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import os
from PIL import Image
from tqdm import tqdm
import torch
import torchvision.transforms as transforms
def center_crop_images(input_folder, output_folder, crop_size=(512, 512)):
# Create output folder if it doesn't exist
os.makedirs(output_folder, exist_ok=True)
# Define the center crop transform
crop_transform = transforms.CenterCrop(crop_size)
# Get list of all image files in the input folder
image_files = [
f
for f in os.listdir(input_folder)
if f.endswith((".png", ".jpg", ".jpeg", ".bmp", ".gif"))
]
# Loop over each image file with progress bar
for image_file in tqdm(image_files, desc="Center cropping images"):
img_path = os.path.join(input_folder, image_file)
try:
# Open the image
img = Image.open(img_path)
# Apply the center crop transform
img_cropped = crop_transform(img)
# Save the cropped image to the output folder
img_cropped.save(os.path.join(output_folder, image_file))
except Exception as e:
print(f"Error processing {img_path}: {e}")
# Usage
input_folder = "/cm/shared/ninhnq3/datasets/cyclegan-rain/testB"
output_folder = input_folder
center_crop_images(input_folder, output_folder)
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