576 lines
14 KiB
Python
576 lines
14 KiB
Python
import numpy as np
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# SMPL_JOINTS = {
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# "hips": 0,
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# "leftUpLeg": 1,
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# "rightUpLeg": 2,
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# "spine": 3,
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# "leftLeg": 4,
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# "rightLeg": 5,
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# "spine1": 6,
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# "leftFoot": 7,
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# "rightFoot": 8,
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# "spine2": 9,
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# "leftToeBase": 10,
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# "rightToeBase": 11,
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# "neck": 12,
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# "leftShoulder": 13,
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# "rightShoulder": 14,
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# "head": 15,
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# "leftArm": 16,
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# "rightArm": 17,
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# "leftForeArm": 18,
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# "rightForeArm": 19,
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# "leftHand": 20,
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# "rightHand": 21,
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# }
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MANO_JOINTS = {
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'wrist': 0,
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'index1': 1,
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'index2': 2,
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'index3': 3,
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'middle1': 4,
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'middle2': 5,
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'middle3': 6,
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'pinky1': 7,
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'pinky2': 8,
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'pinky3': 9,
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'ring1': 10,
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'ring2': 11,
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'ring3': 12,
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'thumb1': 13,
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'thumb2': 14,
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'thumb3': 15,
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}
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OP_IGNORE_JOINTS = None
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OP_NUM_JOINTS = 21
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# SMPL_PARENTS = [
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# -1,
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# 0,
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# 0,
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# 0,
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# 1,
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# 2,
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# 3,
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# 4,
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# 5,
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# 6,
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# 7,
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# 8,
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# 9,
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# 12,
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# 12,
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# 12,
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# 13,
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# 14,
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# 16,
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# 17,
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# 18,
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# 19,
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# ]
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SMPLH_PATH = "./body_models/smplh"
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SMPLX_PATH = "./body_models/smplx"
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SMPL_PATH = "./body_models/smpl"
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VPOSER_PATH = "./body_models/vposer_v1_0"
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# chosen virtual mocap markers that are "keypoints" to work with
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# KEYPT_VERTS = [
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# 4404,
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# 920,
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# 3076,
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# 3169,
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# 823,
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# 4310,
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# 1010,
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# 1085,
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# 4495,
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# 4569,
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# 6615,
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# 3217,
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# 3313,
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# 6713,
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# 6785,
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# 3383,
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# 6607,
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# 3207,
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# 1241,
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# 1508,
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# 4797,
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# 4122,
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# 1618,
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# 1569,
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# 5135,
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# 5040,
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# 5691,
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# 5636,
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# 5404,
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# 2230,
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# 2173,
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# 2108,
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# 134,
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# 3645,
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# 6543,
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# 3123,
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# 3024,
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# 4194,
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# 1306,
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# 182,
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# 3694,
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# 4294,
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# 744,
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# ]
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# """
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# Openpose
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# """
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# OP_NUM_JOINTS = 25
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# # OP_IGNORE_JOINTS = [1, 9, 12] # neck and left/right hip
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# OP_IGNORE_JOINTS = [1] # neck
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# OP_EDGE_LIST = [
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# [1, 8],
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# [1, 2],
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# [1, 5],
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# [2, 3],
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# [3, 4],
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# [5, 6],
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# [6, 7],
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# [8, 9],
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# [9, 10],
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# [10, 11],
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# [8, 12],
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# [12, 13],
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# [13, 14],
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# [1, 0],
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# [0, 15],
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# [15, 17],
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# [0, 16],
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# [16, 18],
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# [14, 19],
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# [19, 20],
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# [14, 21],
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# [11, 22],
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# [22, 23],
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# [11, 24],
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# ]
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# # indices to map an openpose detection to its flipped version
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# OP_FLIP_MAP = [
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# 0,
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# 1,
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# 5,
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# 6,
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# 7,
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# 2,
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# 3,
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# 4,
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# 8,
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# 12,
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# 13,
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# 14,
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# 9,
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# 10,
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# 11,
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# 16,
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# 15,
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# 18,
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# 17,
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# 22,
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# 23,
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# 24,
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# 19,
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# 20,
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# 21,
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# ]
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#
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# From https://github.com/vchoutas/smplify-x/blob/master/smplifyx/utils.py
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# Please see license for usage restrictions.
