backup

2022-09-02 14:15:54 +00:00
parent ee8f1cb68c
commit 977e49900d
16 changed files with 2241 additions and 272 deletions
@@ -0,0 +1,117 @@
+import os
+import sys
+import time
+import cv2
+import random
+import numpy as np
+import tensorflow as tf
+import cmapy as cm
+import plotly.graph_objects as go
+import plotly.express as ex
+
+from dataset import DatasetFactory, StaticDataset
+from custom_utils.custom_utils import batch_to_dict, UV2Mesh, _maskFaces
+from custom_utils.smpl import SMPL
+
+if __name__ == '__main__':
+    os.environ["CUDA_VISIBLE_DEVICES"] = "5"
+
+    uv2mesh = UV2Mesh()
+    smpl = SMPL()
+
+    F = np.load("custom_utils/smpl_faces.npy")
+
+    factory = DatasetFactory()
+    signature_dynamic = { 'id': (),
+                          'pose_shape': (72 + 11,),
+                        #   'uv_posed': (3, 512, 256,),
+                        #   'uv_body_posed': (3, 512, 256,),
+                          # 'mesh_body_posed': (14475, 3,),
+                        #   'mesh_posed_body_no_orient': (14475, 3,),
+                          'mesh_posed': (14475, 3,),
+                          'mesh_unposed': (14475, 3,),
+                          # 'uv_unposed': (3, 512, 256,),
+                        #   'uv_curvature': (512, 256),
+                        #   'mesh_curvature':  (14475)
+                        }
+    signature_static = { #'uv_static': (3, 512, 256,),
+                        #  'mesh_static': (14475, 3,),
+                          'mesh_mask': (14475,),
+                        #  'uv_mask': (512, 256,),
+                        #  'uv_shaped_body': (3, 512, 256,),
+                          }
+
+    dataset = factory.get_dataset(folder='/home/workspace/local-data/jumpsuit_20/train',
+                                  batch_size=1,
+                                  signature=signature_dynamic)
+    static_dataset = StaticDataset(folder='/home/workspace/local-data/jumpsuit_20/train',
+                                   signature=signature_static)
+
+
+    uv_res = 256
+
+
+
+    for i, batch in enumerate(dataset):
+        print(i)
+        batch = static_dataset.expand_batch(batch_to_dict(batch, signature_dynamic))
+
+        mesh_unposed = np.squeeze(batch['mesh_unposed'].numpy())
+        mask = np.squeeze(batch['mesh_mask'].numpy()).astype(bool)
+        pose, shape = batch['pose_shape'][:, :72].numpy(), batch['pose_shape'][:, 72:].numpy()
+        # mesh_posed = np.squeeze(batch['mesh_posed'].numpy())
+        gender = int(shape[0, -1] > 0)
+        print(gender)
+
+        shape_offsets = tf.tensordot(shape[:,:10], smpl.shapedirs[gender], axes=[[1], [2]]).numpy()
+        
+
+        mesh_unposed[mask, :] = mesh_unposed[mask, :] - np.squeeze(shape_offsets)[smpl.to_keep, :][mask, :]
+
+        np.savez_compressed(os.path.join(folder, id, 'mesh_posed_body_no_orient', id + '_' + str(i) + '.npz'), mesh_posed_body_no_orient = T[i, :, :])
+
+        
+        # _, faces = _maskFaces(np.zeros((14475, 3), dtype=np.float32), F, mask)
+
+        # x = mesh_unposed[mask, :]
+        # y = mesh_unposed[mask, :] - np.squeeze(shape_offsets)[smpl.to_keep, :][mask, :]
+
+        # # x = smpl.v_template.numpy()[0, smpl.to_keep, :]
+        # # R = smpl.run_rodrigues(np.zeros((1, 72), dtype=np.float32))
+        # # x = smpl.run(R, shape)[0][0]
+        # # y = smpl.v_template.numpy()[gender, smpl.to_keep, :] + np.squeeze(shape_offsets)[smpl.to_keep, :]
+        # # faces = F
+
+        # fig = go.Figure(data=[
+        #     go.Mesh3d(
+        #         # 8 vertices of a cube
+        #         x=x[:,0],
+        #         y=x[:,1],
+        #         z=x[:,2],
+        #         # i, j and k give the vertices of triangles
+        #         i = faces[:,0],
+        #         j = faces[:,1],
+        #         k = faces[:,2]
+        #     ),
+        #     go.Mesh3d(
+        #         # 8 vertices of a cube
+        #         x=y[:,0],
+        #         y=y[:,1],
+        #         z=y[:,2],
+        #         # i, j and k give the vertices of triangles
+        #         i = faces[:,0],
+        #         j = faces[:,1],
+        #         k = faces[:,2]
+        #     )])
+
+        # fig.update_layout(scene_aspectmode='manual', scene_aspectratio=dict(x=1, y=1, z=1))
+        # fig.update_layout(
+        #     scene = dict(
+        #         xaxis = dict(nticks=4, range=[-1,1],),
+        #                     yaxis = dict(nticks=4, range=[-1,1],),
+        #                     zaxis = dict(nticks=4, range=[-1,1],),)
+        #                     )
+
+        # fig.show()
+
+        print()