def create_prepared_image_dict(img, angle, config):
img_alpha = helpers.add_alpha_channel(img['img'])
rectificator = prep.Rectificator(config)
rect_img = rectificator.rectify_image(img_alpha)
rect_detections = rectificator.rectify_points(img['detections'],
img['size'])
rect_img_w_detections = rectificator.rectify_image(img['img_w_detections'])
rot_img, rot_mat = prep.rotate_image(rect_img, angle)
rot_detections = prep.rotate_points(rect_detections, angle, img['size'])
rot_img_w_detections, rot_mat = prep.rotate_image(rect_img_w_detections,
angle)
d = dict()
d['img'] = rot_img
d['detections'] = rot_detections
d['img_w_detections'] = rot_img_w_detections
return d
def test_rotate_image():
img = np.zeros((30, 40), np.uint8)
border = 1
img[-border:, :] = 100 # bottom
img[:, -border:] = 150 # right
img[:border, :] = 200 # top
img[:, :border] = 250 # left
rot_img, mat = prep.rotate_image(img, 90)
assert img.shape[0] == rot_img.shape[1] and img.shape[1] == rot_img.shape[0]
assert rot_img[-1][15] == 250
assert rot_img[20][-1] == 100
assert rot_img[0][15] == 150
assert rot_img[20][0] == 200
rot_img, mat = prep.rotate_image(img, -90)
assert img.shape[0] == rot_img.shape[1] and img.shape[1] == rot_img.shape[0]
assert rot_img[-1][15] == 150
assert rot_img[20][-1] == 200
assert rot_img[0][15] == 250
assert rot_img[20][0] == 100
def test_rectify_and_rotate_image(left_img, config, outdir):
rectificator = prep.Rectificator(config)
rect_img = rectificator.rectify_image(left_img['img_w_detections'])
rect_detections = rectificator.rectify_points(left_img['detections'],
left_img['size'])
angle = 90
rot_img, rot_mat = prep.rotate_image(rect_img, angle)
rot_detections = prep.rotate_points(rect_detections, angle,
left_img['size'])
marked_img = draw_marks(rot_img, rot_detections)
name_out = ''.join([left_img['name'], '_detections_rectified_rot.jpg'])
out = os.path.join(outdir, name_out)
cv2.imwrite(out, marked_img)
def _prepare_image(self, image, angle=0):
"""Prepare image for stitching.
It rotates and rectifies the image. Ff the Stitcher is initialized with ``rectify=False``
the image will not be rectified.
Args:
image (ndarray): Image to prepare.
angle (int): angle in degree to rotate image.
Returns:
- **image** (ndarray) -- rotated (and rectified) image.
- **affine** (ndarray) -- An affine *(3,3)*--matrix for rotation of image or points.
"""
image = helpers.add_alpha_channel(image)
if self.rectify:
image = self.rectificator.rectify_image(image)
image_rot, affine = prep.rotate_image(image, angle)
return image_rot, affine
def test_rotate_image_specifc(left_img, outdir):
img, mat = prep.rotate_image(left_img['img'], 90)
name_img_rot = ''.join([left_img['name'], '_rotated.jpg'])
out = os.path.join(outdir, name_img_rot)
cv2.imwrite(out, img)