958f8f41da4f00c2e9c8d1be0616fcc59c5ee3f0,doc/examples/edges/plot_random_shapes.py,,,#,15

Before Change

figure = plt.figure(figsize=(10, 10))

for n, i in enumerate([image, image2, image3, image4]):
    axis = plt.subplot(2, 2, n + 1)
    axis.tick_params(bottom="off", top="off", left="off", right="off")
    axis.set_xticklabels([])
    axis.set_yticklabels([])
    plt.imshow(i)

After Change

image4, _ = random_shapes((128, 128), max_shapes=10, min_pixel_intensity=0)

fig, axes = plt.subplots(2, 2, figsize=(10, 10))
for ax, image in zip(axes.ravel(), [image1, image2, image3, image4]):
    ax.imshow(image)
    ax.set_axis_off()

// These shapes are well suited to test segmentation algorithms. Often, we want
// shapes to overlap to test the algorithm. This is also possible:
image, _ = random_shapes(
    (128, 128), min_shapes=5, max_shapes=10, min_size=20, allow_overlap=True)
fig, axis = plt.subplots()
axis.imshow(image)

Instances