コード例 #1
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def test_no_motion_3d():
    rnd = np.random.RandomState(0)
    img = rnd.normal(size=(64, 64, 64))
    img = cp.asarray(img)

    flow = optical_flow_ilk(img, img)

    assert cp.all(flow == 0)
コード例 #2
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def test_optical_flow_dtype():
    # Generate synthetic data
    rnd = np.random.RandomState(0)
    image0 = rnd.normal(size=(256, 256))
    image0 = cp.asarray(image0)
    gt_flow, image1 = _sin_flow_gen(image0)
    # Estimate the flow at double precision
    flow_f64 = optical_flow_ilk(image0, image1, dtype='float64')

    assert flow_f64.dtype == 'float64'

    # Estimate the flow at single precision
    flow_f32 = optical_flow_ilk(image0, image1, dtype='float32')

    assert flow_f32.dtype == 'float32'

    # Assert that floating point precision does not affect the quality
    # of the estimated flow

    assert cp.abs(flow_f64 - flow_f32).mean() < 1e-3
コード例 #3
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def test_3d_motion(gaussian, prefilter):
    # Generate synthetic data
    rnd = np.random.RandomState(0)
    image0 = rnd.normal(size=(50, 55, 60))
    image0 = cp.asarray(image0)
    gt_flow, image1 = _sin_flow_gen(image0, npics=3)
    # Estimate the flow
    flow = optical_flow_ilk(image0,
                            image1,
                            radius=5,
                            gaussian=gaussian,
                            prefilter=prefilter)

    # Assert that the average absolute error is less then half a pixel
    assert abs(flow - gt_flow).mean() < 0.5
コード例 #4
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def test_2d_motion(dtype, gaussian, prefilter):
    # Generate synthetic data
    rnd = np.random.RandomState(0)
    image0 = rnd.normal(size=(256, 256))
    image0 = cp.asarray(image0, dtype=dtype)
    gt_flow, image1 = _sin_flow_gen(image0)
    image1 = image1.astype(dtype, copy=False)
    # Estimate the flow
    flow = optical_flow_ilk(image0,
                            image1,
                            gaussian=gaussian,
                            prefilter=prefilter,
                            dtype=dtype)
    assert flow.dtype == dtype
    # Assert that the average absolute error is less then half a pixel
    assert abs(flow - gt_flow).mean() < 0.5
コード例 #5
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def test_wrong_dtype():
    rnd = cp.random.RandomState(0)
    img = rnd.normal(size=(256, 256))
    with testing.raises(ValueError):
        u, v = optical_flow_ilk(img, img, dtype='int')
コード例 #6
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def test_incompatible_shapes():
    rnd = cp.random.RandomState(0)
    I0 = rnd.normal(size=(256, 256))
    I1 = rnd.normal(size=(255, 256))
    with testing.raises(ValueError):
        u, v = optical_flow_ilk(I0, I1)