712: : 361iter [00:17, 22.39iter/s]
Best score: 1.5712: : 362iter [00:18, 22.39iter/s]
Best score: 1.5712: : 363iter [00:18, 22.39iter/s]
Best score: 1.5712: : 364iter [00:18, 22.44iter/s]
Best score: 1.5712: : 364iter [00:18, 22.44iter/s]
Best score: 1.5712: : 365iter [00:18, 22.44iter/s]
Best score: 1.5712: : 366iter [00:18, 22.44iter/s]
Best score: 1.5712: : 367iter [00:18, 22.50iter/s]
Best score: 1.5712: : 367iter [00:18, 22.50iter/s]
Best score: 1.5712: : 368iter [00:18, 22.50iter/s]
Best score: 1.5712: : 369iter [00:18, 22.50iter/s]
Best score: 1.5712: : 370iter [00:18, 22.29iter/s]
Best score: 1.5712: : 370iter [00:18, 22.29iter/s]
Best score: 1.5712: : 371iter [00:18, 22.29iter/s]
Best score: 1.5712: : 372iter [00:18, 22.29iter/s]
Best score: 1.5712: : 373iter [00:18, 22.38iter/s]
Best score: 1.5712: : 373iter [00:18, 22.38iter/s]
Best score: 1.5712: : 374iter [00:18, 22.38iter/s]
Best score: 1.5712: : 375iter [00:18, 22.38iter/s]
Best score: 1.5712: : 376iter [00:18, 22.46iter/s]
Best score: 1.5712: : 376iter [00:18, 22.46iter/s]
Best score: 1.5712: : 377iter [00:18, 22.46iter/s]
Best score: 1.5712: : 378iter [00:18, 22.46iter/s]
Best score: 1.5712: : 379iter [00:18, 22.49iter/s]
Best score: 1.5707: : 379iter [00:18, 22.49iter/s]
Best score: 1.5707: : 380iter [00:18, 22.49iter/s]
Best score: 1.5707: : 381iter [00:18, 22.49iter/s]
Best score: 1.5707: : 382iter [00:18, 22.30iter/s]
Best score: 1.5707: : 382iter [00:18, 22.30iter/s]
Best score: 1.5707: : 383iter [00:18, 22.30iter/s]
Best score: 1.5707: : 384iter [00:18, 22.30iter/s]
Best score: 1.5707: : 385iter [00:18, 22.43iter/s]
Best score: 1.5707: : 385iter [00:19, 22.43iter/s]
Best score: 1.5707: : 386iter [00:19, 22.43iter/s]
Best score: 1.5707: : 387iter [00:19, 22.43iter/s]
Best score: 1.5707: : 388iter [00:19, 22.53iter/s]
Best score: 1.5707: : 388iter [00:19, 22.53iter/s]
Best score: 1.5707: : 389iter [00:19, 22.53iter/s]
Best score: 1.5707: : 390iter [00:19, 22.53iter/s]
Best score: 1.5707: : 391iter [00:19, 22.37iter/s]
Best score: 1.5707: : 391iter [00:19, 22.37iter/s]
Best score: 1.5707: : 392iter [00:19, 22.37iter/s]
Best score: 1.5707: : 393iter [00:19, 22.37iter/s]
Best score: 1.5707: : 394iter [00:19, 22.48iter/s]
Best score: 1.5707: : 394iter [00:19, 22.48iter/s]
Best score: 1.5707: : 395iter [00:19, 22.48iter/s]
Best score: 1.5707: : 396iter [00:19, 22.48iter/s]
Best score: 1.5707: : 397iter [00:19, 22.58iter/s]
Best score: 1.5707: : 397iter [00:19, 22.58iter/s]
Best score: 1.5707: : 398iter [00:19, 22.58iter/s]
[ITER 400] Best: 1.5707
[PARAMS] Current best parameters:
  fx: 509.2760
  fy: 509.0798
  px: 974.1050
  py: 781.9922
  k1: 0.04893156
  k2: -0.01918634
  k3: 0.00184439
  k4: -0.00007602
  p1: 0.00996898
  p2: -0.00999595
  p3: -0.00019381
  p4: -0.00044505
  scale: 2.9309
  rotation: -0.1653

