identify not white pixels in bmp

[ALIII]

To find the pixels in an image that are different from white and later determine the proportion of non-white pixels in the overall image, you can use image processing libraries such as Python's OpenCV. Here's a step-by-step guide:


1. ** Install OpenCV **: If you haven't already, you'll need to install the OpenCV library. You can do this using pip:
pip install opencv-python

2. ** Load and Process the Image **:

   import cv2
   import numpy as np

   # Load the image
   image = cv2.imread('p2.bmp')

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

   # Define the color white (you may need to adjust this based on your image)
   white = [255, 255, 255]

   # Create a mask for non-white pixels
   mask = cv2.inRange(image, np.array(white), np.array(white))

   # Find the non-white pixels in the original image
   non_white_pixels = cv2.countNonZero(mask)

   # Calculate the proportion of non-white pixels in the image
   total_pixels = image.shape[0] * image.shape[1]
   proportion_non_white = non_white_pixels / total_pixels

   # Display the proportion
   print(f"Proportion of non-white pixels: {proportion_non_white:.4f}")

This code will load your image ('p2.bmp'), convert it to grayscale, and create a mask for the non-white pixels. It then calculates the proportion of non-white pixels in the image.

3. ** Adjust the White Threshold **: In the code above, we assumed that white pixels have the RGB values [255, 255, 255]. If your white is slightly different, you may need to adjust these values accordingly.

4. ** Run the Code **: Save your image as 'p2.bmp' in the same directory as the Python script, and run the code. It will print the proportion of non-white pixels in the image.

This code should help you determine whether your BMP image contains non-white pixels, which can be useful for detecting blank PDFs.

buran write Oct-09-2023, 03:01 AM:
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