utils.py

import cv2
import numpy as np

def sobel_edge_detection(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    sobelx = cv2.Sobel(gray, cv2.CV_64F, 1, 0, ksize=5)
    sobely = cv2.Sobel(gray, cv2.CV_64F, 0, 1, ksize=5)
    magnitude = np.sqrt(sobelx**2 + sobely**2)
    magnitude = np.uint8(magnitude)
    return magnitude

def canny_edge_detection(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    edges = cv2.Canny(gray, 50, 150, apertureSize=3)
    return edges

def hough_lines(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    edges = cv2.Canny(gray, 50, 150)
    lines = cv2.HoughLines(edges, 1, np.pi / 180, threshold=100)
    result = image.copy()
    for line in lines:
        rho, theta = line[0]
        a = np.cos(theta)
        b = np.sin(theta)
        x0 = a * rho
        y0 = b * rho
        x1 = int(x0 + 1000 * (-b))
        y1 = int(y0 + 1000 * (a))
        x2 = int(x0 - 1000 * (-b))
        y2 = int(y0 - 1000 * (a))
        cv2.line(result, (x1, y1), (x2, y2), (0, 0, 255), 2)
    return result

def laplacian_edge_detection(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    laplacian = cv2.Laplacian(gray, cv2.CV_64F)
    laplacian = np.uint8(np.absolute(laplacian))
    return laplacian

def contours_detection(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    contours, _ = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    result = np.zeros_like(image)
    cv2.drawContours(result, contours, -1, (0, 255, 0), 2)
    return result

def prewitt_edge_detection(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    prewittx = cv2.filter2D(gray, cv2.CV_64F, np.array([[-1, 0, 1], [-1, 0, 1], [-1, 0, 1]]))
    prewitty = cv2.filter2D(gray, cv2.CV_64F, np.array([[-1, -1, -1], [0, 0, 0], [1, 1, 1]]))
    magnitude = np.sqrt(prewittx**2 + prewitty**2)
    magnitude = np.uint8(magnitude)
    return magnitude

def gradient_magnitude(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    sobelx = cv2.Sobel(gray, cv2.CV_64F, 1, 0, ksize=5)
    sobely = cv2.Sobel(gray, cv2.CV_64F, 0, 1, ksize=5)
    magnitude = np.sqrt(sobelx**2 + sobely**2)
    magnitude = np.uint8(magnitude)
    return magnitude

def corner_detection(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    corners = cv2.goodFeaturesToTrack(gray, maxCorners=100, qualityLevel=0.01, minDistance=10)
    result = np.zeros_like(image)
    corners = np.int0(corners)
    for i in corners:
        x, y = i.ravel()
        cv2.circle(result, (x, y), 3, 255, -1)
    return result