2026-05-17T22:37:31 - INFO: Slick 0.0.8a11

🟢 Starting Calibration Pipeline

=== Processing MDC017_W029_2026-03-02 ===
2026-05-17T22:37:31 - INFO: Camera ID: 12131582
2026-05-17T22:37:31 - INFO: Wand ID: 
2026-05-17T22:37:31 - INFO: Recorded At: 2026-03-02T15:32:28Z

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

[🔄] Full PTD mode: Processing ALL images then creating calibration subset
[📸] Digitizing ALL images...
[📸] Full dataset mode: Processing ALL images (no debug visualizations)
[INFO] Found 2 las0.zip files to process

Processing Rigs:   0%|          | 0/2 [00:00<?, ?it/s][INFO] Filtered 891 stationary frames, 211 remain


→ 1000 (211 images) Phase 1:   0%|          | 0/211 [00:00<?, ?it/s]

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→ 1000 (211 images) Phase 1:   9%|▉         | 19/211 [00:00<00:05, 38.12it/s]

→ 1000 (211 images) Phase 1:  16%|█▌        | 33/211 [00:01<00:04, 38.32it/s]

→ 1000 (211 images) Phase 1:  21%|██▏       | 45/211 [00:01<00:03, 49.34it/s]

→ 1000 (211 images) Phase 1:  31%|███       | 65/211 [00:01<00:02, 56.79it/s]

→ 1000 (211 images) Phase 1:  36%|███▋      | 77/211 [00:01<00:02, 62.78it/s]

→ 1000 (211 images) Phase 1:  46%|████▌     | 97/211 [00:01<00:01, 64.94it/s]

→ 1000 (211 images) Phase 1:  51%|█████     | 107/211 [00:02<00:01, 67.95it/s]

→ 1000 (211 images) Phase 1:  61%|██████    | 128/211 [00:02<00:00, 93.20it/s]

→ 1000 (211 images) Phase 1:  66%|██████▋   | 140/211 [00:02<00:01, 66.91it/s]

→ 1000 (211 images) Phase 1:  74%|███████▍  | 156/211 [00:02<00:00, 81.66it/s]

→ 1000 (211 images) Phase 1:  80%|███████▉  | 168/211 [00:02<00:00, 65.18it/s]

→ 1000 (211 images) Phase 1:  85%|████████▍ | 179/211 [00:02<00:00, 71.82it/s]

→ 1000 (211 images) Phase 1:  91%|█████████▏| 193/211 [00:03<00:00, 79.18it/s]

→ 1000 (211 images) Phase 1:  96%|█████████▌| 203/211 [00:03<00:00, 79.63it/s]

                                                                              

→ 1000 Phase 2: corners:   0%|          | 0/211 [00:00<?, ?it/s]

→ 1000 Phase 2: corners:   0%|          | 1/211 [00:00<00:27,  7.65it/s]

→ 1000 Phase 2: corners:   6%|▌         | 12/211 [00:00<00:03, 60.78it/s]

→ 1000 Phase 2: corners:  12%|█▏        | 26/211 [00:00<00:02, 87.06it/s]

→ 1000 Phase 2: corners:  21%|██        | 44/211 [00:00<00:01, 116.04it/s]

→ 1000 Phase 2: corners:  27%|██▋       | 56/211 [00:00<00:01, 112.73it/s]

→ 1000 Phase 2: corners:  32%|███▏      | 68/211 [00:00<00:01, 110.28it/s]

→ 1000 Phase 2: corners:  38%|███▊      | 81/211 [00:00<00:01, 116.02it/s]

→ 1000 Phase 2: corners:  44%|████▍     | 93/211 [00:00<00:01, 115.63it/s]

→ 1000 Phase 2: corners:  50%|████▉     | 105/211 [00:01<00:00, 110.10it/s]

→ 1000 Phase 2: corners:  57%|█████▋    | 120/211 [00:01<00:00, 119.47it/s]

→ 1000 Phase 2: corners:  63%|██████▎   | 133/211 [00:01<00:00, 118.23it/s]

→ 1000 Phase 2: corners:  71%|███████   | 150/211 [00:01<00:00, 131.41it/s]

→ 1000 Phase 2: corners:  78%|███████▊  | 164/211 [00:01<00:00, 132.96it/s]

→ 1000 Phase 2: corners:  84%|████████▍ | 178/211 [00:01<00:00, 127.56it/s]

→ 1000 Phase 2: corners:  99%|█████████▉| 209/211 [00:01<00:00, 178.63it/s]

                                                                           [PASS2] Frame 0000372: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000373: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000374: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000375: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000376: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000377: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000378: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000379: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000380: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000381: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000384: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000385: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000386: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000387: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000479: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000480: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000481: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000482: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000484: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000485: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000486: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000487: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000488: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000489: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000490: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000491: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000492: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000493: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000494: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001030: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001031: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001032: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001033: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000380: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000386: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000481: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000486: fixed corners {1, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000491: fixed corners {0, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000493: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001032: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000377: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000486: fixed corners {1} (was_fixed=True, trusted=False)
[PASS2] Summary: 20 frames fixed, 23 untrusted, 211 total


→ 1000 Phase 3: finalize:   0%|          | 0/211 [00:00<?, ?it/s]

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→ 1000 Phase 3: finalize:  46%|████▋     | 98/211 [00:01<00:02, 47.93it/s]

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→ 1000 Phase 3: finalize:  56%|█████▌    | 118/211 [00:02<00:01, 47.54it/s]

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→ 1000 Phase 3: finalize:  61%|██████    | 128/211 [00:02<00:01, 47.60it/s]

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→ 1000 Phase 3: finalize:  68%|██████▊   | 144/211 [00:02<00:01, 49.15it/s]

→ 1000 Phase 3: finalize:  71%|███████   | 150/211 [00:03<00:01, 49.76it/s]

→ 1000 Phase 3: finalize:  74%|███████▍  | 156/211 [00:03<00:01, 50.16it/s]

→ 1000 Phase 3: finalize:  77%|███████▋  | 162/211 [00:03<00:00, 50.66it/s]

→ 1000 Phase 3: finalize:  80%|███████▉  | 168/211 [00:03<00:00, 51.11it/s]

→ 1000 Phase 3: finalize:  82%|████████▏ | 174/211 [00:03<00:00, 51.48it/s]

→ 1000 Phase 3: finalize:  85%|████████▌ | 180/211 [00:03<00:00, 51.73it/s]

→ 1000 Phase 3: finalize:  88%|████████▊ | 186/211 [00:03<00:00, 51.86it/s]

→ 1000 Phase 3: finalize:  91%|█████████ | 192/211 [00:03<00:00, 51.97it/s]

→ 1000 Phase 3: finalize:  94%|█████████▍| 198/211 [00:03<00:00, 51.94it/s]

→ 1000 Phase 3: finalize:  97%|█████████▋| 204/211 [00:04<00:00, 51.66it/s]

→ 1000 Phase 3: finalize: 100%|█████████▉| 210/211 [00:04<00:00, 51.50it/s]

                                                                           
[TIMING] 1000 — 211 frames
  Phase 1  radial detect   (parallel)  :   3.38s  (16.0 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.70s  (8.1 ms/frame)
  Phase 2b corner fix      (sequential):   0.84s
  Phase 3  finalize        (sequential):   4.19s  (19.8 ms/frame)
    decode + undistort                 :   2.12s  (10.1 ms/frame)
    corner apply + refinement          :   1.01s  (4.8 ms/frame)
    segment                            :   0.86s  (4.1 ms/frame)
    smooth                             :   0.12s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  10.11s


Processing Rigs:  50%|█████     | 1/2 [00:14<00:14, 14.93s/it][INFO] Filtered 830 stationary frames, 175 remain


→ 500 (175 images) Phase 1:   0%|          | 0/175 [00:00<?, ?it/s]

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→ 500 (175 images) Phase 1:  61%|██████    | 107/175 [00:01<00:01, 61.69it/s]

→ 500 (175 images) Phase 1:  74%|███████▎  | 129/175 [00:02<00:00, 60.41it/s]

→ 500 (175 images) Phase 1:  88%|████████▊ | 154/175 [00:02<00:00, 83.64it/s]

→ 500 (175 images) Phase 1:  97%|█████████▋| 169/175 [00:02<00:00, 77.14it/s]

                                                                             

→ 500 Phase 2: corners:   0%|          | 0/175 [00:00<?, ?it/s]

→ 500 Phase 2: corners:   1%|          | 1/175 [00:00<00:38,  4.54it/s]

→ 500 Phase 2: corners:  10%|▉         | 17/175 [00:00<00:02, 64.77it/s]

→ 500 Phase 2: corners:  17%|█▋        | 30/175 [00:00<00:01, 84.02it/s]

→ 500 Phase 2: corners:  27%|██▋       | 48/175 [00:00<00:01, 110.69it/s]

→ 500 Phase 2: corners:  35%|███▍      | 61/175 [00:00<00:01, 110.75it/s]

→ 500 Phase 2: corners:  42%|████▏     | 73/175 [00:00<00:00, 112.21it/s]

→ 500 Phase 2: corners:  50%|████▉     | 87/175 [00:00<00:00, 118.17it/s]

→ 500 Phase 2: corners:  57%|█████▋    | 100/175 [00:00<00:00, 118.08it/s]

→ 500 Phase 2: corners:  65%|██████▌   | 114/175 [00:01<00:00, 122.97it/s]

→ 500 Phase 2: corners:  73%|███████▎  | 127/175 [00:01<00:00, 118.28it/s]

→ 500 Phase 2: corners:  80%|████████  | 140/175 [00:01<00:00, 120.56it/s]

→ 500 Phase 2: corners:  89%|████████▊ | 155/175 [00:01<00:00, 120.90it/s]

→ 500 Phase 2: corners:  99%|█████████▉| 173/175 [00:01<00:00, 136.96it/s]

                                                                          [PASS2] Summary: 0 frames fixed, 0 untrusted, 175 total


→ 500 Phase 3: finalize:   0%|          | 0/175 [00:00<?, ?it/s]

→ 500 Phase 3: finalize:   3%|▎         | 6/175 [00:00<00:02, 57.74it/s]

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→ 500 Phase 3: finalize:  11%|█▏        | 20/175 [00:00<00:02, 60.64it/s]

→ 500 Phase 3: finalize:  15%|█▌        | 27/175 [00:00<00:02, 61.67it/s]

→ 500 Phase 3: finalize:  19%|█▉        | 34/175 [00:00<00:02, 62.40it/s]

→ 500 Phase 3: finalize:  23%|██▎       | 41/175 [00:00<00:02, 62.61it/s]

→ 500 Phase 3: finalize:  27%|██▋       | 48/175 [00:00<00:02, 62.37it/s]

→ 500 Phase 3: finalize:  31%|███▏      | 55/175 [00:00<00:01, 61.92it/s]

→ 500 Phase 3: finalize:  35%|███▌      | 62/175 [00:01<00:01, 61.08it/s]

→ 500 Phase 3: finalize:  39%|███▉      | 69/175 [00:01<00:01, 60.49it/s]

→ 500 Phase 3: finalize:  43%|████▎     | 76/175 [00:01<00:01, 60.29it/s]

→ 500 Phase 3: finalize:  47%|████▋     | 83/175 [00:01<00:01, 60.56it/s]

→ 500 Phase 3: finalize:  51%|█████▏    | 90/175 [00:01<00:01, 61.16it/s]

→ 500 Phase 3: finalize:  55%|█████▌    | 97/175 [00:01<00:01, 61.34it/s]

→ 500 Phase 3: finalize:  59%|█████▉    | 104/175 [00:01<00:01, 61.17it/s]

→ 500 Phase 3: finalize:  63%|██████▎   | 111/175 [00:01<00:01, 60.65it/s]

→ 500 Phase 3: finalize:  67%|██████▋   | 118/175 [00:01<00:00, 60.82it/s]

→ 500 Phase 3: finalize:  71%|███████▏  | 125/175 [00:02<00:00, 61.13it/s]

→ 500 Phase 3: finalize:  75%|███████▌  | 132/175 [00:02<00:00, 61.17it/s]

→ 500 Phase 3: finalize:  79%|███████▉  | 139/175 [00:02<00:00, 61.65it/s]

→ 500 Phase 3: finalize:  83%|████████▎ | 146/175 [00:02<00:00, 62.26it/s]

→ 500 Phase 3: finalize:  87%|████████▋ | 153/175 [00:02<00:00, 62.58it/s]

→ 500 Phase 3: finalize:  91%|█████████▏| 160/175 [00:02<00:00, 62.79it/s]

→ 500 Phase 3: finalize:  95%|█████████▌| 167/175 [00:02<00:00, 62.44it/s]

→ 500 Phase 3: finalize:  99%|█████████▉| 174/175 [00:02<00:00, 62.42it/s]

                                                                          
[TIMING] 500 — 175 frames
  Phase 1  radial detect   (parallel)  :   2.75s  (15.7 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.61s  (9.2 ms/frame)
  Phase 2b corner fix      (sequential):   0.04s
  Phase 3  finalize        (sequential):   2.84s  (16.2 ms/frame)
    decode + undistort                 :   1.25s  (7.2 ms/frame)
    corner apply + refinement          :   0.72s  (4.1 ms/frame)
    segment                            :   0.71s  (4.1 ms/frame)
    smooth                             :   0.10s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   7.24s


Processing Rigs: 100%|██████████| 2/2 [00:25<00:00, 12.19s/it]
Processing Rigs: 100%|██████████| 2/2 [00:25<00:00, 12.60s/it]
[💾] Saved RigFrameDataset to /working/MDC017_W029_2026-03-02/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 386 frames from 2 rigs to /working/MDC017_W029_2026-03-02/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC017_W029_2026-03-02/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 1000: 100 frames selected from 211
[📋] 500: 100 frames selected from 175
[💾] Saved RigFrameDataset to /working/MDC017_W029_2026-03-02/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC017_W029_2026-03-02/calibration/debug/1_digitized/rig_frames.json

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

-> 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<02:09,  3.31s/it]
Computing max image from bright frames:   5%|▌         | 2/40 [00:06<02:04,  3.29s/it]
Computing max image from bright frames:   8%|▊         | 3/40 [00:09<02:01,  3.28s/it]
Computing max image from bright frames:  10%|█         | 4/40 [00:13<01:57,  3.26s/it]
Computing max image from bright frames:  12%|█▎        | 5/40 [00:16<01:54,  3.26s/it]
Computing max image from bright frames:  15%|█▌        | 6/40 [00:19<01:50,  3.25s/it]
Computing max image from bright frames:  18%|█▊        | 7/40 [00:22<01:47,  3.25s/it]
Computing max image from bright frames:  20%|██        | 8/40 [00:26<01:44,  3.26s/it]
Computing max image from bright frames:  22%|██▎       | 9/40 [00:29<01:40,  3.24s/it]
Computing max image from bright frames:  25%|██▌       | 10/40 [00:32<01:37,  3.24s/it]
Computing max image from bright frames:  28%|██▊       | 11/40 [00:36<01:37,  3.35s/it]
Computing max image from bright frames:  30%|███       | 12/40 [00:39<01:36,  3.43s/it]
Computing max image from bright frames:  32%|███▎      | 13/40 [00:43<01:34,  3.48s/it]
Computing max image from bright frames:  35%|███▌      | 14/40 [00:46<01:31,  3.53s/it]
Computing max image from bright frames:  38%|███▊      | 15/40 [00:50<01:29,  3.57s/it]
Computing max image from bright frames:  40%|████      | 16/40 [00:53<01:23,  3.48s/it]
Computing max image from bright frames:  42%|████▎     | 17/40 [00:57<01:18,  3.41s/it]
Computing max image from bright frames:  45%|████▌     | 18/40 [01:00<01:13,  3.36s/it]
Computing max image from bright frames:  48%|████▊     | 19/40 [01:03<01:09,  3.33s/it]
Computing max image from bright frames:  50%|█████     | 20/40 [01:06<01:06,  3.32s/it]
Computing max image from bright frames:  52%|█████▎    | 21/40 [01:10<01:03,  3.32s/it]
Computing max image from bright frames:  55%|█████▌    | 22/40 [01:13<00:59,  3.31s/it]
Computing max image from bright frames:  57%|█████▊    | 23/40 [01:16<00:56,  3.30s/it]
Computing max image from bright frames:  60%|██████    | 24/40 [01:20<00:52,  3.29s/it]
Computing max image from bright frames:  62%|██████▎   | 25/40 [01:23<00:50,  3.35s/it]
Computing max image from bright frames:  65%|██████▌   | 26/40 [01:26<00:46,  3.32s/it]
Computing max image from bright frames:  68%|██████▊   | 27/40 [01:30<00:42,  3.31s/it]
Computing max image from bright frames:  70%|███████   | 28/40 [01:33<00:39,  3.29s/it]
Computing max image from bright frames:  72%|███████▎  | 29/40 [01:36<00:36,  3.29s/it]
Computing max image from bright frames:  75%|███████▌  | 30/40 [01:40<00:33,  3.35s/it]
Computing max image from bright frames:  78%|███████▊  | 31/40 [01:43<00:30,  3.44s/it]
Computing max image from bright frames:  80%|████████  | 32/40 [01:47<00:28,  3.50s/it]
Computing max image from bright frames:  82%|████████▎ | 33/40 [01:51<00:24,  3.56s/it]
Computing max image from bright frames:  85%|████████▌ | 34/40 [01:54<00:21,  3.59s/it]
Computing max image from bright frames:  88%|████████▊ | 35/40 [01:58<00:17,  3.51s/it]
Computing max image from bright frames:  90%|█████████ | 36/40 [02:01<00:13,  3.44s/it]
Computing max image from bright frames:  92%|█████████▎| 37/40 [02:04<00:10,  3.39s/it]
Computing max image from bright frames:  95%|█████████▌| 38/40 [02:07<00:06,  3.36s/it]
Computing max image from bright frames:  98%|█████████▊| 39/40 [02:11<00:03,  3.33s/it]
Computing max image from bright frames: 100%|██████████| 40/40 [02:14<00:00,  3.28s/it]
                                                                                       
