Spaces:
Running
on
Zero
Running
on
Zero
File size: 1,225 Bytes
2ada650 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 |
import argparse
import pathlib
import json
from load_aokvqa import load_aokvqa
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--aokvqa-dir', type=pathlib.Path, required=True, dest='aokvqa_dir')
parser.add_argument('--split', type=str, choices=['train', 'val', 'test'], required=True)
parser.add_argument('--mc', type=argparse.FileType('r'), dest='mc_pred_file')
parser.add_argument('--da', type=argparse.FileType('r'), dest='da_pred_file')
parser.add_argument('--out', type=argparse.FileType('w'), dest='output_file')
args = parser.parse_args()
assert args.mc_pred_file or args.da_pred_file
dataset = load_aokvqa(args.aokvqa_dir, args.split)
mc_preds = json.load(args.mc_pred_file) if args.mc_pred_file else None
da_preds = json.load(args.da_pred_file) if args.da_pred_file else None
predictions = {}
for d in dataset:
q = d['question_id']
predictions[q] = {}
if mc_preds and q in mc_preds.keys():
predictions[q]['multiple_choice'] = mc_preds[q]
if da_preds and q in da_preds.keys():
predictions[q]['direct_answer'] = da_preds[q]
json.dump(predictions, args.output_file)
|