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Small fixes.

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This commit is contained in:
Daniel
2024-09-11 11:15:41 +02:00
parent 13aa790de1
commit 7b426d209c
2 changed files with 56 additions and 56 deletions
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108
media/RESULTS.md
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@ -7,16 +7,16 @@ Results of the model in various experiments on different datasets.
(duration 00:01:20) (duration 00:01:20)
```json ```json
{ {
"avg_time_2d": 0.07194638131028515, "avg_time_2d": 0.07035206899804584,
"avg_time_3d": 0.0031490806805885446, "avg_time_3d": 0.003138972945132498,
"avg_fps": 13.316383886439496 "avg_fps": 13.607100587486267
} }
{ {
"person_nums": { "person_nums": {
"total_frames": 600, "total_frames": 600,
"total_labels": 600, "total_labels": 600,
"total_preds": 601, "total_preds": 600,
"considered_empty": 1, "considered_empty": 0,
"valid_preds": 600, "valid_preds": 600,
"invalid_preds": 0, "invalid_preds": 0,
"missing": 0, "missing": 0,
@ -28,9 +28,9 @@ Results of the model in various experiments on different datasets.
}, },
"mpjpe": { "mpjpe": {
"count": 600, "count": 600,
"mean": 0.066878, "mean": 0.066893,
"median": 0.059221, "median": 0.059279,
"std": 0.027763, "std": 0.027761,
"sem": 0.001134, "sem": 0.001134,
"min": 0.043707, "min": 0.043707,
"max": 0.189867, "max": 0.189867,
@ -42,18 +42,18 @@ Results of the model in various experiments on different datasets.
"recall-0.5": 1.0, "recall-0.5": 1.0,
"num_labels": 600, "num_labels": 600,
"ap-0.025": 0.0, "ap-0.025": 0.0,
"ap-0.05": 0.002245, "ap-0.05": 0.002244,
"ap-0.1": 0.895107, "ap-0.1": 0.895111,
"ap-0.15": 0.917238, "ap-0.15": 0.917246,
"ap-0.25": 1.0, "ap-0.25": 1.0,
"ap-0.5": 1.0 "ap-0.5": 1.0
}, },
"nose": { "nose": {
"count": 600, "count": 600,
"mean": 0.117653, "mean": 0.117674,
"median": 0.101455, "median": 0.101455,
"std": 0.042711, "std": 0.042793,
"sem": 0.001745, "sem": 0.001748,
"min": 0.046466, "min": 0.046466,
"max": 0.271134, "max": 0.271134,
"recall-0.025": 0.0, "recall-0.025": 0.0,
@ -66,13 +66,13 @@ Results of the model in various experiments on different datasets.
}, },
"shoulder_left": { "shoulder_left": {
"count": 600, "count": 600,
"mean": 0.033344, "mean": 0.033355,
"median": 0.02547, "median": 0.025557,
"std": 0.032209, "std": 0.032207,
"sem": 0.001316, "sem": 0.001316,
"min": 0.003037, "min": 0.003037,
"max": 0.181945, "max": 0.181945,
"recall-0.025": 0.49, "recall-0.025": 0.488333,
"recall-0.05": 0.875, "recall-0.05": 0.875,
"recall-0.1": 0.946667, "recall-0.1": 0.946667,
"recall-0.15": 0.965, "recall-0.15": 0.965,
@ -82,15 +82,15 @@ Results of the model in various experiments on different datasets.
}, },
"shoulder_right": { "shoulder_right": {
"count": 600, "count": 600,
"mean": 0.048035, "mean": 0.048174,
"median": 0.033333, "median": 0.033305,
"std": 0.04253, "std": 0.042712,
"sem": 0.001738, "sem": 0.001745,
"min": 0.003882, "min": 0.003882,
"max": 0.247363, "max": 0.247363,
"recall-0.025": 0.238333, "recall-0.025": 0.238333,
"recall-0.05": 0.766667, "recall-0.05": 0.766667,
"recall-0.1": 0.903333, "recall-0.1": 0.901667,
"recall-0.15": 0.936667, "recall-0.15": 0.936667,
"recall-0.25": 1.0, "recall-0.25": 1.0,
"recall-0.5": 1.0, "recall-0.5": 1.0,
@ -98,14 +98,14 @@ Results of the model in various experiments on different datasets.