Best score: 1.5707: : 399iter [00:19, 22.58iter/s]
Best score: 1.5707: : 400iter [00:19, 22.46iter/s]
Best score: 1.5707: : 400iter [00:19, 22.46iter/s]
Best score: 1.5707: : 401iter [00:19, 22.46iter/s]
Best score: 1.5707: : 402iter [00:19, 22.46iter/s]
Best score: 1.5707: : 403iter [00:19, 22.54iter/s]
Best score: 1.5707: : 403iter [00:19, 22.54iter/s]
Best score: 1.5707: : 404iter [00:19, 22.54iter/s]
Best score: 1.5707: : 405iter [00:19, 22.54iter/s]
Best score: 1.5707: : 406iter [00:19, 22.57iter/s]
Best score: 1.5707: : 406iter [00:19, 22.57iter/s]
Best score: 1.5707: : 407iter [00:20, 22.57iter/s]
Best score: 1.5707: : 408iter [00:20, 22.57iter/s]
Best score: 1.5707: : 409iter [00:20, 22.67iter/s]
Best score: 1.5681: : 409iter [00:20, 22.67iter/s]
Best score: 1.5681: : 410iter [00:20, 22.67iter/s]
Best score: 1.5681: : 411iter [00:20, 22.67iter/s]
Best score: 1.5681: : 412iter [00:20, 22.49iter/s]
Best score: 1.5681: : 412iter [00:20, 22.49iter/s]
Best score: 1.5681: : 413iter [00:20, 22.49iter/s]
Best score: 1.5681: : 414iter [00:20, 22.49iter/s]
Best score: 1.5681: : 415iter [00:20, 22.55iter/s]
Best score: 1.5681: : 415iter [00:20, 22.55iter/s]
Best score: 1.5681: : 416iter [00:20, 22.55iter/s]
Best score: 1.5681: : 417iter [00:20, 22.55iter/s]
Best score: 1.5681: : 418iter [00:20, 22.56iter/s]
Best score: 1.5681: : 418iter [00:20, 22.56iter/s]
Best score: 1.5674: : 419iter [00:20, 22.56iter/s]
Best score: 1.5674: : 420iter [00:20, 22.56iter/s]
Best score: 1.5674: : 421iter [00:20, 22.35iter/s]
Best score: 1.5674: : 421iter [00:20, 22.35iter/s]
Best score: 1.5674: : 422iter [00:20, 22.35iter/s]
Best score: 1.5674: : 423iter [00:20, 22.35iter/s]
Best score: 1.5674: : 424iter [00:20, 22.46iter/s]
Best score: 1.5674: : 424iter [00:20, 22.46iter/s]
Best score: 1.5674: : 425iter [00:20, 22.46iter/s]
Best score: 1.5674: : 426iter [00:20, 22.46iter/s]
Best score: 1.5674: : 427iter [00:20, 18.46iter/s]
Best score: 1.5674: : 427iter [00:20, 18.46iter/s]
Best score: 1.5674: : 428iter [00:21, 18.46iter/s]
Best score: 1.5674: : 429iter [00:21, 18.46iter/s]
Best score: 1.5674: : 430iter [00:21, 19.38iter/s]
Best score: 1.5674: : 430iter [00:21, 19.38iter/s]
Best score: 1.5674: : 431iter [00:21, 19.38iter/s]
Best score: 1.5674: : 432iter [00:21, 19.38iter/s]
Best score: 1.5674: : 433iter [00:21, 20.24iter/s]
Best score: 1.5674: : 433iter [00:21, 20.24iter/s]
Best score: 1.5674: : 434iter [00:21, 20.24iter/s]
Best score: 1.5674: : 435iter [00:21, 20.24iter/s]
Best score: 1.5674: : 436iter [00:21, 20.89iter/s]
Best score: 1.5674: : 436iter [00:21, 20.89iter/s]
Best score: 1.5674: : 437iter [00:21, 20.89iter/s]
Best score: 1.5674: : 438iter [00:21, 20.89iter/s]
Best score: 1.5674: : 439iter [00:21, 21.37iter/s]
Best score: 1.5655: : 439iter [00:21, 21.37iter/s]
Best score: 1.5655: : 440iter [00:21, 21.37iter/s]
Best score: 1.5655: : 441iter [00:21, 21.37iter/s]
Best score: 1.5655: : 442iter [00:21, 21.53iter/s]
Best score: 1.5655: : 442iter [00:21, 21.53iter/s]
Best score: 1.5655: : 443iter [00:21, 21.53iter/s]
Best score: 1.5655: : 444iter [00:21, 21.53iter/s]
Best score: 1.5655: : 445iter [00:21, 21.87iter/s]
Best score: 1.5655: : 445iter [00:21, 21.87iter/s]
Best score: 1.5655: : 446iter [00:21, 21.87iter/s]
Best score: 1.5655: : 447iter [00:21, 21.87iter/s]
Best score: 1.5655: : 448iter [00:21, 22.12iter/s]
Best score: 1.5655: : 448iter [00:21, 22.12iter/s]
[ITER 450] Best: 1.5655
[PARAMS] Current best parameters:
  fx: 507.1256
  fy: 506.8797
  px: 974.0913
  py: 782.0272
  k1: 0.04931430
  k2: -0.01901597
  k3: 0.00319401
  k4: -0.00061966
  p1: 0.00999949
  p2: -0.00999981
  p3: -0.00049711
  p4: -0.00027062
  scale: 2.9363
  rotation: -0.1605

