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:
颜色可以判断出来了,可以做的事情就方便很多了
比如在尽行压力测试时,去判断截图区域是否是黑色,是黑色就停止运行,不是则继续。文章来源:https://www.toymoban.com/news/detail-510286.html
OK!方便易懂,代码可直接用文章来源地址https://www.toymoban.com/news/detail-510286.html
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