| import pandas as pd | |
| from tqdm import tqdm | |
| import joblib | |
| if __name__ == '__main__': | |
| df_scores = pd.read_csv('../../AVA_src/AVA.txt',sep = " ",header = None) | |
| df_scores.columns = df_scores.columns + 1 | |
| df_scores = df_scores.drop(columns=df_scores.columns[0], axis=1) | |
| df_tags = pd.read_csv('../../AVA_src/tags.txt',sep = "|",header = None) | |
| dict_tags = {0:'None'} | |
| for row in df_tags.iterrows(): | |
| row = row[1] | |
| dict_tags[row[0]] = row[1] | |
| dict_ = {} | |
| for idx in tqdm(range(len(df_scores))): | |
| row = df_scores.iloc[idx,:] | |
| _id = row[2] | |
| ratings = row.values[1:11] | |
| textual_tag0 = dict_tags[row[13]] | |
| textual_tag1 = dict_tags[row[14]] | |
| dict_[_id] = (ratings,textual_tag0,textual_tag1) | |
| joblib.dump(dict_,"../data/metadata.pkl") | |