Best score: 1.5655: : 449iter [00:21, 22.12iter/s]
Best score: 1.5655: : 450iter [00:22, 22.12iter/s]
Best score: 1.5655: : 451iter [00:22, 22.08iter/s]
Best score: 1.5655: : 451iter [00:22, 22.08iter/s]
Best score: 1.5655: : 452iter [00:22, 22.08iter/s]
Best score: 1.5655: : 453iter [00:22, 22.08iter/s]
Best score: 1.5655: : 454iter [00:22, 22.27iter/s]
Best score: 1.5655: : 454iter [00:22, 22.27iter/s]
Best score: 1.5655: : 455iter [00:22, 22.27iter/s]
Best score: 1.5655: : 456iter [00:22, 22.27iter/s]
Best score: 1.5655: : 457iter [00:22, 22.43iter/s]
Best score: 1.5655: : 457iter [00:22, 22.43iter/s]
Best score: 1.5655: : 458iter [00:22, 22.43iter/s]
Best score: 1.5655: : 459iter [00:22, 22.43iter/s]
Best score: 1.5655: : 460iter [00:22, 22.36iter/s]
Best score: 1.5655: : 460iter [00:22, 22.36iter/s]
Best score: 1.5655: : 461iter [00:22, 22.36iter/s]
Best score: 1.5655: : 462iter [00:22, 22.36iter/s]
Best score: 1.5655: : 463iter [00:22, 22.48iter/s]
Best score: 1.5655: : 463iter [00:22, 22.48iter/s]
Best score: 1.5655: : 464iter [00:22, 22.48iter/s]
Best score: 1.5655: : 465iter [00:22, 22.48iter/s]
Best score: 1.5655: : 466iter [00:22, 22.53iter/s]
Best score: 1.5655: : 466iter [00:22, 22.53iter/s]
Best score: 1.5655: : 467iter [00:22, 22.53iter/s]
Best score: 1.5655: : 468iter [00:22, 22.53iter/s]
Best score: 1.5655: : 469iter [00:22, 22.62iter/s]
Best score: 1.5655: : 469iter [00:22, 22.62iter/s]
Best score: 1.5655: : 470iter [00:22, 22.62iter/s]
Best score: 1.5655: : 471iter [00:22, 22.62iter/s]
Best score: 1.5655: : 472iter [00:22, 22.45iter/s]
Best score: 1.5655: : 472iter [00:22, 22.45iter/s]
Best score: 1.5655: : 473iter [00:23, 22.45iter/s]
Best score: 1.5655: : 474iter [00:23, 22.45iter/s]
Best score: 1.5655: : 475iter [00:23, 22.51iter/s]
Best score: 1.5655: : 475iter [00:23, 22.51iter/s]
Best score: 1.5655: : 476iter [00:23, 22.51iter/s]
Best score: 1.5655: : 477iter [00:23, 22.51iter/s]
Best score: 1.5655: : 478iter [00:23, 22.56iter/s]
Best score: 1.5655: : 478iter [00:23, 22.56iter/s]
Best score: 1.5643: : 479iter [00:23, 22.56iter/s]
Best score: 1.5643: : 480iter [00:23, 22.56iter/s]
Best score: 1.5643: : 481iter [00:23, 22.38iter/s]
Best score: 1.5643: : 481iter [00:23, 22.38iter/s]
Best score: 1.5643: : 482iter [00:23, 22.38iter/s]
Best score: 1.5643: : 483iter [00:23, 22.38iter/s]
Best score: 1.5643: : 484iter [00:23, 22.41iter/s]
Best score: 1.5643: : 484iter [00:23, 22.41iter/s]
Best score: 1.5643: : 485iter [00:23, 22.41iter/s]
Best score: 1.5643: : 486iter [00:23, 22.41iter/s]
Best score: 1.5643: : 487iter [00:23, 22.46iter/s]
Best score: 1.5643: : 487iter [00:23, 22.46iter/s]
Best score: 1.5643: : 488iter [00:23, 22.46iter/s]
Best score: 1.5639: : 489iter [00:23, 22.46iter/s]
Best score: 1.5639: : 490iter [00:23, 22.21iter/s]
Best score: 1.5639: : 490iter [00:23, 22.21iter/s]
Best score: 1.5639: : 491iter [00:23, 22.21iter/s]
Best score: 1.5639: : 492iter [00:23, 22.21iter/s]
Best score: 1.5639: : 493iter [00:23, 22.34iter/s]
Best score: 1.5639: : 493iter [00:23, 22.34iter/s]
Best score: 1.5639: : 494iter [00:23, 22.34iter/s]
Best score: 1.5639: : 495iter [00:24, 22.34iter/s]
Best score: 1.5639: : 496iter [00:24, 22.35iter/s]
Best score: 1.5639: : 496iter [00:24, 22.35iter/s]
Best score: 1.5639: : 497iter [00:24, 22.35iter/s]
Best score: 1.5639: : 498iter [00:24, 22.35iter/s]
Best score: 1.5639: : 499iter [00:24, 22.39iter/s]
[ITER 500] Best: 1.5636
[PARAMS] Current best parameters:
  fx: 506.9140
  fy: 506.6770
  px: 974.1181
  py: 782.0119
  k1: 0.04997476
  k2: -0.01870454
  k3: 0.00248985
  k4: -0.00040066
  p1: 0.00999430
  p2: -0.00999599
  p3: -0.00041872
  p4: -0.00031137
  scale: 2.9353
  rotation: -0.1615

