代码收藏家技术教程 2023-07-16

使用Python进行图像颜色识别

场景：在进行压力测试时，需要判断图片的某一块区域是否是黑色

这里使用的是OpenCV库对图片进行颜色的识别，几乎可以识别所有常见的颜色

直接上代码

import cv2
import numpy as np
import collections


class colorList:
    def getColorList(self):
        dict = collections.defaultdict(list)

        # 黑色
        lower_black = np.array([0, 0, 0])
        upper_black = np.array([180, 255, 46])
        color_list = []
        color_list.append(lower_black)
        color_list.append(upper_black)
        dict['黑色'] = color_list

        # 灰色
        lower_gray = np.array([0, 0, 46])
        upper_gray = np.array([180, 43, 220])
        color_list = []
        color_list.append(lower_gray)
        color_list.append(upper_gray)
        dict['灰色'] = color_list

        # 白色
        lower_white = np.array([0, 0, 221])
        upper_white = np.array([180, 30, 255])
        color_list = []
        color_list.append(lower_white)
        color_list.append(upper_white)
        dict['白色'] = color_list

        # 红色
        lower_red = np.array([156, 43, 46])
        upper_red = np.array([180, 255, 255])
        color_list = []
        color_list.append(lower_red)
        color_list.append(upper_red)
        dict['红色'] = color_list

        # 红色2
        lower_red = np.array([0, 43, 46])
        upper_red = np.array([10, 255, 255])
        color_list = []
        color_list.append(lower_red)
        color_list.append(upper_red)
        dict['红色2'] = color_list

        # 橙色
        lower_orange = np.array([11, 43, 46])
        upper_orange = np.array([25, 255, 255])
        color_list = []
        color_list.append(lower_orange)
        color_list.append(upper_orange)
        dict['橙色'] = color_list

        # 黄色
        lower_yellow = np.array([26, 43, 46])
        upper_yellow = np.array([34, 255, 255])
        color_list = []
        color_list.append(lower_yellow)
        color_list.append(upper_yellow)
        dict['黄色'] = color_list

        # 绿色
        lower_green = np.array([35, 43, 46])
        upper_green = np.array([77, 255, 255])
        color_list = []
        color_list.append(lower_green)
        color_list.append(upper_green)
        dict['绿色'] = color_list

        # 青色
        lower_cyan = np.array([78, 43, 46])
        upper_cyan = np.array([99, 255, 255])
        color_list = []
        color_list.append(lower_cyan)
        color_list.append(upper_cyan)
        dict['青色'] = color_list

        # 蓝色
        lower_blue = np.array([100, 43, 46])
        upper_blue = np.array([124, 255, 255])
        color_list = []
        color_list.append(lower_blue)
        color_list.append(upper_blue)
        dict['蓝色'] = color_list

        # 紫色
        lower_purple = np.array([125, 43, 46])
        upper_purple = np.array([155, 255, 255])
        color_list = []
        color_list.append(lower_purple)
        color_list.append(upper_purple)
        dict['紫色'] = color_list

        return dict

    # 处理图片
    def get_color(self):
        print('颜色对比')
        img = cv2.imread('D:\sdcard\XiaLa.png')
        hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
        maxsum = -100
        color = None
        color_dict = colorList().getColorList()
        for d in color_dict:
            mask = cv2.inRange(hsv, color_dict[d][0], color_dict[d][1])
            binary = cv2.threshold(mask, 127, 255, cv2.THRESH_BINARY)[1]
            binary = cv2.dilate(binary, None, iterations=2)
            img, cnts = cv2.findContours(binary.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
            sum = 0
            for c in img:
                sum += cv2.contourArea(c)
            if sum > maxsum:
                maxsum = sum
                color = d
        return color


if __name__ == '__main__':
    print(colorList().get_color())

运行结果如下：