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import os | |
import io | |
from PIL import Image | |
import pandas as pd | |
from datasets import load_dataset | |
def save_images_from_parquet(parquet_path, target_folder): | |
""" | |
Load parquet file using datasets, read each row's BYTES and FILENAME, | |
and save the image to the target folder with the name FILENAME. | |
Args: | |
parquet_path: Path to the input parquet file | |
target_folder: Path to the target folder to save images | |
""" | |
# Load the parquet file | |
dataset = load_dataset('loooooong/Any2anyTryon_vitonhd_test', data_files=parquet_path)['train'] | |
# Ensure target folder exists | |
os.makedirs(target_folder, exist_ok=True) | |
# Process each row | |
for row in dataset: | |
try: | |
# Read image bytes and filename | |
image = row['BYTES'] | |
filename = row['FILENAME'] | |
# Open image using PIL | |
# image = Image.open(io.BytesIO(image_bytes)) | |
# Save image to target folder | |
image.save(os.path.join(target_folder, filename)) | |
except Exception as e: | |
print(f"Failed to process row with filename {row['FILENAME']}: {e}") | |
if __name__ == "__main__": | |
parquet_path = "data/vitonhd_test.parquet" | |
target_folder = "data/zalando-hd-resized/test/image_synthesis" | |
save_images_from_parquet(parquet_path, target_folder) | |