| import base64 |
| from PIL import Image |
| import io |
| import os |
| import pandas as pd |
| from datasets import load_dataset |
|
|
| def decode_and_save_images(df, output_dir): |
| for i, (image_base64, caption) in enumerate(zip(df['image'], df['caption'])): |
| |
| image_data = base64.b64decode(image_base64) |
| image = Image.open(io.BytesIO(image_data)) |
| image.save(os.path.join(output_dir, f"image_{i}.png")) |
|
|
| |
| with open(os.path.join(output_dir, f"caption_{i}.txt"), 'w') as file: |
| file.write(caption) |
|
|
| print(f"Saved Image and Caption {i}") |
|
|
| def main(): |
| |
| dataset = load_dataset("dataautogpt3/Dalle3") |
|
|
| |
| df = pd.DataFrame(dataset[next(iter(dataset))]) |
|
|
| |
| output_dir = '/path/to/your/desired/output' |
| os.makedirs(output_dir, exist_ok=True) |
|
|
| |
| decode_and_save_images(df, output_dir) |
|
|
| if __name__ == "__main__": |
| main() |
|
|