【OpenCV入门学习--python】凸包算法(convex hull)_python convexhull

例子源于OpenCV官网–凸包算法(convex hull)
（https://docs.opencv.org/4.x/d7/d1d/tutorial_hull.html）

代码：

#通俗的说就是：一组平面上的点，求一个包含所有点的最小凸多边形，这个最小凸多边形就是凸包。
from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse
import random as rng
rng.seed(12345)
def thresh_callback(val):
    threshold = val
    # Detect edges using Canny。使用Canny检测边缘
    canny_output = cv.Canny(src_gray, threshold, threshold * 2)
    # Find contours。找到轮廓
    contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
    # Find the convex hull object for each contour。找出每个轮廓的凸包对象
    hull_list = []
    for i in range(len(contours)):
        hull = cv.convexHull(contours[i])
        hull_list.append(hull)
    # Draw contours + hull results。绘制轮廓
    drawing = np.zeros((canny_output.shape[0], canny_output.shape[1], 3), dtype=np.uint8)
    for i in range(len(contours)):
        color = (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256))
        cv.drawContours(drawing, contours, i, color)
        cv.drawContours(drawing, hull_list, i, color)
    # Show in a window
    cv.imshow('Contours', drawing)
# Load source image
parser = argparse.ArgumentParser(description='Code for Convex Hull tutorial.')
parser.add_argument('--input', help='Path to input image.', default='Base_0.png')
args = parser.parse_args()
src = cv.imread(cv.samples.findFile(args.input))
if src is None:
    print('Could not open or find the image:', args.input)
    exit(0)
# Convert image to gray and blur it。转换图像到灰色并且模糊它
src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
src_gray = cv.blur(src_gray, (3,3))
# Create Window
source_window = 'Source'
cv.namedWindow(source_window)
cv.imshow(source_window, src)
max_thresh = 255
thresh = 100 # initial threshold
cv.createTrackbar('Canny thresh:', source_window, thresh, max_thresh, thresh_callback)
thresh_callback(thresh)
cv.waitKey()
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原图：

运行结果：