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generate curv with different radius

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luni
2023-01-28 10:59:41 +00:00
parent ef81e702fa
commit c7e75acc2d
5 changed files with 55 additions and 73 deletions
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convert_to_uv_local_single.py
+31 -17
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@@ -384,9 +384,9 @@ def test(verts, faces, values):
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("-f", "--folder", help = "end of range", default='/home/workspace/local-data/valid')
parser.add_argument("-f", "--folder", help = "end of range", default='/home/workspace/local-data/valid_skirt')
parser.add_argument("-s", "--start", help = "start of range", default=0)
parser.add_argument("-e", "--end", help = "end of range", default=1500)
parser.add_argument("-e", "--end", help = "end of range", default=30000)
parser.add_argument("-n", "--name", help = "end of range", default='lhunor')
parser.add_argument("-sk", "--skirt", help = "end of range", default=1)
args = parser.parse_args()
@@ -408,7 +408,7 @@ if __name__ == '__main__':
m2uv = np.load('custom_utils/m2uv' + ("_skirt" if args.skirt == 1 else "") + '.npy', allow_pickle=True).item()
m2uv = m2uv_array(m2uv)
uv_mask = np.load('custom_utils/mask_256x512' + ("_skirt" if args.skirt == 1 else "") + '.npy')
curvature_label_type = '6_25'
curvature_label_type = '6_25 '
uv_res = 256
uv_mask = (cv2.resize(uv_mask * 255.0, (uv_res, uv_res * 2)) / 255).astype(bool)[:, :, np.newaxis]
@@ -436,9 +436,23 @@ if __name__ == '__main__':
# ids = os.listdir(os.path.join(local_folder, 'mesh_static'))[int(args.start):int(args.end)]
# ids = [id.split('.')[0] for id in ids]
ids = os.listdir(os.path.join(local_folder, 'pose_shape'))
ids = [id.split('_')[0] for id in ids]
ids = sorted(list(set(ids)))[int(args.start):int(args.end)]
is_skirt = True if args.skirt == 1 else False
skirt_modifier = '_skirt' if is_skirt else ''
folder = args.folder
frames_file = 'frames' + skirt_modifier + '_10p.txt'
neighbourhood = 10
frames = []
with open(os.path.join(folder, frames_file), 'r') as f:
lines = f.readlines()
lines = [line.strip() for line in lines]
frames = lines[int(args.start):int(args.end)]
# ids = os.listdir(os.path.join(local_folder, 'pose_shape'))
ids = [frame.split('_')[0] for frame in frames]
ids = sorted(list(set(ids)))#[int(args.start):int(args.end)]
for id in tqdm.tqdm(ids):
@@ -452,16 +466,16 @@ if __name__ == '__main__':
# plt.show()
# pass
frames = glob.glob(os.path.join(local_folder, 'pose_shape', id + '_*'))
frames = len(frames)
assert frames <= 300
frames_len = glob.glob(os.path.join(local_folder, 'pose_shape', id + '_*'))
frames_len = len(frames_len)
assert frames_len <= 300
# offsets = sio.loadmat(os.path.join(folder, id, garment + '_offsets_static.mat'))['label'][:,:3]
verts_static = np.load(os.path.join(local_folder, 'mesh_static', id + '.npz'))['mesh_static']
mask = np.load(os.path.join(local_folder, 'mesh_mask', id + '.npy')).astype(bool)
# body = readPC2(os.path.join(folder, id, 'Body_posed.pc16'), True)['V']
# gt = readPC2(os.path.join(folder, id, garment + '_registered.pc16'), True)['V']
# curvature = np.load(os.path.join(folder, id, 'curvature_label_' + curvature_label_type + '.npy'))
curvature = np.stack([np.load(os.path.join(local_folder, f'mesh_curvature_{neighbourhood}', f'{id}_{i}.npz'))['mesh_curvature'] for i in range(frames_len)])
