dataautogpt3
commited on
Commit
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3a5662d
1
Parent(s):
202fcb6
Update download.py
Browse files- download.py +9 -13
download.py
CHANGED
@@ -6,19 +6,15 @@ import pandas as pd
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from datasets import load_dataset
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def decode_and_save_images(df, output_dir):
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for i,
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# Decode image
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image_data = base64.b64decode(
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image = Image.open(io.BytesIO(image_data))
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# Save
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# Save caption
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caption_filename = f"{output_dir}/caption_{i}.txt"
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with open(caption_filename, 'w') as file:
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file.write(row['caption'])
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print(f"Saved Image and Caption {i}")
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@@ -26,8 +22,8 @@ def main():
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# Load dataset from Hugging Face
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dataset = load_dataset("dataautogpt3/Dalle3")
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#
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df = pd.DataFrame(dataset[
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# Specify your desired output directory here
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output_dir = '/path/to/your/desired/output' # Replace with your specific path
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from datasets import load_dataset
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def decode_and_save_images(df, output_dir):
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for i, (image_base64, caption) in enumerate(zip(df['image'], df['caption'])):
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# Decode and save the image
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image_data = base64.b64decode(image_base64)
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image = Image.open(io.BytesIO(image_data))
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image.save(os.path.join(output_dir, f"image_{i}.png"))
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# Save the caption
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with open(os.path.join(output_dir, f"caption_{i}.txt"), 'w') as file:
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file.write(caption)
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print(f"Saved Image and Caption {i}")
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# Load dataset from Hugging Face
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dataset = load_dataset("dataautogpt3/Dalle3")
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# Assuming the first split contains the data
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df = pd.DataFrame(dataset[next(iter(dataset))])
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# Specify your desired output directory here
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output_dir = '/path/to/your/desired/output' # Replace with your specific path
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