s444498/wko_anime-face-similarity
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Plot results #6

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s444409 merged 10 commits from pretty-results into main 2023-02-01 22:14:52 +01:00
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1 changed files with 24 additions and 24 deletions
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main.py
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@ -59,43 +59,43 @@ def transfer_to_anime(img: np.ndarray):
return cv2.cvtColor(model_out, cv2.COLOR_BGR2RGB) return cv2.cvtColor(model_out, cv2.COLOR_BGR2RGB)
def validate(test_set, anime_faces_set, metric='correlation', top_n=1): def validate(test_set, anime_faces_set, top_n=1):
all_entries = len(test_set['values']) all_entries = len(test_set['values'])
correct = 0 all_metric_names = [
'structural-similarity',
'euclidean-distance',
'chi-square',
'correlation',
'intersection',
'bhattacharyya-distance'
]
hits_per_metric = {metric: 0 for metric in all_metric_names}
for test_image, test_label in zip(test_set['values'], test_set['labels']): for test_image, test_label in zip(test_set['values'], test_set['labels']):
output = get_top_results(compare_with_anime_characters(test_image, anime_faces_set), metric, top_n) test_results = compare_with_anime_characters(test_image, anime_faces_set)
if any(map(lambda single_result: single_result['name'] == test_label, output)): top_results_all_metrics = {m: get_top_results(test_results, m, top_n) for m in all_metric_names}
correct += 1 for metric_name in all_metric_names:
top_current_metric_results = top_results_all_metrics[metric_name]
if any(map(lambda single_result: single_result['name'] == test_label, top_current_metric_results)):
hits_per_metric[metric_name] += 1
accuracy = correct / all_entries all_metrics = {metric: hits_per_metric[metric] / all_entries for metric in all_metric_names}
print(f'Accuracy using {metric}: {accuracy * 100}%') print(f'Top {top_n} matches results:')
return accuracy [print(f'\t{key}: {value*100}%') for key, value in all_metrics.items()]
return all_metrics
def validate_all(test_set, anime_faces_set, metric='correlation', top_n=1):
validate(test_set, anime_faces_set, 'structural-similarity', top_n)
validate(test_set, anime_faces_set, 'euclidean-distance', top_n)
validate(test_set, anime_faces_set, 'chi-square', top_n)
validate(test_set, anime_faces_set, 'correlation', top_n)
validate(test_set, anime_faces_set, 'intersection', top_n)
validate(test_set, anime_faces_set, 'bhattacharyya-distance', top_n)
if __name__ == '__main__': if __name__ == '__main__':
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument('-v', '--validate_only') parser.add_argument('-v', '--validate_only')
args = parser.parse_args() args = parser.parse_args()
anime_faces_set = load_data('data/images', (256, 256)) anime_faces_set = load_data('data/croped_anime_faces', (256, 256))
if args.validate_only: if args.validate_only:
print('Validating') print('Validating')
test_set = load_data('test_set') test_set = load_data('test_set')
print('Top 1 matches results:') validate(test_set, anime_faces_set, 1)
validate_all(test_set, anime_faces_set, 'structural-similarity', 1) validate(test_set, anime_faces_set, 3)
print('Top 3 matches results:') validate(test_set, anime_faces_set, 5)
validate_all(test_set, anime_faces_set, 'structural-similarity', 3)
print('Top 5 matches results:')
validate_all(test_set, anime_faces_set, 'structural-similarity', 5)
exit(0) exit(0)
source = load_source('UAM-Andre.jpg') source = load_source('UAM-Andre.jpg')