图像识别相关

1、airtest项目：airtest、poco；地址： https://github.com/AirtestProject

** pip install -U airtest

** 使用

from airtest.core.api import *
 
# connect an android phone with adb
init_device("Android")
# or use connect_device api
# connect_device("Android:///")
 
install("path/to/your/apk")
start_app("package_name_of_your_apk")
touch(Template("image_of_a_button.png"))
swipe(Template("slide_start.png"), Template("slide_end.png"))
assert_exists(Template("success.png"))
keyevent("BACK")
home()
uninstall("package_name_of_your_apk")

2、图像识别：形状+颜色：https://blog.csdn.net/zgr957254329/article/details/123891504

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

import collections
import math
 
import cv2
import matplotlib.pyplot as plt
import numpy as np
 
 
#颜色字典
def ColorList():
    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
  
    #粉色
    lower_pink = np.array([156, 43, 46])
    upper_pink = np.array([180, 255, 255])
    color_list = []
    color_list.append(lower_pink)
    color_list.append(upper_pink)
    dict['pink']=color_list
  
    #红色
    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['red'] = 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
 
#颜色判断
def findColor(imgcut):
    img_hsv=cv2.cvtColor(imgcut,cv2.COLOR_BGR2HSV)
    color_dict=ColorList()
    #print(color_dict)
    color_most=0
    color_now=None
    for color in color_dict:
        #二值化 和颜色字典比较 在上下限之间的像素变为255，之外的所有像素变为0
        color_cmp=cv2.inRange(img_hsv,color_dict[color][0],color_dict[color][1])
        #膨胀 使颜色分割成块并更突出
        color_boom = cv2.dilate(color_cmp,None,iterations=1)
        #取出每一小块
        contours,hierarchy=cv2.findContours(color_boom.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
        color_area=0
        for img in contours:
            color_area+=cv2.contourArea(img)
        if(color_area>color_most):
            color_most=color_area
            color_now=color
    return color_now
 
#计算斜率
def k_count(x1,y1,x2,y2):
    if((x2-x1)==0):
        x2+=0.01
    k=(y2-y1)/(x2-x1)
    if (k==0):
        k+=0.01
    return k
 
#计算角度
def angle_count(k1,k2):
    angle=math.atan2((k2-k1),(1+k1*k2))
    angle=angle*180/math.pi
    return abs(angle)
 
#图形处理
def LastButNotLeast(imginit,imgcopy):
    # 灰度化
    img_Gray = cv2.cvtColor(imginit, cv2.COLOR_BGR2GRAY)
    # 高斯平滑
    img_Blur = cv2.GaussianBlur(img_Gray, (3, 3), 1)
    # 边缘检测
    img_Canny = cv2.Canny(img_Blur, 50, 50)
    #得到图片中所有图形的轮廓
    #findContours(image, mode, method[, contours[, hierarchy[, offset]]]) -> contours, hierarchy
    contours,hierarchy=cv2.findContours(img_Canny,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
    #参数：输入图像，霍夫梯度法，分辨率，最小距离，检测方法的对应的参数*2，半径
    for img in contours:    
        #计算面积 太小就不算了
        area=cv2.contourArea(img)
        if area>80:
            perimeter=cv2.arcLength(img,True)
            #折线化
            side=cv2.approxPolyDP(img,0.01*perimeter,True)
            #print(side)
            #计算有几条线
            sideNum=len(side)
            #print(sideNum)
            #计算边长
            length=[]
            k=[]
            for i in range(0,sideNum):
                if(i+1<sideNum):                
                    l=((side[i][0][0]-side[i+1][0][0])**2+(side[i][0][1]-side[i+1][0][1])**2)**(1/2)
                    ktemp=k_count(side[i][0][0],side[i][0][1],side[i+1][0][0],side[i+1][0][1])
                else:
                    l=((side[i][0][0]-side[0][0][0])**2+(side[i][0][1]-side[0][0][1])**2)**(1/2)
                    ktemp=k_count(side[i][0][0],side[i][0][1],side[0][0][0],side[0][0][1])
                length.append(l)
                k.append(ktemp)
            #print(length)
            #计算角度
            angle=[]
            for i in range(0,sideNum):
                if(i+1<sideNum):
                    ang=angle_count(k[i],k[i+1])
                else:
                    ang=angle_count(k[i],k[0])
                angle.append(ang)
            #print(angle)
            #形状判断
            #三角形
            if sideNum==3:
                tag="triangle"
            #其他四边形
            elif sideNum==4:
                tag="Other quadrilateral"
                flag=0
                #菱形
                err=5
                if(length[1]-err<=length[0]<=length[1]+err):
                    if(length[2]-err<=length[1]<=length[2]+err):
                        if(length[3]-err<=length[2]<=length[3]+err):
                            if(length[0]-err<=length[3]<=length[0]+err):
                                tag="diamond"
                                flag=1
                #矩形
                if(89<angle[0]<91):
                    if(89<angle[1]<91):
                        if(89<angle[2]<91):
                            if(89<angle[3]<91):
                                tag="rectangular"
                                if(flag==1):
                                    tag="square"
            elif sideNum==5:
                tag="pentagon"
            elif sideNum==6:
                tag="hexagon"
            elif sideNum==10:
                tag="five-pointed star"
            elif sideNum>10:
                tag="circle"
            else:
                tag="None"               
            #定个位
            x,y,wide,high=cv2.boundingRect(side)
            #裁剪中心位置
            x0=int(x+(wide/2))
            y0=int(y+(high/2))
            err=25
            imgCut=imginit[(y0-err):(y0+err),(x0-err):(x0+err)]
            color=findColor(imgCut)
            #添加标签
            cv2.rectangle(imgcopy, (x-5, y-5), (x + wide+5, y + high+5), (0, 235, 6), 2)
            cv2.putText(imgcopy, tag,(x, y-28), cv2.FONT_HERSHEY_TRIPLEX, 0.85,(0,0, 255), 1)
            cv2.putText(imgcopy, color,(x, y-5), cv2.FONT_HERSHEY_TRIPLEX, 0.85,(0, 0, 255), 1)
 
if __name__ == "__main__":
    path=input("图片路径：")
    #path=r"D:\test.png"
    img = cv2.imread(path)
    while(np.all(img==None)):
        print("无法读取图片")
        path=input("图片路径：")
        img = cv2.imread(path)
    img_Copy=img.copy()
     
    #图像处理函数
    LastButNotLeast(img,img_Copy)
 
    #输出结果
    plt.subplot(1,2,1)
    img=cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
    plt.imshow(img)
    plt.title("The original image")
 
    plt.subplot(1,2,2)
    img_Copy=cv2.cvtColor(img_Copy,cv2.COLOR_BGR2RGB)
    plt.imshow(img_Copy)
    plt.title("The image after processing")
 
    plt.show()