[✅] Casing detection complete: cx=1007.0, cy=744.0

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


  0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   1%|          | 1/100 [00:00<00:11,  8.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   2%|▏         | 2/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   2%|▏         | 2/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   3%|▎         | 3/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   4%|▍         | 4/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   5%|▌         | 5/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   6%|▌         | 6/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   7%|▋         | 7/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   8%|▊         | 8/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   9%|▉         | 9/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  10%|█         | 10/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  11%|█         | 11/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  12%|█▏        | 12/100 [00:00<00:05, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  13%|█▎        | 13/100 [00:00<00:04, 17.46it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  14%|█▍        | 14/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  14%|█▍        | 14/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  15%|█▌        | 15/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  16%|█▌        | 16/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  17%|█▋        | 17/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  18%|█▊        | 18/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  19%|█▉        | 19/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  20%|██        | 20/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  21%|██        | 21/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  22%|██▏       | 22/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  23%|██▎       | 23/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  24%|██▍       | 24/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  25%|██▌       | 25/100 [00:00<00:01, 66.40it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 314.141} (0.000):  26%|██▌       | 26/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.000 | Best: {'fx': 483.838} (0.000):  26%|██▌       | 26/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.002 | Best: {'fx': 490.909} (0.002):  27%|██▋       | 27/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.002 | Best: {'fx': 497.98} (0.002):  28%|██▊       | 28/100 [00:00<00:00, 85.99it/s] 
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.007 | Best: {'fx': 505.051} (0.007):  29%|██▉       | 29/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.013 | Best: {'fx': 512.121} (0.013):  30%|███       | 30/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.021 | Best: {'fx': 561.616} (0.021):  31%|███       | 31/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.024 | Best: {'fx': 519.192} (0.024):  32%|███▏      | 32/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.038 | Best: {'fx': 526.263} (0.038):  33%|███▎      | 33/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.064 | Best: {'fx': 533.333} (0.064):  34%|███▍      | 34/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.030 | Best: {'fx': 533.333} (0.064):  35%|███▌      | 35/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.039 | Best: {'fx': 533.333} (0.064):  36%|███▌      | 36/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.025 | Best: {'fx': 533.333} (0.064):  37%|███▋      | 37/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.019 | Best: {'fx': 533.333} (0.064):  38%|███▊      | 38/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.017 | Best: {'fx': 533.333} (0.064):  39%|███▉      | 39/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.016 | Best: {'fx': 533.333} (0.064):  40%|████      | 40/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.015 | Best: {'fx': 533.333} (0.064):  41%|████      | 41/100 [00:00<00:00, 85.99it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.015 | Best: {'fx': 533.333} (0.064):  42%|████▏     | 42/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.012 | Best: {'fx': 533.333} (0.064):  42%|████▏     | 42/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.014 | Best: {'fx': 533.333} (0.064):  43%|████▎     | 43/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.013 | Best: {'fx': 533.333} (0.064):  44%|████▍     | 44/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.012 | Best: {'fx': 533.333} (0.064):  45%|████▌     | 45/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.013 | Best: {'fx': 533.333} (0.064):  46%|████▌     | 46/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.012 | Best: {'fx': 533.333} (0.064):  47%|████▋     | 47/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.011 | Best: {'fx': 533.333} (0.064):  48%|████▊     | 48/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.011 | Best: {'fx': 533.333} (0.064):  49%|████▉     | 49/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.011 | Best: {'fx': 533.333} (0.064):  50%|█████     | 50/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.011 | Best: {'fx': 533.333} (0.064):  51%|█████     | 51/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.011 | Best: {'fx': 533.333} (0.064):  52%|█████▏    | 52/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.010 | Best: {'fx': 533.333} (0.064):  53%|█████▎    | 53/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.010 | Best: {'fx': 533.333} (0.064):  54%|█████▍    | 54/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.010 | Best: {'fx': 533.333} (0.064):  55%|█████▌    | 55/100 [00:00<00:00, 111.74it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.010 | Best: {'fx': 533.333} (0.064):  56%|█████▌    | 56/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.010 | Best: {'fx': 533.333} (0.064):  56%|█████▌    | 56/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  57%|█████▋    | 57/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.010 | Best: {'fx': 533.333} (0.064):  58%|█████▊    | 58/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.010 | Best: {'fx': 533.333} (0.064):  59%|█████▉    | 59/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.010 | Best: {'fx': 533.333} (0.064):  60%|██████    | 60/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  61%|██████    | 61/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.010 | Best: {'fx': 533.333} (0.064):  62%|██████▏   | 62/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  63%|██████▎   | 63/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  64%|██████▍   | 64/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  65%|██████▌   | 65/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  66%|██████▌   | 66/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  67%|██████▋   | 67/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  68%|██████▊   | 68/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  69%|██████▉   | 69/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  70%|███████   | 70/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  71%|███████   | 71/100 [00:00<00:00, 117.92it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  72%|███████▏  | 72/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  72%|███████▏  | 72/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  73%|███████▎  | 73/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  74%|███████▍  | 74/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  75%|███████▌  | 75/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  76%|███████▌  | 76/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  77%|███████▋  | 77/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  78%|███████▊  | 78/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  79%|███████▉  | 79/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  80%|████████  | 80/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  81%|████████  | 81/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  82%|████████▏ | 82/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  83%|████████▎ | 83/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  84%|████████▍ | 84/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  85%|████████▌ | 85/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  86%|████████▌ | 86/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  87%|████████▋ | 87/100 [00:00<00:00, 125.01it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  88%|████████▊ | 88/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  88%|████████▊ | 88/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  89%|████████▉ | 89/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  90%|█████████ | 90/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  91%|█████████ | 91/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  92%|█████████▏| 92/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  93%|█████████▎| 93/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  94%|█████████▍| 94/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  95%|█████████▌| 95/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  96%|█████████▌| 96/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  97%|█████████▋| 97/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  98%|█████████▊| 98/100 [00:00<00:00, 135.29it/s]
Brute | Start: {'fx': 500.0} (0.005) | Current: 0.009 | Best: {'fx': 533.333} (0.064):  99%|█████████▉| 99/100 [00:00<00:00, 135.29it/s]
                                                                                                                                        

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.009 | Best: {'fx': 508.333} (0.009):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.009 | Best: {'fx': 508.333} (0.009):   2%|▏         | 1/50 [00:00<00:06,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.010 | Best: {'fx': 509.354} (0.010):   2%|▏         | 1/50 [00:00<00:06,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.011 | Best: {'fx': 510.374} (0.011):   4%|▍         | 2/50 [00:00<00:06,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.019 | Best: {'fx': 515.476} (0.019):   6%|▌         | 3/50 [00:00<00:06,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.018 | Best: {'fx': 515.476} (0.019):   8%|▊         | 4/50 [00:00<00:06,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.013 | Best: {'fx': 515.476} (0.019):  10%|█         | 5/50 [00:00<00:05,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.015 | Best: {'fx': 515.476} (0.019):  12%|█▏        | 6/50 [00:00<00:05,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.015 | Best: {'fx': 515.476} (0.019):  14%|█▍        | 7/50 [00:00<00:05,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.020 | Best: {'fx': 516.497} (0.020):  16%|█▌        | 8/50 [00:00<00:05,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.022 | Best: {'fx': 517.517} (0.022):  18%|█▊        | 9/50 [00:00<00:05,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.025 | Best: {'fx': 519.558} (0.025):  20%|██        | 10/50 [00:00<00:05,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.023 | Best: {'fx': 519.558} (0.025):  22%|██▏       | 11/50 [00:00<00:05,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.027 | Best: {'fx': 520.578} (0.027):  24%|██▍       | 12/50 [00:00<00:04,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.028 | Best: {'fx': 521.599} (0.028):  26%|██▌       | 13/50 [00:00<00:04,  7.66it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.035 | Best: {'fx': 525.68} (0.035):  28%|██▊       | 14/50 [00:00<00:04,  7.66it/s] 
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.035 | Best: {'fx': 525.68} (0.035):  30%|███       | 15/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.030 | Best: {'fx': 525.68} (0.035):  30%|███       | 15/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.031 | Best: {'fx': 525.68} (0.035):  32%|███▏      | 16/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.033 | Best: {'fx': 525.68} (0.035):  34%|███▍      | 17/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.040 | Best: {'fx': 526.701} (0.040):  36%|███▌      | 18/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.041 | Best: {'fx': 527.721} (0.041):  38%|███▊      | 19/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.046 | Best: {'fx': 528.741} (0.046):  40%|████      | 20/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.063 | Best: {'fx': 533.844} (0.063):  42%|████▏     | 21/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.048 | Best: {'fx': 533.844} (0.063):  44%|████▍     | 22/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.052 | Best: {'fx': 533.844} (0.063):  46%|████▌     | 23/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.058 | Best: {'fx': 533.844} (0.063):  48%|████▊     | 24/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.063 | Best: {'fx': 532.823} (0.063):  50%|█████     | 25/50 [00:00<00:00, 73.06it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.063 | Best: {'fx': 532.823} (0.063):  52%|█████▏    | 26/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.054 | Best: {'fx': 532.823} (0.063):  52%|█████▏    | 26/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.057 | Best: {'fx': 532.823} (0.063):  54%|█████▍    | 27/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.036 | Best: {'fx': 532.823} (0.063):  56%|█████▌    | 28/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.050 | Best: {'fx': 532.823} (0.063):  58%|█████▊    | 29/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.049 | Best: {'fx': 532.823} (0.063):  60%|██████    | 30/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.043 | Best: {'fx': 532.823} (0.063):  62%|██████▏   | 31/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.041 | Best: {'fx': 532.823} (0.063):  64%|██████▍   | 32/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.039 | Best: {'fx': 532.823} (0.063):  66%|██████▌   | 33/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.034 | Best: {'fx': 532.823} (0.063):  68%|██████▊   | 34/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.036 | Best: {'fx': 532.823} (0.063):  70%|███████   | 35/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.028 | Best: {'fx': 532.823} (0.063):  72%|███████▏  | 36/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.032 | Best: {'fx': 532.823} (0.063):  74%|███████▍  | 37/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.031 | Best: {'fx': 532.823} (0.063):  76%|███████▌  | 38/50 [00:00<00:00, 86.19it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.031 | Best: {'fx': 532.823} (0.063):  78%|███████▊  | 39/50 [00:00<00:00, 100.31it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.030 | Best: {'fx': 532.823} (0.063):  78%|███████▊  | 39/50 [00:00<00:00, 100.31it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.029 | Best: {'fx': 532.823} (0.063):  80%|████████  | 40/50 [00:00<00:00, 100.31it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.028 | Best: {'fx': 532.823} (0.063):  82%|████████▏ | 41/50 [00:00<00:00, 100.31it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.027 | Best: {'fx': 532.823} (0.063):  84%|████████▍ | 42/50 [00:00<00:00, 100.31it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.026 | Best: {'fx': 532.823} (0.063):  86%|████████▌ | 43/50 [00:00<00:00, 100.31it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.025 | Best: {'fx': 532.823} (0.063):  88%|████████▊ | 44/50 [00:00<00:00, 100.31it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.025 | Best: {'fx': 532.823} (0.063):  90%|█████████ | 45/50 [00:00<00:00, 100.31it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.023 | Best: {'fx': 532.823} (0.063):  92%|█████████▏| 46/50 [00:00<00:00, 100.31it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.024 | Best: {'fx': 532.823} (0.063):  94%|█████████▍| 47/50 [00:00<00:00, 100.31it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.024 | Best: {'fx': 532.823} (0.063):  96%|█████████▌| 48/50 [00:00<00:00, 100.31it/s]
Brute | Start: {'fx': 533.333} (0.064) | Current: 0.023 | Best: {'fx': 532.823} (0.063):  98%|█████████▊| 49/50 [00:00<00:00, 100.31it/s]
                                                                                                                                         
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 533.3333333333334
    px: 1007.0
    py: 744.0
    k1: 0.0
    k2: 0.0
    k3: 0.0
    k4: 0.0
    p1: 0.0
    p2: 0.0
    p3: 0.0
    p4: 0.0
    scale: 3.0
    rotation: 0.0


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

Initial score: 224.9883: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 224.9883, picklable_objective(x0) = 224.8774

Best score: 224.8774: : 0iter [00:01, ?iter/s] 
Best score: 224.8774: : 1iter [00:01,  1.98s/iter]
Best score: 224.8774: : 1iter [00:02,  1.98s/iter]
Best score: 224.8774: : 2iter [00:02,  1.98s/iter]
Best score: 224.8774: : 3iter [00:02,  1.98s/iter]
Best score: 224.8774: : 4iter [00:02,  1.98s/iter]
Best score: 224.8774: : 5iter [00:02,  3.15iter/s]
Best score: 224.8774: : 5iter [00:02,  3.15iter/s]
Best score: 224.8774: : 6iter [00:02,  3.15iter/s]
Best score: 224.8774: : 7iter [00:02,  3.15iter/s]
Best score: 224.8774: : 8iter [00:02,  3.15iter/s]
Best score: 224.8774: : 9iter [00:02,  6.35iter/s]
Best score: 224.8774: : 9iter [00:02,  6.35iter/s]
Best score: 224.8774: : 10iter [00:02,  6.35iter/s]
Best score: 224.8774: : 11iter [00:02,  6.35iter/s]
Best score: 224.8774: : 12iter [00:02,  6.35iter/s]
Best score: 224.8774: : 13iter [00:02, 10.04iter/s]
Best score: 224.8774: : 13iter [00:02, 10.04iter/s]
Best score: 224.8774: : 14iter [00:02, 10.04iter/s]
Best score: 224.8774: : 15iter [00:02, 10.04iter/s]
Best score: 224.8774: : 16iter [00:02, 10.04iter/s]
Best score: 224.8774: : 17iter [00:02, 14.07iter/s]
Best score: 224.8774: : 17iter [00:02, 14.07iter/s]
Best score: 224.8774: : 18iter [00:02, 14.07iter/s]
Best score: 224.8774: : 19iter [00:02, 14.07iter/s]
Best score: 224.8774: : 20iter [00:02, 14.07iter/s]
Best score: 224.8774: : 21iter [00:02, 18.14iter/s]
Best score: 224.8774: : 21iter [00:02, 18.14iter/s]
Best score: 224.8774: : 22iter [00:02, 18.14iter/s]
Best score: 224.8774: : 23iter [00:02, 18.14iter/s]
Best score: 224.8774: : 24iter [00:02, 18.14iter/s]
Best score: 224.8774: : 25iter [00:02, 22.10iter/s]
Best score: 224.8774: : 25iter [00:02, 22.10iter/s]
Best score: 224.8774: : 26iter [00:02, 22.10iter/s]
Best score: 224.8774: : 27iter [00:02, 22.10iter/s]
Best score: 224.8774: : 28iter [00:02, 22.10iter/s]
Best score: 224.8774: : 29iter [00:02, 25.78iter/s]
Best score: 224.8774: : 29iter [00:02, 25.78iter/s]
Best score: 224.8774: : 30iter [00:02, 25.78iter/s]
Best score: 224.8774: : 31iter [00:02, 25.78iter/s]
Best score: 224.8774: : 32iter [00:02, 25.78iter/s]
Best score: 224.8774: : 33iter [00:02, 28.78iter/s]
Best score: 224.8774: : 33iter [00:02, 28.78iter/s]
Best score: 224.8774: : 34iter [00:02, 28.78iter/s]
Best score: 224.8774: : 35iter [00:02, 28.78iter/s]
Best score: 224.8774: : 36iter [00:02, 28.78iter/s]
Best score: 224.8774: : 37iter [00:02, 31.24iter/s]
Best score: 224.8774: : 37iter [00:02, 31.24iter/s]
Best score: 224.8774: : 38iter [00:02, 31.24iter/s]
Best score: 224.8774: : 39iter [00:02, 31.24iter/s]
Best score: 224.8774: : 40iter [00:03, 31.24iter/s]
Best score: 224.8774: : 41iter [00:03, 33.18iter/s]
Best score: 224.8774: : 41iter [00:03, 33.18iter/s]
Best score: 224.8774: : 42iter [00:03, 33.18iter/s]
Best score: 224.8774: : 43iter [00:03, 33.18iter/s]
Best score: 224.8774: : 44iter [00:03, 33.18iter/s]
Best score: 224.8774: : 45iter [00:03, 34.78iter/s]
Best score: 224.8774: : 45iter [00:03, 34.78iter/s]
Best score: 224.8774: : 46iter [00:03, 34.78iter/s]
Best score: 224.8774: : 47iter [00:03, 34.78iter/s]
Best score: 224.8774: : 48iter [00:03, 34.78iter/s]
Best score: 224.8774: : 49iter [00:03, 35.94iter/s]
[ITER 50] Best: 224.8774
[PARAMS] Current best parameters:
  fx: 533.3333
  fy: 533.3333
  px: 1007.0000
  py: 744.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000

Best score: 224.8774: : 49iter [00:03, 35.94iter/s]
Best score: 224.8774: : 50iter [00:03, 35.94iter/s]
Best score: 224.8774: : 51iter [00:03, 35.94iter/s]
Best score: 224.8774: : 52iter [00:03, 35.94iter/s]
Best score: 224.8774: : 53iter [00:03, 36.52iter/s]
Best score: 224.8774: : 53iter [00:03, 36.52iter/s]
Best score: 224.8774: : 54iter [00:03, 36.52iter/s]
Best score: 224.8774: : 55iter [00:03, 36.52iter/s]
Best score: 224.8774: : 56iter [00:03, 36.52iter/s]
Best score: 224.8774: : 57iter [00:03, 37.27iter/s]
Best score: 224.8774: : 57iter [00:03, 37.27iter/s]
Best score: 224.8774: : 58iter [00:03, 37.27iter/s]
Best score: 224.8774: : 59iter [00:03, 37.27iter/s]
Best score: 224.8774: : 60iter [00:03, 37.27iter/s]
Best score: 224.8774: : 61iter [00:03, 37.69iter/s]
Best score: 224.8774: : 61iter [00:03, 37.69iter/s]
Best score: 224.8774: : 62iter [00:03, 37.69iter/s]
Best score: 224.8774: : 63iter [00:03, 37.69iter/s]
Best score: 224.8774: : 64iter [00:03, 37.69iter/s]
Best score: 224.8774: : 65iter [00:03, 38.07iter/s]
Best score: 224.8774: : 65iter [00:03, 38.07iter/s]
Best score: 224.8774: : 66iter [00:03, 38.07iter/s]
Best score: 224.8774: : 67iter [00:03, 38.07iter/s]
Best score: 224.8774: : 68iter [00:03, 38.07iter/s]
Best score: 224.8774: : 69iter [00:03, 38.32iter/s]
Best score: 224.8774: : 69iter [00:03, 38.32iter/s]
Best score: 224.8774: : 70iter [00:03, 38.32iter/s]
Best score: 224.8774: : 71iter [00:03, 38.32iter/s]
Best score: 224.8774: : 72iter [00:03, 38.32iter/s]
Best score: 224.8774: : 73iter [00:03, 38.38iter/s]
Best score: 224.8774: : 73iter [00:03, 38.38iter/s]
Best score: 224.8774: : 74iter [00:03, 38.38iter/s]
Best score: 224.8774: : 75iter [00:03, 38.38iter/s]
Best score: 224.8774: : 76iter [00:03, 38.38iter/s]
Best score: 224.8774: : 77iter [00:03, 38.70iter/s]
Best score: 224.8774: : 77iter [00:03, 38.70iter/s]
Best score: 224.8774: : 78iter [00:03, 38.70iter/s]
Best score: 224.8774: : 79iter [00:04, 38.70iter/s]
Best score: 224.8774: : 80iter [00:04, 38.70iter/s]
Best score: 224.8774: : 81iter [00:04, 38.71iter/s]
Best score: 224.8774: : 81iter [00:04, 38.71iter/s]
Best score: 224.8774: : 82iter [00:04, 38.71iter/s]
Best score: 224.8774: : 83iter [00:04, 38.71iter/s]
Best score: 224.8774: : 84iter [00:04, 38.71iter/s]
Best score: 224.8774: : 85iter [00:04, 38.80iter/s]
Best score: 224.8774: : 85iter [00:04, 38.80iter/s]
Best score: 224.8774: : 86iter [00:04, 38.80iter/s]
Best score: 224.8774: : 87iter [00:04, 38.80iter/s]
Best score: 224.8774: : 88iter [00:04, 38.80iter/s]
Best score: 224.8774: : 89iter [00:04, 38.94iter/s]
Best score: 224.8774: : 89iter [00:04, 38.94iter/s]
Best score: 224.8774: : 90iter [00:04, 38.94iter/s]
Best score: 224.8774: : 91iter [00:04, 38.94iter/s]
Best score: 224.8774: : 92iter [00:04, 38.94iter/s]
Best score: 224.8774: : 93iter [00:04, 38.71iter/s]
Best score: 224.8774: : 93iter [00:04, 38.71iter/s]
Best score: 224.8774: : 94iter [00:04, 38.71iter/s]
Best score: 224.8774: : 95iter [00:04, 38.71iter/s]
Best score: 224.8774: : 96iter [00:04, 38.71iter/s]
Best score: 224.8774: : 97iter [00:04, 38.80iter/s]
Best score: 224.8774: : 97iter [00:04, 38.80iter/s]
Best score: 224.8774: : 98iter [00:04, 38.80iter/s]
[ITER 100] Best: 224.8774
[PARAMS] Current best parameters:
  fx: 533.3333
  fy: 533.3333
  px: 1007.0000
  py: 744.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000

