imDiffBug

imdifffbug.py

import cv2
import numpy as np
#from skimage.measure import compare_ssim
from skimage.metrics import structural_similarity
import click


@click.command()
@click.option("-o" , "--output" , default = None , type=str  ,  help = "Output File")
@click.argument("image1" , type = str)
@click.argument("image2" , type = str)
def cli(output , image1 , image2):
    x_img = cv2.imread(image1)
    y_img = cv2.imread(image2)

    x_gray = cv2.cvtColor(x_img , cv2.COLOR_BGR2GRAY)
    y_gray = cv2.cvtColor(y_img , cv2.COLOR_BGR2GRAY)


    (ssim_score , df) = structural_similarity(x_gray , y_gray , full=  True)
    df = (df*255).astype("uint8")

    threshold = cv2.threshold(df , 0 , 255 , cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
    contours = cv2.findContours(threshold.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    contours = contours[0] if len(contours) == 2 else contours[1]

    mask = np.zeros(x_img.shape , dtype="uint8")
    filled_y = y_img.copy()

    for c in contours:
        area = cv2.contourArea(c)
        if area >= 15:
            x,y,w,h = cv2.boundingRect(c)
            cv2.rectangle(x_img, (x, y), (x + w, y + h), (12,255,12), 2)
            cv2.rectangle(y_img, (x, y), (x + w, y + h), (12,255,12), 2)
    
    result = np.concatenate((x_img , y_img) , axis = 1)
    if not output:
        cv2.imshow("RESULT" , result)
        cv2.waitKey(0)
        cv2.destroyAllWindows()
    else:
        cv2.imwrite(output , result)
    
cli()

requirements.txt

opencv-python
numpy
click
scikit-image