利用OpenCV识别图片的色调

遍历肯定不行了……

考虑以下思路:

1.给库里每个图片先进行识别颜色并打上标签,如1.jpg色调为红+绿,2.jpg色调为蓝+黄+白

2.对用户上传的图片进行识别并判断颜色标签,再根据颜色标签进行搜索

3.如果有多个搜索结果则再使用一一比对的方法(cv2.matchTemplate)

转自:https://blog.csdn.net/int93/article/details/78954129

1、定义HSV颜色字典,参考网上HSV颜色分类


代码如下:

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])]}
 
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
 
 
if __name__ == '__main__':
    color_dict = getColorList()
    print(color_dict)
 
    num = len(color_dict)
    print('num=',num)
 
    for d in color_dict:
        print('key=',d)
        print('value=',color_dict[d][1])

2、颜色识别

import  cv2
import numpy as np
import colorList
 
filename='car04.jpg'
 
#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 = colorList.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
 
 
if __name__ == '__main__':
    frame = cv2.imread(filename)
    print(get_color(frame))

black
white
red
red2
orange
yellow
green
cyan
blue
purple