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import cv2
import os
import glob
import numpy as np
def apply_mask_and_crop(input_folder, mask, output_folder):
"""
Apply binary mask to all images, crop to masked region, and save to output folder
Args:
input_folder (str): Path to folder containing input images
mask_path (str): Path to binary mask image
output_folder (str): Path to save cropped masked images
"""
# Load and prepare mask
# mask = cv2.imread(mask_path, cv2.IMREAD_GRAYSCALE)
if mask is None:
raise ValueError(f"Could not load mask from {mask_path}")
_, binary_mask = cv2.threshold(mask, 127, 255, cv2.THRESH_BINARY)
# Create output directory if it doesn't exist
os.makedirs(output_folder, exist_ok=True)
# Get list of image files
image_files = glob.glob(os.path.join(input_folder, "*.jpg")) + \
glob.glob(os.path.join(input_folder, "*.png")) + \
glob.glob(os.path.join(input_folder, "*.bmp"))
if not image_files:
print(f"No images found in {input_folder}")
return
print(f"Found {len(image_files)} images to process")
i = 0
for img_path in image_files:
# Load image
img = cv2.imread(img_path)
if img is None:
print(f"Warning: Could not read image {img_path}")
continue
# Resize mask if dimensions don't match
if img.shape[:2] != binary_mask.shape[:2]:
resized_mask = cv2.resize(binary_mask, (img.shape[1], img.shape[0]))
else:
resized_mask = binary_mask
# Apply mask
masked_img = cv2.bitwise_and(img, img, mask=resized_mask)
# Find contours to get bounding box of mask
contours, _ = cv2.findContours(resized_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
if not contours:
print(f"No mask area found in {img_path} - skipping")
continue
# Get bounding rectangle of largest contour
x, y, w, h = cv2.boundingRect(max(contours, key=cv2.contourArea))
# Crop to masked region
cropped_img = masked_img[y:y+h, x:x+w]
# Create output path (preserve original filename)
filename = os.path.basename(img_path)
output_path = os.path.join(output_folder, filename)
# Save cropped image
cv2.imwrite(output_path, cropped_img)
if i == 0:
preview_path = os.path.join(output_folder, f"preview_{filename}")
cv2.imwrite(preview_path, cropped_img)
return preview_path
i= i+1
# print(f"Processed and saved: {output_path}")
print(f"\nProcessing complete! Saved {len(image_files)} cropped images to {output_folder}")
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