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prewit.py
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prewit.py
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import tkinter as tk
import tkinter.filedialog as fd
import cv2
import numpy as np
from scipy.signal import convolve2d
def convolve(image, kernel):
convolved_matrix = convolve2d(image, kernel, mode='same', boundary='symm')
return np.array(convolved_matrix, dtype=np.float64)
def prewit_algorithm(img):
# Apply Prewit Gx kernel
x_gradient_matrix = convolve(img, gx_kernel)
# Apply Prewit Gy kernel
y_gradient_matrix = convolve(img, gy_kernel)
# Combine the gradient matrices to get the gradient magnitude
gradient_magnitude = np.sqrt(x_gradient_matrix**2 + y_gradient_matrix**2)
return gradient_magnitude / np.max(gradient_magnitude) * 255
def on_tr_trackbar(val):
global gradient_image, threshold_tracker, img
gradient_magnitude = prewit_algorithm(img)
threshold_tracker = int(cv2.getTrackbarPos('Threshold', 'Trackbars'))
gradient_image = np.zeros(gradient_magnitude.shape, dtype=np.uint8)
gradient_image[gradient_magnitude > threshold_tracker] = 255
gradient_image = cv2.putText(gradient_image, f'T: {threshold_tracker}', (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
# Show results
cv2.imshow('Gray Scale', img)
cv2.imshow('Prewit Operator', gradient_image)
IMAGE_FILE = '../../test-images/simple-shapes.png'
IMAGE_NAME = IMAGE_FILE.split('/')[-1]
img = cv2.imread(IMAGE_FILE, 0)
threshold_tracker = 0
gradient_image = None
gx_kernel = np.array([[1, 0, -1],
[1, 0, -1],
[1, 0, -1]])
gy_kernel = np.array([[1, 1, 1],
[0, 0, 0],
[-1, -1, -1]])
#Creating trackbar window
cv2.namedWindow('Trackbars')
cv2.resizeWindow('Trackbars', 1000, 240)
cv2.createTrackbar("Threshold", "Trackbars", 0, 255, on_tr_trackbar)
on_tr_trackbar(50)
cv2.waitKey(0)
cv2.destroyAllWindows()
gradient_image = cv2.putText(gradient_image, f'T: {threshold_tracker}', (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 1)
cv2.imwrite('results/' + IMAGE_NAME, gradient_image)