geenrate curv based on frames file
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@@ -9,10 +9,11 @@ if __name__ == '__main__':
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ids = os.listdir(folder + '/mesh_posed')
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count = 0
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step = 15000
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step = 5000
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while count < len(ids):
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# while count < len(ids):
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while count < 30000:
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# os.system('nohup python MeshUtils/curvature_labels.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'curv_train_' + str(count) + '_' + str(count+step) + ' > curv_train_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
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os.system('nohup python curvature_labels.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'curv_gen_50_train_nons_' + str(count) + '_' + str(count+step) + ' > nohup/curv_gen_50_train_nons_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
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os.system('nohup python curvature_labels.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'curv_gen_50_train_' + str(count) + '_' + str(count+step) + ' > nohup/curv_gen_50_train_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
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# os.system('python Data/convert_to_uv.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + '')
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count += step
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+16
-6
@@ -83,9 +83,9 @@ def k_neighbours(k):
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pass
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def calculate_dist(folder, neighbourhood):
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def calculate_dist(folder, neighbourhood, frames):
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out = dict()
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frames = sorted(os.listdir(os.path.join(folder, 'mesh_posed')))[int(args.start):int(args.end)]
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# frames = frames[int(args.start):int(args.end)]
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for frame in tqdm.tqdm(frames):
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id = frame.split('_')[0]
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@@ -98,13 +98,13 @@ def calculate_dist(folder, neighbourhood):
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return out
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def generate_curvatures(folder, neighbourhood):
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def generate_curvatures(folder, neighbourhood, frames):
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# ids = os.listdir(folder)[int(args.start):int(args.end)]
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frames = sorted(os.listdir(os.path.join(folder, 'mesh_posed')))[int(args.start):int(args.end)]
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# frames = frames[int(args.start):int(args.end)]
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os.makedirs(os.path.join(folder, f'mesh_curvature_raw_{neighbourhood}'), exist_ok=True)
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k_neighbors_cache = calculate_dist(folder, neighbourhood)
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k_neighbors_cache = calculate_dist(folder, neighbourhood, frames)
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for frame in tqdm.tqdm(frames):
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@@ -295,6 +295,8 @@ if __name__ == '__main__':
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# k_neighbours(k=25)
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folder = args.folder
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frames_file = 'frames' + skirt_modifier + '_10p.txt'
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nr_of_labels = 6
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neighbourhood = 50
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temp_file = '/home/workspace/local-data/temp/' + ''.join(random.choice(string.ascii_lowercase) for i in range(10)) + '.ply'
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@@ -305,7 +307,15 @@ if __name__ == '__main__':
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print('SKIRT' if is_skirt else 'NOT SKIRT')
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generate_curvatures(folder, neighbourhood)
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# frames = sorted(os.listdir(os.path.join(folder, 'mesh_posed')))[int(args.start):int(args.end)]
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frames = []
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with open(os.path.join(folder, frames_file), 'r') as f:
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lines = f.readlines()
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lines = [line.strip() for line in lines]
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frames = lines[int(args.start):int(args.end)]
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generate_curvatures(folder, neighbourhood, frames)
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# curvatures = read_raw_curvatures(folder)
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# bins = get_bins(curvatures, nr_of_labels)
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# np.save('train_bins_skirt.npy', bins)
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