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generate raw curv values for test set

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luni
2023-01-28 16:18:29 +00:00
parent a5659196a2
commit 632d8db815
2 changed files with 17 additions and 17 deletions
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curvature_labels.py
+13 -13
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@@ -251,9 +251,9 @@ def read_raw_curvatures(folder, frames, neighbourhood):
if __name__ == '__main__':
parser = argparse.ArgumentParser()
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=30000)
parser.add_argument("-f", "--folder", help = "process the given folder", default=r'/home/workspace/data/dataset/test_skirt_ready_2')
parser.add_argument("-s", "--start", help = "start of range", default=5000)
parser.add_argument("-e", "--end", help = "end of range", default=10000)
parser.add_argument("-n", "--name", help = "end of range", default="lhunor")
args = parser.parse_args()
@@ -275,20 +275,20 @@ if __name__ == '__main__':
print('SKIRT' if is_skirt else 'NOT SKIRT')
# frames = sorted(os.listdir(os.path.join(folder, 'mesh_posed')))[int(args.start):int(args.end)]
frames = sorted(os.listdir(os.path.join(folder, 'mesh_posed')))[int(args.start):int(args.end)]
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)]
# 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)]
# generate_curvatures(folder, neighbourhood, frames)
curvatures = read_raw_curvatures(folder, frames, neighbourhood)
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('custom_data/train_bins_skirt.npy')
generate_curvature_labels(folder, bins, curvatures, frames, neighbourhood)
# bins = np.load('custom_data/train_bins_skirt.npy')
# generate_curvature_labels(folder, bins, curvatures, frames, neighbourhood)
# visualize_curvature_labels(folder)
pass