RGB通道并不能很好地反映出物体具体的颜色信息 ， 而相对于RGB空间，HSV空间能够非常直观的表达色彩的明暗，色调，以及鲜艳程度，方便进行颜色之间的对比.

python代码：

import numpy as np
import collections


# 定义字典存放颜色分量上下限
# 例如：{颜色: [min分量, max分量]}
# {'red': [array([160,  43,  46]), array([179, 255, 255])]}

# 设置HSV中颜色范围
def getColorList():
    dict = collections.defaultdict(list)

    # # 设置HSV中黑色范围
    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['black'] = 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['gray']=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['white'] = 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['red'] = 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['red2'] = 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['orange'] = 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['yellow'] = 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['green'] = 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['cyan'] = 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['blue'] = 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['purple'] = color_list
    return dict


if __name__ == '__main__':
        answer = []
        frame=cv2.imread("1.jpg")
        # 利用cvtColor()将BGR格式转成HSV格式
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

        for d in self.color_dict:

            # 利用inRange()函数和HSV模型中某种颜色范围的上下界获取mask,mask中原视频中的某种颜色部分会被弄成白色，其他部分黑色。
            mask = cv2.inRange(hsv, self.color_dict[d][0], self.color_dict[d][1])

            # 将mask于原视频帧进行按位与操作，则会把mask中的白色用真实的图像替换
            res = cv2.bitwise_and(frame, frame, mask=mask)
            answer.append([d,res])

         print(answer)