Ejemplo n.º 1
0
def test_types(img, n_rays, grid):
    mode = "cpp"
    rays = Rays_GoldenSpiral(n_rays)
    gt = star_dist3D(img, rays=rays, grid=grid, mode=mode)
    for dtype in (np.int8, np.int16, np.int32,
                  np.uint8, np.uint16, np.uint32):
        x = star_dist3D(img.astype(dtype), rays=rays, grid=grid, mode=mode)
        print("test_stardist3D (mode {mode}) for shape {img.shape} and type {dtype}".format(mode =mode, img = img, dtype = dtype))
        check_similar(gt, x)
Ejemplo n.º 2
0
def test_cpu_gpu(img, n_rays, grid):
    print(tuple(s//g for s, g in zip(img.shape, grid)))
    rays = Rays_GoldenSpiral(n_rays)
    with Timer(f"stardist {img.shape} {n_rays} rays - CPU"):
        s_cpp = star_dist3D(img, rays=rays, grid=grid, mode="cpp")
    with Timer(f"stardist {img.shape} {n_rays} rays - GPU"):
        s_ocl = star_dist3D(img, rays=rays, grid=grid, mode="opencl")
    check_similar(s_cpp, s_ocl)
    return s_cpp, s_ocl
Ejemplo n.º 3
0
def test_grid(grid,shape):
    ss_grid = tuple(slice(0, None, g) for g in grid)
    
    lbl = circle_image(shape=shape, radius=min(shape)//3)

    rays = Rays_GoldenSpiral(32)
    
    t1 = time()
    d1 = star_dist3D(lbl, rays = rays)
    d1 = d1[ss_grid]
    t1 = time()-t1
    
    t2 = time()
    d2 = star_dist3D(lbl, rays = rays, grid = grid)
    t2 = time()-t2

    print(f"time 1: {1000*t1:.2f}ms")
    print(f"time 2: {1000*t2:.2f}ms")
    assert np.allclose(d1,d2)
    return lbl, d1, d2
Ejemplo n.º 4
0
def test_cpu_gpu(img, n_rays, grid):
    rays = Rays_GoldenSpiral(n_rays)
    s_cpp = star_dist3D(img, rays=rays, grid=grid, mode="cpp")
    s_ocl = star_dist3D(img, rays=rays, grid=grid, mode="opencl")
    check_similar(s_cpp, s_ocl)
Ejemplo n.º 5
0
    mode = "opencl"
    rays = Rays_GoldenSpiral(n_rays)
    gt = star_dist3D(img, rays=rays, grid=grid, mode=mode)
    for dtype in (np.int8, np.int16, np.int32,
                  np.uint8, np.uint16, np.uint32):
        x = star_dist3D(img.astype(dtype), rays=rays, grid=grid, mode=mode)
        print("test_stardist3D (mode {mode}) for shape {img.shape} and type {dtype}".format(mode =mode, img = img, dtype = dtype))
        check_similar(gt, x)


@pytest.mark.gpu
@pytest.mark.parametrize('img', (real_image3d()[1], random_image((33, 44, 55))))
@pytest.mark.parametrize('n_rays', (4, 16, 32))
@pytest.mark.parametrize('grid', ((1,1,1),(1,2,4)))
def test_cpu_gpu(img, n_rays, grid):
    rays = Rays_GoldenSpiral(n_rays)
    s_cpp = star_dist3D(img, rays=rays, grid=grid, mode="cpp")
    s_ocl = star_dist3D(img, rays=rays, grid=grid, mode="opencl")
    check_similar(s_cpp, s_ocl)


if __name__ == '__main__':
    from utils import circle_image

    rays = Rays_GoldenSpiral(4)
    lbl = circle_image((64,) * 3)

    a = star_dist3D(lbl, rays=rays, grid=(1, 2, 2), mode="cpp")
    b = star_dist3D(lbl, rays=rays, grid=(1, 2, 2), mode="opencl")
    print(np.amax(np.abs(a - b)))