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#
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# def smpl_to_openpose(
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# model_type="smplx",
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# use_hands=True,
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# use_face=True,
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# use_face_contour=False,
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# openpose_format="coco25",
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# ):
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# """Returns the indices of the permutation that maps SMPL to OpenPose
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# Parameters
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# ----------
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# model_type: str, optional
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# The type of SMPL-like model that is used. The default mapping
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# returned is for the SMPLX model
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# use_hands: bool, optional
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# Flag for adding to the returned permutation the mapping for the
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# hand keypoints. Defaults to True
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# use_face: bool, optional
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# Flag for adding to the returned permutation the mapping for the
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# face keypoints. Defaults to True
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# use_face_contour: bool, optional
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# Flag for appending the facial contour keypoints. Defaults to False
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# openpose_format: bool, optional
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# The output format of OpenPose. For now only COCO-25 and COCO-19 is
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# supported. Defaults to 'coco25'
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# """
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# if openpose_format.lower() == "coco25":
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# if model_type == "smpl":
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# return np.array(
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# [
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# 24,
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# 12,
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# 17,
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# 19,
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# 21,
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# 16,
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# 18,
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# 20,
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# 0,
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# 2,
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# 5,
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# 8,
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# 1,
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# 4,
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# 7,
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# 25,
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# 26,
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# 27,
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# 28,
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# 29,
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# 30,
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# 31,
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# 32,
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# 33,
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# 34,
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# ],
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# dtype=np.int32,
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# )
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# elif model_type == "smplh":
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# body_mapping = np.array(
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# [
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# 52,
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# 12,
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# 17,
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# 19,
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# 21,
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# 16,
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# 18,
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# 20,
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# 0,
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# 2,
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# 5,
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# 8,
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# 1,
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# 4,
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# 7,
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# 53,
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# 54,
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# 55,
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# 56,
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# 57,
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# 58,
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# 59,
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# 60,
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# 61,
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# 62,
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# ],
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# dtype=np.int32,
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# )
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# mapping = [body_mapping]
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# if use_hands:
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# lhand_mapping = np.array(
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# [
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# 20,
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# 34,
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# 35,
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# 36,
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# 63,
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# 22,
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# 23,
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# 24,
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# 64,
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# 25,
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# 26,
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# 27,
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# 65,
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# 31,
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# 32,
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# 33,
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# 66,
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# 28,
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# 29,
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# 30,
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# 67,
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# ],
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# dtype=np.int32,
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# )
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# rhand_mapping = np.array(
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# [
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# 21,
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# 49,
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# 50,
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# 51,
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# 68,
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# 37,
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# 38,
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# 39,
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# 69,
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# 40,
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# 41,
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# 42,
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# 70,
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# 46,
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# 47,
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# 48,
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# 71,
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# 43,
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# 44,
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# 45,
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# 72,
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# ],
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# dtype=np.int32,
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# )
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# mapping += [lhand_mapping, rhand_mapping]
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# return np.concatenate(mapping)
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# # SMPLX
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# elif model_type == "smplx":
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# body_mapping = np.array(
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# [
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# 55,
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# 12,
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# 17,
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# 19,
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# 21,
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# 16,
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# 18,
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# 20,
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# 0,
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# 2,
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# 5,
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# 8,
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# 1,
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# 4,
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# 7,
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# 56,
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# 57,
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# 58,
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# 59,
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# 60,
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# 61,
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# 62,
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# 63,
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# 64,
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# 65,
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# ],
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# dtype=np.int32,
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# )
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# mapping = [body_mapping]
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# if use_hands:
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# lhand_mapping = np.array(
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# [
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# 20,
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# 37,
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# 38,
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# 39,
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# 66,
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# 25,
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# 26,
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# 27,
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# 67,
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# 28,