Best score: 224.8774: : 99iter [00:04, 38.80iter/s]
Best score: 224.8774: : 100iter [00:04, 38.80iter/s]
Best score: 224.8774: : 101iter [00:04, 36.14iter/s]
Best score: 224.8774: : 101iter [00:04, 36.14iter/s]
Best score: 224.8774: : 102iter [00:04, 36.14iter/s]
Best score: 224.8774: : 103iter [00:04, 36.14iter/s]
Best score: 224.8774: : 104iter [00:04, 36.14iter/s]
Best score: 224.8774: : 105iter [00:04, 36.87iter/s]
Best score: 224.8774: : 105iter [00:04, 36.87iter/s]
Best score: 224.8774: : 106iter [00:04, 36.87iter/s]
Best score: 224.8774: : 107iter [00:04, 36.87iter/s]
Best score: 224.8774: : 108iter [00:04, 36.87iter/s]
Best score: 224.8774: : 109iter [00:04, 37.37iter/s]
Best score: 224.8774: : 109iter [00:04, 37.37iter/s]
Best score: 224.8774: : 110iter [00:04, 37.37iter/s]
Best score: 224.8774: : 111iter [00:04, 37.37iter/s]
Best score: 224.8774: : 112iter [00:04, 37.37iter/s]
Best score: 224.8774: : 113iter [00:04, 37.61iter/s]
Best score: 224.8774: : 113iter [00:04, 37.61iter/s]
Best score: 224.8774: : 114iter [00:04, 37.61iter/s]
Best score: 224.8774: : 115iter [00:04, 37.61iter/s]
Best score: 224.8774: : 116iter [00:05, 37.61iter/s]
Best score: 224.8774: : 117iter [00:05, 38.03iter/s]
Best score: 224.8774: : 117iter [00:05, 38.03iter/s]
Best score: 224.8774: : 118iter [00:05, 38.03iter/s]
Best score: 224.8774: : 119iter [00:05, 38.03iter/s]
Best score: 224.8774: : 120iter [00:05, 38.03iter/s]
Best score: 224.8774: : 121iter [00:05, 38.13iter/s]
Best score: 224.8774: : 121iter [00:05, 38.13iter/s]
Best score: 224.8774: : 122iter [00:05, 38.13iter/s]
Best score: 224.8774: : 123iter [00:05, 38.13iter/s]
Best score: 224.8774: : 124iter [00:05, 38.13iter/s]
Best score: 224.8774: : 125iter [00:05, 38.42iter/s]
Best score: 224.8774: : 125iter [00:05, 38.42iter/s]
Best score: 224.8774: : 126iter [00:05, 38.42iter/s]
Best score: 224.8774: : 127iter [00:05, 38.42iter/s]
Best score: 224.8774: : 128iter [00:05, 38.42iter/s]
Best score: 224.8774: : 129iter [00:05, 38.48iter/s]
Best score: 224.8774: : 129iter [00:05, 38.48iter/s]
Best score: 224.8774: : 130iter [00:05, 38.48iter/s]
Best score: 224.8774: : 131iter [00:05, 38.48iter/s]
Best score: 224.8774: : 132iter [00:05, 38.48iter/s]
Best score: 224.8774: : 133iter [00:05, 38.46iter/s]
Best score: 224.8774: : 133iter [00:05, 38.46iter/s]
Best score: 224.8774: : 134iter [00:05, 38.46iter/s]
Best score: 224.8774: : 135iter [00:05, 38.46iter/s]
Best score: 224.8774: : 136iter [00:05, 38.46iter/s]
Best score: 224.8774: : 137iter [00:05, 38.66iter/s]
Best score: 224.8774: : 137iter [00:05, 38.66iter/s]
Best score: 224.8774: : 138iter [00:05, 38.66iter/s]
Best score: 224.8774: : 139iter [00:05, 38.66iter/s]
Best score: 224.8774: : 140iter [00:05, 38.66iter/s]
Best score: 224.8774: : 141iter [00:05, 38.34iter/s]
Best score: 224.8774: : 141iter [00:05, 38.34iter/s]
Best score: 224.8774: : 142iter [00:05, 38.34iter/s]
Best score: 224.8774: : 143iter [00:05, 38.34iter/s]
Best score: 224.8774: : 144iter [00:05, 38.34iter/s]
Best score: 224.8774: : 145iter [00:05, 38.53iter/s]
Best score: 224.8774: : 145iter [00:05, 38.53iter/s]
Best score: 224.8774: : 146iter [00:05, 38.53iter/s]
Best score: 224.8774: : 147iter [00:05, 38.53iter/s]
Best score: 224.8774: : 148iter [00:05, 38.53iter/s]
Best score: 224.8774: : 149iter [00:05, 38.69iter/s]
[ITER 150] Best: 224.8774
[PARAMS] Current best parameters:
  fx: 533.3333
  fy: 533.3333
  px: 1007.0000
  py: 744.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000

Best score: 224.8774: : 149iter [00:05, 38.69iter/s]
Best score: 224.8774: : 150iter [00:05, 38.69iter/s]
Best score: 224.8774: : 151iter [00:05, 38.69iter/s]
Best score: 224.8774: : 152iter [00:06, 38.69iter/s]
Best score: 224.8774: : 153iter [00:06, 31.43iter/s]
Best score: 224.8774: : 153iter [00:06, 31.43iter/s]
Best score: 224.8774: : 154iter [00:06, 31.43iter/s]
Best score: 224.8774: : 155iter [00:06, 31.43iter/s]
Best score: 224.8774: : 156iter [00:06, 31.43iter/s]
Best score: 224.8774: : 157iter [00:06, 33.32iter/s]
Best score: 224.8774: : 157iter [00:06, 33.32iter/s]
Best score: 224.8774: : 158iter [00:06, 33.32iter/s]
Best score: 224.8774: : 159iter [00:06, 33.32iter/s]
Best score: 224.8774: : 160iter [00:06, 33.32iter/s]
Best score: 224.8774: : 161iter [00:06, 34.74iter/s]
Best score: 224.8774: : 161iter [00:06, 34.74iter/s]
Best score: 224.8774: : 162iter [00:06, 34.74iter/s]
Best score: 224.8774: : 163iter [00:06, 34.74iter/s]
Best score: 224.8774: : 164iter [00:06, 34.74iter/s]
Best score: 224.8774: : 165iter [00:06, 36.03iter/s]
Best score: 224.8774: : 165iter [00:06, 36.03iter/s]
Best score: 224.8774: : 166iter [00:06, 36.03iter/s]
Best score: 224.8774: : 167iter [00:06, 36.03iter/s]
Best score: 224.8774: : 168iter [00:06, 36.03iter/s]
Best score: 224.8774: : 169iter [00:06, 36.97iter/s]
Best score: 224.8774: : 169iter [00:06, 36.97iter/s]
Best score: 224.8774: : 170iter [00:06, 36.97iter/s]
Best score: 224.8774: : 171iter [00:06, 36.97iter/s]
Best score: 224.8774: : 172iter [00:06, 36.97iter/s]
Best score: 224.8774: : 173iter [00:06, 37.52iter/s]
Best score: 224.8774: : 173iter [00:06, 37.52iter/s]
Best score: 224.8774: : 174iter [00:06, 37.52iter/s]
Best score: 224.8774: : 175iter [00:06, 37.52iter/s]
Best score: 224.8774: : 176iter [00:06, 37.52iter/s]
Best score: 224.8774: : 177iter [00:06, 38.19iter/s]
Best score: 224.8774: : 177iter [00:06, 38.19iter/s]
Best score: 224.8774: : 178iter [00:06, 38.19iter/s]
Best score: 136.5339: : 179iter [00:06, 38.19iter/s]
Best score: 136.5339: : 180iter [00:06, 38.19iter/s]
Best score: 136.5339: : 181iter [00:06, 38.37iter/s]
Best score: 136.5339: : 181iter [00:06, 38.37iter/s]
Best score: 136.5339: : 182iter [00:06, 38.37iter/s]
Best score: 136.5339: : 183iter [00:06, 38.37iter/s]
Best score: 136.5339: : 184iter [00:06, 38.37iter/s]
Best score: 136.5339: : 185iter [00:06, 38.75iter/s]
Best score: 136.5339: : 185iter [00:06, 38.75iter/s]
Best score: 136.5339: : 186iter [00:06, 38.75iter/s]
Best score: 136.5339: : 187iter [00:06, 38.75iter/s]
Best score: 136.5339: : 188iter [00:06, 38.75iter/s]
Best score: 136.5339: : 189iter [00:06, 39.10iter/s]
Best score: 80.4964: : 189iter [00:06, 39.10iter/s] 
Best score: 80.4964: : 190iter [00:06, 39.10iter/s]
Best score: 80.4964: : 191iter [00:07, 39.10iter/s]
Best score: 80.4964: : 192iter [00:07, 39.10iter/s]
Best score: 80.4964: : 193iter [00:07, 38.85iter/s]
Best score: 80.4964: : 193iter [00:07, 38.85iter/s]
Best score: 80.4964: : 194iter [00:07, 38.85iter/s]
Best score: 80.4964: : 195iter [00:07, 38.85iter/s]
Best score: 80.4964: : 196iter [00:07, 38.85iter/s]
Best score: 80.4964: : 197iter [00:07, 39.02iter/s]
Best score: 80.4964: : 197iter [00:07, 39.02iter/s]
Best score: 80.4964: : 198iter [00:07, 39.02iter/s]
[ITER 200] Best: 80.4964
[PARAMS] Current best parameters:
  fx: 479.4794
  fy: 476.6741
  px: 982.5510
  py: 756.6810
  k1: 0.03880473
  k2: -0.01800211
  k3: 0.03524950
  k4: -0.01250121
  p1: 0.00590412
  p2: -0.02990534
  p3: 0.00946938
  p4: -0.00687860
  s1: 0.0267
  s2: -0.0036
  s3: -0.0063
  s4: -0.0092
  tilt_x: 0.0236
  tilt_y: -0.0241
  scale: 3.0396
  rotation: 1.3629

Best score: 80.4964: : 199iter [00:07, 39.02iter/s]
Best score: 80.4964: : 200iter [00:07, 39.02iter/s]
Best score: 80.4964: : 201iter [00:07, 31.41iter/s]
Best score: 80.4964: : 201iter [00:07, 31.41iter/s]
Best score: 80.4964: : 202iter [00:07, 31.41iter/s]
Best score: 80.4964: : 203iter [00:07, 31.41iter/s]
Best score: 80.4964: : 204iter [00:07, 31.41iter/s]
Best score: 80.4964: : 205iter [00:07, 33.50iter/s]
Best score: 80.4964: : 205iter [00:07, 33.50iter/s]
Best score: 80.4964: : 206iter [00:07, 33.50iter/s]
Best score: 80.4964: : 207iter [00:07, 33.50iter/s]
Best score: 80.4964: : 208iter [00:07, 33.50iter/s]
Best score: 80.4964: : 209iter [00:07, 35.08iter/s]
Best score: 41.6447: : 209iter [00:07, 35.08iter/s]
Best score: 41.6447: : 210iter [00:07, 35.08iter/s]
Best score: 41.6447: : 211iter [00:07, 35.08iter/s]
Best score: 41.6447: : 212iter [00:07, 35.08iter/s]
Best score: 41.6447: : 213iter [00:07, 36.23iter/s]
Best score: 41.6447: : 213iter [00:07, 36.23iter/s]
Best score: 41.6447: : 214iter [00:07, 36.23iter/s]
Best score: 41.6447: : 215iter [00:07, 36.23iter/s]
Best score: 41.6447: : 216iter [00:07, 36.23iter/s]
Best score: 41.6447: : 217iter [00:07, 37.19iter/s]
Best score: 41.6447: : 217iter [00:07, 37.19iter/s]
Best score: 41.6447: : 218iter [00:07, 37.19iter/s]
Best score: 36.0155: : 219iter [00:07, 37.19iter/s]
Best score: 36.0155: : 220iter [00:07, 37.19iter/s]
Best score: 36.0155: : 221iter [00:07, 37.60iter/s]
Best score: 36.0155: : 221iter [00:07, 37.60iter/s]
Best score: 36.0155: : 222iter [00:07, 37.60iter/s]
Best score: 36.0155: : 223iter [00:07, 37.60iter/s]
Best score: 36.0155: : 224iter [00:07, 37.60iter/s]
Best score: 36.0155: : 225iter [00:07, 38.20iter/s]
Best score: 36.0155: : 225iter [00:07, 38.20iter/s]
Best score: 36.0155: : 226iter [00:07, 38.20iter/s]
Best score: 36.0155: : 227iter [00:08, 38.20iter/s]
Best score: 36.0155: : 228iter [00:08, 38.20iter/s]
Best score: 36.0155: : 229iter [00:08, 38.71iter/s]
Best score: 32.6487: : 229iter [00:08, 38.71iter/s]
Best score: 32.6487: : 230iter [00:08, 38.71iter/s]
Best score: 32.6487: : 231iter [00:08, 38.71iter/s]
Best score: 32.6487: : 232iter [00:08, 38.71iter/s]
Best score: 32.6487: : 233iter [00:08, 38.79iter/s]
Best score: 32.6487: : 233iter [00:08, 38.79iter/s]
Best score: 32.6487: : 234iter [00:08, 38.79iter/s]
Best score: 32.6487: : 235iter [00:08, 38.79iter/s]
Best score: 32.6487: : 236iter [00:08, 38.79iter/s]
Best score: 32.6487: : 237iter [00:08, 38.79iter/s]
Best score: 32.6487: : 238iter [00:08, 39.27iter/s]
Best score: 32.6487: : 238iter [00:08, 39.27iter/s]
Best score: 24.4795: : 239iter [00:08, 39.27iter/s]
Best score: 24.4795: : 240iter [00:08, 39.27iter/s]
Best score: 24.4795: : 241iter [00:08, 39.27iter/s]
Best score: 24.4795: : 242iter [00:08, 39.14iter/s]
Best score: 24.4795: : 242iter [00:08, 39.14iter/s]
Best score: 24.4795: : 243iter [00:08, 39.14iter/s]
Best score: 24.4795: : 244iter [00:08, 39.14iter/s]
Best score: 24.4795: : 245iter [00:08, 39.14iter/s]
Best score: 24.4795: : 246iter [00:08, 39.31iter/s]
Best score: 24.4795: : 246iter [00:08, 39.31iter/s]
Best score: 24.4795: : 247iter [00:08, 39.31iter/s]
Best score: 24.4795: : 248iter [00:08, 39.31iter/s]
[ITER 250] Best: 21.8354
[PARAMS] Current best parameters:
  fx: 464.6150
  fy: 465.3858
  px: 978.9602
  py: 760.0363
  k1: 0.05724025
  k2: 0.02268474
  k3: -0.01613091
  k4: 0.00281062
  p1: 0.00394270
  p2: -0.02971869
  p3: -0.00240478
  p4: 0.00286051
  s1: 0.0154
  s2: -0.0026
  s3: 0.0296
  s4: -0.0031
  tilt_x: 0.0054
  tilt_y: -0.0007
  scale: 3.0332
  rotation: -0.2197

Best score: 21.8354: : 249iter [00:08, 39.31iter/s]
Best score: 21.8354: : 250iter [00:08, 39.13iter/s]
Best score: 21.8354: : 250iter [00:08, 39.13iter/s]
Best score: 21.8354: : 251iter [00:08, 39.13iter/s]
Best score: 21.8354: : 252iter [00:08, 39.13iter/s]
Best score: 21.8354: : 253iter [00:08, 39.13iter/s]
Best score: 21.8354: : 254iter [00:08, 32.14iter/s]
Best score: 21.8354: : 254iter [00:08, 32.14iter/s]
Best score: 21.8354: : 255iter [00:08, 32.14iter/s]
Best score: 21.8354: : 256iter [00:08, 32.14iter/s]
Best score: 21.8354: : 257iter [00:08, 32.14iter/s]
Best score: 21.8354: : 258iter [00:08, 33.99iter/s]
Best score: 21.8354: : 258iter [00:08, 33.99iter/s]
Best score: 21.8354: : 259iter [00:08, 33.99iter/s]
Best score: 21.8354: : 260iter [00:08, 33.99iter/s]
Best score: 21.8354: : 261iter [00:08, 33.99iter/s]
Best score: 21.8354: : 262iter [00:08, 35.20iter/s]
Best score: 21.8354: : 262iter [00:08, 35.20iter/s]
Best score: 21.8354: : 263iter [00:08, 35.20iter/s]
Best score: 21.8354: : 264iter [00:09, 35.20iter/s]
Best score: 21.8354: : 265iter [00:09, 35.20iter/s]
Best score: 21.8354: : 266iter [00:09, 36.43iter/s]
Best score: 21.8354: : 266iter [00:09, 36.43iter/s]
Best score: 21.8354: : 267iter [00:09, 36.43iter/s]
Best score: 21.8354: : 268iter [00:09, 36.43iter/s]
Best score: 11.2037: : 269iter [00:09, 36.43iter/s]
Best score: 11.2037: : 270iter [00:09, 37.10iter/s]
Best score: 11.2037: : 270iter [00:09, 37.10iter/s]
Best score: 11.2037: : 271iter [00:09, 37.10iter/s]
Best score: 11.2037: : 272iter [00:09, 37.10iter/s]
Best score: 11.2037: : 273iter [00:09, 37.10iter/s]
Best score: 11.2037: : 274iter [00:09, 37.10iter/s]
Best score: 11.2037: : 275iter [00:09, 38.09iter/s]
Best score: 11.2037: : 275iter [00:09, 38.09iter/s]
Best score: 11.2037: : 276iter [00:09, 38.09iter/s]
Best score: 11.2037: : 277iter [00:09, 38.09iter/s]
Best score: 11.2037: : 278iter [00:09, 38.09iter/s]
Best score: 11.2037: : 279iter [00:09, 38.09iter/s]
Best score: 11.2037: : 280iter [00:09, 38.53iter/s]
Best score: 11.2037: : 280iter [00:09, 38.53iter/s]
Best score: 11.2037: : 281iter [00:09, 38.53iter/s]
Best score: 11.2037: : 282iter [00:09, 38.53iter/s]
Best score: 11.2037: : 283iter [00:09, 38.53iter/s]
Best score: 11.2037: : 284iter [00:09, 38.53iter/s]
Best score: 11.2037: : 285iter [00:09, 39.08iter/s]
Best score: 11.2037: : 285iter [00:09, 39.08iter/s]
Best score: 11.2037: : 286iter [00:09, 39.08iter/s]
Best score: 11.2037: : 287iter [00:09, 39.08iter/s]
Best score: 11.2037: : 288iter [00:09, 39.08iter/s]
Best score: 11.2037: : 289iter [00:09, 39.08iter/s]
Best score: 11.2037: : 290iter [00:09, 39.26iter/s]
Best score: 11.2037: : 290iter [00:09, 39.26iter/s]
Best score: 11.2037: : 291iter [00:09, 39.26iter/s]
Best score: 11.2037: : 292iter [00:09, 39.26iter/s]
Best score: 11.2037: : 293iter [00:09, 39.26iter/s]
Best score: 11.2037: : 294iter [00:09, 39.26iter/s]
Best score: 11.2037: : 295iter [00:09, 39.59iter/s]
Best score: 11.2037: : 295iter [00:09, 39.59iter/s]
Best score: 11.2037: : 296iter [00:09, 39.59iter/s]
Best score: 11.2037: : 297iter [00:09, 39.59iter/s]
Best score: 11.2037: : 298iter [00:09, 39.59iter/s]
[ITER 300] Best: 9.0742
[PARAMS] Current best parameters:
  fx: 492.3417
  fy: 491.2720
  px: 994.0324
  py: 757.3232
  k1: 0.02839250
  k2: 0.01692366
  k3: -0.01052244
  k4: 0.00185421
  p1: -0.00158457
  p2: -0.01055252
  p3: 0.00431871
  p4: -0.00511126
  s1: 0.0024
  s2: 0.0055
  s3: 0.0155
  s4: -0.0036
  tilt_x: 0.0204
  tilt_y: -0.0222
  scale: 3.0191
  rotation: -0.1884

