Create download.py

download.py

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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()