def _by_points(self,
case_name,
n,
*,
angle_min=0,
angle_max=359,
noise_error=0.0):
w, h = 300, 150
ellipse = shapes.Ellipse(w // 2, h // 2, w // 3, h // 3, 20)
img_contour = np.zeros((h, w), np.uint8)
ellipse.draw(img_contour, 255)
self.dump_debug_img(Path(case_name) / '0_ellipse.png', img_contour)
np.random.seed(239)
angles = np.random.randint(angle_min, angle_max, (n, ))
xys = np.float32(list(map(ellipse.calculate_point, angles)))
xys += np.random.random_sample((len(xys), 2)) * noise_error
img_points = img_contour // 3
draw_pixels(img_points, xys, 255)
self.dump_debug_img(Path(case_name) / '1_points.png', img_points)
estimation = fit_ellipse(xys)
estimation.draw(img_points, 255)
self.dump_debug_img(Path(case_name) / '2_estimation.png', img_points)
self.assertTrue(
np.all(np.abs(np.array(ellipse) - np.array(estimation)) < 3.0))
def _process(self, case_name, img):
self.dump_debug_img(Path(case_name) / '01_input.png', img)
edges = self.processor.process(img)
self.dump_debug_img(Path(case_name) / '02_gaussed_grayscale.png', np.uint8(self.processor._debug_last_values['gaussed_grayscale']))
self.dump_debug_img(Path(case_name) / '03_intencity_dx.png', np.uint8(127 + self.processor._debug_last_values['intensity_dx']))
self.dump_debug_img(Path(case_name) / '04_intencity_dy.png', np.uint8(127 + self.processor._debug_last_values['intensity_dy']))
self.dump_debug_img(Path(case_name) / '05_intencity_dnorm.png', np.uint8(self.processor._debug_last_values['intensity_dnorm']))
self.dump_debug_img(Path(case_name) / '06_is_extremum.png', np.uint8(self.processor._debug_last_values['is_extremum']) * 255)
self.dump_debug_img(Path(case_name) / '07_weak_edges.png', np.uint8(self.processor._debug_last_values['weak_edges']) * 255)
self.dump_debug_img(Path(case_name) / '08_strong_edges.png', np.uint8(self.processor._debug_last_values['strong_edges']) * 255)
self.dump_debug_img(Path(case_name) / '09_edges.png', edges * 255)
contours = extract_contours(edges)
pointsNumber = 0
h, w = img.shape[:2]
extracted_edges = np.zeros((h, w, 3), np.uint8)
np.random.seed(239)
for contour in contours:
colour = np.random.randint(60, 255, (3,))
draw_pixels(extracted_edges, contour, colour)
pointsNumber += len(contour)
self.assertTrue(np.all(edges == draw_pixels(edges.copy(), contour, 1))) # assertion, that all pixels from contours are from edges
self.dump_debug_img(Path(case_name) / '10_extracted_edges.png', extracted_edges)
self.assertEqual(pointsNumber, len(edges.nonzero()[0]))
return contours
def draw_pixels_test_grayscale_multi_points(self):
w, h = 10, 6
img = np.zeros((h, w), np.uint8)
img2 = shapes.draw_pixels(img, [[0, 0], [3, 0]], 1)
self.assertIs(img2, img)
self.assertEqual(img[0, 0], 1)
self.assertEqual(img[0, 3], 1)
self.assertEqual(img.sum(), 2)
center_yx = [h//2, w//2]
expected_img = shapes.draw_pixels(img.copy(), center_yx, 30)
for x, y in [[0, -1], [-1, 0], [0, h + 1], [w + 1, 0]]:
shapes.draw_pixels(img, [[x, y], center_yx], 30)
self.assertTrue(np.all(img == expected_img))
def draw_pixels_test_color_one_point(self):
w, h = 10, 6
img = np.zeros((h, w, 3), np.uint8)
img2 = shapes.draw_pixels(img, [0, 0], (239, 0, 30))
self.assertIs(img2, img)
self.assertTrue(np.all(img[0, 0] == [239, 0, 30]))
shapes.draw_pixels(img, [w - 1, 0], (0, 200, 15))
self.assertTrue(np.all(img[0, w - 1] == [0, 200, 15]))
for x, y in [[0, -1], [-1, 0], [0, h + 1], [w + 1, 0]]:
img_copy = img.copy()
shapes.draw_pixels(img_copy, [x, y], (124, 2, 6))
self.assertTrue(np.all(img == img_copy))
def draw_pixels_test_grayscale_one_point(self):
w, h = 10, 6
img = np.zeros((h, w), np.uint8)
img2 = shapes.draw_pixels(img, [0, 0], 239)
self.assertIs(img2, img)
self.assertEqual(img[0, 0], 239)
shapes.draw_pixels(img, [w - 1, 0], 240)
self.assertEqual(img[0, w - 1], 240)
for x, y in [[0, -1], [-1, 0], [0, h + 1], [w + 1, 0]]:
img_copy = img.copy()
shapes.draw_pixels(img_copy, [x, y], 30)
self.assertTrue(np.all(img == img_copy))
