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
def test_point_rotate(self):
x, y = 1.0, 1.0
theta = np.pi/2
x_rot, y_rot = gzapi.point_rotate(x, y, theta)
self.assertAlmostEqual(x_rot, -1)
self.assertAlmostEqual(y_rot, 1)