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import os |
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import pickle |
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import numpy as np |
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from scipy.sparse import csc_matrix |
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def generate_smpl_weight_file(output_dir): |
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"""Generate a SMPL model weight file to initialize SMPL model, and generate |
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a 3D joints regressor file.""" |
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if not os.path.exists(output_dir): |
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os.makedirs(output_dir) |
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joint_regressor_file = os.path.join(output_dir, 'test_joint_regressor.npy') |
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np.save(joint_regressor_file, np.zeros([24, 6890])) |
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test_data = {} |
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test_data['f'] = np.zeros([1, 3], dtype=np.int32) |
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test_data['J_regressor'] = csc_matrix(np.zeros([24, 6890])) |
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test_data['kintree_table'] = np.zeros([2, 24], dtype=np.uint32) |
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test_data['J'] = np.zeros([24, 3]) |
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test_data['weights'] = np.zeros([6890, 24]) |
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test_data['posedirs'] = np.zeros([6890, 3, 207]) |
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test_data['v_template'] = np.zeros([6890, 3]) |
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test_data['shapedirs'] = np.zeros([6890, 3, 10]) |
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with open(os.path.join(output_dir, 'SMPL_NEUTRAL.pkl'), 'wb') as out_file: |
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pickle.dump(test_data, out_file) |
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with open(os.path.join(output_dir, 'SMPL_MALE.pkl'), 'wb') as out_file: |
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pickle.dump(test_data, out_file) |
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with open(os.path.join(output_dir, 'SMPL_FEMALE.pkl'), 'wb') as out_file: |
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pickle.dump(test_data, out_file) |
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return |
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