opencv 轮廓特征

# -*-encoding:utf-8-*-
import pytesseract
from PIL import Image
from PIL import ImageFilter
from PIL import ImageFont
from PIL import ImageDraw
import numpy as np
from PIL import Image

import cv2


def main():
    # 计算物体的周长、面积、质心、最小外接矩形等
    # OpenCV函数：cv2.contourArea(), cv2.arcLength(), cv2.approxPolyDP()
    # 等
    # =================================寻找轮廓
    img = cv2.imread('handwriting2.jpg', 0)
    _, thresh = cv2.threshold(img, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
    image, contours, hierarchy = cv2.findContours(thresh, 3, 2)
    # 以数字3的轮廓为例
    cnt = contours[0]

    # =================================轮廓面积
    area = cv2.contourArea(cnt)  # 4386.5
    print("area == " , area)

    # =================================轮廓周长
    perimeter = cv2.arcLength(cnt, True)  # 585.7
    # 参数2表示轮廓是否封闭，显然我们的轮廓是封闭的，所以是True
    print("perimeter == ", perimeter)

    # =================================外接矩形
    # 形状的外接矩形有两种，如下图，绿色的叫外接矩形，表示不考虑旋转并且能包含整个轮廓的矩形。
    x, y, w, h = cv2.boundingRect(cnt)  # 外接矩形
    cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
    # =================================# 最小外接矩形
    rect = cv2.minAreaRect(cnt)  # 最小外接矩形
    print(rect)

    box = np.int0(cv2.boxPoints(rect))  # 矩形的四个角点取整
    cv2.drawContours(img, [box], 0, (255, 0, 0), 2)

    # =================================最小外接圆
    (x, y), radius = cv2.minEnclosingCircle(cnt)
    (x, y, radius) = np.int0((x, y, radius))  # 圆心和半径取整
    cv2.circle(img, (x, y), radius, (0, 0, 255), 2)

    # =================================拟合椭圆
    ellipse = cv2.fitEllipse(cnt)
    cv2.ellipse(img, ellipse, (255, 255, 0), 2)

    # =================================形状匹配
    img2 = cv2.imread('shapes.jpg', 0)
    _, thresh = cv2.threshold(img2, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
    image, contours, hierarchy = cv2.findContours(thresh, 3, 2)
    img_color = cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR)  # 用于绘制的彩色图

    cnt_a, cnt_b, cnt_c = contours[0], contours[1], contours[2]
    print(cv2.matchShapes(cnt_b, cnt_b, 1, 0.0))  # 0.0
    print(cv2.matchShapes(cnt_b, cnt_c, 1, 0.0))  # 2.17e-05
    print(cv2.matchShapes(cnt_b, cnt_a, 1, 0.0))  # 0.418
    # matchShapes(contour1, contour2, method, parameter)
    # 参数3是匹配方法，详情可参考：ShapeMatchModes，参数4是OpenCV的预留参数，暂时没有实现，
    # 形状匹配是通过图像的Hu矩来实现的(cv2.HuMoments())，大家如果感兴趣，

    # # cv2.imshow('thresh', thresh)
    # # cv2.imshow('edges', edges)
    cv2.imshow('img', img)
    cv2.imshow('img2', img2)
    cv2.waitKey(0)


if __name__ == '__main__':
    main()