Approximate objects in a binary image with polygon outline using opencv

mask_to_path.py

import cv2
import matplotlib.patches as mpatches
import copy
import numpy as np
import matplotlib.pyplot as plt

def binary_to_patches(binary_img):
    assert np.unique(binary_img).shape[0] == 2, \
        'Input image must be a binary image'
    contours, _ = cv2.findContours(
        binary_img.astype(np.uint8),
        cv2.RETR_TREE, 
        cv2.CHAIN_APPROX_SIMPLE
    )
    verts = [
        c.reshape(c.shape[0], c.shape[-1])
        for c in contours
    ]
    patches = [
        mpatches.Polygon(p, closed=True, facecolor='none') 
        for p in verts
    ]
    return patches

test_img = np.zeros((200, 400))
test_img[0, 150] = 1
gradient_img = cv2.GaussianBlur(test_img, (0, 0), 50)

steps = np.linspace(gradient_img.min(), gradient_img.max(), num=10)
patches = []
masks = []
for low, high in zip(steps[:-1], steps[1:]):
    mask = np.logical_and(gradient_img >= low, gradient_img < high)
    masks.append(mask)
    patch = binary_to_patches(mask)
    patches.append(patch)

fig, axs = plt.subplots(2, 1)
axs[0].imshow(
    np.sum([idx * m for idx, m in enumerate(masks)], axis=0)
)
axs[1].imshow(gradient_img)
for idx, level in enumerate(patches):
    for p in level:
        cp_p = copy.copy(p)
        color_channel = 1 - (idx / len(patches))
        cp_p.set_edgecolor((color_channel,)*3)
        axs[1].add_patch(cp_p)