}, },
"elbow_left": { "elbow_left": {
"count": 600, "count": 600,
"mean": 0.042537, "mean": 0.042548,
"median": 0.034439, "median": 0.034439,
"std": 0.0346, "std": 0.034603,
"sem": 0.001414, "sem": 0.001414,
"min": 0.002682, "min": 0.002682,
"max": 0.193558, "max": 0.193558,
"recall-0.025": 0.273333, "recall-0.025": 0.273333,
"recall-0.05": 0.82, "recall-0.05": 0.818333,
"recall-0.1": 0.943333, "recall-0.1": 0.943333,
"recall-0.15": 0.956667, "recall-0.15": 0.956667,
"recall-0.25": 1.0, "recall-0.25": 1.0,
@ -114,8 +114,8 @@ Results of the model in various experiments on different datasets.
}, },
"elbow_right": { "elbow_right": {
"count": 600, "count": 600,
"mean": 0.043251, "mean": 0.04325,
"median": 0.033208, "median": 0.03319,
"std": 0.035165, "std": 0.035165,
"sem": 0.001437, "sem": 0.001437,
"min": 0.00667, "min": 0.00667,
@ -130,12 +130,12 @@ Results of the model in various experiments on different datasets.
}, },
"wrist_left": { "wrist_left": {
"count": 600, "count": 600,
"mean": 0.040583, "mean": 0.040627,
"median": 0.024203, "median": 0.024203,
"std": 0.04223, "std": 0.042377,
"sem": 0.001725, "sem": 0.001731,
"min": 0.001517, "min": 0.001517,
"max": 0.184684, "max": 0.18543,
"recall-0.025": 0.516667, "recall-0.025": 0.516667,
"recall-0.05": 0.746667, "recall-0.05": 0.746667,
"recall-0.1": 0.908333, "recall-0.1": 0.908333,
@ -146,13 +146,13 @@ Results of the model in various experiments on different datasets.
}, },
"wrist_right": { "wrist_right": {
"count": 600, "count": 600,
"mean": 0.042641, "mean": 0.042646,
"median": 0.025715, "median": 0.025673,
"std": 0.046903, "std": 0.046896,
"sem": 0.001916, "sem": 0.001916,
"min": 0.001698, "min": 0.001698,
"max": 0.425617, "max": 0.425617,
"recall-0.025": 0.48, "recall-0.025": 0.481667,
"recall-0.05": 0.771667, "recall-0.05": 0.771667,
"recall-0.1": 0.896667, "recall-0.1": 0.896667,
"recall-0.15": 0.921667, "recall-0.15": 0.921667,
@ -162,9 +162,9 @@ Results of the model in various experiments on different datasets.
}, },
"hip_left": { "hip_left": {
"count": 600, "count": 600,
"mean": 0.089628, "mean": 0.089623,
"median": 0.086723, "median": 0.086723,
"std": 0.032971, "std": 0.032973,
"sem": 0.001347, "sem": 0.001347,
"min": 0.01535, "min": 0.01535,
"max": 0.236764, "max": 0.236764,
@ -178,10 +178,10 @@ Results of the model in various experiments on different datasets.
}, },
"hip_right": { "hip_right": {
"count": 600, "count": 600,
"mean": 0.11452, "mean": 0.114501,
"median": 0.114981, "median": 0.114981,
"std": 0.026088, "std": 0.026109,
"sem": 0.001066, "sem": 0.001067,
"min": 0.046173, "min": 0.046173,
"max": 0.234935, "max": 0.234935,
"recall-0.025": 0.0, "recall-0.025": 0.0,
@ -194,9 +194,9 @@ Results of the model in various experiments on different datasets.
