def test_interpol(self):
asm, imgshps = load_incisor()
shape = imgshps[0].shape
image = imgshps[0].image
vecs, tck = shape.get_orthogonal_vectors(with_tck=True)
plot_shape(shape, display=False, overlay_image=image)
plot_vecs(vecs, shape.as_point_list(), display=False)
plot_interpol(tck)
def test_conform_to_rect(self):
s1 = Shape([(-20, 20), (0, 20), (0, -40), (-20, -40)])
bottom_left = Point(0, 0)
top_right = Point(50, 50)
plot_rectangle(bottom_left, top_right, display=False)
s2 = s1.conform_to_rect(bottom_left, top_right)
plot_shape([s1, s2])
npt.assert_equal(s2.axis_means(), np.array([25, 25]))
def test_propose_shape(self):
# Arrange
asm, image_shapes = load_incisor(blur=True, sobel=True)
# Manually fit
bottom_left = Point(1310, 745)
top_right = Point(1410, 1000)
original_imgshp = ImageShape(
image_shapes[0].image,
asm.mean_shape.conform_to_rect(bottom_left, top_right),
)
# Act
imageshape = original_imgshp
for i in range(5):
proposed_shape = asm.propose_shape(imageshape)
matched_shape, *_ = asm.match_target(proposed_shape)
# Assert
plot_image_shape(imageshape, display=False)
plot_shape([proposed_shape, matched_shape])
imageshape = ImageShape(imageshape.image, matched_shape)
def test_get_orthogonal_vectors(self):
round_shape = Shape(
[
(4.5, 1),
(4, 1),
(3.5, 1),
(3, 1),
(2.5, 1.5),
(2, 2),
(1.5, 2.5),
(1, 3),
(1, 3.5),
(1, 4),
(1.5, 4.5),
(2, 5),
(2.5, 5.5),
(3, 6),
(3.5, 6),
(4, 6),
(4.5, 6),
(5, 6),
(5.5, 5.5),
(6, 5),
(6.5, 4.5),
(7, 4),
(7, 3.5),
(7, 3),
(6.5, 2.5),
(6, 2),
(5.5, 1.5),
(5, 1),
]
)
ort_vects = round_shape.get_orthogonal_vectors()
print(ort_vects)
plot_shape(round_shape, display=False)
plot_vecs(ort_vects, round_shape.as_point_list())
s1 = Shape([(1, 2), (1, 3), (1, 4), (2, 4), (3, 4), (3, 3), (3, 2), (2, 2)]) s2 = Shape([(5, 2), (6, 3), (7, 4), (8, 3), (9, 2), (8, 1), (7, 0), (6, 1)]) s3 = Shape([(5, 2), (6, 3), (8, 4), (8, 3), (9, 2), (8, 1), (7, 0), (6, 1)]) s4 = Shape([(5, 2), (6, 3), (6, 4), (8, 3), (9, 2), (8, 1), (7, 0), (6, 1)]) s5 = Shape([(5, 2), (6, 2), (8, 4), (8, 3), (9, 2), (8, 1), (7, 0), (6, 1)]) s6 = Shape([(5, 2), (6, 4), (8, 4), (8, 3), (9, 2), (8, 1), (7, 0), (6, 1)]) se1 = Shape([(1, 1), (2, 1), (3, 1), (3, 2), (3, 3), (2, 3), (1, 3), (1, 2)]) se2 = Shape([(1, 1), (2, 1), (3, 1), (3, 2), (3, 4), (2, 3.5), (1, 3), (1, 2)]) # am = ActiveShapeModel.from_shapes([se1, se2]) # util.plot_shape([se1, se2] + [am.mean_shape] + # [am.create_shape(am.eigenvalues)]) am = ActiveShapeModel.from_shapes([s1, s2, s3, s4, s5, s6]) # Estimated shape 1 es1 = am.match_target(s1) # shapes = [] # for b in np.arange(-0.3 * am.eigenvalues[0], 0.3 * am.eigenvalues[0], # 0.6 * am.eigenvalues[0] / 5): # shape_params = np.zeros(len(am)) # shape_params[0] = b # print(shape_params) # shapes.append(am.create_shape(shape_params)) util.plot_shape([es1, s1]) # s1.get_orthogonal_vectors()
def test_apply_procrustes(self):
asm, image_shapes = load_incisor()
shapes = [imgshp.shape for imgshp in image_shapes]
Shape.apply_procrustes(shapes)
# Shape.translate_all_to_origin(shapes)
plot_shape(shapes, dots=False)