Best score: 9.0742: : 299iter [00:09, 39.59iter/s] 
Best score: 9.0742: : 300iter [00:09, 39.52iter/s]
Best score: 9.0742: : 300iter [00:10, 39.52iter/s]
Best score: 9.0742: : 301iter [00:10, 39.52iter/s]
Best score: 9.0742: : 302iter [00:10, 39.52iter/s]
Best score: 9.0742: : 303iter [00:10, 39.52iter/s]
Best score: 9.0742: : 304iter [00:10, 32.79iter/s]
Best score: 9.0742: : 304iter [00:10, 32.79iter/s]
Best score: 9.0742: : 305iter [00:10, 32.79iter/s]
Best score: 9.0742: : 306iter [00:10, 32.79iter/s]
Best score: 9.0742: : 307iter [00:10, 32.79iter/s]
Best score: 9.0742: : 308iter [00:10, 32.79iter/s]
Best score: 9.0742: : 309iter [00:10, 34.79iter/s]
Best score: 5.3841: : 309iter [00:10, 34.79iter/s]
Best score: 5.3841: : 310iter [00:10, 34.79iter/s]
Best score: 5.3841: : 311iter [00:10, 34.79iter/s]
Best score: 5.3841: : 312iter [00:10, 34.79iter/s]
Best score: 5.3841: : 313iter [00:10, 35.85iter/s]
Best score: 5.3841: : 313iter [00:10, 35.85iter/s]
Best score: 5.3841: : 314iter [00:10, 35.85iter/s]
Best score: 5.3841: : 315iter [00:10, 35.85iter/s]
Best score: 5.3841: : 316iter [00:10, 35.85iter/s]
Best score: 5.3841: : 317iter [00:10, 36.90iter/s]
Best score: 5.3841: : 317iter [00:10, 36.90iter/s]
Best score: 5.3841: : 318iter [00:10, 36.90iter/s]
Best score: 5.3841: : 319iter [00:10, 36.90iter/s]
Best score: 5.3841: : 320iter [00:10, 36.90iter/s]
Best score: 5.3841: : 321iter [00:10, 37.54iter/s]
Best score: 5.3841: : 321iter [00:10, 37.54iter/s]
Best score: 5.3841: : 322iter [00:10, 37.54iter/s]
Best score: 5.3841: : 323iter [00:10, 37.54iter/s]
Best score: 5.3841: : 324iter [00:10, 37.54iter/s]
Best score: 5.3841: : 325iter [00:10, 38.19iter/s]
Best score: 5.3841: : 325iter [00:10, 38.19iter/s]
Best score: 5.3841: : 326iter [00:10, 38.19iter/s]
Best score: 5.3841: : 327iter [00:10, 38.19iter/s]
Best score: 5.3841: : 328iter [00:10, 38.19iter/s]
Best score: 5.3841: : 329iter [00:10, 38.65iter/s]
Best score: 4.4799: : 329iter [00:10, 38.65iter/s]
Best score: 4.4799: : 330iter [00:10, 38.65iter/s]
Best score: 4.4799: : 331iter [00:10, 38.65iter/s]
Best score: 4.4799: : 332iter [00:10, 38.65iter/s]
Best score: 4.4799: : 333iter [00:10, 38.76iter/s]
Best score: 4.4799: : 333iter [00:10, 38.76iter/s]
Best score: 4.4799: : 334iter [00:10, 38.76iter/s]
Best score: 4.4799: : 335iter [00:10, 38.76iter/s]
Best score: 4.4799: : 336iter [00:10, 38.76iter/s]
Best score: 4.4799: : 337iter [00:10, 39.04iter/s]
Best score: 4.4799: : 337iter [00:10, 39.04iter/s]
Best score: 4.4799: : 338iter [00:10, 39.04iter/s]
Best score: 4.4799: : 339iter [00:10, 39.04iter/s]
Best score: 4.4799: : 340iter [00:11, 39.04iter/s]
Best score: 4.4799: : 341iter [00:11, 39.03iter/s]
Best score: 4.4799: : 341iter [00:11, 39.03iter/s]
Best score: 4.4799: : 342iter [00:11, 39.03iter/s]
Best score: 4.4799: : 343iter [00:11, 39.03iter/s]
Best score: 4.4799: : 344iter [00:11, 39.03iter/s]
Best score: 4.4799: : 345iter [00:11, 39.30iter/s]
Best score: 4.4799: : 345iter [00:11, 39.30iter/s]
Best score: 4.4799: : 346iter [00:11, 39.30iter/s]
Best score: 4.4799: : 347iter [00:11, 39.30iter/s]
Best score: 4.4799: : 348iter [00:11, 39.30iter/s]
Best score: 4.4799: : 349iter [00:11, 38.61iter/s]
[ITER 350] Best: 3.7815
[PARAMS] Current best parameters:
  fx: 530.9626
  fy: 530.8401
  px: 996.0822
  py: 755.9761
  k1: 0.02425086
  k2: 0.00846403
  k3: -0.02814967
  k4: 0.00908175
  p1: -0.00243841
  p2: -0.02148394
  p3: 0.01218693
  p4: 0.00553396
  s1: -0.0101
  s2: 0.0028
  s3: 0.0144
  s4: -0.0128
  tilt_x: 0.0129
  tilt_y: -0.0532
  scale: 2.9165
  rotation: 0.1119

Best score: 3.7815: : 349iter [00:11, 38.61iter/s]
Best score: 3.7815: : 350iter [00:11, 38.61iter/s]
Best score: 3.7815: : 351iter [00:11, 38.61iter/s]
Best score: 3.7815: : 352iter [00:11, 38.61iter/s]
Best score: 3.7815: : 353iter [00:11, 31.34iter/s]
Best score: 3.7815: : 353iter [00:11, 31.34iter/s]
Best score: 3.7815: : 354iter [00:11, 31.34iter/s]
Best score: 3.7815: : 355iter [00:11, 31.34iter/s]
Best score: 3.7815: : 356iter [00:11, 31.34iter/s]
Best score: 3.7815: : 357iter [00:11, 31.34iter/s]
Best score: 3.7815: : 358iter [00:11, 33.94iter/s]
Best score: 3.7815: : 358iter [00:11, 33.94iter/s]
Best score: 3.1184: : 359iter [00:11, 33.94iter/s]
Best score: 3.1184: : 360iter [00:11, 33.94iter/s]
Best score: 3.1184: : 361iter [00:11, 33.94iter/s]
Best score: 3.1184: : 362iter [00:11, 35.26iter/s]
Best score: 3.1184: : 362iter [00:11, 35.26iter/s]
Best score: 3.1184: : 363iter [00:11, 35.26iter/s]
Best score: 3.1184: : 364iter [00:11, 35.26iter/s]
Best score: 3.1184: : 365iter [00:11, 35.26iter/s]
Best score: 3.1184: : 366iter [00:11, 36.35iter/s]
Best score: 3.1184: : 366iter [00:11, 36.35iter/s]
Best score: 3.1184: : 367iter [00:11, 36.35iter/s]
Best score: 3.1184: : 368iter [00:11, 36.35iter/s]
Best score: 2.6403: : 369iter [00:11, 36.35iter/s]
Best score: 2.6403: : 370iter [00:11, 36.96iter/s]
Best score: 2.6403: : 370iter [00:11, 36.96iter/s]
Best score: 2.6403: : 371iter [00:11, 36.96iter/s]
Best score: 2.6403: : 372iter [00:11, 36.96iter/s]
Best score: 2.6403: : 373iter [00:11, 36.96iter/s]
Best score: 2.6403: : 374iter [00:11, 37.60iter/s]
Best score: 2.6403: : 374iter [00:11, 37.60iter/s]
Best score: 2.6403: : 375iter [00:11, 37.60iter/s]
Best score: 2.6403: : 376iter [00:12, 37.60iter/s]
Best score: 2.6403: : 377iter [00:12, 37.60iter/s]
Best score: 2.6403: : 378iter [00:12, 37.60iter/s]
Best score: 2.6403: : 379iter [00:12, 38.42iter/s]
Best score: 2.4891: : 379iter [00:12, 38.42iter/s]
Best score: 2.4891: : 380iter [00:12, 38.42iter/s]
Best score: 2.4891: : 381iter [00:12, 38.42iter/s]
Best score: 2.4891: : 382iter [00:12, 38.42iter/s]
Best score: 2.4891: : 383iter [00:12, 38.24iter/s]
Best score: 2.4891: : 383iter [00:12, 38.24iter/s]
Best score: 2.4891: : 384iter [00:12, 38.24iter/s]
Best score: 2.4891: : 385iter [00:12, 38.24iter/s]
Best score: 2.4891: : 386iter [00:12, 38.24iter/s]
Best score: 2.4891: : 387iter [00:12, 38.24iter/s]
Best score: 2.4891: : 388iter [00:12, 38.91iter/s]
Best score: 2.4891: : 388iter [00:12, 38.91iter/s]
Best score: 2.0664: : 389iter [00:12, 38.91iter/s]
Best score: 2.0664: : 390iter [00:12, 38.91iter/s]
Best score: 2.0664: : 391iter [00:12, 38.91iter/s]
Best score: 2.0664: : 392iter [00:12, 38.95iter/s]
Best score: 2.0664: : 392iter [00:12, 38.95iter/s]
Best score: 2.0664: : 393iter [00:12, 38.95iter/s]
Best score: 2.0664: : 394iter [00:12, 38.95iter/s]
Best score: 2.0664: : 395iter [00:12, 38.95iter/s]
Best score: 2.0664: : 396iter [00:12, 31.47iter/s]
Best score: 2.0664: : 396iter [00:12, 31.47iter/s]
Best score: 2.0664: : 397iter [00:12, 31.47iter/s]
Best score: 2.0664: : 398iter [00:12, 31.47iter/s]
[ITER 400] Best: 1.8444
[PARAMS] Current best parameters:
  fx: 517.5813
  fy: 517.6503
  px: 992.5646
  py: 753.1024
  k1: 0.01150903
  k2: 0.03384930
  k3: -0.02967617
  k4: 0.00622075
  p1: 0.01017292
  p2: -0.01735090
  p3: -0.01429350
  p4: 0.00245851
  s1: 0.0094
  s2: 0.0026
  s3: 0.0076
  s4: -0.0024
  tilt_x: -0.0189
  tilt_y: -0.0295
  scale: 2.9328
  rotation: 0.2125

Best score: 1.8444: : 399iter [00:12, 31.47iter/s]
Best score: 1.8444: : 400iter [00:12, 33.30iter/s]
Best score: 1.8444: : 400iter [00:12, 33.30iter/s]
Best score: 1.8444: : 401iter [00:12, 33.30iter/s]
Best score: 1.8444: : 402iter [00:12, 33.30iter/s]
Best score: 1.8444: : 403iter [00:12, 33.30iter/s]
Best score: 1.8444: : 404iter [00:12, 29.25iter/s]
Best score: 1.8444: : 404iter [00:12, 29.25iter/s]
Best score: 1.8444: : 405iter [00:12, 29.25iter/s]
Best score: 1.8444: : 406iter [00:12, 29.25iter/s]
Best score: 1.8444: : 407iter [00:12, 29.25iter/s]
Best score: 1.8444: : 408iter [00:12, 29.25iter/s]
Best score: 1.8444: : 409iter [00:12, 32.24iter/s]
Best score: 1.4389: : 409iter [00:13, 32.24iter/s]
Best score: 1.4389: : 410iter [00:13, 32.24iter/s]
Best score: 1.4389: : 411iter [00:13, 32.24iter/s]
Best score: 1.4389: : 412iter [00:13, 32.24iter/s]
Best score: 1.4389: : 413iter [00:13, 33.94iter/s]
Best score: 1.4389: : 413iter [00:13, 33.94iter/s]
Best score: 1.4389: : 414iter [00:13, 33.94iter/s]
Best score: 1.4389: : 415iter [00:13, 33.94iter/s]
Best score: 1.4389: : 416iter [00:13, 33.94iter/s]
Best score: 1.4389: : 417iter [00:13, 35.46iter/s]
Best score: 1.4389: : 417iter [00:13, 35.46iter/s]
Best score: 1.4389: : 418iter [00:13, 35.46iter/s]
Best score: 1.1677: : 419iter [00:13, 35.46iter/s]
Best score: 1.1677: : 420iter [00:13, 35.46iter/s]
Best score: 1.1677: : 421iter [00:13, 36.32iter/s]
Best score: 1.1677: : 421iter [00:13, 36.32iter/s]
Best score: 1.1677: : 422iter [00:13, 36.32iter/s]
Best score: 1.1677: : 423iter [00:13, 36.32iter/s]
Best score: 1.1677: : 424iter [00:13, 36.32iter/s]
Best score: 1.1677: : 425iter [00:13, 36.32iter/s]
Best score: 1.1677: : 426iter [00:13, 37.59iter/s]
Best score: 1.1677: : 426iter [00:13, 37.59iter/s]
Best score: 1.1677: : 427iter [00:13, 37.59iter/s]
Best score: 1.1677: : 428iter [00:13, 37.59iter/s]
Best score: 1.1677: : 429iter [00:13, 37.59iter/s]
Best score: 1.1677: : 430iter [00:13, 37.89iter/s]
Best score: 1.1677: : 430iter [00:13, 37.89iter/s]
Best score: 1.1677: : 431iter [00:13, 37.89iter/s]
Best score: 1.1677: : 432iter [00:13, 37.89iter/s]
Best score: 1.1677: : 433iter [00:13, 37.89iter/s]
Best score: 1.1677: : 434iter [00:13, 37.89iter/s]
Best score: 1.1677: : 435iter [00:13, 38.65iter/s]
Best score: 1.1677: : 435iter [00:13, 38.65iter/s]
Best score: 1.1677: : 436iter [00:13, 38.65iter/s]
Best score: 1.1677: : 437iter [00:13, 38.65iter/s]
Best score: 1.1677: : 438iter [00:13, 38.65iter/s]
Best score: 1.1381: : 439iter [00:13, 38.65iter/s]
Best score: 1.1381: : 440iter [00:13, 38.88iter/s]
Best score: 1.1381: : 440iter [00:13, 38.88iter/s]
Best score: 1.1381: : 441iter [00:13, 38.88iter/s]
Best score: 1.1381: : 442iter [00:13, 38.88iter/s]
Best score: 1.1381: : 443iter [00:13, 38.88iter/s]
Best score: 1.1381: : 444iter [00:13, 38.88iter/s]
Best score: 1.1381: : 445iter [00:13, 39.43iter/s]
Best score: 1.1381: : 445iter [00:13, 39.43iter/s]
Best score: 1.1381: : 446iter [00:13, 39.43iter/s]
Best score: 1.1381: : 447iter [00:13, 39.43iter/s]
Best score: 1.1381: : 448iter [00:14, 39.43iter/s]
[ITER 450] Best: 1.0241
[PARAMS] Current best parameters:
  fx: 520.2728
  fy: 520.3565
  px: 991.2684
  py: 754.3999
  k1: 0.01222074
  k2: 0.04145207
  k3: -0.04419655
  k4: 0.01143664
  p1: -0.00487249
  p2: -0.02487723
  p3: 0.00200025
  p4: 0.00550850
  s1: 0.0044
  s2: -0.0024
  s3: 0.0200
  s4: -0.0103
  tilt_x: 0.0131
  tilt_y: -0.0366
  scale: 2.9358
  rotation: 0.3142

Best score: 1.0241: : 449iter [00:14, 39.43iter/s]
Best score: 1.0241: : 450iter [00:14, 39.41iter/s]
Best score: 1.0241: : 450iter [00:14, 39.41iter/s]
Best score: 1.0241: : 451iter [00:14, 39.41iter/s]
Best score: 1.0241: : 452iter [00:14, 39.41iter/s]
Best score: 1.0241: : 453iter [00:14, 39.41iter/s]
Best score: 1.0241: : 454iter [00:14, 32.71iter/s]
Best score: 1.0241: : 454iter [00:14, 32.71iter/s]
Best score: 1.0241: : 455iter [00:14, 32.71iter/s]
Best score: 1.0241: : 456iter [00:14, 32.71iter/s]
Best score: 1.0241: : 457iter [00:14, 32.71iter/s]
Best score: 1.0241: : 458iter [00:14, 32.71iter/s]
Best score: 1.0241: : 459iter [00:14, 34.74iter/s]
Best score: 1.0241: : 459iter [00:14, 34.74iter/s]
Best score: 1.0241: : 460iter [00:14, 34.74iter/s]
Best score: 1.0241: : 461iter [00:14, 34.74iter/s]
Best score: 1.0241: : 462iter [00:14, 34.74iter/s]
Best score: 1.0241: : 463iter [00:14, 35.84iter/s]
Best score: 1.0241: : 463iter [00:14, 35.84iter/s]
Best score: 1.0241: : 464iter [00:14, 35.84iter/s]
Best score: 1.0241: : 465iter [00:14, 35.84iter/s]
Best score: 1.0241: : 466iter [00:14, 35.84iter/s]
Best score: 1.0241: : 467iter [00:14, 35.84iter/s]
Best score: 1.0241: : 468iter [00:14, 37.14iter/s]
Best score: 1.0241: : 468iter [00:14, 37.14iter/s]
Best score: 1.0241: : 469iter [00:14, 37.14iter/s]
Best score: 1.0241: : 470iter [00:14, 37.14iter/s]
Best score: 1.0241: : 471iter [00:14, 37.14iter/s]
Best score: 1.0241: : 472iter [00:14, 37.55iter/s]
Best score: 1.0241: : 472iter [00:14, 37.55iter/s]
Best score: 1.0241: : 473iter [00:14, 37.55iter/s]
Best score: 1.0241: : 474iter [00:14, 37.55iter/s]
Best score: 1.0241: : 475iter [00:14, 37.55iter/s]
Best score: 1.0241: : 476iter [00:14, 37.55iter/s]
Best score: 1.0241: : 477iter [00:14, 38.34iter/s]
Best score: 1.0241: : 477iter [00:14, 38.34iter/s]
Best score: 1.0241: : 478iter [00:14, 38.34iter/s]
Best score: 1.0041: : 479iter [00:14, 38.34iter/s]
Best score: 1.0041: : 480iter [00:14, 38.34iter/s]
Best score: 1.0041: : 481iter [00:14, 38.62iter/s]
Best score: 1.0041: : 481iter [00:14, 38.62iter/s]
Best score: 1.0041: : 482iter [00:14, 38.62iter/s]
Best score: 1.0041: : 483iter [00:14, 38.62iter/s]
Best score: 1.0041: : 484iter [00:14, 38.62iter/s]
Best score: 1.0041: : 485iter [00:15, 38.62iter/s]
Best score: 1.0041: : 486iter [00:15, 39.15iter/s]
Best score: 1.0041: : 486iter [00:15, 39.15iter/s]
Best score: 1.0041: : 487iter [00:15, 39.15iter/s]
Best score: 1.0041: : 488iter [00:15, 39.15iter/s]
Best score: 1.0041: : 489iter [00:15, 39.15iter/s]
Best score: 1.0041: : 490iter [00:15, 39.01iter/s]
Best score: 1.0041: : 490iter [00:15, 39.01iter/s]
Best score: 1.0041: : 491iter [00:15, 39.01iter/s]
Best score: 1.0041: : 492iter [00:15, 39.01iter/s]
Best score: 1.0041: : 493iter [00:15, 39.01iter/s]
Best score: 1.0041: : 494iter [00:15, 39.01iter/s]
Best score: 1.0041: : 495iter [00:15, 39.40iter/s]
Best score: 1.0041: : 495iter [00:15, 39.40iter/s]
Best score: 1.0041: : 496iter [00:15, 39.40iter/s]
Best score: 1.0041: : 497iter [00:15, 39.40iter/s]
Best score: 1.0041: : 498iter [00:15, 39.40iter/s]
Best score: 1.0041: : 499iter [00:15, 39.50iter/s]
[ITER 500] Best: 0.7445
[PARAMS] Current best parameters:
  fx: 516.4809
  fy: 515.8358
  px: 997.8449
  py: 752.7735
  k1: 0.06246308
  k2: -0.03501955
  k3: 0.00358689
  k4: 0.00080892
  p1: -0.00347708
  p2: -0.01003495
  p3: 0.00222470
  p4: 0.00365111
  s1: -0.0052
  s2: 0.0000
  s3: 0.0017
  s4: -0.0004
  tilt_x: 0.0023
  tilt_y: -0.0388
  scale: 2.8894
  rotation: 0.1623

