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models/common/vqa_tools/aokvqa/data_scripts/build_vocab.py

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+import os
+import argparse
+from collections import Counter
+import pathlib
+
+from load_aokvqa import load_aokvqa
+
+
+parser = argparse.ArgumentParser()
+parser.add_argument('--aokvqa-dir', type=pathlib.Path, required=True, dest='aokvqa_dir')
+parser.add_argument('--out', type=pathlib.Path, required=True, dest='output_file')
+args = parser.parse_args()
+
+
+# Build vocab from train set: correct choices + (direct answers appearing in >= 3 )
+
+train_set = load_aokvqa(args.aokvqa_dir, 'train')
+
+vocab = []
+all_choices = Counter()
+direct_answers = Counter()
+
+for i in train_set:
+    vocab.append( i['choices'][i['correct_choice_idx']] )
+    all_choices.update(i['choices'])
+    direct_answers.update(set(i['direct_answers']))
+vocab += [k for k,v in all_choices.items() if v >= 3]
+vocab += [k for k,v in direct_answers.items() if v >= 3]
+
+vocab = sorted(set(vocab))
+print(f"Vocab size: {len(vocab)}")
+
+# Save vocabulary Output
+
+with open(args.output_file, 'w') as f:
+    for v in vocab:
+        print(v, file=f)
+
+## Check validation set coverage
+
+val_set = load_aokvqa(args.aokvqa_dir, 'val')
+
+val_acc = [v['choices'][v['correct_choice_idx']] in vocab for v in val_set]
+val_acc = sum(val_acc) / len(val_acc) * 100
+print(f"Val set coverage: {val_acc:.2f}" )