Object_feature_extract_using_OpenCV.py

#https://blog.csdn.net/qq_36699423/article/details/84728238

#!usr/env/bin python3

from math import *
import cv2 as cv
import numpy as np

file = '/Users/apple/Desktop/video/image-1/'
p=file+'data.txt'
#f = open(p, 'a')


def myCut(img, x, y, w, h):
    cut = img[y:y + h, x:x + w]
    cv.imshow("cut", cut)
    return cut


def GetColor(img, point_height, point_width):
    R = 0
    G = 0
    B = 0
    count = 0
    color = []
    for i in range(0, len(point_height), 1):
        count += 1
        R += img[point_height[i], point_width[i]][0]
        G += img[point_height[i], point_width[i]][1]
        B += img[point_height[i], point_width[i]][2]
    R = int(R / count)
    G = int(G / count)
    B = int(B / count)
    color.append(R)
    color.append(G)
    color.append(B)
    return color


# 返回面积
def GetArea(img):
    count = 0
    point_height = []
    point_width = []
    height, width = img.shape
    for h in range(0, height, 1):
        for w in range(0, width, 1):
            if (img[h, w] == 0):
                count += 1
                point_height.append(h)
                point_width.append(w)
    return count, point_width, point_height


# 返回周长
def GetCircumference(img):
    count = 0
    height, width = img.shape
    for h in range(0, height, 1):
        for w in range(0, width, 1):
            if (img[h, w] == 255):
                count += 1
    return count

def edge(img):
    # 灰度图像
    gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)

    # 高斯模糊,降低噪声
    blurred = cv.GaussianBlur(gray, (3, 3), 0)

    # 图像梯度
    xgrad = cv.Sobel(blurred, cv.CV_16SC1, 1, 0)
    ygrad = cv.Sobel(blurred, cv.CV_16SC1, 0, 1)
    # 计算边缘
    # 50和150参数必须符合1：3或者1：2
    edge_output = cv.Canny(xgrad, ygrad, 50, 150)


    cloneImg, contours, heriachy = cv.findContours(edge_output, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)

    # max = 0
    # maxA = 0
    num = []
    for i, contour in enumerate(contours):
        x, y, w, h = cv.boundingRect(contour)
        # if (w * h > maxA):
        #     max = i
        #     maxA = w * h

        if w < 50 or h < 50:
            continue
        num.append(i)

    for i in num:
        # cv.drawContours(img, contours, i, (0, 0, 255), 2)
        # x, y, w, h = cv.boundingRect(contours[i])
        # img = cv.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
        if i == 0:
            continue
        contours[0] = np.concatenate((contours[i], contours[0]))

    cv.imshow('img', img)

    x, y, w, h = cv.boundingRect(contours[0])

    cut_img = myCut(img, x, y, w, h)
    cut_blurred = myCut(blurred, x, y, w, h)
    cv.imshow('cut', cut_blurred)

    ret, binary = cv.threshold(cut_blurred, 70, 255, cv.THRESH_BINARY)
    cv.imshow("bi", binary)  # 求面积

    edge = cv.Canny(binary, 40, 100)
    cv.imshow("edge", edge)  # 求周长

    longth = 0
    width = 0
    if w > h:
        longth = w
        width = h
    else:
        longth = h
        width = w
    area, point_width, point_height = GetArea(binary)
    circumference = GetCircumference(edge)
    color = GetColor(cut_img, point_height, point_width)

    print('area:', area, 'circumference:', circumference, 'longth:', longth, 'width:', width, 'color:', color)
    # f.write(str(area))
    # f.write(' ')
    # f.write(str(circumference))
    # f.write(' ')
    # f.write(str(longth))
    # f.write(' ')
    # f.write(str(width))
    # f.write(' ')
    # for i in range(3):
    #     f.write(str(color[i]))
    #     f.write(' ')
    # f.write('\n')


def do():
    for i in range(1, 8, 1):
        print(i, ':')
        path = file + str(i) + '.jpg'

        src1 = cv.imread(path)

        # 图三（原图）
        size = src1.shape
        src = cv.resize(src1, ((int)(size[1] / 5), (int)(size[0] / 5)), cv.INTER_LINEAR)
        edge(src)
        cv.waitKey(0)

    cv.destroyAllWindows()
    #f.closed()
do()