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 _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 process_edges(self, is_edge):
contours = extract_contours(is_edge)
for contour in contours:
self.process_contour(contour)
return self.ellipses