}, },
"knee_left": { "knee_left": {
"count": 600, "count": 600,
"mean": 0.060824, "mean": 0.060815,
"median": 0.045004, "median": 0.045004,
"std": 0.061352, "std": 0.061356,
"sem": 0.002507, "sem": 0.002507,
"min": 0.01946, "min": 0.01946,
"max": 0.425374, "max": 0.425374,
@ -210,14 +210,14 @@ Results of the model in various experiments on different datasets.
}, },
"knee_right": { "knee_right": {
"count": 600, "count": 600,
"mean": 0.051047, "mean": 0.051079,
"median": 0.043249, "median": 0.043279,
"std": 0.034972, "std": 0.034968,
"sem": 0.001429, "sem": 0.001429,
"min": 0.017082, "min": 0.017082,
"max": 0.259899, "max": 0.259899,
"recall-0.025": 0.038333, "recall-0.025": 0.038333,
"recall-0.05": 0.735, "recall-0.05": 0.733333,
"recall-0.1": 0.943333, "recall-0.1": 0.943333,
"recall-0.15": 0.945, "recall-0.15": 0.945,
"recall-0.25": 0.998333, "recall-0.25": 0.998333,
@ -226,7 +226,7 @@ Results of the model in various experiments on different datasets.
}, },
"ankle_left": { "ankle_left": {
"count": 598, "count": 598,
"mean": 0.098282, "mean": 0.098276,
"median": 0.086303, "median": 0.086303,
"std": 0.049778, "std": 0.049778,
"sem": 0.002037, "sem": 0.002037,
@ -242,9 +242,9 @@ Results of the model in various experiments on different datasets.
}, },
"ankle_right": { "ankle_right": {
"count": 600, "count": 600,
"mean": 0.085558, "mean": 0.085539,
"median": 0.068594, "median": 0.068594,
"std": 0.058547, "std": 0.058554,
"sem": 0.002392, "sem": 0.002392,
"min": 0.032987, "min": 0.032987,
"max": 0.463238, "max": 0.463238,
@ -258,8 +258,8 @@ Results of the model in various experiments on different datasets.
}, },
"joint_recalls": { "joint_recalls": {
"num_labels": 7800, "num_labels": 7800,
"recall-0.025": 0.17962, "recall-0.025": 0.17949,
"recall-0.05": 0.47603, "recall-0.05": 0.47564,
"recall-0.1": 0.82154, "recall-0.1": 0.82154,
"recall-0.15": 0.92923, "recall-0.15": 0.92923,
"recall-0.25": 0.99397, "recall-0.25": 0.99397,
@ -268,8 +268,8 @@ Results of the model in various experiments on different datasets.
} }
{ {
"total_parts": 8400, "total_parts": 8400,
"correct_parts": 8092, "correct_parts": 8091,
"pcp": 0.963333 "pcp": 0.963214
} }
``` ```

4
scripts/triangulate_poses.py
View File

@ -247,8 +247,8 @@ def calc_grouping(all_pairs, min_score: float):
if best_group >= 0: if best_group >= 0:
# Add pair to existing group and update the mean positions # Add pair to existing group and update the mean positions
group = groups[best_group] group = groups[best_group]
new_center = (group[0] * len(group[1]) + pair[3]) / (len(group[1]) + 1) new_center = (group[0] * len(group[2]) + pair[3]) / (len(group[2]) + 1)
new_pose = (group[1] * len(group[1]) + pair[2][0]) / (len(group[1]) + 1) new_pose = (group[1] * len(group[2]) + pair[2][0]) / (len(group[2]) + 1)
group[2].append(pair) group[2].append(pair)
group[0] = new_center group[0] = new_center
group[1] = new_pose group[1] = new_pose