| import json |
| import base64 |
| import pandas as pd |
| from pathlib import Path |
| from io import BytesIO |
| from collections import defaultdict |
|
|
|
|
| INPUT_DIR = "./ROCO-QA/data" |
| OUTPUT_DIR = "./ROCO-QA/images" |
|
|
| FILE_ORDER = [ |
| "Vaild-00000-of-00001-1ddc94eb806f44ae.parquet", |
| "Train-00000-of-00001-91a106d1a22c7cc9.parquet", |
| "Valid-00001-of-00002.parquet", |
| "Test-00000-of-00001-91a106d1a22c7cc9.parquet", |
| "Valid-00000-of-00002.parquet", |
| ] |
| |
| def extract_split_name(parquet_path) -> str: |
| return Path(parquet_path).stem.split("-")[0] |
| |
| |
| def extract_image_bytes(image_field) -> bytes: |
| if isinstance(image_field, dict): |
| return image_field["bytes"] |
| elif isinstance(image_field, bytes): |
| return image_field |
| elif isinstance(image_field, str): |
| return base64.b64decode(image_field) |
| else: |
| buf = BytesIO() |
| image_field.save(buf, format="JPEG") |
| return buf.getvalue() |
| |
| |
| def process_parquet_files(input_dir: str, output_dir: str): |
| input_dir = Path(input_dir) |
| output_dir = Path(output_dir) |
| images_dir = output_dir / "images" |
| images_dir.mkdir(parents=True, exist_ok=True) |
| |
| parquet_files = [input_dir / f for f in FILE_ORDER] |
| for pq_file in parquet_files: |
| if not pq_file.exists(): |
| print(f"File not found: {pq_file}") |
| return |
| |
| print(f"Found {len(parquet_files)} parquet file(s)") |
| for pq_file in parquet_files: |
| print(f" Order: {pq_file.name}") |
| |
| final_json = [] |
| global_seq = 0 |
| |
| for pq_file in parquet_files: |
| split_name = extract_split_name(pq_file) |
| print(f"Processing: {pq_file.name} -> split = {split_name}") |
| |
| df = pd.read_parquet(pq_file) |
| print(f" Rows: {len(df)}") |
| |
| for _, row in df.iterrows(): |
| global_seq += 1 |
| |
| image_name = f"{split_name}_sample_{global_seq:06d}.jpg" |
| image_path = images_dir / image_name |
| |
| img_bytes = extract_image_bytes(row["image"]) |
| with open(image_path, "wb") as f: |
| f.write(img_bytes) |
| |
| final_json.append({ |
| "Question": row["question"], |
| "Answer": row["answer"], |
| "ImageName": image_name, |
| "split": split_name, |
| }) |
| |
| json_path = output_dir / "dataset.json" |
| with open(json_path, "w", encoding="utf-8") as f: |
| json.dump(final_json, f, ensure_ascii=False, indent=4) |
| |
| print(f"Done. Total images: {len(final_json)}") |
| print(f"Images saved to: {images_dir}") |
| print(f"JSON saved to: {json_path}") |
| |
| |
| if __name__ == "__main__": |
| process_parquet_files(INPUT_DIR, OUTPUT_DIR) |
| |
|
|
