shape-models-checkpoints / body /body_shape_norm.json

Upload body/body_shape_norm.json with huggingface_hub

aa7d215 verified 2 days ago

2.77 kB

{
  "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)."
}

	{
	"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)."
	}