Python Automation and Machine Learning for EM and ICs

The developed Python script quantitatively evaluates the distribution of pixel intensities within a specified contrast range in a grayscale image. By reading the image using OpenCV and applying logical thresholding, the script identifies all pixels with intensity values falling between a user-defined lower and upper limit. It then calculates the percentage of these selected pixels relative to the total number of pixels in the image. This percentage serves as a metric to characterize regions of interest based on their contrast properties, which is particularly useful for assessing image uniformity, detecting subtle features, or comparing contrast variations across different imaging conditions or sample regions.