59 lines
1.9 KiB
Python
59 lines
1.9 KiB
Python
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# function to read data
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"""
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This class provides:
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| write | vis
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- keypoints2d | x | o
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- keypoints3d | x | o
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- smpl | x | o
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"""
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import numpy as np
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from .file_utils import read_json
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def read_keypoints2d(filename):
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pass
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def read_keypoints3d(filename):
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data = read_json(filename)
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res_ = []
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for d in data:
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pid = d['id'] if 'id' in d.keys() else d['personID']
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pose3d = np.array(d['keypoints3d'])
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if pose3d.shape[0] > 25:
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# 对于有手的情况，把手的根节点赋值成body25上的点
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pose3d[25, :] = pose3d[7, :]
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pose3d[46, :] = pose3d[4, :]
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res_.append({
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'id': pid,
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'keypoints3d': pose3d
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})
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return res_
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def read_smpl(filename):
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datas = read_json(filename)
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outputs = []
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for data in datas:
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for key in ['Rh', 'Th', 'poses', 'shapes']:
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data[key] = np.array(data[key])
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# for smplx results
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outputs.append(data)
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return outputs
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def read_keypoints3d_a4d(outname):
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res_ = []
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with open(outname, "r") as file:
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lines = file.readlines()
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if len(lines) < 2:
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return res_
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nPerson, nJoints = int(lines[0]), int(lines[1])
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# 只包含每个人的结果
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lines = lines[1:]
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# 每个人的都写了关键点数量
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line_per_person = 1 + 1 + nJoints
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for i in range(nPerson):
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trackId = int(lines[i*line_per_person+1])
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content = ''.join(lines[i*line_per_person+2:i*line_per_person+2+nJoints])
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pose3d = np.fromstring(content, dtype=float, sep=' ').reshape((nJoints, 4))
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# association4d 的关节顺序和正常的定义不一样
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pose3d = pose3d[[4, 1, 5, 9, 13, 6, 10, 14, 0, 2, 7, 11, 3, 8, 12], :]
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res_.append({'id':trackId, 'keypoints3d':np.array(pose3d)})
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return res_
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