Eval with all panoptic cameras.
This commit is contained in:
Daniel
287
media/RESULTS.md
287
media/RESULTS.md
@ -1948,6 +1948,293 @@ Results of the model in various experiments on different datasets. \
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}
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}
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```
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```
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##### 31 cameras
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```json
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{
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"img_loading": 0.316871,
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"demosaicing": 0.0110794,
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"avg_time_2d": 0.0985203,
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"avg_time_3d": 0.0129658,
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"fps": 8.15891
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}
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{
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"triangulator_calls": 420,
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"init_time": 6.01526e-05,
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"undistort_time": 0.000318677,
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"project_time": 0.000553076,
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"match_time": 0.000529147,
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"pairs_time": 0.00223077,
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"pair_scoring_time": 0.00300736,
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"grouping_time": 0.00276694,
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"full_time": 0.002134,
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"merge_time": 0.000522887,
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"post_time": 1.79106e-05,
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"convert_time": 9.62974e-07,
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"total_time": 0.0121423
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}
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{
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"person_nums": {
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"total_frames": 420,
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"total_labels": 1466,
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"total_preds": 1505,
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"considered_empty": 0,
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"valid_preds": 1465,
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"invalid_preds": 40,
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"missing": 1,
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"invalid_fraction": 0.02658,
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"precision": 0.97342,
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"recall": 0.99932,
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"f1": 0.9862,
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"non_empty": 1505
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},
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"mpjpe": {
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"count": 1465,
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"mean": 0.021378,
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"median": 0.019413,
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"std": 0.007745,
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"sem": 0.000202,
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"min": 0.009697,
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"max": 0.102079,
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"recall-0.025": 0.733288,
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"recall-0.05": 0.995225,
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"recall-0.1": 0.998636,
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"recall-0.15": 0.999318,
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"recall-0.25": 0.999318,
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"recall-0.5": 0.999318,
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"num_labels": 1466,
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"ap-0.025": 0.660592,
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"ap-0.05": 0.983876,
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"ap-0.1": 0.988209,
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"ap-0.15": 0.989728,
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"ap-0.25": 0.989728,
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"ap-0.5": 0.989728
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},
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"nose": {
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"count": 1462,
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"mean": 0.009366,
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"median": 0.008127,
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"std": 0.007158,
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"sem": 0.000187,
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"min": 0.001832,
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"max": 0.089174,
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"recall-0.025": 0.982912,
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"recall-0.05": 0.98838,
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"recall-0.1": 0.999316,
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"recall-0.15": 0.999316,
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"recall-0.25": 0.999316,
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"recall-0.5": 0.999316,
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"num_labels": 1463
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},
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"shoulder_left": {
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"count": 1465,
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"mean": 0.010461,
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"median": 0.009022,
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"std": 0.006253,
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"sem": 0.000163,
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"min": 0.000486,
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"max": 0.042895,
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"recall-0.025": 0.965211,
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"recall-0.05": 0.999318,
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"recall-0.1": 0.999318,
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"recall-0.15": 0.999318,
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"recall-0.25": 0.999318,
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"recall-0.5": 0.999318,
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"num_labels": 1466
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},
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"shoulder_right": {
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"count": 1464,
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"mean": 0.011754,
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"median": 0.010296,
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"std": 0.006613,
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"sem": 0.000173,
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"min": 0.000586,
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"max": 0.082849,
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"recall-0.025": 0.963823,
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"recall-0.05": 0.99727,
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"recall-0.1": 0.999317,
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"recall-0.15": 0.999317,
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"recall-0.25": 0.999317,
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"recall-0.5": 0.999317,
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"num_labels": 1465
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},
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"elbow_left": {
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"count": 1464,
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"mean": 0.013819,
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"median": 0.012248,
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"std": 0.008099,
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"sem": 0.000212,
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"min": 0.001903,
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"max": 0.065253,
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"recall-0.025": 0.92628,
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"recall-0.05": 0.992491,
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"recall-0.1": 0.999317,
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"recall-0.15": 0.999317,
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"recall-0.25": 0.999317,
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"recall-0.5": 0.999317,
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"num_labels": 1465
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},
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"elbow_right": {
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"count": 1462,
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"mean": 0.013849,
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"median": 0.012421,
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"std": 0.008812,
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"sem": 0.000231,
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"min": 0.000687,
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"max": 0.167748,
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"recall-0.025": 0.935065,
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"recall-0.05": 0.991114,
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"recall-0.1": 0.998633,
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"recall-0.15": 0.998633,
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"recall-0.25": 0.999316,
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"recall-0.5": 0.999316,
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"num_labels": 1463
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},
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"wrist_left": {
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"count": 1433,
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"mean": 0.015001,
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"median": 0.010714,
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"std": 0.016661,
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"sem": 0.00044,
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"min": 0.000797,
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"max": 0.148407,
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"recall-0.025": 0.887727,
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"recall-0.05": 0.967225,
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"recall-0.1": 0.990237,
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"recall-0.15": 0.999303,
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"recall-0.25": 0.999303,
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"recall-0.5": 0.999303,
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"num_labels": 1434
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},
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"wrist_right": {
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"count": 1456,
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"mean": 0.014295,
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"median": 0.010251,
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"std": 0.012861,
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"sem": 0.000337,
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"min": 0.000738,
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"max": 0.093478,