Best score: 0.7445: : 499iter [00:15, 39.50iter/s]
Best score: 0.7445: : 500iter [00:15, 39.50iter/s]
Best score: 0.7445: : 501iter [00:15, 39.50iter/s]
Best score: 0.7445: : 502iter [00:15, 39.50iter/s]
Best score: 0.7445: : 503iter [00:15, 32.40iter/s]
Best score: 0.7445: : 503iter [00:15, 32.40iter/s]
Best score: 0.7445: : 504iter [00:15, 32.40iter/s]
Best score: 0.7445: : 505iter [00:15, 32.40iter/s]
Best score: 0.7445: : 506iter [00:15, 32.40iter/s]
Best score: 0.7445: : 507iter [00:15, 34.14iter/s]
Best score: 0.7445: : 507iter [00:15, 34.14iter/s]
Best score: 0.7445: : 508iter [00:15, 34.14iter/s]
Best score: 0.6467: : 509iter [00:15, 34.14iter/s]
Best score: 0.6467: : 510iter [00:15, 34.14iter/s]
Best score: 0.6467: : 511iter [00:15, 35.40iter/s]
Best score: 0.6467: : 511iter [00:15, 35.40iter/s]
Best score: 0.6467: : 512iter [00:15, 35.40iter/s]
Best score: 0.6467: : 513iter [00:15, 35.40iter/s]
Best score: 0.6467: : 514iter [00:15, 35.40iter/s]
Best score: 0.6467: : 515iter [00:15, 36.61iter/s]
Best score: 0.6467: : 515iter [00:15, 36.61iter/s]
Best score: 0.6467: : 516iter [00:15, 36.61iter/s]
Best score: 0.6467: : 517iter [00:15, 36.61iter/s]
Best score: 0.6467: : 518iter [00:15, 36.61iter/s]
Best score: 0.6204: : 519iter [00:15, 36.61iter/s]
Best score: 0.6204: : 520iter [00:15, 37.56iter/s]
Best score: 0.6204: : 520iter [00:15, 37.56iter/s]
Best score: 0.6204: : 521iter [00:16, 37.56iter/s]
Best score: 0.6204: : 522iter [00:16, 37.56iter/s]
Best score: 0.6204: : 523iter [00:16, 37.56iter/s]
Best score: 0.6204: : 524iter [00:16, 37.56iter/s]
Best score: 0.6204: : 525iter [00:16, 38.38iter/s]
Best score: 0.6204: : 525iter [00:16, 38.38iter/s]
Best score: 0.6204: : 526iter [00:16, 38.38iter/s]
Best score: 0.6204: : 527iter [00:16, 38.38iter/s]
Best score: 0.6204: : 528iter [00:16, 38.38iter/s]
Best score: 0.6204: : 529iter [00:16, 38.74iter/s]
Best score: 0.4897: : 529iter [00:16, 38.74iter/s]
Best score: 0.4897: : 530iter [00:16, 38.74iter/s]
Best score: 0.4897: : 531iter [00:16, 38.74iter/s]
Best score: 0.4897: : 532iter [00:16, 38.74iter/s]
Best score: 0.4897: : 533iter [00:16, 38.94iter/s]
Best score: 0.4897: : 533iter [00:16, 38.94iter/s]
Best score: 0.4897: : 534iter [00:16, 38.94iter/s]
Best score: 0.4897: : 535iter [00:16, 38.94iter/s]
Best score: 0.4897: : 536iter [00:16, 38.94iter/s]
Best score: 0.4897: : 537iter [00:16, 39.24iter/s]
Best score: 0.4897: : 537iter [00:16, 39.24iter/s]
Best score: 0.4897: : 538iter [00:16, 39.24iter/s]
Best score: 0.4158: : 539iter [00:16, 39.24iter/s]
Best score: 0.4158: : 540iter [00:16, 39.24iter/s]
Best score: 0.4158: : 541iter [00:16, 39.32iter/s]
Best score: 0.4158: : 541iter [00:16, 39.32iter/s]
Best score: 0.4158: : 542iter [00:16, 39.32iter/s]
Best score: 0.4158: : 543iter [00:16, 39.32iter/s]
Best score: 0.4158: : 544iter [00:16, 39.32iter/s]
Best score: 0.4158: : 545iter [00:16, 39.50iter/s]
Best score: 0.4158: : 545iter [00:16, 39.50iter/s]
Best score: 0.4158: : 546iter [00:16, 39.50iter/s]
Best score: 0.4158: : 547iter [00:16, 39.50iter/s]
Best score: 0.4158: : 548iter [00:16, 39.50iter/s]
[ITER 550] Best: 0.3913
[PARAMS] Current best parameters:
  fx: 507.3942
  fy: 506.9777
  px: 998.8957
  py: 749.9839
  k1: 0.07994950
  k2: -0.06696252
  k3: 0.03013152
  k4: -0.00583751
  p1: -0.01157000
  p2: -0.00268846
  p3: 0.00354274
  p4: 0.00327524
  s1: -0.0071
  s2: -0.0023
  s3: 0.0122
  s4: -0.0029
  tilt_x: 0.0055
  tilt_y: -0.0268
  scale: 2.9211
  rotation: 0.1748

Best score: 0.3913: : 549iter [00:16, 39.50iter/s]
Best score: 0.3913: : 550iter [00:16, 39.47iter/s]
Best score: 0.3913: : 550iter [00:16, 39.47iter/s]
Best score: 0.3913: : 551iter [00:16, 39.47iter/s]
Best score: 0.3913: : 552iter [00:16, 39.47iter/s]
Best score: 0.3913: : 553iter [00:16, 39.47iter/s]
Best score: 0.3913: : 554iter [00:16, 32.39iter/s]
Best score: 0.3913: : 554iter [00:16, 32.39iter/s]
Best score: 0.3913: : 555iter [00:16, 32.39iter/s]
Best score: 0.3913: : 556iter [00:16, 32.39iter/s]
Best score: 0.3913: : 557iter [00:16, 32.39iter/s]
Best score: 0.3913: : 558iter [00:16, 34.25iter/s]
Best score: 0.3913: : 558iter [00:17, 34.25iter/s]
Best score: 0.3913: : 559iter [00:17, 34.25iter/s]
Best score: 0.3913: : 560iter [00:17, 34.25iter/s]
Best score: 0.3913: : 561iter [00:17, 34.25iter/s]
Best score: 0.3913: : 562iter [00:17, 35.50iter/s]
Best score: 0.3913: : 562iter [00:17, 35.50iter/s]
Best score: 0.3913: : 563iter [00:17, 35.50iter/s]
Best score: 0.3913: : 564iter [00:17, 35.50iter/s]
Best score: 0.3913: : 565iter [00:17, 35.50iter/s]
Best score: 0.3913: : 566iter [00:17, 36.64iter/s]
Best score: 0.3913: : 566iter [00:17, 36.64iter/s]
Best score: 0.3913: : 567iter [00:17, 36.64iter/s]
Best score: 0.3913: : 568iter [00:17, 36.64iter/s]
Best score: 0.3793: : 569iter [00:17, 36.64iter/s]
Best score: 0.3793: : 570iter [00:17, 37.31iter/s]
Best score: 0.3793: : 570iter [00:17, 37.31iter/s]
Best score: 0.3793: : 571iter [00:17, 37.31iter/s]
Best score: 0.3793: : 572iter [00:17, 37.31iter/s]
Best score: 0.3793: : 573iter [00:17, 37.31iter/s]
Best score: 0.3793: : 574iter [00:17, 37.31iter/s]
Best score: 0.3793: : 575iter [00:17, 38.30iter/s]
Best score: 0.3793: : 575iter [00:17, 38.30iter/s]
Best score: 0.3793: : 576iter [00:17, 38.30iter/s]
Best score: 0.3793: : 577iter [00:17, 38.30iter/s]
Best score: 0.3793: : 578iter [00:17, 38.30iter/s]
Best score: 0.3793: : 579iter [00:17, 38.30iter/s]
Best score: 0.3793: : 580iter [00:17, 38.69iter/s]
Best score: 0.3793: : 580iter [00:17, 38.69iter/s]
Best score: 0.3793: : 581iter [00:17, 38.69iter/s]
Best score: 0.3793: : 582iter [00:17, 38.69iter/s]
Best score: 0.3793: : 583iter [00:17, 38.69iter/s]
Best score: 0.3793: : 584iter [00:17, 38.69iter/s]
Best score: 0.3793: : 585iter [00:17, 39.26iter/s]
Best score: 0.3793: : 585iter [00:17, 39.26iter/s]
Best score: 0.3793: : 586iter [00:17, 39.26iter/s]
Best score: 0.3793: : 587iter [00:17, 39.26iter/s]
Best score: 0.3793: : 588iter [00:17, 39.26iter/s]
Best score: 0.3737: : 589iter [00:17, 39.26iter/s]
Best score: 0.3737: : 590iter [00:17, 39.34iter/s]
Best score: 0.3737: : 590iter [00:17, 39.34iter/s]
Best score: 0.3737: : 591iter [00:17, 39.34iter/s]
Best score: 0.3737: : 592iter [00:17, 39.34iter/s]
Best score: 0.3737: : 593iter [00:17, 39.34iter/s]
Best score: 0.3737: : 594iter [00:17, 39.47iter/s]
Best score: 0.3737: : 594iter [00:17, 39.47iter/s]
Best score: 0.3737: : 595iter [00:17, 39.47iter/s]
Best score: 0.3737: : 596iter [00:17, 39.47iter/s]
Best score: 0.3737: : 597iter [00:17, 39.47iter/s]
Best score: 0.3737: : 598iter [00:17, 39.59iter/s]
Best score: 0.3737: : 598iter [00:18, 39.59iter/s]
[ITER 600] Best: 0.3545
[PARAMS] Current best parameters:
  fx: 506.5424
  fy: 506.0711
  px: 1000.3696
  py: 750.2399
  k1: 0.07866390
  k2: -0.06284742
  k3: 0.02794216
  k4: -0.00551956
  p1: -0.00743819
  p2: 0.00542996
  p3: -0.00027835
  p4: -0.00062809
  s1: -0.0084
  s2: 0.0010
  s3: 0.0132
  s4: 0.0001
  tilt_x: -0.0016
  tilt_y: -0.0164
  scale: 2.9179
  rotation: 0.1766

Best score: 0.3545: : 599iter [00:18, 39.59iter/s]
Best score: 0.3545: : 600iter [00:18, 39.59iter/s]
Best score: 0.3545: : 601iter [00:18, 39.59iter/s]
Best score: 0.3545: : 602iter [00:18, 31.96iter/s]
Best score: 0.3545: : 602iter [00:18, 31.96iter/s]
Best score: 0.3545: : 603iter [00:18, 31.96iter/s]
Best score: 0.3545: : 604iter [00:18, 31.96iter/s]
Best score: 0.3545: : 605iter [00:18, 31.96iter/s]
Best score: 0.3545: : 606iter [00:18, 33.87iter/s]
Best score: 0.3545: : 606iter [00:18, 33.87iter/s]
Best score: 0.3545: : 607iter [00:18, 33.87iter/s]
Best score: 0.3545: : 608iter [00:18, 33.87iter/s]
Best score: 0.3545: : 609iter [00:18, 33.87iter/s]
Best score: 0.3545: : 610iter [00:18, 35.23iter/s]
Best score: 0.3545: : 610iter [00:18, 35.23iter/s]
Best score: 0.3545: : 611iter [00:18, 35.23iter/s]
Best score: 0.3545: : 612iter [00:18, 35.23iter/s]
Best score: 0.3545: : 613iter [00:18, 35.23iter/s]
Best score: 0.3545: : 614iter [00:18, 35.23iter/s]
Best score: 0.3545: : 615iter [00:18, 36.86iter/s]
Best score: 0.3545: : 615iter [00:18, 36.86iter/s]
Best score: 0.3545: : 616iter [00:18, 36.86iter/s]
Best score: 0.3545: : 617iter [00:18, 36.86iter/s]
Best score: 0.3545: : 618iter [00:18, 36.86iter/s]
Best score: 0.3442: : 619iter [00:18, 36.86iter/s]
Best score: 0.3442: : 620iter [00:18, 37.80iter/s]
Best score: 0.3442: : 620iter [00:18, 37.80iter/s]
Best score: 0.3442: : 621iter [00:18, 37.80iter/s]
Best score: 0.3442: : 622iter [00:18, 37.80iter/s]
Best score: 0.3442: : 623iter [00:18, 37.80iter/s]
Best score: 0.3442: : 624iter [00:18, 37.80iter/s]
Best score: 0.3442: : 625iter [00:18, 38.59iter/s]
Best score: 0.3442: : 625iter [00:18, 38.59iter/s]
Best score: 0.3442: : 626iter [00:18, 38.59iter/s]
Best score: 0.3442: : 627iter [00:18, 38.59iter/s]
Best score: 0.3442: : 628iter [00:18, 38.59iter/s]
Best score: 0.3442: : 629iter [00:18, 38.59iter/s]
Best score: 0.3442: : 630iter [00:18, 38.83iter/s]
Best score: 0.3442: : 630iter [00:18, 38.83iter/s]
Best score: 0.3442: : 631iter [00:18, 38.83iter/s]
Best score: 0.3442: : 632iter [00:18, 38.83iter/s]
Best score: 0.3442: : 633iter [00:18, 38.83iter/s]
Best score: 0.3442: : 634iter [00:18, 39.05iter/s]
Best score: 0.3442: : 634iter [00:19, 39.05iter/s]
Best score: 0.3442: : 635iter [00:19, 39.05iter/s]
Best score: 0.3442: : 636iter [00:19, 39.05iter/s]
Best score: 0.3442: : 637iter [00:19, 39.05iter/s]
Best score: 0.3442: : 638iter [00:19, 39.19iter/s]
Best score: 0.3442: : 638iter [00:19, 39.19iter/s]
Best score: 0.3442: : 639iter [00:19, 39.19iter/s]
Best score: 0.3442: : 640iter [00:19, 39.19iter/s]
Best score: 0.3442: : 641iter [00:19, 39.19iter/s]
Best score: 0.3442: : 642iter [00:19, 39.07iter/s]
Best score: 0.3442: : 642iter [00:19, 39.07iter/s]
Best score: 0.3442: : 643iter [00:19, 39.07iter/s]
Best score: 0.3442: : 644iter [00:19, 39.07iter/s]
Best score: 0.3442: : 645iter [00:19, 39.07iter/s]
Best score: 0.3442: : 646iter [00:19, 39.07iter/s]
Best score: 0.3442: : 647iter [00:19, 39.46iter/s]
Best score: 0.3442: : 647iter [00:19, 39.46iter/s]
Best score: 0.3442: : 648iter [00:19, 39.46iter/s]
[ITER 650] Best: 0.3442
[PARAMS] Current best parameters:
  fx: 506.8214
  fy: 506.2846
  px: 999.1094
  py: 750.4712
  k1: 0.07580832
  k2: -0.05505892
  k3: 0.02149518
  k4: -0.00387119
  p1: -0.01348630
  p2: -0.00414919
  p3: 0.01103970
  p4: 0.00100486
  s1: -0.0116
  s2: -0.0007
  s3: 0.0090
  s4: -0.0017
  tilt_x: 0.0113
  tilt_y: -0.0301
  scale: 2.9171
  rotation: 0.1350

Best score: 0.3442: : 649iter [00:19, 39.46iter/s]
Best score: 0.3442: : 650iter [00:19, 39.46iter/s]
Best score: 0.3442: : 651iter [00:19, 32.46iter/s]
Best score: 0.3442: : 651iter [00:19, 32.46iter/s]
Best score: 0.3442: : 652iter [00:19, 32.46iter/s]
Best score: 0.3442: : 653iter [00:19, 32.46iter/s]
Best score: 0.3442: : 654iter [00:19, 32.46iter/s]
Best score: 0.3442: : 655iter [00:19, 34.28iter/s]
Best score: 0.3442: : 655iter [00:19, 34.28iter/s]
Best score: 0.3442: : 656iter [00:19, 34.28iter/s]
Best score: 0.3442: : 657iter [00:19, 34.28iter/s]
Best score: 0.3442: : 658iter [00:19, 34.28iter/s]
Best score: 0.3318: : 659iter [00:19, 34.28iter/s]
Best score: 0.3318: : 660iter [00:19, 35.89iter/s]
Best score: 0.3318: : 660iter [00:19, 35.89iter/s]
Best score: 0.3318: : 661iter [00:19, 35.89iter/s]
Best score: 0.3318: : 662iter [00:19, 35.89iter/s]
Best score: 0.3318: : 663iter [00:19, 35.89iter/s]
Best score: 0.3318: : 664iter [00:19, 35.89iter/s]
Best score: 0.3318: : 665iter [00:19, 37.27iter/s]
Best score: 0.3318: : 665iter [00:19, 37.27iter/s]
Best score: 0.3318: : 666iter [00:19, 37.27iter/s]
Best score: 0.3318: : 667iter [00:19, 37.27iter/s]
Best score: 0.3318: : 668iter [00:19, 37.27iter/s]
Best score: 0.3318: : 669iter [00:19, 37.96iter/s]
Best score: 0.3318: : 669iter [00:19, 37.96iter/s]
Best score: 0.3318: : 670iter [00:20, 37.96iter/s]
Best score: 0.3318: : 671iter [00:20, 37.96iter/s]
Best score: 0.3318: : 672iter [00:20, 37.96iter/s]
Best score: 0.3318: : 673iter [00:20, 38.29iter/s]
Best score: 0.3318: : 673iter [00:20, 38.29iter/s]
Best score: 0.3318: : 674iter [00:20, 38.29iter/s]
Best score: 0.3318: : 675iter [00:20, 38.29iter/s]
Best score: 0.3318: : 676iter [00:20, 38.29iter/s]
Best score: 0.3318: : 677iter [00:20, 38.29iter/s]
Best score: 0.3318: : 678iter [00:20, 38.90iter/s]
Best score: 0.3318: : 678iter [00:20, 38.90iter/s]
Best score: 0.3318: : 679iter [00:20, 38.90iter/s]
Best score: 0.3318: : 680iter [00:20, 38.90iter/s]
Best score: 0.3318: : 681iter [00:20, 38.90iter/s]
Best score: 0.3318: : 682iter [00:20, 39.03iter/s]
Best score: 0.3318: : 682iter [00:20, 39.03iter/s]
Best score: 0.3318: : 683iter [00:20, 39.03iter/s]
Best score: 0.3318: : 684iter [00:20, 39.03iter/s]
Best score: 0.3318: : 685iter [00:20, 39.03iter/s]
Best score: 0.3318: : 686iter [00:20, 39.03iter/s]
Best score: 0.3318: : 687iter [00:20, 39.58iter/s]
Best score: 0.3318: : 687iter [00:20, 39.58iter/s]
Best score: 0.3318: : 688iter [00:20, 39.58iter/s]
Best score: 0.3318: : 689iter [00:20, 39.58iter/s]
Best score: 0.3318: : 690iter [00:20, 39.58iter/s]
Best score: 0.3318: : 691iter [00:20, 39.22iter/s]
Best score: 0.3318: : 691iter [00:20, 39.22iter/s]
Best score: 0.3318: : 692iter [00:20, 39.22iter/s]
Best score: 0.3318: : 693iter [00:20, 39.22iter/s]
Best score: 0.3318: : 694iter [00:20, 39.22iter/s]
Best score: 0.3318: : 695iter [00:20, 39.22iter/s]
Best score: 0.3318: : 696iter [00:20, 39.59iter/s]
Best score: 0.3318: : 696iter [00:20, 39.59iter/s]
Best score: 0.3318: : 697iter [00:20, 39.59iter/s]
Best score: 0.3318: : 698iter [00:20, 39.59iter/s]
[ITER 700] Best: 0.3277
[PARAMS] Current best parameters:
  fx: 509.7920
  fy: 509.2591
  px: 1000.7763
  py: 750.4584
  k1: 0.05774558
  k2: -0.04416989
  k3: 0.02173075
  k4: -0.00491595
  p1: -0.00925045
  p2: 0.00121225
  p3: 0.00095940
  p4: 0.00204250
  s1: -0.0076
  s2: -0.0007
  s3: 0.0147
  s4: -0.0029
  tilt_x: 0.0028
  tilt_y: -0.0273
  scale: 2.9451
  rotation: 0.1394

