def apply_double_mesh(matrix, mesh):
shape = matrix.shape
if len(shape) > 2:
out = np.zeros(shape, dtype=np.int16)
for i in range(shape[2]):
out[:, :,
i] = apply_double_mesh_one_dimension(matrix[:, :, i], mesh)
return actions.linear_transform(out).astype(np.uint8)
else:
return actions.linear_transform(
apply_double_mesh_one_dimension(matrix, mesh)).astype(np.uint8)
def harris(matrix, threshold):
if len(matrix.shape) == 3:
matrix_to_op = actions.to_grayscale(matrix)
else:
matrix_to_op = matrix
dx = sp.signal.convolve2d(matrix_to_op,
sobel_matrix,
boundary='symm',
mode='same')
dy = sp.signal.convolve2d(matrix_to_op,
np.transpose(sobel_matrix),
boundary='symm',
mode='same')
gm = mesh.gauss_mesh(7, 2)
dx2 = sp.signal.convolve2d(np.power(dx, 2),
gm,
boundary='symm',
mode='same')
dy2 = sp.signal.convolve2d(np.power(dy, 2),
gm,
boundary='symm',
mode='same')
lxy = sp.signal.convolve2d(np.multiply(dx, dy),
gm,
boundary='symm',
mode='same')
k = 0.04
res = (np.multiply(dx2, dy2) -
np.power(lxy, 2)) - k * np.power(np.add(dx2, dy2), 2)
res = actions.linear_transform(res)
return combine(matrix, thresholds.threshold(res, threshold))
def multi_sobel(matrix):
m1 = np.array([[-1, -2, -1], [0, 0, 0], [1, 2, 1]])
out1 = mesh.apply_mesh_one_dimension(matrix, m1, 3)
m2 = m1.transpose()
out2 = mesh.apply_mesh_one_dimension(matrix, m2, 3)
m3 = np.array([[-2, -1, 0], [-1, 0, 1], [0, 1, 2]])
out3 = mesh.apply_mesh_one_dimension(matrix, m3, 3)
m4 = m3.transpose()
out4 = mesh.apply_mesh_one_dimension(matrix, m4, 3)
out = np.zeros(matrix.shape, dtype=np.int16)
for i in range(matrix.shape[0]):
for j in range(matrix.shape[1]):
out[i, j] = max(abs(out1[i, j]), abs(out2[i, j]), abs(out3[i, j]),
abs(out4[i, j]))
return actions.linear_transform(out).astype(np.uint8)
def save(self, event):
filename = filedialog.asksaveasfilename(parent=root)
image = Image.fromarray(
actions.linear_transform(np.array(self.true_image)))
image.save(filename)
print(filename)