File size: 2,769 Bytes
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"model_version": "3.3.0",
"feature_schema_version": 2,
"feature_names": [
"shoulder_hip_ratio",
"waist_hip_ratio",
"waist_shoulder_ratio",
"bust_hip_ratio",
"bust_waist_ratio",
"shoulder_waist_diff",
"hip_shoulder_diff",
"hip_waist_diff"
],
"feature_units": {
"shoulder_hip_ratio": "dimensionless (ratio of two widths)",
"waist_hip_ratio": "dimensionless (ratio of two widths)",
"waist_shoulder_ratio": "dimensionless (ratio of two widths)",
"bust_hip_ratio": "dimensionless (ratio of two widths)",
"bust_waist_ratio": "dimensionless (ratio of two widths)",
"shoulder_waist_diff": "dimensionless (width diff / hip width)",
"hip_shoulder_diff": "dimensionless (width diff / hip width)",
"hip_waist_diff": "dimensionless (width diff / hip width)"
},
"hip_cm_reference": 1.0,
"mean": [
0.37780097126960754,
0.8161380887031555,
2.200714111328125,
0.9687443375587463,
1.1990960836410522,
-0.43833690881729126,
0.6221989393234253,
0.18386207520961761
],
"std": [
0.05251329392194748,
0.0854557454586029,
0.3728339374065399,
0.09726245701313019,
0.17114204168319702,
0.0974234789609909,
0.05251329392194748,
0.08545612543821335
],
"raw_min": [
0.2409999966621399,
0.611299991607666,
1.417099952697754,
0.6786999702453613,
0.8282999992370605,
-0.7000498175621033,
0.45520004630088806,
-0.04578861966729164
],
"raw_max": [
0.5447999835014343,
1.045799970626831,
3.4370999336242676,
1.2482999563217163,
1.700600028038025,
-0.20338687300682068,
0.7590000033378601,
0.38873669505119324
],
"normalized_min": [
-2.6050732135772705,
-2.397007942199707,
-2.101778030395508,
-2.982079267501831,
-2.1665985584259033,
-2.686343193054199,
-3.1801259517669678,
-2.687351942062378
],
"normalized_max": [
3.180128335952759,
2.687494993209839,
3.3161838054656982,
2.874239683151245,
2.930337429046631,
2.4116365909576416,
2.605074882507324,
2.3974246978759766
],
"class_names": [
"Hourglass",
"Pear",
"Apple",
"Rectangle",
"Inverted Triangle"
],
"input": {
"shape": [
1,
8
],
"dtype": "float32",
"note": "standardize raw values as (x - mean) / std BEFORE inference"
},
"output": {
"shape": [
1,
5
],
"dtype": "float32",
"type": "softmax"
},
"note_app_side": "All 8 features are DIMENSIONLESS. Compute them from pose keypoint distances in pixels: ratios as the width ratio directly, and diffs as (widthA - widthB) / hipWidth. Then standardize with mean/std. hip_cm_reference should be ignored (it is 1.0)."
} |