unimed-clip-medical-image-zero-shot-classification
/
data_prepration_scripts
/ROCOV2
/roco_webdataset.py
import os | |
import tarfile | |
import io | |
import pandas as pd | |
from tqdm import tqdm | |
import argparse | |
def create_webdataset(csv_file, output_dir, parent_dataset_path, tar_size=1000): | |
os.makedirs(output_dir, exist_ok=True) | |
with open(csv_file, newline='') as f: | |
reader = pd.read_csv(csv_file, delimiter=',') | |
tar_index = 0 | |
file_count = 0 | |
tar = None | |
for row in tqdm(reader.values): | |
if file_count % tar_size == 0: | |
if tar: | |
tar.close() | |
tar_index += 1 | |
tar_path = os.path.join(output_dir, f"dataset-{tar_index:06d}.tar") | |
tar = tarfile.open(tar_path, 'w') | |
filename = row[0] + '.jpg' | |
# label = ast.literal_eval(row[1]) | |
all_caption = row[1] | |
caption = all_caption.strip().strip("\n\n").strip("\n") | |
# Read the image file | |
image_path = os.path.join(parent_dataset_path, filename) | |
with open(image_path, 'rb') as img_file: | |
img_data = img_file.read() | |
# Create an in-memory tarfile | |
img_tarinfo = tarfile.TarInfo(name=f"{file_count:06d}.jpg") | |
img_tarinfo.size = len(img_data) | |
tar.addfile(img_tarinfo, io.BytesIO(img_data)) | |
# Add caption.txt to the tarfile | |
caption_data = caption.encode('utf-8') | |
caption_tarinfo = tarfile.TarInfo(name=f"{file_count:06d}.txt") | |
caption_tarinfo.size = len(caption_data) | |
tar.addfile(caption_tarinfo, io.BytesIO(caption_data)) | |
file_count += 1 | |
if tar: | |
tar.close() | |
if __name__ == "__main__": | |
# Argument parser setup | |
parser = argparse.ArgumentParser(description="Create a WebDataset from CSV") | |
parser.add_argument('--csv_file', type=str, required=True, help="Path to the CSV file") | |
parser.add_argument('--output_dir', type=str, required=True, help="Directory to store the output tar files") | |
parser.add_argument('--parent_dataset_path', type=str, required=True, | |
help="Path to the parent dataset containing images") | |
parser.add_argument('--tar_size', type=int, default=1000, help="Number of files per tar file") | |
# Parse the arguments | |
args = parser.parse_args() | |
# Call the function with the parsed arguments | |
create_webdataset(args.csv_file, args.output_dir, args.parent_dataset_path, args.tar_size) | |