Best score: 0.3277: : 699iter [00:20, 39.59iter/s]
Best score: 0.3277: : 700iter [00:20, 39.49iter/s]
Best score: 0.3277: : 700iter [00:20, 39.49iter/s]
Best score: 0.3277: : 701iter [00:20, 39.49iter/s]
Best score: 0.3277: : 702iter [00:20, 39.49iter/s]
Best score: 0.3277: : 703iter [00:20, 39.49iter/s]
Best score: 0.3277: : 704iter [00:20, 32.41iter/s]
Best score: 0.3277: : 704iter [00:21, 32.41iter/s]
Best score: 0.3277: : 705iter [00:21, 32.41iter/s]
Best score: 0.3277: : 706iter [00:21, 32.41iter/s]
Best score: 0.3277: : 707iter [00:21, 32.41iter/s]
Best score: 0.3277: : 708iter [00:21, 28.34iter/s]
Best score: 0.3277: : 708iter [00:21, 28.34iter/s]
Best score: 0.3234: : 709iter [00:21, 28.34iter/s]
Best score: 0.3234: : 710iter [00:21, 28.34iter/s]
Best score: 0.3234: : 711iter [00:21, 28.34iter/s]
Best score: 0.3234: : 712iter [00:21, 30.70iter/s]
Best score: 0.3234: : 712iter [00:21, 30.70iter/s]
Best score: 0.3234: : 713iter [00:21, 30.70iter/s]
Best score: 0.3234: : 714iter [00:21, 30.70iter/s]
Best score: 0.3234: : 715iter [00:21, 30.70iter/s]
Best score: 0.3234: : 716iter [00:21, 32.87iter/s]
Best score: 0.3234: : 716iter [00:21, 32.87iter/s]
Best score: 0.3234: : 717iter [00:21, 32.87iter/s]
Best score: 0.3234: : 718iter [00:21, 32.87iter/s]
Best score: 0.3223: : 719iter [00:21, 32.87iter/s]
Best score: 0.3223: : 720iter [00:21, 34.39iter/s]
Best score: 0.3223: : 720iter [00:21, 34.39iter/s]
Best score: 0.3223: : 721iter [00:21, 34.39iter/s]
Best score: 0.3223: : 722iter [00:21, 34.39iter/s]
Best score: 0.3223: : 723iter [00:21, 34.39iter/s]
Best score: 0.3223: : 724iter [00:21, 34.39iter/s]
Best score: 0.3223: : 725iter [00:21, 36.29iter/s]
Best score: 0.3223: : 725iter [00:21, 36.29iter/s]
Best score: 0.3223: : 726iter [00:21, 36.29iter/s]
Best score: 0.3223: : 727iter [00:21, 36.29iter/s]
Best score: 0.3223: : 728iter [00:21, 36.29iter/s]
Best score: 0.3223: : 729iter [00:21, 37.19iter/s]
Best score: 0.3223: : 729iter [00:21, 37.19iter/s]
Best score: 0.3223: : 730iter [00:21, 37.19iter/s]
Best score: 0.3223: : 731iter [00:21, 37.19iter/s]
Best score: 0.3223: : 732iter [00:21, 37.19iter/s]
Best score: 0.3223: : 733iter [00:21, 37.63iter/s]
Best score: 0.3223: : 733iter [00:21, 37.63iter/s]
Best score: 0.3223: : 734iter [00:21, 37.63iter/s]
Best score: 0.3223: : 735iter [00:21, 37.63iter/s]
Best score: 0.3223: : 736iter [00:21, 37.63iter/s]
Best score: 0.3223: : 737iter [00:21, 38.22iter/s]
Best score: 0.3223: : 737iter [00:21, 38.22iter/s]
Best score: 0.3223: : 738iter [00:21, 38.22iter/s]
Best score: 0.3220: : 739iter [00:21, 38.22iter/s]
Best score: 0.3220: : 740iter [00:21, 38.22iter/s]
Best score: 0.3220: : 741iter [00:21, 38.50iter/s]
Best score: 0.3220: : 741iter [00:21, 38.50iter/s]
Best score: 0.3220: : 742iter [00:21, 38.50iter/s]
Best score: 0.3220: : 743iter [00:22, 38.50iter/s]
Best score: 0.3220: : 744iter [00:22, 38.50iter/s]
Best score: 0.3220: : 745iter [00:22, 38.50iter/s]
Best score: 0.3220: : 746iter [00:22, 39.03iter/s]
Best score: 0.3220: : 746iter [00:22, 39.03iter/s]
Best score: 0.3220: : 747iter [00:22, 39.03iter/s]
Best score: 0.3220: : 748iter [00:22, 39.03iter/s]
[ITER 750] Best: 0.3155
[PARAMS] Current best parameters:
  fx: 508.5875
  fy: 508.0988
  px: 999.7990
  py: 749.4529
  k1: 0.06018918
  k2: -0.04532038
  k3: 0.02209341
  k4: -0.00497733
  p1: -0.00933384
  p2: 0.00107370
  p3: 0.00131521
  p4: 0.00143581
  s1: -0.0074
  s2: -0.0007
  s3: 0.0128
  s4: -0.0018
  tilt_x: -0.0018
  tilt_y: -0.0229
  scale: 2.9424
  rotation: 0.1497

Best score: 0.3155: : 749iter [00:22, 39.03iter/s]
Best score: 0.3155: : 750iter [00:22, 38.95iter/s]
Best score: 0.3155: : 750iter [00:22, 38.95iter/s]
Best score: 0.3155: : 751iter [00:22, 38.95iter/s]
Best score: 0.3155: : 752iter [00:22, 38.95iter/s]
Best score: 0.3155: : 753iter [00:22, 38.95iter/s]
Best score: 0.3155: : 754iter [00:22, 32.07iter/s]
Best score: 0.3155: : 754iter [00:22, 32.07iter/s]
Best score: 0.3155: : 755iter [00:22, 32.07iter/s]
Best score: 0.3155: : 756iter [00:22, 32.07iter/s]
Best score: 0.3155: : 757iter [00:22, 32.07iter/s]
Best score: 0.3155: : 758iter [00:22, 34.01iter/s]
Best score: 0.3155: : 758iter [00:22, 34.01iter/s]
Best score: 0.3112: : 759iter [00:22, 34.01iter/s]
Best score: 0.3112: : 760iter [00:22, 34.01iter/s]
Best score: 0.3112: : 761iter [00:22, 34.01iter/s]
Best score: 0.3112: : 762iter [00:22, 35.36iter/s]
Best score: 0.3112: : 762iter [00:22, 35.36iter/s]
Best score: 0.3112: : 763iter [00:22, 35.36iter/s]
Best score: 0.3112: : 764iter [00:22, 35.36iter/s]
Best score: 0.3112: : 765iter [00:22, 35.36iter/s]
Best score: 0.3112: : 766iter [00:22, 35.36iter/s]
Best score: 0.3112: : 767iter [00:22, 37.02iter/s]
Best score: 0.3112: : 767iter [00:22, 37.02iter/s]
Best score: 0.3112: : 768iter [00:22, 37.02iter/s]
Best score: 0.3090: : 769iter [00:22, 37.02iter/s]
Best score: 0.3090: : 770iter [00:22, 37.02iter/s]
Best score: 0.3090: : 771iter [00:22, 37.61iter/s]
Best score: 0.3090: : 771iter [00:22, 37.61iter/s]
Best score: 0.3090: : 772iter [00:22, 37.61iter/s]
Best score: 0.3090: : 773iter [00:22, 37.61iter/s]
Best score: 0.3090: : 774iter [00:22, 37.61iter/s]
Best score: 0.3090: : 775iter [00:22, 37.61iter/s]
Best score: 0.3090: : 776iter [00:22, 38.42iter/s]
Best score: 0.3090: : 776iter [00:22, 38.42iter/s]
Best score: 0.3090: : 777iter [00:22, 38.42iter/s]
Best score: 0.3090: : 778iter [00:22, 38.42iter/s]
Best score: 0.3020: : 779iter [00:22, 38.42iter/s]
Best score: 0.3020: : 780iter [00:22, 38.56iter/s]
Best score: 0.3020: : 780iter [00:23, 38.56iter/s]
Best score: 0.3020: : 781iter [00:23, 38.56iter/s]
Best score: 0.3020: : 782iter [00:23, 38.56iter/s]
Best score: 0.3020: : 783iter [00:23, 38.56iter/s]
Best score: 0.3020: : 784iter [00:23, 38.56iter/s]
Best score: 0.3020: : 785iter [00:23, 39.08iter/s]
Best score: 0.3020: : 785iter [00:23, 39.08iter/s]
Best score: 0.3020: : 786iter [00:23, 39.08iter/s]
Best score: 0.3020: : 787iter [00:23, 39.08iter/s]
Best score: 0.3020: : 788iter [00:23, 39.08iter/s]
Best score: 0.3020: : 789iter [00:23, 39.32iter/s]
Best score: 0.2964: : 789iter [00:23, 39.32iter/s]
Best score: 0.2964: : 790iter [00:23, 39.32iter/s]
Best score: 0.2964: : 791iter [00:23, 39.32iter/s]
Best score: 0.2964: : 792iter [00:23, 39.32iter/s]
Best score: 0.2964: : 793iter [00:23, 39.20iter/s]
Best score: 0.2964: : 793iter [00:23, 39.20iter/s]
Best score: 0.2964: : 794iter [00:23, 39.20iter/s]
Best score: 0.2964: : 795iter [00:23, 39.20iter/s]
Best score: 0.2964: : 796iter [00:23, 39.20iter/s]
Best score: 0.2964: : 797iter [00:23, 39.39iter/s]
Best score: 0.2964: : 797iter [00:23, 39.39iter/s]
Best score: 0.2964: : 798iter [00:23, 39.39iter/s]
[ITER 800] Best: 0.2964
[PARAMS] Current best parameters:
  fx: 514.3708
  fy: 514.1437
  px: 998.9476
  py: 748.2445
  k1: 0.04506449
  k2: -0.03517370
  k3: 0.01843731
  k4: -0.00451674
  p1: -0.00749245
  p2: 0.00230031
  p3: 0.00806938
  p4: 0.00187469
  s1: -0.0150
  s2: -0.0017
  s3: 0.0039
  s4: -0.0028
  tilt_x: -0.0112
  tilt_y: -0.0169
  scale: 2.9536
  rotation: 0.1529

Best score: 0.2964: : 799iter [00:23, 39.39iter/s]
Best score: 0.2964: : 800iter [00:23, 39.39iter/s]
Best score: 0.2964: : 801iter [00:23, 32.24iter/s]
Best score: 0.2964: : 801iter [00:23, 32.24iter/s]
Best score: 0.2964: : 802iter [00:23, 32.24iter/s]
Best score: 0.2964: : 803iter [00:23, 32.24iter/s]
Best score: 0.2964: : 804iter [00:23, 32.24iter/s]
Best score: 0.2964: : 805iter [00:23, 32.24iter/s]
Best score: 0.2964: : 806iter [00:23, 34.68iter/s]
Best score: 0.2964: : 806iter [00:23, 34.68iter/s]
Best score: 0.2964: : 807iter [00:23, 34.68iter/s]
Best score: 0.2964: : 808iter [00:23, 34.68iter/s]
Best score: 0.2964: : 809iter [00:23, 34.68iter/s]
Best score: 0.2964: : 810iter [00:23, 35.90iter/s]
Best score: 0.2964: : 810iter [00:23, 35.90iter/s]
Best score: 0.2964: : 811iter [00:23, 35.90iter/s]
Best score: 0.2964: : 812iter [00:23, 35.90iter/s]
Best score: 0.2964: : 813iter [00:23, 35.90iter/s]
Best score: 0.2964: : 814iter [00:23, 35.90iter/s]
Best score: 0.2964: : 815iter [00:23, 37.30iter/s]
Best score: 0.2964: : 815iter [00:23, 37.30iter/s]
Best score: 0.2964: : 816iter [00:24, 37.30iter/s]
Best score: 0.2964: : 817iter [00:24, 37.30iter/s]
Best score: 0.2964: : 818iter [00:24, 37.30iter/s]
Best score: 0.2964: : 819iter [00:24, 37.99iter/s]
Best score: 0.2931: : 819iter [00:24, 37.99iter/s]
Best score: 0.2931: : 820iter [00:24, 37.99iter/s]
Best score: 0.2931: : 821iter [00:24, 37.99iter/s]
Best score: 0.2931: : 822iter [00:24, 37.99iter/s]
Best score: 0.2931: : 823iter [00:24, 38.23iter/s]
Best score: 0.2931: : 823iter [00:24, 38.23iter/s]
Best score: 0.2931: : 824iter [00:24, 38.23iter/s]
Best score: 0.2931: : 825iter [00:24, 38.23iter/s]
Best score: 0.2931: : 826iter [00:24, 38.23iter/s]
Best score: 0.2931: : 827iter [00:24, 38.67iter/s]
Best score: 0.2931: : 827iter [00:24, 38.67iter/s]
Best score: 0.2931: : 828iter [00:24, 38.67iter/s]
Best score: 0.2875: : 829iter [00:24, 38.67iter/s]
Best score: 0.2875: : 830iter [00:24, 38.67iter/s]
Best score: 0.2875: : 831iter [00:24, 38.86iter/s]
Best score: 0.2875: : 831iter [00:24, 38.86iter/s]
Best score: 0.2875: : 832iter [00:24, 38.86iter/s]
Best score: 0.2875: : 833iter [00:24, 38.86iter/s]
Best score: 0.2875: : 834iter [00:24, 38.86iter/s]
Best score: 0.2875: : 835iter [00:24, 39.05iter/s]
Best score: 0.2875: : 835iter [00:24, 39.05iter/s]
Best score: 0.2875: : 836iter [00:24, 39.05iter/s]
Best score: 0.2875: : 837iter [00:24, 39.05iter/s]
Best score: 0.2875: : 838iter [00:24, 39.05iter/s]
Best score: 0.2875: : 839iter [00:24, 38.88iter/s]
Best score: 0.2816: : 839iter [00:24, 38.88iter/s]
Best score: 0.2816: : 840iter [00:24, 38.88iter/s]
Best score: 0.2816: : 841iter [00:24, 38.88iter/s]
Best score: 0.2816: : 842iter [00:24, 38.88iter/s]
Best score: 0.2816: : 843iter [00:24, 38.50iter/s]
Best score: 0.2816: : 843iter [00:24, 38.50iter/s]
Best score: 0.2816: : 844iter [00:24, 38.50iter/s]
Best score: 0.2816: : 845iter [00:24, 38.50iter/s]
Best score: 0.2816: : 846iter [00:24, 38.50iter/s]
Best score: 0.2816: : 847iter [00:24, 38.50iter/s]
Best score: 0.2816: : 848iter [00:24, 39.05iter/s]
Best score: 0.2816: : 848iter [00:24, 39.05iter/s]
[ITER 850] Best: 0.2777
[PARAMS] Current best parameters:
  fx: 509.0035
  fy: 508.9255
  px: 998.4419
  py: 745.8081
  k1: 0.08141539
  k2: -0.07398505
  k3: 0.03578101
  k4: -0.00733209
  p1: -0.00662876
  p2: 0.00263220
  p3: 0.01644097
  p4: -0.00137719
  s1: -0.0240
  s2: 0.0015
  s3: -0.0086
  s4: 0.0012
  tilt_x: -0.0243
  tilt_y: -0.0135
  scale: 2.9150
  rotation: 0.1658

