def cross_entropy_error(y, t):
if y.ndim == 1:
t = t.reshape(1, t.size)
y = y.reshape(1, y.size)
# 教師データ(t)がone-hot-vectorの場合、正解ラベルのインデックスに変換される ⇒ ex) [0,0,1,0,0,0] = [2]
if t.size == y.size:
t = t.argmax(axis=1)
batch_size = y.shape[0]
return -np.sum(np.log(y[np.arange(batch_size), t] + 1e-7)) / batch_size
def depthmap_to_ply(shot, depth, image):
"""Export depthmap points as a PLY string"""
height, width = depth.shape
K = shot.camera.get_K_in_pixel_coordinates(width, height)
R = shot.pose.get_rotation_matrix()
t = shot.pose.translation
y, x = np.mgrid[:height, :width]
v = np.vstack((x.ravel(), y.ravel(), np.ones(width * height)))
camera_coords = depth.reshape((1, -1)) * np.linalg.inv(K).dot(v)
points = R.T.dot(camera_coords - t.reshape(3, 1))
vertices = []
for p, c, d in zip(points.T, image.reshape(-1, 3), depth.reshape(-1, 1)):
if d != 0: # ignore points with zero depth
s = "{} {} {} {} {} {}".format(p[0], p[1], p[2], c[0], c[1], c[2])
vertices.append(s)
return io.points_to_ply_string(vertices)