Best score: 1.5636: : 499iter [00:24, 22.39iter/s]
Best score: 1.5636: : 500iter [00:24, 20.65iter/s]

[📈] Running L-BFGS-B polish after 500 DE iterations...
  Polish improved score: 1.563627 -> 1.562959
  Success: True
  Tangential distortion: p1=0.010000, p2=-0.010000, p3=-0.000418, p4=-0.000309
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 1.5630
[✅] Parameters copied to: /working/MDC101_W036_2025-12-31/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


-------------------------------------------------------------------
                        Step 3: Undistortion                       
-------------------------------------------------------------------


[DEBUG] Parameters being applied to PTD conversion:
    fx: 506.9140098772861
    fy: 506.67703776831473
    px: 974.1180888480204
    py: 782.011912550204
    k1: 0.04997391681177041
    k2: -0.018711911193043527
    k3: 0.0024877327446755147
    k4: -0.0003956973849129945
    p1: 0.01
    p2: -0.01
    p3: -0.000417718997305216
    p4: -0.00030885357642916573
    scale: 2.935249508910983
    rotation: -0.1614937081865308
    mmpp: 1.273812555030545
    nmpp: 1273812.555030545

[🔄] Converting 417 frames to PTD, creating debug images for 200 calibration frames...

📁 Rigs:   0%|          | 0/2 [00:00<?, ?rig/s]

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   🔄 1000:  93%|█████████▎| 199/213 [00:01<00:00, 178.96frame/s]

                                                                 
📁 Rigs:  50%|█████     | 1/2 [00:02<00:02,  2.19s/rig]

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📁 Rigs: 100%|██████████| 2/2 [00:04<00:00,  2.05s/rig]
📁 Rigs: 100%|██████████| 2/2 [00:04<00:00,  2.07s/rig]
[✅] Saved PTDs: /working/MDC101_W036_2025-12-31/calibration/debug/3_undistorted/output/ptd

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📁 Rigs:  50%|█████     | 1/2 [00:01<00:01,  1.00s/rig]

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   🔄 500:  74%|███████▍  | 74/100 [00:00<00:00, 184.82frame/s]

   🔄 500:  93%|█████████▎| 93/100 [00:00<00:00, 181.76frame/s]

                                                               
📁 Rigs: 100%|██████████| 2/2 [00:02<00:00,  1.00s/rig]
📁 Rigs: 100%|██████████| 2/2 [00:02<00:00,  1.00s/rig]
[✅] Saved PTDs: /working/MDC101_W036_2025-12-31/calibration/debug/3_undistorted/temp_ptd
[WARN] No .tfd files found for serial extraction
[WARN] Failed to extract serial number from .tfd file. Check that .tfd files exist and contain 'LASERbidh' or 'LASERbidg' pattern. Using 'unknown' as fallback.