Best score: 0.2777: : 849iter [00:24, 39.05iter/s]
Best score: 0.2777: : 850iter [00:24, 39.05iter/s]
Best score: 0.2777: : 851iter [00:24, 39.05iter/s]
Best score: 0.2777: : 852iter [00:24, 32.01iter/s]
Best score: 0.2777: : 852iter [00:24, 32.01iter/s]
Best score: 0.2777: : 853iter [00:25, 32.01iter/s]
Best score: 0.2777: : 854iter [00:25, 32.01iter/s]
Best score: 0.2777: : 855iter [00:25, 32.01iter/s]
Best score: 0.2777: : 856iter [00:25, 32.01iter/s]
Best score: 0.2777: : 857iter [00:25, 34.37iter/s]
Best score: 0.2777: : 857iter [00:25, 34.37iter/s]
Best score: 0.2777: : 858iter [00:25, 34.37iter/s]
Best score: 0.2777: : 859iter [00:25, 34.37iter/s]
Best score: 0.2777: : 860iter [00:25, 34.37iter/s]
Best score: 0.2777: : 861iter [00:25, 35.40iter/s]
Best score: 0.2777: : 861iter [00:25, 35.40iter/s]
Best score: 0.2777: : 862iter [00:25, 35.40iter/s]
Best score: 0.2777: : 863iter [00:25, 35.40iter/s]
Best score: 0.2777: : 864iter [00:25, 35.40iter/s]
Best score: 0.2777: : 865iter [00:25, 36.53iter/s]
Best score: 0.2777: : 865iter [00:25, 36.53iter/s]
Best score: 0.2777: : 866iter [00:25, 36.53iter/s]
Best score: 0.2777: : 867iter [00:25, 36.53iter/s]
Best score: 0.2777: : 868iter [00:25, 36.53iter/s]
Best score: 0.2777: : 869iter [00:25, 37.43iter/s]
Best score: 0.2777: : 869iter [00:25, 37.43iter/s]
Best score: 0.2777: : 870iter [00:25, 37.43iter/s]
Best score: 0.2777: : 871iter [00:25, 37.43iter/s]
Best score: 0.2777: : 872iter [00:25, 37.43iter/s]
Best score: 0.2777: : 873iter [00:25, 37.92iter/s]
Best score: 0.2777: : 873iter [00:25, 37.92iter/s]
Best score: 0.2777: : 874iter [00:25, 37.92iter/s]
Best score: 0.2777: : 875iter [00:25, 37.92iter/s]
Best score: 0.2777: : 876iter [00:25, 37.92iter/s]
Best score: 0.2777: : 877iter [00:25, 37.92iter/s]
Best score: 0.2777: : 878iter [00:25, 38.61iter/s]
Best score: 0.2777: : 878iter [00:25, 38.61iter/s]
Best score: 0.2777: : 879iter [00:25, 38.61iter/s]
Best score: 0.2777: : 880iter [00:25, 38.61iter/s]
Best score: 0.2777: : 881iter [00:25, 38.61iter/s]
Best score: 0.2777: : 882iter [00:25, 38.45iter/s]
Best score: 0.2777: : 882iter [00:25, 38.45iter/s]
Best score: 0.2777: : 883iter [00:25, 38.45iter/s]
Best score: 0.2777: : 884iter [00:25, 38.45iter/s]
Best score: 0.2777: : 885iter [00:25, 38.45iter/s]
Best score: 0.2777: : 886iter [00:25, 38.45iter/s]
Best score: 0.2777: : 887iter [00:25, 39.00iter/s]
Best score: 0.2777: : 887iter [00:25, 39.00iter/s]
Best score: 0.2777: : 888iter [00:25, 39.00iter/s]
Best score: 0.2755: : 889iter [00:25, 39.00iter/s]
Best score: 0.2755: : 890iter [00:25, 39.00iter/s]
Best score: 0.2755: : 891iter [00:25, 39.07iter/s]
Best score: 0.2755: : 891iter [00:25, 39.07iter/s]
Best score: 0.2755: : 892iter [00:26, 39.07iter/s]
Best score: 0.2755: : 893iter [00:26, 39.07iter/s]
Best score: 0.2755: : 894iter [00:26, 39.07iter/s]
Best score: 0.2755: : 895iter [00:26, 39.07iter/s]
Best score: 0.2755: : 896iter [00:26, 39.63iter/s]
Best score: 0.2755: : 896iter [00:26, 39.63iter/s]
Best score: 0.2755: : 897iter [00:26, 39.63iter/s]
Best score: 0.2755: : 898iter [00:26, 39.63iter/s]
[ITER 900] Best: 0.2729
[PARAMS] Current best parameters:
  fx: 510.6129
  fy: 510.4464
  px: 1000.8815
  py: 747.8987
  k1: 0.07317149
  k2: -0.06570791
  k3: 0.03196967
  k4: -0.00665745
  p1: -0.00222565
  p2: 0.00677315
  p3: 0.00462486
  p4: -0.00097288
  s1: -0.0148
  s2: 0.0014
  s3: 0.0012
  s4: 0.0005
  tilt_x: -0.0233
  tilt_y: -0.0167
  scale: 2.9245
  rotation: 0.1792

Best score: 0.2729: : 899iter [00:26, 39.63iter/s]
Best score: 0.2729: : 900iter [00:26, 39.51iter/s]
Best score: 0.2729: : 900iter [00:26, 39.51iter/s]
Best score: 0.2729: : 901iter [00:26, 39.51iter/s]
Best score: 0.2729: : 902iter [00:26, 39.51iter/s]
Best score: 0.2729: : 903iter [00:26, 39.51iter/s]
Best score: 0.2729: : 904iter [00:26, 32.55iter/s]
Best score: 0.2729: : 904iter [00:26, 32.55iter/s]
Best score: 0.2729: : 905iter [00:26, 32.55iter/s]
Best score: 0.2729: : 906iter [00:26, 32.55iter/s]
Best score: 0.2729: : 907iter [00:26, 32.55iter/s]
Best score: 0.2729: : 908iter [00:26, 32.55iter/s]
Best score: 0.2729: : 909iter [00:26, 34.76iter/s]
Best score: 0.2697: : 909iter [00:26, 34.76iter/s]
Best score: 0.2697: : 910iter [00:26, 34.76iter/s]
Best score: 0.2697: : 911iter [00:26, 34.76iter/s]
Best score: 0.2697: : 912iter [00:26, 34.76iter/s]
Best score: 0.2697: : 913iter [00:26, 35.91iter/s]
Best score: 0.2697: : 913iter [00:26, 35.91iter/s]
Best score: 0.2697: : 914iter [00:26, 35.91iter/s]
Best score: 0.2697: : 915iter [00:26, 35.91iter/s]
Best score: 0.2697: : 916iter [00:26, 35.91iter/s]
Best score: 0.2697: : 917iter [00:26, 36.97iter/s]
Best score: 0.2697: : 917iter [00:26, 36.97iter/s]
Best score: 0.2697: : 918iter [00:26, 36.97iter/s]
Best score: 0.2687: : 919iter [00:26, 36.97iter/s]
Best score: 0.2687: : 920iter [00:26, 36.97iter/s]
Best score: 0.2687: : 921iter [00:26, 37.61iter/s]
Best score: 0.2687: : 921iter [00:26, 37.61iter/s]
Best score: 0.2687: : 922iter [00:26, 37.61iter/s]
Best score: 0.2687: : 923iter [00:26, 37.61iter/s]
Best score: 0.2687: : 924iter [00:26, 37.61iter/s]
Best score: 0.2687: : 925iter [00:26, 38.25iter/s]
Best score: 0.2687: : 925iter [00:26, 38.25iter/s]
Best score: 0.2687: : 926iter [00:26, 38.25iter/s]
Best score: 0.2687: : 927iter [00:26, 38.25iter/s]
Best score: 0.2687: : 928iter [00:26, 38.25iter/s]
Best score: 0.2687: : 929iter [00:26, 38.72iter/s]
Best score: 0.2687: : 929iter [00:27, 38.72iter/s]
Best score: 0.2687: : 930iter [00:27, 38.72iter/s]
Best score: 0.2687: : 931iter [00:27, 38.72iter/s]
Best score: 0.2687: : 932iter [00:27, 38.72iter/s]
Best score: 0.2687: : 933iter [00:27, 38.78iter/s]
Best score: 0.2687: : 933iter [00:27, 38.78iter/s]
Best score: 0.2687: : 934iter [00:27, 38.78iter/s]
Best score: 0.2687: : 935iter [00:27, 38.78iter/s]
Best score: 0.2687: : 936iter [00:27, 38.78iter/s]
Best score: 0.2687: : 937iter [00:27, 38.78iter/s]
Best score: 0.2687: : 938iter [00:27, 39.25iter/s]
Best score: 0.2687: : 938iter [00:27, 39.25iter/s]
Best score: 0.2687: : 939iter [00:27, 39.25iter/s]
Best score: 0.2687: : 940iter [00:27, 39.25iter/s]
Best score: 0.2687: : 941iter [00:27, 39.25iter/s]
Best score: 0.2687: : 942iter [00:27, 39.21iter/s]
Best score: 0.2687: : 942iter [00:27, 39.21iter/s]
Best score: 0.2687: : 943iter [00:27, 39.21iter/s]
Best score: 0.2687: : 944iter [00:27, 39.21iter/s]
Best score: 0.2687: : 945iter [00:27, 39.21iter/s]
Best score: 0.2687: : 946iter [00:27, 39.43iter/s]
Best score: 0.2687: : 946iter [00:27, 39.43iter/s]
Best score: 0.2687: : 947iter [00:27, 39.43iter/s]
Best score: 0.2687: : 948iter [00:27, 39.43iter/s]
[ITER 950] Best: 0.2668
[PARAMS] Current best parameters:
  fx: 507.7550
  fy: 507.5787
  px: 1002.0223
  py: 746.4639
  k1: 0.09052366
  k2: -0.08570459
  k3: 0.04199946
  k4: -0.00848268
  p1: -0.00269447
  p2: 0.00615370
  p3: 0.01005575
  p4: -0.00223626
  s1: -0.0193
  s2: 0.0029
  s3: -0.0051
  s4: 0.0018
  tilt_x: -0.0291
  tilt_y: -0.0235
  scale: 2.9105
  rotation: 0.1734

Best score: 0.2668: : 949iter [00:27, 39.43iter/s]
Best score: 0.2668: : 950iter [00:27, 39.28iter/s]
Best score: 0.2668: : 950iter [00:27, 39.28iter/s]
Best score: 0.2668: : 951iter [00:27, 39.28iter/s]
Best score: 0.2668: : 952iter [00:27, 39.28iter/s]
Best score: 0.2668: : 953iter [00:27, 39.28iter/s]
Best score: 0.2668: : 954iter [00:27, 32.12iter/s]
Best score: 0.2668: : 954iter [00:27, 32.12iter/s]
Best score: 0.2668: : 955iter [00:27, 32.12iter/s]
Best score: 0.2668: : 956iter [00:27, 32.12iter/s]
Best score: 0.2668: : 957iter [00:27, 32.12iter/s]
Best score: 0.2668: : 958iter [00:27, 32.12iter/s]
Best score: 0.2668: : 959iter [00:27, 34.53iter/s]
Best score: 0.2653: : 959iter [00:27, 34.53iter/s]
Best score: 0.2653: : 960iter [00:27, 34.53iter/s]
Best score: 0.2653: : 961iter [00:27, 34.53iter/s]
Best score: 0.2653: : 962iter [00:27, 34.53iter/s]
Best score: 0.2653: : 963iter [00:27, 35.65iter/s]
Best score: 0.2653: : 963iter [00:27, 35.65iter/s]
Best score: 0.2653: : 964iter [00:27, 35.65iter/s]
Best score: 0.2653: : 965iter [00:28, 35.65iter/s]
Best score: 0.2653: : 966iter [00:28, 35.65iter/s]
Best score: 0.2653: : 967iter [00:28, 36.74iter/s]
Best score: 0.2653: : 967iter [00:28, 36.74iter/s]
Best score: 0.2653: : 968iter [00:28, 36.74iter/s]
Best score: 0.2635: : 969iter [00:28, 36.74iter/s]
Best score: 0.2635: : 970iter [00:28, 36.74iter/s]
Best score: 0.2635: : 971iter [00:28, 37.27iter/s]
Best score: 0.2635: : 971iter [00:28, 37.27iter/s]
Best score: 0.2635: : 972iter [00:28, 37.27iter/s]
Best score: 0.2635: : 973iter [00:28, 37.27iter/s]
Best score: 0.2635: : 974iter [00:28, 37.27iter/s]
Best score: 0.2635: : 975iter [00:28, 37.87iter/s]
Best score: 0.2635: : 975iter [00:28, 37.87iter/s]
Best score: 0.2635: : 976iter [00:28, 37.87iter/s]
Best score: 0.2635: : 977iter [00:28, 37.87iter/s]
Best score: 0.2635: : 978iter [00:28, 37.87iter/s]
Best score: 0.2635: : 979iter [00:28, 38.41iter/s]
Best score: 0.2635: : 979iter [00:28, 38.41iter/s]
Best score: 0.2635: : 980iter [00:28, 38.41iter/s]
Best score: 0.2635: : 981iter [00:28, 38.41iter/s]
Best score: 0.2635: : 982iter [00:28, 38.41iter/s]
Best score: 0.2635: : 983iter [00:28, 38.60iter/s]
Best score: 0.2635: : 983iter [00:28, 38.60iter/s]
Best score: 0.2635: : 984iter [00:28, 38.60iter/s]
Best score: 0.2635: : 985iter [00:28, 38.60iter/s]
Best score: 0.2635: : 986iter [00:28, 38.60iter/s]
Best score: 0.2635: : 987iter [00:28, 38.98iter/s]
Best score: 0.2635: : 987iter [00:28, 38.98iter/s]
Best score: 0.2635: : 988iter [00:28, 38.98iter/s]
Best score: 0.2632: : 989iter [00:28, 38.98iter/s]
Best score: 0.2632: : 990iter [00:28, 38.98iter/s]
Best score: 0.2632: : 991iter [00:28, 39.02iter/s]
Best score: 0.2632: : 991iter [00:28, 39.02iter/s]
Best score: 0.2632: : 992iter [00:28, 39.02iter/s]
Best score: 0.2632: : 993iter [00:28, 39.02iter/s]
Best score: 0.2632: : 994iter [00:28, 39.02iter/s]
Best score: 0.2632: : 995iter [00:28, 39.30iter/s]
Best score: 0.2632: : 995iter [00:28, 39.30iter/s]
Best score: 0.2632: : 996iter [00:28, 39.30iter/s]
Best score: 0.2632: : 997iter [00:28, 39.30iter/s]
Best score: 0.2632: : 998iter [00:28, 39.30iter/s]
[ITER 1000] Best: 0.2629
[PARAMS] Current best parameters:
  fx: 506.7118
  fy: 506.6144
  px: 1002.0211
  py: 745.0363
  k1: 0.09668018
  k2: -0.09116282
  k3: 0.04406606
  k4: -0.00878692
  p1: -0.00506024
  p2: 0.00599571
  p3: 0.01251138
  p4: -0.00248800
  s1: -0.0204
  s2: 0.0026
  s3: -0.0060
  s4: 0.0019
  tilt_x: -0.0309
  tilt_y: -0.0235
  scale: 2.9015
  rotation: 0.1771

Best score: 0.2629: : 999iter [00:28, 39.30iter/s]
Best score: 0.2629: : 1000iter [00:28, 39.24iter/s]
Best score: 0.2629: : 1000iter [00:28, 39.24iter/s]
Best score: 0.2629: : 1001iter [00:28, 39.24iter/s]
Best score: 0.2629: : 1002iter [00:29, 39.24iter/s]
Best score: 0.2629: : 1003iter [00:29, 39.24iter/s]
Best score: 0.2629: : 1004iter [00:29, 32.44iter/s]
Best score: 0.2629: : 1004iter [00:29, 32.44iter/s]
Best score: 0.2629: : 1005iter [00:29, 32.44iter/s]
Best score: 0.2629: : 1006iter [00:29, 32.44iter/s]
Best score: 0.2629: : 1007iter [00:29, 32.44iter/s]
Best score: 0.2629: : 1008iter [00:29, 34.17iter/s]
Best score: 0.2629: : 1008iter [00:29, 34.17iter/s]
Best score: 0.2620: : 1009iter [00:29, 34.17iter/s]
Best score: 0.2620: : 1010iter [00:29, 34.17iter/s]
Best score: 0.2620: : 1011iter [00:29, 34.17iter/s]
Best score: 0.2620: : 1012iter [00:29, 35.16iter/s]
Best score: 0.2620: : 1012iter [00:29, 35.16iter/s]
Best score: 0.2620: : 1013iter [00:29, 35.16iter/s]
Best score: 0.2620: : 1014iter [00:29, 35.16iter/s]
Best score: 0.2620: : 1015iter [00:29, 35.16iter/s]
Best score: 0.2620: : 1016iter [00:29, 36.24iter/s]
Best score: 0.2620: : 1016iter [00:29, 36.24iter/s]
Best score: 0.2620: : 1017iter [00:29, 36.24iter/s]
Best score: 0.2620: : 1018iter [00:29, 36.24iter/s]
Best score: 0.2615: : 1019iter [00:29, 36.24iter/s]
Best score: 0.2615: : 1020iter [00:29, 36.92iter/s]
Best score: 0.2615: : 1020iter [00:29, 36.92iter/s]
Best score: 0.2615: : 1021iter [00:29, 36.92iter/s]
Best score: 0.2615: : 1022iter [00:29, 36.92iter/s]
Best score: 0.2615: : 1023iter [00:29, 36.92iter/s]
Best score: 0.2615: : 1024iter [00:29, 37.74iter/s]
Best score: 0.2615: : 1024iter [00:29, 37.74iter/s]
Best score: 0.2615: : 1025iter [00:29, 37.74iter/s]
Best score: 0.2615: : 1026iter [00:29, 37.74iter/s]
Best score: 0.2615: : 1027iter [00:29, 37.74iter/s]
Best score: 0.2615: : 1028iter [00:29, 30.64iter/s]
Best score: 0.2615: : 1028iter [00:29, 30.64iter/s]
Best score: 0.2609: : 1029iter [00:29, 30.64iter/s]
Best score: 0.2609: : 1030iter [00:29, 30.64iter/s]
Best score: 0.2609: : 1031iter [00:29, 30.64iter/s]
Best score: 0.2609: : 1032iter [00:29, 32.77iter/s]
Best score: 0.2609: : 1032iter [00:29, 32.77iter/s]
Best score: 0.2609: : 1033iter [00:29, 32.77iter/s]
Best score: 0.2609: : 1034iter [00:29, 32.77iter/s]
Best score: 0.2609: : 1035iter [00:29, 32.77iter/s]
Best score: 0.2609: : 1036iter [00:29, 34.60iter/s]
Best score: 0.2609: : 1036iter [00:29, 34.60iter/s]
Best score: 0.2609: : 1037iter [00:30, 34.60iter/s]
Best score: 0.2609: : 1038iter [00:30, 34.60iter/s]
Best score: 0.2599: : 1039iter [00:30, 34.60iter/s]
Best score: 0.2599: : 1040iter [00:30, 35.75iter/s]
Best score: 0.2599: : 1040iter [00:30, 35.75iter/s]
Best score: 0.2599: : 1041iter [00:30, 35.75iter/s]
Best score: 0.2599: : 1042iter [00:30, 35.75iter/s]
Best score: 0.2599: : 1043iter [00:30, 35.75iter/s]
Best score: 0.2599: : 1044iter [00:30, 36.88iter/s]
Best score: 0.2599: : 1044iter [00:30, 36.88iter/s]
Best score: 0.2599: : 1045iter [00:30, 36.88iter/s]
Best score: 0.2599: : 1046iter [00:30, 36.88iter/s]
Best score: 0.2599: : 1047iter [00:30, 36.88iter/s]
Best score: 0.2599: : 1048iter [00:30, 37.72iter/s]
Best score: 0.2599: : 1048iter [00:30, 37.72iter/s]
[ITER 1050] Best: 0.2587
[PARAMS] Current best parameters:
  fx: 503.8514
  fy: 503.6875
  px: 1001.7019
  py: 743.5065
  k1: 0.09336007
  k2: -0.08190606
  k3: 0.03909657
  k4: -0.00788422
  p1: -0.01030484
  p2: 0.00328211
  p3: 0.01897260
  p4: -0.00218656
  s1: -0.0246
  s2: 0.0023
  s3: -0.0091
  s4: 0.0019
  tilt_x: -0.0273
  tilt_y: -0.0271
  scale: 2.9088
  rotation: 0.1656

