def show_results():
piece = fm.load_img_piece()
edge_img = prep.canny(piece)
tooth = fm.load_tooth_of_piece(2)
fm.show_with_points(edge_img, tooth)
new_tooth = active_contour(tooth, edge_img, 25, 1)
fm.show_with_points(edge_img, new_tooth)
def preperation_all(radiograph, all_landmarks):
#median = prep.median_filter(radiograph)
# edge_img = prep.edge_detection_low(median)
edge_img = prep.calc_external_img_active_contour(radiograph)
pcas_tooth = PCA.PCA_analysis_all(all_landmarks, None)
return edge_img, pcas_tooth
def active_shape_scale(img, tooth_points, pca_tooth, length, scale):
scaled_img, scaled_tooth_points = scaling(img, tooth_points, 1 / scale)
edge_img = prep.calc_external_img_active_contour(scaled_img)
new_points = active_shape(edge_img, scaled_tooth_points, pca_tooth, length)
new_img, new_scaled_points = scaling(scaled_img, new_points, scale)
return new_scaled_points
def preperation(radiograph, tooth_variations):
#median = prep.median_filter(radiograph)
# edge_img = prep.edge_detection_low(median)
edge_img = prep.calc_external_img_active_contour(radiograph)
pca_tooth = PCA.PCA_analysis(tooth_variations, None)
return edge_img, pca_tooth
def show_results_fitting():
piece = fm.load_img_piece()
edge_img = prep.canny(piece)
tooth = fm.load_tooth_of_piece(0)
new_points_list, total_error = fit_measure(tooth, 25, edge_img)
for i in range(7):
tooth = fm.load_tooth_of_piece(i + 1)
new_points, total_error = fit_measure(tooth, 25, edge_img)
new_points_list = np.append(new_points_list, new_points)
fm.show_with_points(edge_img, new_points_list.reshape(-1, 2))
def run(img, centroid):
# --------------- TESTING ----------------- #
idge_canny = prep.calc_external_img_active_contour(img)
edge_sobel = prep.sobel(img)
testimage, testlandmarks = test_set
test = Shape(testlandmarks)
pose_para = aligner.get_pose_parameters(pca.mean, test)
lst = list(pose_para)
lst[0] = 0
lst[1] = 0
lst[2] = pose_para[2]
lst[3] = 0
t = tuple(lst)
points = aligner.transform(pca.mean, t)
plt.imshow(img)
plt.plot(points.x, points.y, "r.")
meanShapeCentroid = (np.sum(points.x) / 30, np.sum(points.y) / 30)
#perform manual centroid
# centroid= tran.set_clicked_center(np.uint8(testimage))
matches1 = tran.initalizeShape(centroid, meanShapeCentroid,
points.matrix.T)
if not isinstance(matches1, Shape):
matches1 = Shape(matches1.T)
# meanShapeCentroid = (np.sum(testlandmarks.x)/30,np.sum(testlandmarks.y)/30)
plt.imshow(img)
plt.plot(matches1.x, matches1.y, '.')
plt.show()
x, y, new_p = active_shape(edge_sobel, matches1, pca, img, centroid)
return y
def active_shape_scale_n_times(img, tooth_points, pca_tooth, length, scale,
n_times):
points = [0] * (n_times + 1)
points[0] = tooth_points
scaled_img, scaled_tooth_points = scaling(img, tooth_points, 1 / scale)
edge_img = prep.calc_external_img_active_contour(scaled_img)
new_points = active_shape(edge_img, scaled_tooth_points, pca_tooth, length)
for i in range(n_times):
new_points = active_shape(edge_img, new_points, pca_tooth, length)
points[i + 1] = np.around(new_points * scale)
return points
def test_normal_on_edge():
piece = fm.load_img_piece()
new_pice = piece[300:450, 100:250]
tooth = fm.load_tooth_of_piece()
points = tooth
fm.show_with_points(piece, points)
new_points = np.copy(points)
new_points[:, 0] = points[:, 0] - 100
new_points[:, 1] = points[:, 1] - 300
a, b, c = new_points[0:3]
rad = get_normal_angle(a, b, c)
p1 = get_point_at_distance(b, 20, rad)
p2 = get_point_at_distance(b, -20, rad)
img_copy = new_pice.copy()
p1 = np.array(p1, dtype=int)
p2 = np.array(p2, dtype=int)
make_line(img_copy, p1, p2)
visualize_points = new_points.take([38, 39, 0, 1, 2, 3], axis=0)
proj = project_on(b, a, c)
visualize_points = np.append(visualize_points, proj).reshape(-1, 2)
show_with_points(img_copy, visualize_points)
edges = get_points_on_angle_normal(b, rad, 20)
edge_img = prep.edge_detection_high(new_pice)
strength = edge_strength_at_points(edges, edge_img)
show_with_points(new_pice, edges)
fig, ax = plt.subplots(figsize=(7, 7))
plt.plot(np.arange(-20, 21), strength)
plt.show()
def pre_pocess(img):
median = prep.median_filter(img)
contrast = prep.contrast_stretching(median)
return contrast
img_copy = new_pice.copy()
p1 = np.array(p1, dtype=int)
p2 = np.array(p2, dtype=int)
make_line(img_copy, p1, p2)
visualize_points = new_points.take([38, 39, 0, 1, 2, 3, 4, 5], axis=0)
proj = project_on(b, a, c)
#new_visualize_points = np.append(visualize_points,proj).reshape(-1,2)
show_with_points(img_copy, visualize_points)
edges = get_points_on_angle_normal(b, rad, 20)
#edge_img = prep.sobel(new_pice)
edge_img = prep.canny(new_pice)
strength = edge_strength_at_points(edges, edge_img)
#show_with_points(new_pice,np.append(edges,visualize_points).reshape(-1,2))
fig, ax = plt.subplots(figsize=(7, 7))
plt.plot(np.arange(-20, 21), strength)
plt.show()
p = strongest_edge_point_on_normal(a, b, c, 20, edge_img)
show_with_points(edge_img, np.append(visualize_points, p).reshape(-1, 2))
show_results_fitting()
# piece = prep.median_filter(piece)
# edge_img = prep.edge_detection_high(piece)
# show_with_points(edge_img, points)
def calc_external_img2(img):
median = prep.median_filter(img)
edges = prep.edge_detection_low(median)
return -edges
tooth = fm.load_tooth_of_piece(2)
fm.show_with_points(edge_img, tooth)
new_tooth = active_contour(tooth, edge_img, 25, 1)
fm.show_with_points(edge_img, new_tooth)
def show_influence_ext_int():
new_piece, new_tooth = piece, tooth
mean = calc_mean(new_tooth)
ext = calc_external_img(new_piece)
fm.show_with_points(ext, new_tooth[0:2])
print(calc_external(new_tooth[0],ext))
print(calc_internal(new_tooth[0], new_tooth[1], mean))
print(calc_energy(new_tooth[0],new_tooth[1],ext,mean,10))
# In[ ]:
if __name__ == "__main__":
piece = fm.load_img_piece()
tooth = fm.load_tooth_of_piece()
ext = prep.calc_external_img_active_contour(piece)
fm.show_with_points(ext, tooth)
ext2, stooth = fm.resolution_scale(ext, tooth, 1/6)
fm.show_with_points(ext2, stooth)