def test_get_largest_region(self):
test_img = np.zeros((1000,1000), dtype=np.uint8)
rr, cc = circle(100,100,50)
test_img[rr,cc] = 1
rr, cc = circle(500,500,100)
test_img[rr, cc] = 1
largest_region = gzapi.get_largest_region(test_img)
self.assertTupleEqual(largest_region.centroid, (500,500))
def test_processed_image(self):
largest = None
while largest is None:
self.di.data_id = self.di.get_random_image()
top = self.di.image.plot_components[2]
im = top.data.arrays.get('im')
# Assert that the orientation is indeed zero
largest = get_largest_region(im)
self.assertLessEqual(round(largest.orientation), 1)
def test_rotate_largest_region(self):
test_img = np.zeros((1000,1000), dtype=np.uint8)
rr, cc = circle(100,100,50)
test_img[rr,cc] = 1
rr, cc = ellipse(500,500,300,100)
test_img[rr, cc] = 1
rotated = gzapi.rotate_largest_region(test_img)
largest_region = gzapi.get_largest_region(rotated)
self.assertAlmostEqual(largest_region.orientation, 0)
self.assertIsNone(gzapi.rotate_largest_region(None))
def process_image(x):
org_region = di.get_largest_region(x)
rr1, cc1 = di.get_bbox_center(org_region.bbox)
rotated_x = di.rotate_largest_region(x)
_x = cc1 - x.shape[1]/2
_y = rr1 - x.shape[0]/2
cc2, rr2 = di.point_rotate(_x, _y, -org_region.orientation)
rr2 += rotated_x.shape[0]/2
cc2 += rotated_x.shape[1]/2
cropped = di.crop_around_centroid(rotated_x, rr2, cc2)
return cropped
def update_cropped_image_data(self):
x = self.image_data.arrays.get('im')[:, :, 0]
org_region = get_largest_region(x)
rr1, cc1 = get_bbox_center(org_region.bbox)
rotated_x = rotate_largest_region(x)
_x = cc1 - x.shape[1] / 2
_y = rr1 - x.shape[0] / 2
cc2, rr2 = point_rotate(_x, _y, -org_region.orientation)
rr2 += rotated_x.shape[0] / 2
cc2 += rotated_x.shape[1] / 2
cropped = crop_around_centroid(rotated_x, rr2, cc2)
self.cropped_image_data.set_data('im', cropped)
def _cropped_image_data_default(self):
x = self.image_data.arrays.get('im')[:, :, 0]
org_region = get_largest_region(x)
rr1, cc1 = get_bbox_center(org_region.bbox)
rotated_x = rotate_largest_region(x)
_x = cc1 - x.shape[1] / 2
_y = rr1 - x.shape[0] / 2
cc2, rr2 = point_rotate(_x, _y, -org_region.orientation)
rr2 += rotated_x.shape[0] / 2
cc2 += rotated_x.shape[1] / 2
cropped = crop_around_centroid(rotated_x, rr2, cc2)
apd = ArrayPlotData(im=cropped)
return apd
