add

2023-05-23 18:24:16 +08:00
parent da758a9ca7
commit b388fba03e
470 changed files with 2523750 additions and 7307 deletions
--- a/models/LLaVA/scripts/convert_sqa_to_llava.py
+++ b/models/LLaVA/scripts/convert_sqa_to_llava.py
@@ -0,0 +1,88 @@
+import json
+import os
+import fire
+import re
+from convert_sqa_to_llava_base_prompt import build_prompt_chatbot
+
+
+def convert_to_llava(base_dir, split, prompt_format="QCM-LEPA"):
+    split_indices = json.load(open(os.path.join(base_dir, "pid_splits.json")))[split]
+    problems = json.load(open(os.path.join(base_dir, "problems.json")))
+
+    split_problems = build_prompt_chatbot(
+        problems, split_indices, prompt_format,
+        use_caption=False, is_test=False)
+
+    target_format = []
+    for prob_id, (input, output) in split_problems.items():
+        if input.startswith('Question: '):
+            input = input.replace('Question: ', '')
+        if output.startswith('Answer: '):
+            output = output.replace('Answer: ', '')
+
+        raw_prob_data = problems[prob_id]
+        if raw_prob_data['image'] is None:
+            target_format.append({
+                "id": prob_id,
+                "conversations": [
+                    {'from': 'human', 'value': f"{input}"},
+                    {'from': 'gpt', 'value': f"{output}"},
+                ],
+            })
+
+        else:
+            target_format.append({
+                "id": prob_id,
+                "image": os.path.join(prob_id, raw_prob_data['image']),
+                "conversations": [
+                    {'from': 'human', 'value': f"{input}\n<image>"},
+                    {'from': 'gpt', 'value': f"{output}"},
+                ],
+            })
+
+    print(f'Number of samples: {len(target_format)}')
+
+    with open(os.path.join(base_dir, f"llava_{split}_{prompt_format}.json"), "w") as f:
+        json.dump(target_format, f, indent=2)
+
+
+def convert_to_jsonl(base_dir, split, prompt_format="QCM-LEPA"):
+    split_indices = json.load(open(os.path.join(base_dir, "pid_splits.json")))[split]
+    problems = json.load(open(os.path.join(base_dir, "problems.json")))
+
+    split_problems = build_prompt_chatbot(
+        problems, split_indices, prompt_format,
+        use_caption=False, is_test=False)
+
+    writer = open(os.path.join(base_dir, f"scienceqa_{split}_{prompt_format}.jsonl"), "w")
+    for prob_id, (input, output) in split_problems.items():
+        if input.startswith('Question: '):
+            input = input.replace('Question: ', '')
+        if output.startswith('Answer: '):
+            output = output.replace('Answer: ', '')
+
+        raw_prob_data = problems[prob_id]
+        if raw_prob_data['image'] is None:
+            data = {
+                "id": prob_id,
+                "instruction": f"{input}",
+                "output": f"{output}",
+            }
+
+        else:
+            data = {
+                "id": prob_id,
+                "image": os.path.join(prob_id, raw_prob_data['image']),
+                "instruction": f"{input}\n<image>",
+                "output": f"{output}",
+            }
+        writer.write(json.dumps(data) + '\n')
+    writer.close()
+
+
+def main(task, **kwargs):
+    globals()[task](**kwargs)
+
+
+if __name__ == "__main__":
+    fire.Fire(main)