Exemplo n.º 1
0
def visualize_direction(seg, segment_id):
    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D

    SUBSAMPLE_TARGET = 500
    MIN_SAMPLE_STRIDE = 10
    BOX_RADIUS = 110

    binary_volume1 = imio.extract_segments(seg, [segment_id])
    all_points_1 = points_from_binary_volume(binary_volume1)
    print all_points_1.shape
    center = random_edge_point(all_points_1, seg)
    binary_volume2 = imio.extract_segments(seg, [seg[tuple(center)]])
    all_points_2 = points_from_binary_volume(binary_volume2)
    stretch_dimension(all_points_1, 0, 5)
    stretch_dimension(all_points_2, 0, 5)

    vectors = features.direction.compute_pc_vectors(
        all_points_1, all_points_2, center, BOX_RADIUS, SUBSAMPLE_TARGET, MIN_SAMPLE_STRIDE
    )
    cropped_points_1 = features.direction.limit_to_radius(
        all_points_1, center, BOX_RADIUS, SUBSAMPLE_TARGET, MIN_SAMPLE_STRIDE
    )
    cropped_points_2 = features.direction.limit_to_radius(
        all_points_2, center, BOX_RADIUS, SUBSAMPLE_TARGET, MIN_SAMPLE_STRIDE
    )
    print "pc vectors:", vectors
    print "feature vector:", features.direction.compute_feature_vector(vectors)
    center_of_1 = cropped_points_1.mean(axis=0)
    center_of_2 = cropped_points_2.mean(axis=0)
    svd_1_points = generate_points_on_vector(vectors[0, :], center_of_1, BOX_RADIUS)
    svd_2_points = generate_points_on_vector(vectors[1, :], center_of_2, BOX_RADIUS)
    between_center_points = generate_points_on_vector(
        vectors[2, :],
        center_of_2,
        np.sqrt((center_of_1 - center_of_2).dot(center_of_1 - center_of_2)).astype(np.integer),
    )

    fig = plt.figure()
    ax = fig.add_subplot(111, projection="3d")
    for points, color, marker in [
        (cropped_points_2, "b", "o"),
        (cropped_points_1, "y", "s"),
        (svd_1_points, "g", "^"),
        (svd_2_points, "r", "v"),
        (between_center_points, "k", "<"),
    ]:
        print points.shape
        ax.scatter(points[:, 2], points[:, 1], points[:, 0], c=color, marker=marker)
    plt.show()
Exemplo n.º 2
0
def view_biggest_cross_section(seg, segment_ids):
    extracted = imio.extract_segments(seg, segment_ids)
    biggest_index = np.argmax(extracted.sum(axis=2).sum(axis=1))
    disp = np.zeros_like(seg)
    disp[biggest_index, :, :] = extracted[biggest_index, :, :]
    mayavi.mlab.contour3d(disp)
    mayavi.mlab.show()
Exemplo n.º 3
0
def view_mistake(seg, gt, target_id, overlap_ids, seg_color_map, gt_color_map):
    fig = mayavi.mlab.gcf()

    # display attempts
    for idx, overlap_id in enumerate(overlap_ids):
        extracted = imio.extract_segments(seg, [overlap_id])
        unsquished = np.repeat(extracted, 5, axis=0)
        color = seg_color_map(idx, len(overlap_ids))
        print "Writing contour with color " + str(color)
        mayavi.mlab.contour3d(unsquished, color=color, figure=fig)

    # display target
    extracted = imio.extract_segments(gt, [target_id])
    unsquished = np.repeat(extracted, 5, axis=0)
    color = gt_color_map(0, 1)
    mayavi.mlab.contour3d(unsquished, color=color, figure=mayavi.mlab.figure())

    mayavi.mlab.show()
Exemplo n.º 4
0
def view_segments(seg, segment_ids):
    fig = maya.mlab.gcf()
    extracted = imio.extract_segments(seg, segment_ids)
    unsquished = np.repeat(extracted, 5, axis=0)
    mayavi.mlab.contour3d(unsquished)
    mayavi.mlab.show()