Zzier
609aa0e9aa
* Update ParsingGait * Clear up the confusion Clear up the confusion about gait3d and gait3d-parsing. * Update 0.get_started.md * Add BaseParsingCuttingTransform * Update gcn.py * Create gaitbase_gait3d_parsing_btz32x2_fixed.yaml * Add gait3d_parsing config file * Update 1.model_zoo.md Update Gait3D-Parsing checkpoints * Update 1.model_zoo.md add configuration * Update 1.model_zoo.md center text --------- Co-authored-by: Junhao Liang <43094337+darkliang@users.noreply.github.com>
83 lines
2.7 KiB
Python
83 lines
2.7 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Author : jinkai Zheng
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date： 2021/10/30
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E-mail: zhengjinkai3@qq.com
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"""
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import os.path as osp
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import time
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import os
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import threading
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import itertools
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import numpy as np
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import pickle
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import argparse
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parser = argparse.ArgumentParser(description='Test')
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parser.add_argument('-i', '--input_path', default='', type=str,
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help='Root path of raw dataset.')
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parser.add_argument('-o', '--output_path', default='', type=str,
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help='Root path for output.')
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opt = parser.parse_args()
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def get_pickle(thread_id, id_list, save_dir):
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for id in sorted(id_list):
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print(f"Process threadID-PID: {thread_id}-{id}")
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cam_list = os.listdir(osp.join(data_dir, id))
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cam_list.sort()
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for cam in cam_list:
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seq_list = os.listdir(osp.join(data_dir, id, cam))
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seq_list.sort()
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for seq in seq_list:
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npz_list = os.listdir(osp.join(data_dir, id, cam, seq))
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npz_list.sort()
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smpl_paras_fras = []
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for npz in npz_list:
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npz_path = osp.join(data_dir, id, cam, seq, npz)
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frame = np.load(npz_path, allow_pickle=True)['results'][()][0]
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smpl_cam = frame['cam'] # 3-D
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smpl_pose = frame['poses'] # 72-D
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smpl_shape = frame['betas'] # 10-D
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smpl_paras = np.concatenate((smpl_cam, smpl_pose, smpl_shape), 0)
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smpl_paras_fras.append(smpl_paras)
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smpl_paras_fras = np.asarray(smpl_paras_fras)
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out_dir = osp.join(save_dir, id, cam, seq)
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os.makedirs(out_dir)
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smpl_paras_fras_pkl = os.path.join(out_dir, '{}.pkl'.format(seq))
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pickle.dump(smpl_paras_fras, open(smpl_paras_fras_pkl, 'wb'))
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if __name__ == '__main__':
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data_dir = opt.input_path
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save_dir = opt.output_path
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start_time = time.time()
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maxnum_thread = 8
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all_ids = sorted(os.listdir(data_dir))
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num_ids = len(all_ids)
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proces = []
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for thread_id in range(maxnum_thread):
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indices = itertools.islice(range(num_ids), thread_id, num_ids, maxnum_thread)
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id_list = [all_ids[i] for i in indices]
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thread_func = threading.Thread(target=get_pickle, args=(thread_id, id_list, save_dir))
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thread_func.start()
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proces.append(thread_func)
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for proc in proces:
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proc.join()
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time_elapsed = time.time() - start_time
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print('Training complete in {:.0f}h {:.0f}m {:.0f}s'.format(
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time_elapsed // 3600,
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(time_elapsed - (time_elapsed // 3600) * 3600) // 60,
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time_elapsed % 60)) |