Trim image to remove whitespace using Python

Guide on using Python to trim whitespace around an image (trim image) using the OpenCV library. This Python code helps to crop out excess whitespace around an image to highlight the main content.

import cv2
import numpy as np

def trim_image(image_path, output_path):
    # Read the image from file
    image = cv2.imread(image_path)

    # Convert the image from BGR to grayscale
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    # Create a mask to identify non-white areas
    _, thresh = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)

    # Find the bounding box of non-white areas
    x, y, w, h = cv2.boundingRect(thresh)

    # Crop the image based on the bounding box
    trimmed_image = image[y:y+h, x:x+w]

    # Save the cropped image
    cv2.imwrite(output_path, trimmed_image)

# Example usage
trim_image('input_image.jpg', 'trimmed_image.jpg')

Detailed explanation:

1. Read the image from file:

   • cv2.imread(image_path): Reads the image from the file path.

2. Convert image to grayscale:

   • cv2.cvtColor(image, cv2.COLOR_BGR2GRAY): Converts the image from BGR color space to grayscale for easier processing.

3. Create mask and identify non-white areas:

   • cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV): Creates a binary mask where pixels with values > 240 are considered white and inverted (to black) to identify non-white areas.

4. Find bounding box of non-white areas:

   • cv2.boundingRect(thresh): Determines the bounding rectangle around non-white areas.

5. Crop the image:

   • image[y:y+h, x:x+w]: Crops the image based on the bounding rectangle found.

6. Save the cropped image:

   • cv2.imwrite(output_path, trimmed_image): Saves the cropped image to the output file path.

Python Version:

This code uses the OpenCV library and can run on Python 3.6 and above. Ensure that the OpenCV library is installed, which can be done using pip install opencv-python.