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# 29,
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# 30,
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# 68,
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# 34,
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# 35,
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# 36,
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# 69,
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# 31,
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# 32,
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# 33,
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# 70,
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# ],
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# dtype=np.int32,
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# )
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# rhand_mapping = np.array(
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# [
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# 21,
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# 52,
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# 53,
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# 54,
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# 71,
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# 40,
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# 41,
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# 42,
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# 72,
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# 43,
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# 44,
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# 45,
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# 73,
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# 49,
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# 50,
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# 51,
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# 74,
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# 46,
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# 47,
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# 48,
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# 75,
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# ],
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# dtype=np.int32,
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# )
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# mapping += [lhand_mapping, rhand_mapping]
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# if use_face:
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# # end_idx = 127 + 17 * use_face_contour
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# face_mapping = np.arange(
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# 76, 127 + 17 * use_face_contour, dtype=np.int32
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# )
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# mapping += [face_mapping]
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# return np.concatenate(mapping)
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# else:
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# raise ValueError("Unknown model type: {}".format(model_type))
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# elif openpose_format == "coco19":
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# if model_type == "smpl":
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# return np.array(
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# [24, 12, 17, 19, 21, 16, 18, 20, 0, 2, 5, 8, 1, 4, 7, 25, 26, 27, 28],
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# dtype=np.int32,
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# )
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# elif model_type == "smplh":
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# body_mapping = np.array(
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# [52, 12, 17, 19, 21, 16, 18, 20, 0, 2, 5, 8, 1, 4, 7, 53, 54, 55, 56],
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# dtype=np.int32,
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# )
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# mapping = [body_mapping]
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# if use_hands:
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# lhand_mapping = np.array(
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# [
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# 20,
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# 34,
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# 35,
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# 36,
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# 57,
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# 22,
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# 23,
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# 24,
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# 58,
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# 25,
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# 26,
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# 27,
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# 59,
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# 31,
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# 32,
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# 33,
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# 60,
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# 28,
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# 29,
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# 30,
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# 61,
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# ],
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# dtype=np.int32,
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# )
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# rhand_mapping = np.array(
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# [
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# 21,
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# 49,
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# 50,
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# 51,
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# 62,
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# 37,
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# 38,
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# 39,
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# 63,
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# 40,
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# 41,
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# 42,
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# 64,
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# 46,
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# 47,
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# 48,
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# 65,
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# 43,
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# 44,
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# 45,
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# 66,
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# ],
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# dtype=np.int32,
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# )
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# mapping += [lhand_mapping, rhand_mapping]
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# return np.concatenate(mapping)
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# # SMPLX
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# elif model_type == "smplx":
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# body_mapping = np.array(
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# [55, 12, 17, 19, 21, 16, 18, 20, 0, 2, 5, 8, 1, 4, 7, 56, 57, 58, 59],
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# dtype=np.int32,
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# )
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# mapping = [body_mapping]
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# if use_hands:
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# lhand_mapping = np.array(
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# [
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# 20,
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# 37,
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# 38,
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# 39,
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# 60,
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# 25,
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# 26,
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# 27,
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# 61,
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# 28,
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# 29,
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# 30,
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# 62,
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# 34,
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# 35,
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# 36,
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# 63,
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# 31,
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# 32,
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# 33,
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# 64,
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# ],
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# dtype=np.int32,
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# )
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# rhand_mapping = np.array(
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# [
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# 21,
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# 52,
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# 53,
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# 54,
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# 65,
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# 40,
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# 41,
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# 42,
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# 66,
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# 43,
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# 44,
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# 45,
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# 67,
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# 49,
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# 50,
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# 51,
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# 68,
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# 46,
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# 47,
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# 48,
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# 69,
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# ],
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# dtype=np.int32,
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# )
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# mapping += [lhand_mapping, rhand_mapping]
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# if use_face:
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# face_mapping = np.arange(
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# 70, 70 + 51 + 17 * use_face_contour, dtype=np.int32
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# )
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# mapping += [face_mapping]
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# return np.concatenate(mapping)
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# else:
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# raise ValueError("Unknown model type: {}".format(model_type))
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# else:
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# raise ValueError("Unknown joint format: {}".format(openpose_format))
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