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| # Copyright (c) 2025 Bytedance Ltd. and/or its affiliates | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """ | |
| You can convert npz file back to obj(mesh) and txt(rig) files using this python script. | |
| """ | |
| import os | |
| import numpy as np | |
| import scipy.sparse as sp | |
| def export_obj(vertices, faces, normals, output_path): | |
| with open(output_path, 'w') as f: | |
| for v in vertices: | |
| f.write(f"v {v[0]} {v[1]} {v[2]}\n") | |
| for n in normals: | |
| f.write(f"vn {n[0]} {n[1]} {n[2]}\n") | |
| for i, face in enumerate(faces): | |
| # OBJ format is 1-based, so we add 1 to all indices | |
| f.write(f"f {face[0]+1}//{face[0]+1} {face[1]+1}//{face[1]+1} {face[2]+1}//{face[2]+1}\n") | |
| def export_rig_txt(joints, bones, root_index, joint_names, skinning_weights, output_path): | |
| """ | |
| joints [joint_name] [x] [y] [z] | |
| root [root_joint_name] | |
| skin [vertex_index] [joint_name1] [weight1] [joint_name2] [weight2] ... | |
| hier [parent_joint_name] [child_joint_name] | |
| """ | |
| n_joints = len(joints) | |
| n_verts = skinning_weights.shape[0] # (n_vertex, n_joints) | |
| with open(output_path, 'w') as f: | |
| # 1) joints | |
| for i in range(n_joints): | |
| x, y, z = joints[i] | |
| jn = joint_names[i] | |
| f.write(f"joints {jn} {x} {y} {z}\n") | |
| # 2) root | |
| root_name = joint_names[root_index] | |
| f.write(f"root {root_name}\n") | |
| # 3) skin | |
| for vidx in range(n_verts): | |
| row_weights = skinning_weights[vidx] | |
| non_zero_indices = np.where(row_weights != 0)[0] | |
| if len(non_zero_indices) == 0: | |
| continue | |
| line_parts = [f"skin {vidx}"] # vertex_idx | |
| for jidx in non_zero_indices: | |
| w = row_weights[jidx] | |
| jn = joint_names[jidx] | |
| line_parts.append(jn) | |
| line_parts.append(str(w)) | |
| f.write(" ".join(line_parts) + "\n") | |
| # 4) hier | |
| for p_idx, c_idx in bones: | |
| p_name = joint_names[p_idx] | |
| c_name = joint_names[c_idx] | |
| f.write(f"hier {p_name} {c_name}\n") | |
| if __name__ == "__main__": | |
| data = np.load('articulation_xlv2_test.npz', allow_pickle=True) | |
| data_list = data['arr_0'] | |
| print(f"Loaded {len(data_list)} data entries") | |
| model_data = data_list[0] | |
| print("Data keys:", model_data.keys()) | |
| # 'vertices', 'faces', 'normals', 'joints', 'bones', 'root_index', 'uuid', 'joint_names', | |
| # 'skinning_weights_value', 'skinning_weights_row', 'skinning_weights_col', 'skinning_weights_shape' | |
| vertices = model_data['vertices'] # (n_vertex, 3) | |
| faces = model_data['faces'] # (n_faces, 3) | |
| normals = model_data['normals'] # (n_vertex, 3) | |
| joints = model_data['joints'] # (n_joints, 3) | |
| bones = model_data['bones'] # (n_bones, 2) | |
| root_index = model_data['root_index'] # int | |
| joint_names = model_data['joint_names'] # list of str | |
| uuid_str = model_data['uuid'] | |
| skin_val = model_data['skinning_weights_value'] | |
| skin_row = model_data['skinning_weights_row'] | |
| skin_col = model_data['skinning_weights_col'] | |
| skin_shape = model_data['skinning_weights_shape'] | |
| skin_sparse = sp.coo_matrix((skin_val, (skin_row, skin_col)), shape=skin_shape) | |
| skinning_weights = skin_sparse.toarray() # (n_vertex, n_joints) | |
| obj_path = f"{uuid_str}.obj" | |
| export_obj(vertices, faces, normals, obj_path) | |
| rig_txt_path = f"{uuid_str}.txt" | |
| export_rig_txt(joints, bones, root_index, joint_names, skinning_weights, rig_txt_path) | |
| print("Done!") | |