# mesh_unposed = [np.load(os.path.join(folder, id, 'mesh_unposed', id + '_' + str(i) + '.npz')) for i in range(gt.shape[0])]
# mesh_unposed = np.stack([mesh_unposed[i]['mesh_unposed'] for i in range(gt.shape[0])])
# mesh_unposed_no_shape = [np.load(os.path.join(folder, id, 'mesh_unposed_no_shape', id + '_' + str(i) + '.npz')) for i in range(gt.shape[0])]
@@ -470,8 +484,8 @@ if __name__ == '__main__':
# body_no_orient = np.stack([body_no_orient[i]['mesh_posed_body_no_orient'] for i in range(gt.shape[0])])
# mesh_unposed_no_shape_one_hot = [np.load(os.path.join(local_folder, 'mesh_unposed_no_shape_one_hot', id + '_' + str(i) + '.npz')) for i in range(frames)]
# mesh_unposed_no_shape_one_hot = [mesh_unposed_no_shape_one_hot[i]['mesh_unposed_no_shape'] for i in range(frames)]
mesh_posed_no_orient = [np.load(os.path.join(local_folder, 'mesh_posed_no_orient', id + '_' + str(i) + '.npz')) for i in range(frames)]
mesh_posed_no_orient = [mesh_posed_no_orient[i]['mesh_posed_no_orient'] for i in range(frames)]
# mesh_posed_no_orient = [np.load(os.path.join(local_folder, 'mesh_posed_no_orient', id + '_' + str(i) + '.npz')) for i in range(frames)]
# mesh_posed_no_orient = [mesh_posed_no_orient[i]['mesh_posed_no_orient'] for i in range(frames)]
# verts_dynamic = gt
@@ -491,11 +505,11 @@ if __name__ == '__main__':
# uv_body = convert_to_uv_batch(uv_res, m2uv, uv_map, body[:, :, :], neighbours=3, mask=None, method='rbf', garment_uv_mask=None, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
# uv_posed_body_no_orient = convert_to_uv_batch(uv_res, m2uv, uv_map, body_no_orient[:, :, :], neighbours=3, mask=None, method='rbf', garment_uv_mask=None, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
# uv_gt = convert_to_uv_batch(uv_res, m2uv, uv_map, gt[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
# uv_curvature = convert_to_uv_batch_label(uv_res, m2uv, uv_map, curvature[:, :], neighbours=3, mask=mask, method='nearest', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
uv_curvature = convert_to_uv_batch_label(uv_res, m2uv, uv_map, curvature[:, :], neighbours=3, mask=mask, method='nearest', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
# uv_unposed = convert_to_uv_batch(uv_res, m2uv, uv_map, mesh_unposed[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
# uv_unposed_no_shape = convert_to_uv_batch(uv_res, m2uv, uv_map, mesh_unposed_no_shape[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
# uv_unposed_no_shape_one_hot = convert_to_uv_batch(uv_res, m2uv, uv_map, mesh_unposed_no_shape_one_hot, neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border, id=id)
uv_posed_no_orient = convert_to_uv_batch(uv_res, m2uv, uv_map, mesh_posed_no_orient, neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border, id=id)
# uv_posed_no_orient = convert_to_uv_batch(uv_res, m2uv, uv_map, mesh_posed_no_orient, neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border, id=id)
# uv_shaped_body = convert_to_uv(uv_res, m2uv, uv_map, shaped_body, neighbours=3, mask=None, method='rbf', garment_uv_mask=None).astype(np.float32)
print(time.perf_counter() - start)
@@ -516,9 +530,9 @@ if __name__ == '__main__':
# for i in range(uv_gt.shape[0]):
# np.savez_compressed(os.path.join(folder, id, 'gt_uv', garment + '_' + str(i) + '.npz'), uv_gt=uv_gt[i, :, :, :])
# os.makedirs(os.path.join(folder, id, 'curvature_uv'), exist_ok=True)
# for i in range(uv_curvature.shape[0]):
# np.savez_compressed(os.path.join(folder, id, 'curvature_uv', garment + '_' + str(i) + '.npz'), curvature_uv=uv_curvature[i, :, :])
os.makedirs(os.path.join(folder, id, f'curvature_uv_{neighbourhood}'), exist_ok=True)
for i in range(uv_curvature.shape[0]):
np.savez_compressed(os.path.join(folder, id, f'curvature_uv_{neighbourhood}', id + '_' + str(i) + '.npz'), curvature_uv=uv_curvature[i, :, :])
