Update README.md

README.md

@@ -129,4 +129,89 @@ ds.map(
     },
     remove_columns=["images"],
 ).rename_column("images_t", "images")
-```
+```
+
+<details>
+  <summary>Show the code used to generate this dataset.</summary>
+  This assumes that the directory `m3exam/multimodal-question/` exists and is an exact copy from the original GitHub repository.
+  ```python
+  import pandas as pd
+  from pathlib import Path
+  from datasets import Image, DatasetDict, Dataset, Value, Sequence
+  from PIL import Image as PILImage
+  from tqdm.auto import tqdm
+  from copy import deepcopy
+  from functools import partial
+  import re
+  
+  tqdm.pandas()
+
+  def get_img_ids(row, img_base_p):
+    p = r"\(image\)\[image-.*\..*\]"
+    imgs = re.findall(p, row["question_text"])
+    for option in row["options"]:
+        imgs.extend(re.findall(p, option))
+    for bgdesc in row["background_description"]:
+        imgs.extend(re.findall(p, bgdesc))
+
+    img_ids = [img.split("[")[1].split("]")[0] for img in imgs]
+    # remove the last character if it is a period (eg. image-1.png. -> image-1.png)
+    img_ids = [img_id[:-1] if img_id[-1] == "." else img_id for img_id in img_ids]
+    # remove character after the last digit (eg. image-13c.png -> image-13.png)
+    img_ids = [re.sub(r"\D*\.", ".", img_id) for img_id in img_ids]
+    # remove character between dots (eg. image-13.c.png -> image-13.png)
+    img_ids = [re.sub(r"\.\D*\.", ".", img_id) for img_id in img_ids]
+
+    for img_id in img_ids:
+        if not (img_base_p / img_id).exists():
+            # print(f"MISSING IMAGE: {img_id=}, {imgs=}, {row.name=}")
+            return None
+    return img_ids
+
+  def load_images(img_ids, img_base_p):
+    if img_ids is None:
+        return None
+    img = Image()
+    return [
+        img.encode_example(deepcopy(PILImage.open(img_base_p / img_id).convert("RGB")))
+        for img_id in img_ids
+    ]
+
+  if __name__ == "__main__":
+    dsd = DatasetDict()
+    img_base_p = "m3exam/multimodal-question/images-"
+    for p in (
+        pbar := tqdm(
+            list(Path("m3exam/multimodal-question").glob("*-questions-image.json"))
+        )
+    ):
+        lang = p.stem.split("-")[0]
+        pbar.set_description(lang)
+    
+        df = pd.read_json(p)
+        df["image_ids"] = df.apply(
+            partial(get_img_ids, img_base_p=Path(img_base_p + lang)), axis=1
+        )
+        df["images"] = df["image_ids"].progress_apply(
+            partial(load_images, img_base_p=Path(img_base_p + lang))
+        )
+        df = df[~df.image_ids.isna()]
+        df["year"] = df["year"].astype(str).str.strip()
+        df["answer_text"] = df["answer_text"].astype(str).str.strip()
+        df["question_text"] = df["question_text"].astype(str).str.strip()
+        ds = Dataset.from_pandas(df.reset_index(drop=True))
+        # for javanese there are no background descs thus it is interpreted as dtype null. We need to change it to string
+        features = ds.features.copy()
+        features["background_description"] = Sequence(
+            feature=Value(dtype="string", id=None), length=-1, id=None
+        )
+        ds = ds.cast(features)
+    
+        dsd[lang] = ds
+
+        dsd.push_to_hub(
+          "floschne/multimodal-m3exam", token=<OMITTED>
+        )
+  
+  ```
+</details>