mult-skill-act-models / normalization /point4_v30_norm.py
QRP123's picture
Upload folder using huggingface_hub
e5214b3 verified
Raw History Blame Contribute Delete
2.08 kB
"""
归一化常量 - point4_v30
从 data/each-point-V30/point4_v30/meta/stats.json 自动生成
"""
import numpy as np
# ====== 归一化统计量(从 point4_v30 数据集提取)======
# State 归一化参数 (observation.state) - 14D
STATE_MEAN = np.array([
-0.21735365385481095,
1.146649527479852,
-0.8639224236397658,
-0.0366343220295033,
0.9104707563216103,
-0.021397598130488894,
0.059362471541857365,
0.023706428706645966,
-0.031137484798775067,
-0.15235542476220895,
-0.005826317618105161,
0.5936171133118961,
-0.05018620966114964,
7.000005880953068e-05
], dtype=np.float32)
STATE_STD = np.array([
0.2102253805949658,
0.7658808333158452,
0.5529057432367724,
0.07265797427364623,
0.23469697324617478,
0.09436715707689124,
0.03222894862077091,
0.0,
7.767954915336072e-05,
0.0004781704950766074,
5.168509104714842e-09,
0.001913202964455008,
0.00010597815677546606,
3.859463417203669e-08
], dtype=np.float32)
# Action 反归一化参数 - 14D (left_arm 7D + right_arm 7D)
ACTION_MEAN = np.array([
-0.21809362965479312,
1.1355306549402504,
-0.8904613166359503,
-0.04333029593342418,
0.8643201283589087,
-0.023920130371530745,
0.059623906544497396,
0.02365400729111893,
-0.03171323145067094,
-0.17187523067041208,
-0.005878658843141073,
0.5043942354545788,
-0.051233134417770415,
-0.021100036475361048
], dtype=np.float32)
ACTION_STD = np.array([
0.21219605932089225,
0.75205568886306,
0.5567277356808167,
0.08035356119525855,
0.26816162993954756,
0.09766573132322597,
0.03677641727915061,
3.229803036732761e-05,
1.9943653300040918e-05,
0.0004333556851899771,
2.4517295805128176e-09,
3.0683424331473354e-08,
1.388979743365584e-08,
9.329212659536094e-06
], dtype=np.float32)
# Image 归一化参数(ImageNet 标准)
IMAGE_MEAN = np.array([0.485, 0.456, 0.406], dtype=np.float32)
IMAGE_STD = np.array([0.229, 0.224, 0.225], dtype=np.float32)