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 test_get_region_bounds(self):
test_img = np.zeros((1000,1000), dtype=np.uint8)
rr, cc = circle(100,100,50)
test_img[rr,cc] = 1
bx, by = gzapi.get_region_bounds(test_img)
bx, by = bx[0], by[0]
minc, maxc = bx
minr, maxr = by
self.assertEqual(maxc - minc + 1, 100)
self.assertEqual(maxr - minr + 1, 100)
center = gzapi.get_bbox_center((minr, minc, maxr, maxc))
self.assertTupleEqual(center, (100,100))
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