def _main(): # pragma: no cover
img = cv2.imread(r"img/imori.jpg", cv2.IMREAD_GRAYSCALE)
diff_kernel_v = np.array([
[0, -1, 0],
[0, 1, 0],
[0, 0, 0],
])
diff_kernel_h = np.array([
[0, 0, 0],
[-1, 1, 0],
[0, 0, 0],
])
img_v = q9.apply_filter(
img, diff_kernel_v.shape[0],
functools.partial(q9.get_filter_value, kernel=diff_kernel_v))
img_h = q9.apply_filter(
img, diff_kernel_h.shape[0],
functools.partial(q9.get_filter_value, kernel=diff_kernel_h))
cv2.imshow("result_v", img_v)
cv2.waitKey(0)
cv2.imshow("result_h", img_h)
cv2.waitKey(0)
cv2.imwrite(r"img/answer_14_v.jpg", img_v)
cv2.imwrite(r"img/answer_14_h.jpg", img_h)
def _main(): # pragma: no cover
img = cv2.imread(r"img/imori.jpg", 0)
img = q9.apply_filter(img, 3, _get_maxmin_diff)
cv2.imshow("result", img)
cv2.waitKey(0)
cv2.imwrite(r"img/answer_13.jpg", img)
def _main(): # pragma: no cover
img = cv2.imread(r"img/imori_noise.jpg")
img = q9.apply_filter(img, 3, np.median)
cv2.imshow("result", img)
cv2.waitKey(0)
cv2.imwrite(r"img/answer_10.jpg", img)
def _main(): # pragma: no cover
img = cv2.imread(r"img/imori.jpg")
motion_kernel = np.array([
[1 / 3, 0, 0],
[0, 1 / 3, 0],
[0, 0, 1 / 3],
])
img = q9.apply_filter(
img, motion_kernel.shape[0],
functools.partial(q9.get_filter_value, kernel=motion_kernel))
cv2.imshow("result", img)
cv2.waitKey(0)
cv2.imwrite(r"img/answer_12.jpg", img)
def _main(): # pragma: no cover
img = cv2.imread(r"img/imori.jpg", 0)
laplacian_kernel = np.array([
[0, 1, 0],
[1, -4, 1],
[0, 1, 0],
])
img = q9.apply_filter(
img, laplacian_kernel.shape[0],
functools.partial(q9.get_filter_value, kernel=laplacian_kernel))
cv2.imshow("result", img)
cv2.waitKey(0)
cv2.imwrite(r"img/answer_17.jpg", img)
def _main(): # pragma: no cover
img = cv2.imread(r"img/imori.jpg", 0)
emboss_kernel = np.array([
[-2, -1, 0],
[-1, 1, 1],
[0, 1, 2],
])
img = q9.apply_filter(
img, emboss_kernel.shape[0],
functools.partial(q9.get_filter_value, kernel=emboss_kernel))
cv2.imshow("result", img)
cv2.waitKey(0)
cv2.imwrite(r"img/answer_18.jpg", img)
def _main(): # pragma: no cover
img = cv2.imread(r"img/imori_noise.jpg", 0)
log_kernel = np.array([
[1, 3, 4, 3, 1],
[3, 6, 7, 6, 3],
[4, 7, 8, 7, 4],
[3, 6, 7, 6, 3],
[1, 3, 4, 3, 1],
]) / 100
img = q9.apply_filter(img, log_kernel.shape[0], functools.partial(
q9.get_filter_value, kernel=log_kernel))
cv2.imshow("result", img)
cv2.waitKey(0)
cv2.imwrite(r"img/answer_19.jpg", img)
