def test_translate_points(self):
horizontal_shift = 50
vertical_shift = 40
points = np.asarray([[100., 200.]])
test_image = self.get_test_image()
shape = test_image.shape
translated_points = image_utils.translate_points(
points,
horizontal_shift=horizontal_shift,
vertical_shift=vertical_shift)
translated_test_image = image_utils.translate_image(
test_image,
horizontal_shift=horizontal_shift,
vertical_shift=vertical_shift)
print(points)
print(translated_points)
scaled_points = image_utils.downscale_points(points, shape=shape)
scaled_translated_points = image_utils.downscale_points(
translated_points, shape=shape)
test_image_points = image_utils.get_image_with_points(
test_image, scaled_points)
translated_test_image_points = image_utils.get_image_with_points(
translated_test_image, scaled_translated_points)
image_utils.show_multiple_images(
[test_image_points, translated_test_image_points])
def test_rotate_and_translate(self):
rotation_angle = 30
horizontal_shift = 50
vertical_shift = 40
points = np.asarray([[100., 200.]])
test_image = self.get_test_image()
shape = test_image.shape
rotated_points = image_utils.rotate_points(
points, rotation_angle=-rotation_angle)
rotated_test_image = image_utils.rotate_image(
test_image, rotation_angle=rotation_angle)
translated_points = image_utils.translate_points(
rotated_points,
horizontal_shift=horizontal_shift,
vertical_shift=vertical_shift)
translated_test_image = image_utils.translate_image(
rotated_test_image,
horizontal_shift=horizontal_shift,
vertical_shift=vertical_shift)
scaled_points = image_utils.downscale_points(points, shape=shape)
scaled_translated_points = image_utils.downscale_points(
translated_points, shape=shape)
test_image_points = image_utils.get_image_with_points(
test_image, scaled_points)
translated_test_image_points = image_utils.get_image_with_points(
translated_test_image, scaled_translated_points)
image_utils.show_multiple_images(
[test_image_points, translated_test_image_points])
def view_sample_data_list(X, y, num_sample=5):
for i in range(num_sample):
idx = np.random.randint(len(X))
image = cv2.imread(X[idx], 0)
points = y[idx]
image_utils.show_image(image_utils.get_image_with_points(
image, points))
def test_rotate_points(self):
rotation_angle = 30
points = np.asarray([[100., 200.]])
test_image = self.get_test_image()
shape = test_image.shape
rotated_points = image_utils.rotate_points(
points, rotation_angle=rotation_angle)
rotated_test_image = image_utils.rotate_image(
test_image, rotation_angle=rotation_angle)
scaled_points = image_utils.downscale_points(points, shape=shape)
scaled_rotated_points = image_utils.downscale_points(rotated_points,
shape=shape)
test_image_points = image_utils.get_image_with_points(
test_image, scaled_points)
rotated_test_image_points = image_utils.get_image_with_points(
rotated_test_image, scaled_rotated_points)
image_utils.show_multiple_images(
[test_image_points, rotated_test_image_points])
def view_sample_data(data, num_sample):
X = data["X"]
y_skeleton = data["y_skel"]
y_clf = data["y_clf"]
for i in range(num_sample):
idx = np.random.randint(X.shape[0])
image = X[idx].copy()
image = np.stack((image, ) * 3, axis=-1)
print(y_skeleton[idx])
image_with_points = image_utils.get_image_with_points(
image, y_skeleton[idx])
print("Class: " + str(y_clf[idx] + 1))
image_utils.show_image(image_with_points, cmap=None)