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luni
2023-03-14 14:08:03 +00:00
parent abecb2d20a
commit d92a18e212
5 changed files with 32 additions and 31 deletions
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get_error.py
+23 -23
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@@ -8,11 +8,11 @@ if __name__ == '__main__':
garment_type_table = np.load('custom_data/garment_type_table_test.npy', allow_pickle=True).item()
folder = '/home/workspace/data/results/errors/iccv'
checkpoint_name = 'iccv_pyr_32_64_128_skin'
checkpoint_name = 'iccv_pyr_32_64_128_256_seq_2'
checkpoint_name_skirt = 'iccv_pyr_32_64_128_skin_skirt'
iteration = '75' + '000'
iteration = '185' + '000'
iteration_skirt : str = '155' + '000'
error_type = 'collision' # 'euclidean' 'collision' edge normal
error_type = 'euclidean' # 'euclidean' 'collision' edge normal
errors = []
@@ -21,31 +21,31 @@ if __name__ == '__main__':
per_garment_errors_skirt = { 'Tshirt': [], 'Dress': [], 'Skirt': [], 'Top': [] }
# with open(os.path.join(folder, f'{checkpoint_name}-{iteration}-{error_type}.csv'), 'r') as f:
# csv_reader = csv.reader(f, delimiter=',')
# for row in csv_reader:
# per_garment_errors[garment_type_table[row[0].split('_')[0]]].append(float(row[1]))
# print('\nNon-skirt:')
# for key in per_garment_errors.keys():
# avg = np.mean(per_garment_errors[key])
# errors.append(avg)
# print(key + ': ' + str(avg))
# print('\nAvg non-skirt: ' + str(np.mean(errors)))
with open(os.path.join(folder, f'{checkpoint_name_skirt}-{iteration_skirt}-{error_type}.csv'), 'r') as f:
with open(os.path.join(folder, f'{checkpoint_name}-{iteration}-{error_type}.csv'), 'r') as f:
csv_reader = csv.reader(f, delimiter=',')
for row in csv_reader:
per_garment_errors_skirt[garment_type_table[row[0].split('_')[0]]].append(float(row[1]))
per_garment_errors[garment_type_table[row[0].split('_')[0]]].append(float(row[1]))
print('\nSkirt:')
for key in per_garment_errors_skirt.keys():
avg = np.mean(per_garment_errors_skirt[key])
errors_skirt.append(avg)
print('\nNon-skirt:')
for key in per_garment_errors.keys():
avg = np.mean(per_garment_errors[key])
errors.append(avg)
print(key + ': ' + str(avg))
print('Avg skirt: ' + str(np.mean(errors_skirt)))
print('\nAvg non-skirt: ' + str(np.mean(errors)))
# with open(os.path.join(folder, f'{checkpoint_name_skirt}-{iteration_skirt}-{error_type}.csv'), 'r') as f:
# csv_reader = csv.reader(f, delimiter=',')
# for row in csv_reader:
# per_garment_errors_skirt[garment_type_table[row[0].split('_')[0]]].append(float(row[1]))
# print('\nSkirt:')
# for key in per_garment_errors_skirt.keys():
# avg = np.mean(per_garment_errors_skirt[key])
# errors_skirt.append(avg)
# print(key + ': ' + str(avg))
# print('Avg skirt: ' + str(np.mean(errors_skirt)))
# cum_avg_shirt = np.mean(per_garment_errors['Tshirt'] + per_garment_errors_skirt['Tshirt'])
# cum_avg_top = np.mean(per_garment_errors['Top'] + per_garment_errors_skirt['Top'])