def registration_test(register: RegistrationAlgorithm,
test_name: str,
export_number=(0, 0)):
registration_test_folder = f'{const.REGISTRATION}/{test_name}/'
files = collect(registration_test_folder, '.npz')
progress = tqdm(total=len(files),
desc=f'Registration | {test_name} | {register.name}')
total_error = 0
total_check = 0
for i, file in enumerate(files):
data = np.load(''.join(file))
source, target = data['test_vs'][0], data['test_vs'][1]
rot, trnl = data['rotations'], data['translations']
rot_, trnl_ = register(source, target)
target_ = apply_affine(source, rot_, trnl_)
error = mse_error(source, target_, rot, trnl)
if np.isnan(error):
print('error')
total_error += min(error, 1)
total_check += 1
progress.update()
progress.set_postfix(error=error,
average=total_error / max(1, total_check))
print(f'testeted: {total_check} / {len(files)}')
print(f'error: {total_error / max(1, total_check)}')
progress.set_postfix({'error': total_error / max(1, total_check)})
progress.close()
def init_prefix(prefix: str, saving_index: int, saving_folder: str):
nonlocal saving_dict, suffix
same_type_file = collect(saving_folder, suffix[saving_index], prefix=prefix)
if len(same_type_file) == 0:
saving_dict[saving_index][prefix] = 0
else:
last_number_file_name = same_type_file[-1][1]
saving_dict[saving_index][prefix] = int(last_number_file_name.split('_')[1]) + 1
def get_taxonomy_models_paths(self):
with open(self.join2root('taxonomy.json'), 'r') as f:
metadata = json.load(f)
for info in metadata:
class_name = info['name'].split(',')[0].replace(' ', '_')
if class_name == self.opt.tag:
taxonomy_dir = self.join2root(info['synsetId'])
if os.path.isdir(taxonomy_dir):
return files_utils.collect(taxonomy_dir, '.obj', '.off')
np_images = [
render_mesh(mesh, ambient_color, light_dir) for mesh in meshes
]
im = make_pretty(np_images)
if save_path:
save_path = files_utils.add_suffix(save_path, '.png')
files_utils.init_folders(save_path)
im.save(save_path)
elif 'DISPLAY' in os.environ:
im.show()
if __name__ == '__main__':
meshes = [
''.join(path) for path in files_utils.collect(
'/home/amir/projects/mishmesh/checkpoints/bunny_noise/inference/',
'.obj')
]
plot_mesh(
*meshes,
save_path=
'/home/amir/projects/mishmesh/checkpoints/sphere_rail_noise/inference/bunnies'
)
# plot_mesh('/home/amir/projects/mishmesh/checkpoints/sphere_rail_noise/inference/temp15.obj',
# '/home/amir/projects/mishmesh/checkpoints/sphere_rail_noise/inference/temp24.obj',
# '/home/amir/projects/mishmesh/checkpoints/sphere_rail_noise/inference/temp24.obj',
# '/home/amir/projects/mishmesh/checkpoints/sphere_rail_noise/inference/temp23.obj',
# '/home/amir/projects/mishmesh/checkpoints/sphere_rail_noise/inference/temp44.obj',
# '/home/amir/projects/mishmesh/checkpoints/sphere_rail_noise/inference/temp33.obj',
# save_path='/home/amir/projects/mishmesh/checkpoints/sphere_rail_noise/inference/sphere_rail_bunny')