def show(self):
while True:
ret, frame = self.value.read()
if ret:
cv2.imshow("Exercise A", frame)
key = cv2.waitKey(20)
if esc_pressed(key):
break
self.value.release()
def exercise_3():
cv2.namedWindow('Exercise 1.3')
cv2.setMouseCallback('Exercise 1.3',draw_window)
cv2.imshow("Exercise 1.3", img)
while(1):
key = cv2.waitKey(20)
if esc_pressed(key):
break
cv2.destroyAllWindows()
def test_video(path):
cap = cv2.VideoCapture(path)
while (True):
ret, frame = cap.read()
processed = pipeline(frame)
if processed is not None:
cv2.imshow("Teste", processed)
if esc_pressed(cv2.waitKey(1)):
break
#same values as quiz
rho = 2
theta = np.pi/180
#threshold is minimum number of intersections in a grid for candidate line to go to output
threshold = 20
min_line_len = 50
max_line_gap = 200
line_image = hough_lines(roi_image, rho, theta, threshold, min_line_len, max_line_gap)
result = weighted_img(line_image, image, α=0.8, β=1., λ=0.)
return result
# for source_img in os.listdir("test_images/"):
# image = mpimg.imread("test_images/"+source_img)
# image = cv2.imread("images/lane_test.jpeg")
# processed = process_frame(image)
# cv2.imshow("Teste", processed)
# cv2.waitKey()
# mpimg.imsave("test_images/annotated_"+source_img,processed)
cap = cv2.VideoCapture("images/challenge.mp4")
while(True):
ret, frame = cap.read()
processed = process_frame(frame)
cv2.imshow("Teste", processed)
if esc_pressed(cv2.waitKey(1)):
break