This program is run using the following command structure:
python color_change.pyFor this project, files are organized into a single folder in the following way:
image_color_change/
├── color_change.py
├── input_image.png
├── output_image.png (generated)TBD
Below is the code for the core function of the color_change.py file.
def color_change(input_path, output_path, black_threshold=10, white_threshold=245):
"""
Convert black pixels to white and white pixels to transparent.
Parameters:
- input_path: Path to the input image
- output_path: Path to save the converted image (should be PNG)
- black_threshold: Pixel darkness threshold (0-255). Pixels with RGB values
below this are considered black. Default is 10.
- white_threshold: Pixel brightness threshold (0-255). Pixels with RGB values
above this are considered white. Default is 245.
"""
# Read the image with alpha channel (transparency)
img = cv2.imread(input_path, cv2.IMREAD_UNCHANGED)
if img is None:
raise FileNotFoundError(f"Could not read image from {input_path}")
# Check if image has alpha channel
has_alpha = img.shape[2] == 4 if len(img.shape) == 3 else False
if not has_alpha:
# Add alpha channel if it doesn't exist
alpha = np.ones((img.shape[0], img.shape[1]), dtype=img.dtype) * 255
img = np.dstack((img, alpha))
# Separate color channels and alpha channel
bgr = img[:, :, :3]
alpha = img[:, :, 3]
# Create mask for black pixels that are NOT already transparent
# Only consider pixels where alpha > 0 (not fully transparent)
black_mask = np.all(bgr <= black_threshold, axis=2) & (alpha > 0)
# Create mask for white pixels that are NOT already transparent
white_mask = np.all(bgr >= white_threshold, axis=2) & (alpha > 0)
# Convert black pixels to white
bgr[black_mask] = [255, 255, 255]
# Make white pixels transparent (set alpha to 0)
alpha[white_mask] = 0
# Update the image
img[:, :, :3] = bgr
img[:, :, 3] = alpha
print(f"Converted {np.sum(black_mask)} black pixels to white")
print(f"Made {np.sum(white_mask)} white pixels transparent")
print(f"Total transparent pixels: {np.sum(alpha == 0)}")
# Save the result
cv2.imwrite(output_path, img)
print(f"Image saved to {output_path}")