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"recall-0.025": 0.876374,
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"recall-0.05": 0.972527,
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"recall-0.1": 1.0,
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"recall-0.15": 1.0,
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"recall-0.25": 1.0,
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"recall-0.5": 1.0,
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"num_labels": 1456
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},
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"hip_left": {
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"count": 1464,
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"mean": 0.02108,
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"median": 0.01849,
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"std": 0.011596,
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"sem": 0.000303,
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"min": 0.001987,
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"max": 0.084873,
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"recall-0.025": 0.746075,
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"recall-0.05": 0.967918,
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"recall-0.1": 0.999317,
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"recall-0.15": 0.999317,
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"recall-0.25": 0.999317,
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"recall-0.5": 0.999317,
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"num_labels": 1465
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},
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"hip_right": {
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"count": 1465,
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"mean": 0.022031,
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"median": 0.021111,
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"std": 0.010293,
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"sem": 0.000269,
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"min": 0.001982,
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"max": 0.184573,
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"recall-0.025": 0.651432,
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"recall-0.05": 0.992497,
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"recall-0.1": 0.998636,
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"recall-0.15": 0.998636,
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"recall-0.25": 0.999318,
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"recall-0.5": 0.999318,
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"num_labels": 1466
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},
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"knee_left": {
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"count": 1464,
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"mean": 0.023031,
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"median": 0.020769,
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"std": 0.012813,
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"sem": 0.000335,
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"min": 0.002548,
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"max": 0.113513,
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"recall-0.025": 0.640273,
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"recall-0.05": 0.958362,
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"recall-0.1": 0.997952,
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"recall-0.15": 0.999317,
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"recall-0.25": 0.999317,
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"recall-0.5": 0.999317,
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"num_labels": 1465
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},
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"knee_right": {
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"count": 1458,
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"mean": 0.024958,
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"median": 0.022737,
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"std": 0.016621,
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"sem": 0.000435,
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"min": 0.001307,
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"max": 0.175266,
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"recall-0.025": 0.579849,
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"recall-0.05": 0.957505,
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"recall-0.1": 0.986292,
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"recall-0.15": 0.998629,
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"recall-0.25": 0.999315,
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"recall-0.5": 0.999315,
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"num_labels": 1459
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},
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"ankle_left": {
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"count": 1462,
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"mean": 0.048153,
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"median": 0.032151,
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"std": 0.042385,
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"sem": 0.001109,
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"min": 0.001567,
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"max": 0.240114,
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"recall-0.025": 0.386193,
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"recall-0.05": 0.67054,
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"recall-0.1": 0.859193,
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"recall-0.15": 0.966507,
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"recall-0.25": 0.999316,
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"recall-0.5": 0.999316,
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"num_labels": 1463
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},
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"ankle_right": {
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"count": 1458,
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"mean": 0.049114,
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"median": 0.028611,
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"std": 0.047326,
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"sem": 0.00124,
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"min": 0.001747,
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"max": 0.286754,
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"recall-0.025": 0.444521,
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"recall-0.05": 0.670548,
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"recall-0.1": 0.854795,
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"recall-0.15": 0.95274,
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"recall-0.25": 0.99589,
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"recall-0.5": 0.99863,
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"num_labels": 1460
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},
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"joint_recalls": {
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"num_labels": 18990,
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"recall-0.025": 0.76777,
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"recall-0.05": 0.93244,
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"recall-0.1": 0.9752,
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"recall-0.15": 0.99273,
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"recall-0.25": 0.99868,
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"recall-0.5": 0.99889
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}
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}
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{
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"total_parts": 20444,
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"correct_parts": 20400,
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"pcp": 0.997848
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}
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```
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### IkeaAsm
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### IkeaAsm
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(duration 00:01:45)
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(duration 00:01:45)
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@ -66,11 +66,13 @@ datasets = {
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"cams": ["00_03", "00_06", "00_12", "00_13", "00_23"],
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"cams": ["00_03", "00_06", "00_12", "00_13", "00_23"],
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# "cams": ["00_03", "00_06", "00_12"],
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# "cams": ["00_03", "00_06", "00_12"],
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# "cams": ["00_03", "00_06", "00_12", "00_13", "00_23", "00_15", "00_10", "00_21", "00_09", "00_01"],
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# "cams": ["00_03", "00_06", "00_12", "00_13", "00_23", "00_15", "00_10", "00_21", "00_09", "00_01"],
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# "cams": [],
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"take_interval": 3,
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"take_interval": 3,
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"min_match_score": 0.95,
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"min_match_score": 0.95,
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"use_scenes": ["160906_pizza1", "160422_haggling1", "160906_ian5"],
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"use_scenes": ["160906_pizza1", "160422_haggling1", "160906_ian5"],
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"min_group_size": 1,
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"min_group_size": 1,
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# "min_group_size": 4,
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# "min_group_size": 4,
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# "min_group_size": 11,
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"min_bbox_area": 0.05 * 0.05,
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"min_bbox_area": 0.05 * 0.05,
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},
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},
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"mvor": {
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"mvor": {
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@ -220,7 +222,7 @@ def load_labels(dataset: dict):
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]
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]
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# Filter cameras
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# Filter cameras
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if not "cameras_depth" in labels[0]:
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if not "cameras_depth" in labels[0] and len(dataset["panoptic"]["cams"]) > 0:
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for label in labels:
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for label in labels:
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for i, cam in reversed(list(enumerate(label["cameras"]))):
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for i, cam in reversed(list(enumerate(label["cameras"]))):
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if cam["name"] not in dataset["panoptic"]["cams"]:
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if cam["name"] not in dataset["panoptic"]["cams"]:
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Reference in New Issue
Block a user