# os.makedirs(os.path.join(folder, id, 'uv_unposed'), exist_ok=True)
# for i in range(uv_unposed.shape[0]):
curvature_labels.py
+20 -52
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@@ -153,41 +153,23 @@ def get_bins(values, nr_of_bins):
return bins
def generate_curvature_labels(folder, bins, curvatures):
def generate_curvature_labels(folder, bins, curvatures, frames, neighbourhood):
ids = os.listdir(folder)#[:10]
os.makedirs(os.path.join(folder, f'mesh_curvature_{neighbourhood}'), exist_ok=True)
labels = np.linspace(0, bins.shape[0] - 2, bins.shape[0] - 1)
i = 0
for id in tqdm.tqdm(ids):
garment_dir = os.path.join(folder, id)
if not os.path.isdir(garment_dir):
continue
garments = [f.replace('.pc16','') for f in os.listdir(garment_dir) if f.find('_') == -1 and f != 'info.mat' and not f.endswith('.obj')]
# assert len (garments) == 1
if len (garments) != 1:
continue
garment = garments[0]
mask = np.squeeze(sio.loadmat(os.path.join(garment_dir, garment + '_mask.mat'))['mask'].astype(bool))
for i, frame in enumerate(tqdm.tqdm(frames)):
# id = frame.split('_')[0]
# mask = np.load(os.path.join(folder, 'mesh_mask', f'{id}.npy'))
# print(i)
curvature = curvatures[i]
i += 1
curvature_label = np.zeros((curvature.shape[0], curvature.shape[1]))
frame = 0
for frame in range(curvature.shape[0]):
frame_labels = np.zeros((curvature.shape[1]), dtype=np.float32)
for j in range(bins.shape[0] - 2):
frame_labels[(curvature[frame, :] >= bins[j]) * (curvature[frame, :] < bins[j+1])] = labels[j]
frame_labels[curvature[frame, :] >= bins[-2]] = labels[-1]
curvature_label[frame, :] = frame_labels
frame += 1
frame_labels = np.zeros((curvature.shape[0]), dtype=np.float32)
for j in range(bins.shape[0] - 2):
frame_labels[(curvature >= bins[j]) * (curvature < bins[j+1])] = labels[j]
frame_labels[curvature >= bins[-2]] = labels[-1]
unmasked_label = np.zeros((curvature.shape[0], 14475), dtype=np.float32)
unmasked_label[:, mask] = curvature_label
np.save(os.path.join(garment_dir, "curvature_label_" + str(nr_of_labels) + "_" + str(neighbourhood) + ".npy"), unmasked_label)
np.savez_compressed(os.path.join(folder, f'mesh_curvature_{neighbourhood}', f'{frame}.npz'), mesh_curvature=frame_labels)
# writePC2(os.path.join(garment_dir, "curvature_label_" + str(nr_of_labels) + "_" + str(neighbourhood) + ".pc16"), unmasked_label, True)
@@ -258,24 +240,10 @@ def visualize_curvature_labels(folder):
print()
def read_raw_curvatures(folder):
ids = os.listdir(folder)[int(args.start):int(args.end)]
def read_raw_curvatures(folder, frames, neighbourhood):
curvatures_all = []
for id in tqdm.tqdm(ids):
garment_dir = os.path.join(folder, id)
if not os.path.isdir(garment_dir):
continue
garments = [f.replace('.pc16','') for f in os.listdir(garment_dir) if f.find('_') == -1 and f != 'info.mat' and not f.endswith('.obj')]
# assert len (garments) == 1
if len (garments) != 1:
continue
curv = np.load(garment_dir + '/curvature_25_raw.npy')
for frame in tqdm.tqdm(frames):
curv = np.load(os.path.join(folder, f'mesh_curvature_raw_{neighbourhood}', f'{frame}.npz'))['mesh_curvature_raw']
curvatures_all.append(curv)
return curvatures_all
@@ -283,9 +251,9 @@ def read_raw_curvatures(folder):
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("-f", "--folder", help = "process the given folder", default=r'/home/workspace/local-data/valid_skirt')
parser.add_argument("-f", "--folder", help = "process the given folder", default=r'/home/workspace/data/dataset/local-cache/train_skirt')
parser.add_argument("-s", "--start", help = "start of range", default=0)
parser.add_argument("-e", "--end", help = "end of range", default=10)
