Update README.md

README.md

@@ -18,10 +18,10 @@ dataset_info:
     num_bytes: 43177192.912
     num_examples: 2101
   - name: validation
-    num_bytes: 6007816.0
+    num_bytes: 6007816
     num_examples: 300
   - name: test
-    num_bytes: 12230350.0
+    num_bytes: 12230350
     num_examples: 601
   download_size: 59198003
   dataset_size: 61415358.912
@@ -34,4 +34,52 @@ configs:
     path: data/validation-*
   - split: test
     path: data/test-*
+license: mit
+task_categories:
+- visual-question-answering
+language:
+- en
+size_categories:
+- 1K<n<10K
 ---
+
+This dataset was converted from [https://github.com/lupantech/InterGPS](https://github.com/lupantech/InterGPS) using the following script.
+
+```python
+import os
+import json
+from PIL import Image
+from datasets import Dataset, DatasetDict, Sequence
+from datasets import Image as ImageData
+
+
+MAPPING = {"A": 0, "B": 1, "C": 2, "D": 3}
+
+
+def generate_data(data_path: str):
+    for folder in os.listdir(data_path):
+        folder_path = os.path.join(data_path, folder)
+        image = Image.open(os.path.join(folder_path, "img_diagram.png"), "r")
+        with open(os.path.join(folder_path, "data.json"), "r", encoding="utf-8") as f:
+            data = json.load(f)
+            yield {
+                "images": [image],
+                "problem": data["annotat_text"],
+                "answer": data["choices"][MAPPING[data["answer"]]],
+                "id": data["id"],
+                "choices": data["choices"],
+                "ground_truth": data["answer"],
+            }
+
+
+def main():
+    trainset = Dataset.from_generator(generate_data, gen_kwargs={"data_path": os.path.join("data", "geometry3k", "train")})
+    valset = Dataset.from_generator(generate_data, gen_kwargs={"data_path": os.path.join("data", "geometry3k", "val")})
+    testset = Dataset.from_generator(generate_data, gen_kwargs={"data_path": os.path.join("data", "geometry3k", "test")})
+    dataset = DatasetDict({"train": trainset, "validation": valset, "test": testset}).cast_column("images", Sequence(ImageData()))
+    dataset.push_to_hub("hiyouga/geometry3k")
+
+
+if __name__ == "__main__":
+    main()
+```