📤 Writing LUT:   0%|          | 0/3080448 [00:00<?, ?px/s]
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📤 Writing LUT:  58%|█████▊    | 1777540/3080448 [00:02<00:01, 890139.39px/s]
📤 Writing LUT:  61%|██████    | 1867075/3080448 [00:02<00:01, 891697.58px/s]
📤 Writing LUT:  64%|██████▎   | 1956248/3080448 [00:02<00:01, 887438.89px/s]
📤 Writing LUT:  66%|██████▋   | 2044998/3080448 [00:02<00:01, 885157.16px/s]
📤 Writing LUT:  69%|██████▉   | 2134114/3080448 [00:02<00:01, 886947.30px/s]
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📤 Writing LUT:  75%|███████▌  | 2313080/3080448 [00:02<00:00, 890556.16px/s]
📤 Writing LUT:  78%|███████▊  | 2402139/3080448 [00:02<00:00, 888165.01px/s]
📤 Writing LUT:  81%|████████  | 2491180/3080448 [00:02<00:00, 888834.13px/s]
📤 Writing LUT:  84%|████████▍ | 2580738/3080448 [00:02<00:00, 890851.82px/s]
📤 Writing LUT:  87%|████████▋ | 2671622/3080448 [00:03<00:00, 896239.62px/s]
📤 Writing LUT:  90%|████████▉ | 2763006/3080448 [00:03<00:00, 901513.04px/s]
📤 Writing LUT:  93%|█████████▎| 2854533/3080448 [00:03<00:00, 905634.70px/s]
📤 Writing LUT:  96%|█████████▌| 2945099/3080448 [00:03<00:00, 905196.69px/s]
📤 Writing LUT:  99%|█████████▊| 3035620/3080448 [00:03<00:00, 903412.97px/s]
📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 890350.24px/s]
[✅] LUT written to: /working/MDC101_W036_2025-12-31/calibration/debug/3_undistorted/output/LUT.lut
[WARN] Folder name 'MDC101_W036_2025-12-31' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC101_W036_2025-12-31/calibration/MDC101_W036_2025-12-31_unknown.lut

-------------------------------------------------------------------
                          Step 4: Heatmap                          
-------------------------------------------------------------------


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   🔥 1000:  61%|██████    | 130/213 [00:00<00:00, 158.60frame/s]

   🔥 1000:  69%|██████▊   | 146/213 [00:00<00:00, 158.99frame/s]

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   🔥 1000: 100%|█████████▉| 212/213 [00:01<00:00, 159.96frame/s]

                                                                 [✅] 1000: /working/MDC101_W036_2025-12-31/calibration/debug/4_heatmap/1000_heatmap.png

📁 Rigs (heatmap):  50%|█████     | 1/2 [00:04<00:04,  4.35s/rig]

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   🔥 500:   8%|▊         | 16/204 [00:00<00:01, 151.41frame/s]

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   🔥 500:  24%|██▍       | 49/204 [00:00<00:00, 156.50frame/s]

   🔥 500:  32%|███▏      | 65/204 [00:00<00:00, 156.67frame/s]

   🔥 500:  40%|███▉      | 81/204 [00:00<00:00, 157.56frame/s]

   🔥 500:  48%|████▊     | 98/204 [00:00<00:00, 161.49frame/s]

   🔥 500:  57%|█████▋    | 117/204 [00:00<00:00, 168.16frame/s]

   🔥 500:  66%|██████▌   | 135/204 [00:00<00:00, 169.13frame/s]

   🔥 500:  75%|███████▍  | 152/204 [00:00<00:00, 165.28frame/s]

   🔥 500:  83%|████████▎ | 169/204 [00:01<00:00, 162.02frame/s]

   🔥 500:  91%|█████████ | 186/204 [00:01<00:00, 160.24frame/s]

   🔥 500: 100%|█████████▉| 203/204 [00:01<00:00, 158.49frame/s]

                                                                [✅] 500: /working/MDC101_W036_2025-12-31/calibration/debug/4_heatmap/500_heatmap.png

📁 Rigs (heatmap): 100%|██████████| 2/2 [00:06<00:00,  3.27s/rig]
📁 Rigs (heatmap): 100%|██████████| 2/2 [00:06<00:00,  3.43s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] Heatmaps saved to: /working/MDC101_W036_2025-12-31/calibration/debug/4_heatmap
[🏁] Finished processing MDC101_W036_2025-12-31


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