def draw_pixels_test_grayscale_multi_points(self):
w, h = 10, 6
img = np.zeros((h, w), np.uint8)
img2 = shapes.draw_pixels(img, [[0, 0], [3, 0]], 1)
self.assertIs(img2, img)
self.assertEqual(img[0, 0], 1)
self.assertEqual(img[0, 3], 1)
self.assertEqual(img.sum(), 2)
center_yx = [h // 2, w // 2]
expected_img = shapes.draw_pixels(img.copy(), center_yx, 30)
for x, y in [[0, -1], [-1, 0], [0, h + 1], [w + 1, 0]]:
shapes.draw_pixels(img, [[x, y], center_yx], 30)
self.assertTrue(np.all(img == expected_img))
def draw_pixels_test_color_one_point(self):
w, h = 10, 6
img = np.zeros((h, w, 3), np.uint8)
img2 = shapes.draw_pixels(img, [0, 0], (239, 0, 30))
self.assertIs(img2, img)
self.assertTrue(np.all(img[0, 0] == [239, 0, 30]))
shapes.draw_pixels(img, [w - 1, 0], (0, 200, 15))
self.assertTrue(np.all(img[0, w - 1] == [0, 200, 15]))
for x, y in [[0, -1], [-1, 0], [0, h + 1], [w + 1, 0]]:
img_copy = img.copy()
shapes.draw_pixels(img_copy, [x, y], (124, 2, 6))
self.assertTrue(np.all(img == img_copy))
def draw_pixels_test_grayscale_one_point(self):
w, h = 10, 6
img = np.zeros((h, w), np.uint8)
img2 = shapes.draw_pixels(img, [0, 0], 239)
self.assertIs(img2, img)
self.assertEqual(img[0, 0], 239)
shapes.draw_pixels(img, [w - 1, 0], 240)
self.assertEqual(img[0, w - 1], 240)
for x, y in [[0, -1], [-1, 0], [0, h + 1], [w + 1, 0]]:
img_copy = img.copy()
shapes.draw_pixels(img_copy, [x, y], 30)
self.assertTrue(np.all(img == img_copy))
def _process(self, case_name, img):
self.dump_debug_img(Path(case_name) / '01_input.png', img)
edges = self.processor.process(img)
self.dump_debug_img(
Path(case_name) / '02_gaussed_grayscale.png',
np.uint8(self.processor._debug_last_values['gaussed_grayscale']))
self.dump_debug_img(
Path(case_name) / '03_intencity_dx.png',
np.uint8(127 + self.processor._debug_last_values['intensity_dx']))
self.dump_debug_img(
Path(case_name) / '04_intencity_dy.png',
np.uint8(127 + self.processor._debug_last_values['intensity_dy']))
self.dump_debug_img(
Path(case_name) / '05_intencity_dnorm.png',
np.uint8(self.processor._debug_last_values['intensity_dnorm']))
self.dump_debug_img(
Path(case_name) / '06_is_extremum.png',
np.uint8(self.processor._debug_last_values['is_extremum']) * 255)
self.dump_debug_img(
Path(case_name) / '07_weak_edges.png',
np.uint8(self.processor._debug_last_values['weak_edges']) * 255)
self.dump_debug_img(
Path(case_name) / '08_strong_edges.png',
np.uint8(self.processor._debug_last_values['strong_edges']) * 255)
self.dump_debug_img(Path(case_name) / '09_edges.png', edges * 255)
contours = extract_contours(edges)
pointsNumber = 0
h, w = img.shape[:2]
extracted_edges = np.zeros((h, w, 3), np.uint8)
np.random.seed(239)
for contour in contours:
colour = np.random.randint(60, 255, (3, ))
draw_pixels(extracted_edges, contour, colour)
pointsNumber += len(contour)
self.assertTrue(
np.all(edges == draw_pixels(edges.copy(), contour, 1))
) # assertion, that all pixels from contours are from edges
self.dump_debug_img(
Path(case_name) / '10_extracted_edges.png', extracted_edges)
self.assertEqual(pointsNumber, len(edges.nonzero()[0]))
return contours
def _by_points(self, case_name, n, *,
angle_min=0, angle_max=359, noise_error=0.0):
w, h = 300, 150
ellipse = shapes.Ellipse(w // 2, h // 2, w // 3, h // 3, 20)
img_contour = np.zeros((h, w), np.uint8)
ellipse.draw(img_contour, 255)
self.dump_debug_img(Path(case_name) / '0_ellipse.png', img_contour)
np.random.seed(239)
angles = np.random.randint(angle_min, angle_max, (n,))
xys = np.float32(list(map(ellipse.calculate_point, angles)))
xys += np.random.random_sample((len(xys), 2)) * noise_error
img_points = img_contour // 3
draw_pixels(img_points, xys, 255)
self.dump_debug_img(Path(case_name) / '1_points.png', img_points)
estimation = fit_ellipse(xys)
estimation.draw(img_points, 255)
self.dump_debug_img(Path(case_name) / '2_estimation.png', img_points)
self.assertTrue(np.all(np.abs(np.array(ellipse) - np.array(estimation)) < 3.0))
