explore tailornet dataset

tailornet.py

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+import os
+import numpy as np
+import plotly.express as ex
+from simpleicp import PointCloud, SimpleICP
+from scipy.spatial.distance import cdist
+
+folder = '/home/workspace/data/dataset/tailornet'
+
+def get_data_split():
+    data = np.load(os.path.join(folder, 'split_static_pose_shape.npz'))
+    return data['train'], data['test']
+
+
+def get_garment_info(garment_class):
+    data = np.load(os.path.join(folder, 'garment_class_info.pkl'), allow_pickle=True)
+    return data[garment_class]
+
+
+def get_smpl():
+    data = np.load(os.path.join('TailorNet_dataset/smpl/smpl_female.npz'), allow_pickle=True)
+    data_high_res = np.load(os.path.join('TailorNet_dataset/smpl/smpl_hres_female.npz'), allow_pickle=True)
+    supersmpl = np.load(os.path.join('custom_utils/super_model_f.pkl'), allow_pickle=True)
+
+    return data_high_res['v_template'], supersmpl['v_template']
+
+    print()
+
+
+def register_smpl(verts_1, verts_2):
+
+    # Create point cloud objects
+    pc_fix = PointCloud(verts_1, columns=["x", "y", "z"])
+    pc_mov = PointCloud(verts_2, columns=["x", "y", "z"])
+
+    # Create simpleICP object, add point clouds, and run algorithm!
+    icp = SimpleICP()
+    icp.add_point_clouds(pc_fix, pc_mov)
+    H, X_mov_transformed, rigid_body_transformation_params = icp.run(correspondences=10000, min_change=0.01, neighbors=25)
+
+    dist = cdist(verts_1, X_mov_transformed)
+    matching_dist = np.min(dist, axis=1)
+    matching = np.argmin(dist, axis=1)
+    
+
+    print()
+
+
+if __name__ == '__main__':
+    train_split, test_split = get_data_split()
+    garment_info = get_garment_info('old-t-shirt')
+    smpl = get_smpl()
+    tailornet_smpl, super_smpl = get_smpl()
+    # registration = register_smpl(super_smpl, tailornet_smpl)
+
+    print()