使用 opencv 进行图片颜色识别

场景：在长城证券 POC 测试中在机器人点击某个节点的图标之前，需要判断图标的颜色是否是绿色！目前我们的组件不支持颜色识别，但是想到在运行中支持截图，并且可以自定义函数，然后用 opencv 库就行对图片颜色的识别，代码如下：

import numpy as np 
import collections
import cv2

def getColorList():

    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['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


# 处理图片
def get_color(frame):
    print('go in get_color')
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    maxsum = -100
    color = None
    color_dict = getColorList()
    for d in color_dict:
        mask = cv2.inRange(hsv, color_dict[d][0], color_dict[d][1])
        cv2.imwrite(d + '.jpg', mask)
        binary = cv2.threshold(mask, 127, 255, cv2.THRESH_BINARY)[1]
        binary = cv2.dilate(binary, None, iterations=2)
        img, cnts, hiera = cv2.findContours(binary.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        sum = 0
        for c in cnts:
            sum += cv2.contourArea(c)
        if sum > maxsum:
            maxsum = sum
            color = d
    return color


def color(filename):
    '''
    :param filename: 图片路径
    :return: 图片颜色
    '''
    frame = cv2.imread(filename)
    c = get_color(frame)
    return c

流程中需要一定时间去截图在进行颜色判断和刷新