Best score: 0.2587: : 1049iter [00:30, 37.72iter/s]
Best score: 0.2587: : 1050iter [00:30, 37.72iter/s]
Best score: 0.2587: : 1051iter [00:30, 37.72iter/s]
Best score: 0.2587: : 1052iter [00:30, 30.88iter/s]
Best score: 0.2587: : 1052iter [00:30, 30.88iter/s]
Best score: 0.2587: : 1053iter [00:30, 30.88iter/s]
Best score: 0.2587: : 1054iter [00:30, 30.88iter/s]
Best score: 0.2587: : 1055iter [00:30, 30.88iter/s]
Best score: 0.2587: : 1056iter [00:30, 30.88iter/s]
Best score: 0.2587: : 1057iter [00:30, 33.68iter/s]
Best score: 0.2587: : 1057iter [00:30, 33.68iter/s]
Best score: 0.2587: : 1058iter [00:30, 33.68iter/s]
Best score: 0.2587: : 1059iter [00:30, 33.68iter/s]
Best score: 0.2587: : 1060iter [00:30, 33.68iter/s]
Best score: 0.2587: : 1061iter [00:30, 35.12iter/s]
Best score: 0.2587: : 1061iter [00:30, 35.12iter/s]
Best score: 0.2587: : 1062iter [00:30, 35.12iter/s]
Best score: 0.2587: : 1063iter [00:30, 35.12iter/s]
Best score: 0.2587: : 1064iter [00:30, 35.12iter/s]
Best score: 0.2587: : 1065iter [00:30, 36.38iter/s]
Best score: 0.2587: : 1065iter [00:30, 36.38iter/s]
Best score: 0.2587: : 1066iter [00:30, 36.38iter/s]
Best score: 0.2587: : 1067iter [00:30, 36.38iter/s]
Best score: 0.2587: : 1068iter [00:30, 36.38iter/s]
Best score: 0.2587: : 1069iter [00:30, 36.38iter/s]
Best score: 0.2587: : 1070iter [00:30, 37.27iter/s]
Best score: 0.2587: : 1070iter [00:30, 37.27iter/s]
Best score: 0.2587: : 1071iter [00:30, 37.27iter/s]
Best score: 0.2587: : 1072iter [00:30, 37.27iter/s]
Best score: 0.2587: : 1073iter [00:30, 37.27iter/s]
Best score: 0.2587: : 1074iter [00:30, 37.89iter/s]
Best score: 0.2587: : 1074iter [00:31, 37.89iter/s]
Best score: 0.2587: : 1075iter [00:31, 37.89iter/s]
Best score: 0.2587: : 1076iter [00:31, 37.89iter/s]
Best score: 0.2587: : 1077iter [00:31, 37.89iter/s]
Best score: 0.2587: : 1078iter [00:31, 38.06iter/s]
Best score: 0.2587: : 1078iter [00:31, 38.06iter/s]
Best score: 0.2587: : 1079iter [00:31, 38.06iter/s]
Best score: 0.2587: : 1080iter [00:31, 38.06iter/s]
Best score: 0.2587: : 1081iter [00:31, 38.06iter/s]
Best score: 0.2587: : 1082iter [00:31, 38.28iter/s]
Best score: 0.2587: : 1082iter [00:31, 38.28iter/s]
Best score: 0.2587: : 1083iter [00:31, 38.28iter/s]
Best score: 0.2587: : 1084iter [00:31, 38.28iter/s]
Best score: 0.2587: : 1085iter [00:31, 38.28iter/s]
Best score: 0.2587: : 1086iter [00:31, 38.28iter/s]
Best score: 0.2587: : 1087iter [00:31, 38.95iter/s]
Best score: 0.2587: : 1087iter [00:31, 38.95iter/s]
Best score: 0.2587: : 1088iter [00:31, 38.95iter/s]
Best score: 0.2585: : 1089iter [00:31, 38.95iter/s]
Best score: 0.2585: : 1090iter [00:31, 38.95iter/s]
Best score: 0.2585: : 1091iter [00:31, 39.05iter/s]
Best score: 0.2585: : 1091iter [00:31, 39.05iter/s]
Best score: 0.2585: : 1092iter [00:31, 39.05iter/s]
Best score: 0.2585: : 1093iter [00:31, 39.05iter/s]
Best score: 0.2585: : 1094iter [00:31, 39.05iter/s]
Best score: 0.2585: : 1095iter [00:31, 39.05iter/s]
Best score: 0.2585: : 1096iter [00:31, 39.43iter/s]
Best score: 0.2585: : 1096iter [00:31, 39.43iter/s]
Best score: 0.2585: : 1097iter [00:31, 39.43iter/s]
Best score: 0.2585: : 1098iter [00:31, 39.43iter/s]
[ITER 1100] Best: 0.2585
[PARAMS] Current best parameters:
  fx: 503.7865
  fy: 503.6272
  px: 1001.8431
  py: 743.5956
  k1: 0.09327822
  k2: -0.08193824
  k3: 0.03922527
  k4: -0.00792411
  p1: -0.00948110
  p2: 0.00356382
  p3: 0.01843983
  p4: -0.00241990
  s1: -0.0245
  s2: 0.0027
  s3: -0.0092
  s4: 0.0020
  tilt_x: -0.0285
  tilt_y: -0.0272
  scale: 2.9097
  rotation: 0.1664

Best score: 0.2585: : 1099iter [00:31, 39.43iter/s]
Best score: 0.2585: : 1100iter [00:31, 39.27iter/s]
[📈] Running L-BFGS-B polish after 1100 DE iterations...

Best score: 0.2585: : 1100iter [00:31, 34.66iter/s]
  Polish improved score: 0.258494 -> 0.257358

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 25,802 → 25,802 within 3500mm ring
  Ring polish did not improve score: 0.257358
  Success: True
  Tangential distortion: p1=-0.009479, p2=0.003582, p3=0.018445, p4=-0.002415
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.2574
[✅] Parameters copied to: /working/MDC017_W029_2026-03-02/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 503.78653174160183
    fy: 503.62716129969976
    px: 1001.8431309382922
    py: 743.5955580115736
    k1: 0.09330860155252482
    k2: -0.08192805290785068
    k3: 0.03923243050615319
    k4: -0.007939026268763177
    p1: -0.009479241725522641
    p2: 0.003582239706532056
    p3: 0.018445127175510792
    p4: -0.002415089769766028
    scale: 2.9096637884273737
    rotation: 0.1664257653037587
    mmpp: 1.2719850532439947

[🔄] Converting 386 frames to PTD, creating debug images for 200 calibration frames...

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

   🔄 1000:   0%|          | 0/211 [00:00<?, ?frame/s]

   🔄 1000:   9%|▊         | 18/211 [00:00<00:01, 174.18frame/s]

   🔄 1000:  17%|█▋        | 36/211 [00:00<00:01, 174.06frame/s]

   🔄 1000:  26%|██▌       | 54/211 [00:00<00:00, 174.49frame/s]

   🔄 1000:  34%|███▍      | 72/211 [00:00<00:00, 173.60frame/s]

   🔄 1000:  43%|████▎     | 90/211 [00:00<00:00, 172.55frame/s]

   🔄 1000:  51%|█████     | 108/211 [00:00<00:00, 172.00frame/s]

   🔄 1000:  60%|█████▉    | 126/211 [00:00<00:00, 172.11frame/s]

   🔄 1000:  68%|██████▊   | 144/211 [00:00<00:00, 172.57frame/s]

   🔄 1000:  77%|███████▋  | 162/211 [00:00<00:00, 173.13frame/s]

   🔄 1000:  85%|████████▌ | 180/211 [00:01<00:00, 173.77frame/s]

   🔄 1000:  94%|█████████▍| 198/211 [00:01<00:00, 174.19frame/s]

                                                                 
📁 Rigs:  50%|█████     | 1/2 [00:02<00:02,  2.22s/rig]

   🔄 500:   0%|          | 0/175 [00:00<?, ?frame/s]

   🔄 500:  10%|█         | 18/175 [00:00<00:00, 175.88frame/s]

   🔄 500:  21%|██        | 36/175 [00:00<00:00, 176.55frame/s]

   🔄 500:  31%|███       | 54/175 [00:00<00:00, 176.35frame/s]

   🔄 500:  41%|████      | 72/175 [00:00<00:00, 176.15frame/s]

   🔄 500:  52%|█████▏    | 91/175 [00:00<00:00, 178.02frame/s]

   🔄 500:  62%|██████▏   | 109/175 [00:00<00:00, 177.98frame/s]

   🔄 500:  73%|███████▎  | 127/175 [00:00<00:00, 177.77frame/s]

   🔄 500:  83%|████████▎ | 145/175 [00:00<00:00, 177.92frame/s]

   🔄 500:  93%|█████████▎| 163/175 [00:00<00:00, 177.74frame/s]

                                                                
📁 Rigs: 100%|██████████| 2/2 [00:03<00:00,  1.95s/rig]
📁 Rigs: 100%|██████████| 2/2 [00:03<00:00,  1.99s/rig]
[✅] Saved PTDs: /working/MDC017_W029_2026-03-02/calibration/debug/4_undistorted/output/ptd

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

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

   🔄 1000:  18%|█▊        | 18/100 [00:00<00:00, 174.28frame/s]

   🔄 1000:  36%|███▌      | 36/100 [00:00<00:00, 173.77frame/s]

   🔄 1000:  54%|█████▍    | 54/100 [00:00<00:00, 171.46frame/s]

   🔄 1000:  72%|███████▏  | 72/100 [00:00<00:00, 171.75frame/s]

   🔄 1000:  90%|█████████ | 90/100 [00:00<00:00, 173.23frame/s]

                                                                
📁 Rigs:  50%|█████     | 1/2 [00:00<00:00,  1.08rig/s]

   🔄 500:   0%|          | 0/100 [00:00<?, ?frame/s]

   🔄 500:  18%|█▊        | 18/100 [00:00<00:00, 175.77frame/s]

   🔄 500:  36%|███▌      | 36/100 [00:00<00:00, 175.44frame/s]

   🔄 500:  54%|█████▍    | 54/100 [00:00<00:00, 176.92frame/s]

   🔄 500:  72%|███████▏  | 72/100 [00:00<00:00, 176.54frame/s]

   🔄 500:  90%|█████████ | 90/100 [00:00<00:00, 176.89frame/s]

                                                               
📁 Rigs: 100%|██████████| 2/2 [00:01<00:00,  1.01rig/s]
📁 Rigs: 100%|██████████| 2/2 [00:01<00:00,  1.02rig/s]
[✅] Saved PTDs: /working/MDC017_W029_2026-03-02/calibration/debug/4_undistorted/temp_ptd
[WARN] No .tfd files found for serial extraction
[WARN] Failed to extract serial number from .tfd file. Check that .tfd files exist and contain 'LASERbidh' or 'LASERbidg' pattern. Using 'unknown' as fallback.

📤 Writing LUT:   0%|          | 0/3080448 [00:00<?, ?px/s]
📤 Writing LUT:   3%|▎         | 90738/3080448 [00:00<00:03, 907298.66px/s]
📤 Writing LUT:   6%|▌         | 187291/3080448 [00:00<00:03, 941546.37px/s]
📤 Writing LUT:   9%|▉         | 281446/3080448 [00:00<00:03, 921147.43px/s]
📤 Writing LUT:  12%|█▏        | 373613/3080448 [00:00<00:03, 901136.14px/s]
📤 Writing LUT:  15%|█▌        | 463799/3080448 [00:00<00:02, 887087.93px/s]
📤 Writing LUT:  18%|█▊        | 552562/3080448 [00:00<00:02, 886153.36px/s]
📤 Writing LUT:  21%|██        | 641211/3080448 [00:00<00:02, 874577.91px/s]
📤 Writing LUT:  24%|██▎       | 728702/3080448 [00:00<00:02, 866256.52px/s]
📤 Writing LUT:  26%|██▋       | 815350/3080448 [00:00<00:02, 860701.43px/s]
📤 Writing LUT:  29%|██▉       | 904101/3080448 [00:01<00:02, 868815.43px/s]
📤 Writing LUT:  32%|███▏      | 991007/3080448 [00:01<00:02, 861992.80px/s]
📤 Writing LUT:  35%|███▌      | 1079258/3080448 [00:01<00:02, 868139.48px/s]
📤 Writing LUT:  38%|███▊      | 1166095/3080448 [00:01<00:02, 867170.11px/s]
📤 Writing LUT:  41%|████      | 1252828/3080448 [00:01<00:02, 864364.08px/s]
📤 Writing LUT:  44%|████▎     | 1342211/3080448 [00:01<00:01, 873172.67px/s]
📤 Writing LUT:  46%|████▋     | 1429645/3080448 [00:01<00:01, 873519.20px/s]
📤 Writing LUT:  49%|████▉     | 1517224/3080448 [00:01<00:01, 874198.34px/s]
📤 Writing LUT:  52%|█████▏    | 1604652/3080448 [00:01<00:01, 868622.27px/s]
📤 Writing LUT:  55%|█████▌    | 1694379/3080448 [00:01<00:01, 877169.58px/s]
📤 Writing LUT:  58%|█████▊    | 1782110/3080448 [00:02<00:01, 876452.33px/s]
📤 Writing LUT:  61%|██████    | 1869765/3080448 [00:02<00:01, 869949.98px/s]
📤 Writing LUT:  64%|██████▎   | 1956776/3080448 [00:02<00:01, 863736.07px/s]
📤 Writing LUT:  66%|██████▋   | 2043166/3080448 [00:02<00:01, 860009.76px/s]
📤 Writing LUT:  69%|██████▉   | 2130871/3080448 [00:02<00:01, 865069.01px/s]
📤 Writing LUT:  72%|███████▏  | 2217392/3080448 [00:02<00:01, 862279.33px/s]
📤 Writing LUT:  75%|███████▍  | 2303630/3080448 [00:02<00:00, 858985.08px/s]
📤 Writing LUT:  78%|███████▊  | 2389536/3080448 [00:02<00:00, 857212.48px/s]
📤 Writing LUT:  80%|████████  | 2477052/3080448 [00:02<00:00, 862558.88px/s]
📤 Writing LUT:  83%|████████▎ | 2565984/3080448 [00:02<00:00, 870545.15px/s]
📤 Writing LUT:  86%|████████▌ | 2653886/3080448 [00:03<00:00, 873076.65px/s]
📤 Writing LUT:  89%|████████▉ | 2742140/3080448 [00:03<00:00, 875907.21px/s]
📤 Writing LUT:  92%|█████████▏| 2831923/3080448 [00:03<00:00, 882471.33px/s]
📤 Writing LUT:  95%|█████████▍| 2922549/3080448 [00:03<00:00, 889597.21px/s]
📤 Writing LUT:  98%|█████████▊| 3012950/3080448 [00:03<00:00, 893917.08px/s]
📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 875708.67px/s]
[✅] LUT written to: /working/MDC017_W029_2026-03-02/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDC017_W029_2026-03-02' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC017_W029_2026-03-02/calibration/MDC017_W029_2026-03-02_unknown.lut

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

[ℹ️] Detected device type: MD (rigs: [500, 1000]mm)

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

   🔥 1000:   0%|          | 0/211 [00:00<?, ?frame/s]

   🔥 1000:   4%|▍         | 8/211 [00:00<00:02, 77.47frame/s]

   🔥 1000:   8%|▊         | 17/211 [00:00<00:02, 82.31frame/s]

   🔥 1000:  12%|█▏        | 26/211 [00:00<00:02, 82.50frame/s]

   🔥 1000:  17%|█▋        | 35/211 [00:00<00:02, 82.98frame/s]

   🔥 1000:  21%|██        | 44/211 [00:00<00:02, 82.01frame/s]

   🔥 1000:  25%|██▌       | 53/211 [00:00<00:01, 82.36frame/s]

   🔥 1000:  29%|██▉       | 62/211 [00:00<00:01, 83.27frame/s]

   🔥 1000:  34%|███▎      | 71/211 [00:00<00:01, 83.42frame/s]

   🔥 1000:  38%|███▊      | 80/211 [00:00<00:01, 82.95frame/s]

   🔥 1000:  42%|████▏     | 89/211 [00:01<00:01, 82.58frame/s]

   🔥 1000:  46%|████▋     | 98/211 [00:01<00:01, 82.79frame/s]

   🔥 1000:  51%|█████     | 107/211 [00:01<00:01, 84.28frame/s]

   🔥 1000:  55%|█████▍    | 116/211 [00:01<00:01, 84.53frame/s]

   🔥 1000:  59%|█████▉    | 125/211 [00:01<00:01, 84.97frame/s]

   🔥 1000:  64%|██████▎   | 134/211 [00:01<00:00, 82.87frame/s]

   🔥 1000:  68%|██████▊   | 143/211 [00:01<00:00, 83.19frame/s]

   🔥 1000:  72%|███████▏  | 152/211 [00:01<00:00, 83.95frame/s]

   🔥 1000:  76%|███████▋  | 161/211 [00:01<00:00, 84.39frame/s]

   🔥 1000:  81%|████████  | 170/211 [00:02<00:00, 83.88frame/s]

   🔥 1000:  85%|████████▍ | 179/211 [00:02<00:00, 84.00frame/s]

   🔥 1000:  89%|████████▉ | 188/211 [00:02<00:00, 83.86frame/s]

   🔥 1000:  93%|█████████▎| 197/211 [00:02<00:00, 85.04frame/s]

   🔥 1000:  98%|█████████▊| 206/211 [00:02<00:00, 85.43frame/s]

                                                                [✅] 1000: /working/MDC017_W029_2026-03-02/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDC017_W029_2026-03-02/calibration/debug/5_heatmap/1000_heatmap_fitted.png

📁 Rigs (heatmap):  50%|█████     | 1/2 [00:05<00:05,  5.56s/rig]

   🔥 500:   0%|          | 0/175 [00:00<?, ?frame/s]

   🔥 500:   4%|▍         | 7/175 [00:00<00:02, 67.67frame/s]

   🔥 500:   9%|▊         | 15/175 [00:00<00:02, 73.32frame/s]

   🔥 500:  13%|█▎        | 23/175 [00:00<00:02, 75.38frame/s]

   🔥 500:  18%|█▊        | 31/175 [00:00<00:01, 76.20frame/s]

   🔥 500:  23%|██▎       | 40/175 [00:00<00:01, 78.45frame/s]

   🔥 500:  28%|██▊       | 49/175 [00:00<00:01, 79.71frame/s]

   🔥 500:  33%|███▎      | 58/175 [00:00<00:01, 79.89frame/s]

   🔥 500:  38%|███▊      | 67/175 [00:00<00:01, 80.02frame/s]

   🔥 500:  43%|████▎     | 76/175 [00:00<00:01, 81.78frame/s]

   🔥 500:  49%|████▊     | 85/175 [00:01<00:01, 81.75frame/s]

   🔥 500:  54%|█████▎    | 94/175 [00:01<00:01, 79.87frame/s]

   🔥 500:  58%|█████▊    | 102/175 [00:01<00:00, 78.52frame/s]

   🔥 500:  63%|██████▎   | 110/175 [00:01<00:00, 77.90frame/s]

   🔥 500:  67%|██████▋   | 118/175 [00:01<00:00, 78.04frame/s]

   🔥 500:  72%|███████▏  | 126/175 [00:01<00:00, 77.69frame/s]

   🔥 500:  77%|███████▋  | 134/175 [00:01<00:00, 77.67frame/s]

   🔥 500:  81%|████████  | 142/175 [00:01<00:00, 77.74frame/s]

   🔥 500:  86%|████████▌ | 150/175 [00:01<00:00, 78.14frame/s]

   🔥 500:  90%|█████████ | 158/175 [00:02<00:00, 77.80frame/s]

   🔥 500:  95%|█████████▍| 166/175 [00:02<00:00, 77.31frame/s]

   🔥 500:  99%|█████████▉| 174/175 [00:02<00:00, 77.80frame/s]

                                                               [✅] 500: /working/MDC017_W029_2026-03-02/calibration/debug/5_heatmap/500_heatmap.png
[✅] 500 (fitted): /working/MDC017_W029_2026-03-02/calibration/debug/5_heatmap/500_heatmap_fitted.png

📁 Rigs (heatmap): 100%|██████████| 2/2 [00:09<00:00,  4.35s/rig]
📁 Rigs (heatmap): 100%|██████████| 2/2 [00:09<00:00,  4.53s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDC017_W029_2026-03-02/calibration/debug/5_heatmap
[🏁] Finished processing MDC017_W029_2026-03-02


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