def draw_corner_harris(self):
img = Utils.fetch_image(ImageURL.CHESS)
orig = img.copy()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
dts = cv2.cornerHarris(src=gray, blockSize=2, ksize=3, k=.0001)
img[dts > 0.01 * dts.max()] = [0, 0, 255]
return img, orig
def hough_circles_process(self):
image = Utils.fetch_image(url=ImageURL.OPENCV_LOGO)
orig = image.copy()
circles = self.get_hough_circles(image)
for [x, y, raduis] in circles[0, :]:
cv2.circle(img=image,
center=(x, y),
radius=raduis,
color=(0, 0, 255),
thickness=2)
return image, orig
def affin_rotate(self):
src = Utils.fetch_image(ImageURL.RANDOM)
orig = src.copy()
srcTri = np.array([[0, 0], [src.shape[1] - 1, 0],
[0, src.shape[0] - 1]]).astype(np.float32)
dstTri = np.array([[0, src.shape[1] * 0.33],
[src.shape[1] * 0.85, src.shape[0] * 0.25],
[src.shape[1] * 0.15,
src.shape[0] * 0.7]]).astype(np.float32)
warp_mat = cv2.getAffineTransform(srcTri, dstTri)
warp_dst = cv2.warpAffine(src, warp_mat, (src.shape[1], src.shape[0]))
center = (warp_dst.shape[1] // 2, warp_dst.shape[0] // 2)
angle = 90
scale = 1
rotated = cv2.getRotationMatrix2D(center, angle, scale)
return src, orig
def contours_process(self):
image = Utils.fetch_image(url=ImageURL.RANDOM)
orig = image.copy()
contours = self.get_contours(image)
cv2.drawContours(image=image,
contours=contours,
contourIdx=-1,
color=(0, 0, 255),
thickness=3)
cv2.putText(img=image,
text=f"contours: {str(len(contours))}",
org=(10, 40),
fontScale=1.2,
fontFace=cv2.FONT_HERSHEY_SIMPLEX,
color=(0, 0, 0),
thickness=2)
return image, orig
def draw_good_features_to_track(self):
img = Utils.fetch_image(ImageURL.CHESS)
orig = img.copy()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
koseler = cv2.goodFeaturesToTrack(image=gray,
maxCorners=50,
qualityLevel=0.0001,
minDistance=10)
for kose in koseler:
x, y = kose.ravel()
cv2.circle(img=img,
center=(x, y),
radius=3,
color=(0, 0, 255),
thickness=-1)
return img, orig
def hough_lines_process(self):
image = Utils.fetch_image(url=ImageURL.BUILDING)
orig = image.copy()
lines = self.get_hough_lines(image)
for rho, theta in lines[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(image, (x1, y1), (x2, y2), (0, 0, 255), 2)
return image, orig
import cv2 from lib.utils import Utils from lib.helpers import ImageURL img = Utils.fetch_image(url=ImageURL.RANDOM) print(img) gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) Utils.show_image_compare(img, gray) cv2.waitKey(0)
