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use original cloth3d functions

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luni
2022-12-23 22:15:22 +00:00
parent 67891530a2
commit 156d7c0245
6 changed files with 506 additions and 10 deletions
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data/dataset.py
+16 -6
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@@ -18,6 +18,8 @@ from render import Render, DepthRenderer
sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/..')
from superSMPL.IO import readPC2Frame, writePC2
from utils.data_utils import Frame, read_frames_file, mask_faces
from cloth3d.read import DataReader
from cloth3d.util import quads2tris
class Dataset(Dataset):
@@ -27,30 +29,38 @@ class Dataset(Dataset):
self.frames = read_frames_file(os.path.join(folder, frames_file))
self.render = DepthRenderer()
self.deodr_render : Render = Render(max_depth=10)
self.body_faces = np.load('custom_data/smpl_faces.npy')
self.reader = DataReader(folder, 'superSMPL')
def __len__(self):
return len(self.frames)
# TODO: make it work kwith two part outfits
def __getitem__(self, idx):
frame : Frame = self.frames[idx]
path = os.path.join(self.folder, frame.id)
mesh_posed = readPC2Frame(os.path.join(path, frame.garment + '_registered.pc16'), frame.frame_nr, True)
# mesh_posed = readPC2Frame(os.path.join(path, frame.garment + '_registered.pc16'), frame.frame_nr, True)
mesh_posed = self.reader.read_garment_vertices(frame.id, frame.garment, frame.frame_nr)
mask = np.load(os.path.join(path, frame.garment + '_mask.npy'))
faces = mask_faces(self.body_faces, mask)
body = readPC2Frame(os.path.join(path, 'Body_posed.pc16'), frame.frame_nr, True)
# faces = quads2tris(self.reader.read_garment_topology(frame.id, frame.garment))
# body = readPC2Frame(os.path.join(path, 'Body_posed.pc16'), frame.frame_nr, True)
body, body_faces = self.reader.read_human(frame.id, frame.frame_nr)
body_faces = quads2tris(body_faces)
info = sio.loadmat(os.path.join(path, 'info.mat'))
info = self.reader.read_info(frame.id)
combined = torch.Tensor(np.concatenate((body, mesh_posed[mask, :]))).to('cuda')
combined_faces = torch.Tensor(np.concatenate((self.body_faces, faces + 14475))).to('cuda')
combined_faces = torch.Tensor(np.concatenate((body_faces, faces + body.shape[0]))).to('cuda')
start = time.perf_counter()
# depth_image = self.render.render(mesh_posed[mask, :], faces, info['camLoc'][0])[:,:,0]
# depth_image = self.render.render(combined, combined_faces, info['camLoc'][0])[:,:,0]
depth_image = self.render(combined, combined_faces, info['camLoc'][0])
deodr_depth = self.deodr_render.render(cam=info['camLoc'].astype(np.float32), mesh=combined.cpu().numpy(), faces=combined_faces.cpu().numpy().astype(np.int32))
depth_image = self.render(combined, combined_faces, info['camLoc'])
t = time.perf_counter() - start
print(t)
@@ -65,7 +75,7 @@ if __name__ == '__main__':
# dataset = Dataset('/home/workspace/local-data/train')
dataset = Dataset('dataset/CLOTH3D/train')
train_dataloader = DataLoader(dataset, batch_size=4, drop_last=True, shuffle=True)
train_dataloader = DataLoader(dataset, batch_size=4, drop_last=True, shuffle=False)
for batch in train_dataloader:
batch