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import os
import pandas as pd
from scripts.PlipDataProcess import PlipDataProcess # Updated folder name
from transformers import CLIPImageProcessor
import argparse
def main(csv_file, root_dir, save_dir):
# Load the CSV file and set 'PatientID' as the index
df4 = pd.read_csv(csv_file).set_index('PatientID')
# List directories in the root directory (assuming each directory corresponds to a patient)
files = [file for file in os.listdir(root_dir) if os.path.isdir(os.path.join(root_dir, file))]
# Initialize the image processor
img_processor = CLIPImageProcessor.from_pretrained("./plip/")
# Initialize the dataset processing object
dataset = PlipDataProcess(
root_dir=root_dir,
files=files,
df=df4,
img_processor=img_processor,
num_tiles_per_patient=2000,
max_workers=64,
save_dir=save_dir
)
# Process each item in the dataset
for i in range(len(dataset)):
_ = dataset[i] # Trigger processing of the i-th item
if __name__ == '__main__':
parser = argparse.ArgumentParser(description="Process WSI images and generate tiles")
# Define arguments
parser.add_argument('--csv_file', type=str, required=True, help='Path to the CSV file with patient scores')
parser.add_argument('--root_dir', type=str, required=True, help='Root directory for WSI tiles')
parser.add_argument('--save_dir', type=str, required=True, help='Directory to save the processed tile data')
# Parse arguments
args = parser.parse_args()
# Call the main function with the parsed arguments
main(csv_file=args.csv_file, root_dir=args.root_dir, save_dir=args.save_dir)
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