| | |
| | | new_pool = pd.DataFrame(columns=list(card_pool.columns.values)) |
| | | for hs in hash_size: |
| | | new_pool['card_hash_%d' % hs] = np.NaN |
| | | new_pool['set_hash_%d' % hs] = np.NaN |
| | | new_pool['set_hash_%d' % 64] = np.NaN |
| | | #new_pool['art_hash_%d' % hs] = np.NaN |
| | | for ind, card_info in card_pool.iterrows(): |
| | | if ind % 100 == 0: |
| | |
| | | img_set = Image.fromarray(set_img) |
| | | for hs in hash_size: |
| | | card_hash = ih.phash(img_card, hash_size=hs) |
| | | set_hash = ih.whash(img_set, hash_size=hs) |
| | | set_hash = ih.whash(img_set, hash_size=64) |
| | | card_info['card_hash_%d' % hs] = card_hash |
| | | card_info['set_hash_%d' % hs] = set_hash |
| | | card_info['set_hash_%d' % 64] = set_hash |
| | | #print('Setting set_hash_%d' % hs) |
| | | #art_hash = ih.phash(img_art, hash_size=hs) |
| | | #card_info['art_hash_%d' % hs] = art_hash |
| | |
| | | print('Idx:', ix, 'Name:', cd['name'], 'Set:', cd['set'], 'Diff:', top_matches[ix]) |
| | | |
| | | |
| | | cd_data['set_hash_diff'] = cd_data['set_hash_%d' % hash_size] |
| | | cd_data['set_hash_diff'] = cd_data['set_hash_%d' % 64] |
| | | cd_data['set_hash_diff'] = cd_data['set_hash_diff'].apply(lambda x: np.count_nonzero(x != set_img_hash)) |
| | | conf = sorted(cd_data['set_hash_diff']) |
| | | print('Confs:', conf) |
| | |
| | | card_pool.drop('Unnamed: 0', axis=1, inplace=True, errors='ignore') |
| | | card_pool = calc_image_hashes(card_pool, save_to=pck_path, hash_size=hash_sizes) |
| | | ch_key = 'card_hash_%d' % args.hash_size |
| | | set_key = 'set_hash_%d' % args.hash_size |
| | | set_key = 'set_hash_%d' % 64 |
| | | if ch_key not in card_pool.columns: |
| | | # we did not generate this hash_size yet |
| | | print('We need to add hash_size=%d' % (args.hash_size,)) |