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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, row in df.iterrows():
# Decode image
image_data = base64.b64decode(row['image'])
image = Image.open(io.BytesIO(image_data))
# Save image
image_filename = f"{output_dir}/image_{i}.png"
image.save(image_filename)
# Save caption
caption_filename = f"{output_dir}/caption_{i}.txt"
with open(caption_filename, 'w') as file:
file.write(row['caption'])
print(f"Saved Image and Caption {i}")
def main():
# Load dataset from Hugging Face
dataset = load_dataset("dataautogpt3/Dalle3")
# Convert to Pandas DataFrame (assuming the dataset is in the first split)
df = pd.DataFrame(dataset['train'])
# Specify your desired output directory here
output_dir = '/path/to/your/desired/output' # Replace with your specific path
os.makedirs(output_dir, exist_ok=True)
# Process and save images and captions
decode_and_save_images(df, output_dir)
if __name__ == "__main__":
main()
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