| import os |
| import random |
| import pandas as pd |
|
|
| def predictor(image_link, category_id, entity_name): |
| ''' |
| Call your model/approach here |
| ''' |
| |
| return "" if random.random() > 0.5 else "10 inch" |
|
|
| if __name__ == "__main__": |
| DATASET_FOLDER = '../dataset/' |
| |
| test = pd.read_csv(os.path.join(DATASET_FOLDER, 'test.csv')) |
| |
| test['prediction'] = test.apply( |
| lambda row: predictor(row['image_link'], row['group_id'], row['entity_name']), axis=1) |
| |
| output_filename = os.path.join(DATASET_FOLDER, 'test_out.csv') |
| test[['index', 'prediction']].to_csv(output_filename, index=False) |