parser.add_argument("-e", "--end", help = "end of range", default=30000)
parser.add_argument("-n", "--name", help = "end of range", default="lhunor")
args = parser.parse_args()
@@ -315,12 +283,12 @@ if __name__ == '__main__':
lines = [line.strip() for line in lines]
frames = lines[int(args.start):int(args.end)]
generate_curvatures(folder, neighbourhood, frames)
# curvatures = read_raw_curvatures(folder)
# generate_curvatures(folder, neighbourhood, frames)
curvatures = read_raw_curvatures(folder, frames, neighbourhood)
# bins = get_bins(curvatures, nr_of_labels)
# np.save('train_bins_skirt.npy', bins)
# bins = np.load('train_bins.npy')
# generate_curvature_labels(folder, bins, curvatures)
bins = np.load('custom_data/train_bins_skirt.npy')
generate_curvature_labels(folder, bins, curvatures, frames, neighbourhood)
# visualize_curvature_labels(folder)
pass
custom_data/train_bins.npy
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custom_data/train_bins_skirt.npy
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run_parallel.py
+4 -4
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@@ -4,7 +4,7 @@ import os
if __name__ == '__main__':
folder = '/home/workspace/data/dataset/test_skirt_ready_2'
folder = '/home/workspace/data/dataset/local-cache/train_skirt'
# folder = '/home/workspace/local-data/cape_processed/train/male'
# folder = '/home/workspace/local-data/valid_skirt'
# folder = '/home/workspace/local-data/valid'
@@ -13,15 +13,15 @@ if __name__ == '__main__':
skirt = 0
count = 0
step = 2000
step = 5000
# !!!!!!! change skirt parameter in script
while count < len(ids):
while count < 30000:
# os.system('nohup python convert_to_uv_cape.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_2_cape_train_male_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_2_cape_train_male_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('nohup python convert_to_uv.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_train_unposed_onehot_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_train_unposed_onehot_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('nohup python convert_to_uv_local.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_train_local_unposed_onehot_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_train_local_unposed_onehot_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
os.system('nohup python convert_to_uv_local_single.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_posed_no_orient_test_skirt_ready_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_posed_no_orient_test_skirt_ready_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
os.system('nohup python convert_to_uv_local_single.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_curv_10_train_skirt_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_curv_10_train_skirt_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('nohup python convert_to_uv_local_single.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_train_skirt_local_unposed_onehot_3_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_train_skirt_local_unposed_onehot_3_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('nohup python convert_to_uv_local_single.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_valid_skirt_local_unposed_onehot_3_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_valid_skirt_local_unposed_onehot_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('nohup python downscale.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'downscale_valid_posed_no_orient_' + str(count) + '_' + str(count+step) + ' > nohup/downscale_valid_posed_no_orient_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')