new

CascadeClassifier.py

@@ -13,21 +13,87 @@ def detecvFace(self,img):
                     gray,
                     scaleFactor=1.1,
                     minNeighbors=5,
-                    minSize=(30, 30)
+                    minSize=(20, 20)
                     )
         return faces
 
-    def detecvFaceImgOne(self,img): #return one
+    def getNewLocFromDetection(self,centerX,centerY,img,reSize=None):       
+        newW = reSize[0]
+        newH = reSize[1]
+        H,W = img.shape[0],img.shape[1]
+        if newW>W:
+            newW = W
+        if newH>H:
+            newH = H 
+
+        newX = int(centerX-newW/2)
+        newY = int(centerY-newH/2)
+        if newX<0:
+            newX = 0
+        if newY<0:
+            newY = 0
+        return newX,newY,newW,newH
+    '''
+    def getNewLocFromDetection(self,x,y,w,h,img,reSize=None):
+        if reSize is None:
+            return x,y,w,h
+        
+        centerX = int(x + w/2)
+        centerY = int(y + h/2)
+        
+        newW = reSize[0]
+        newH = reSize[1]
+        H,W = img.shape[0],img.shape[1]
+        if newW>W:
+            newW = W
+        if newH>H:
+            newH = H 
+        
+        newX = int(centerX-newW/2)
+        newY = int(centerY-newH/2)
+        if newX<0:
+            newX = 0
+        if newY<0:
+            newY = 0
+        return newX,newY,newW,newH
+        '''
+
+    def detecvFaceImgOne(self,img,reSize=None): #return one
         faces = self.detecvFace(img)
-        if len(faces)>0:
-            (x, y, w, h) = faces[-1]
+        for (x, y, w, h) in faces:
             #return img[x:x+w,y:y+h]
-            return img[y:y+h,x:x+w]
+            #print(x, y, w, h)
+            if reSize is None:
+                return img[y:y+h,x:x+w]
+            else:
+                centerX = int(x + w/2)
+                centerY = int(y + h/2)
+                #print('center=',centerX,centerY)
+                newX,newY,newW,newH = self.getNewLocFromDetection(centerX,centerY,img,reSize)    
+                #print('changesize=',newW,newH,reSize[0],reSize[1])              
+                return img[newY:newY+newH, newX:newX+newW]
+
+        print('Warning!,No detection of face!')
         return None
-        # for (x, y, w, h) in faces:
-        #     print(x,y,w,h)
-        #     #return img[x:x+w,y:y+h].copy()
-        #     return img[x:x+w,y:y+h]
+
+    def getDetectImg(self,image,reSize=None):
+        faces = self.detecvFace(image)
+        #print("Found {0} faces!".format(len(faces)))
+        newImg = image.copy() 
+        for (x, y, w, h) in faces:
+            print(x, y, w, h)
+            if reSize is None:
+                cv2.rectangle(newImg, (x, y), (x+w, y+h), (0, 255, 0), 2)
+            else:
+                #cv2.rectangle(newImg, (x, y), (x+w, y+h), (255, 255, 0), 2)
+
+                centerX = int(x + w/2)
+                centerY = int(y + h/2)
+                print('center=',centerX,centerY)
+                x,y,w,h = self.getNewLocFromDetection(centerX,centerY,newImg,reSize)
+                cv2.rectangle(newImg, (x, y), (x+w, y+h), (0, 255, 0), 2)
+            break
+        return newImg
 
     def detecvFaceImgs(self,img): #return one
         faces = self.detecvFace(img)
@@ -36,16 +102,6 @@ def detecvFaceImgs(self,img): #return one
             imgList.append(img[x:x+w,y:y+h].copy())
         return imgList
 
-    def getDetectImg(self,image):
-        faces = self.detecvFace(image)
-        #print("Found {0} faces!".format(len(faces)))
-        newImg = image.copy() 
-        for (x, y, w, h) in faces:
-            #print(x, y, w, h)
-            cv2.rectangle(newImg, (x, y), (x+w, y+h), (0, 255, 0), 2)
-
-        return newImg
-
     def showDetectImg(self,image):
         faces = self.detecvFace(image)
         #print("Found {0} faces!".format(len(faces)))

commonModule/imagePlot.py

@@ -62,6 +62,7 @@ def plotImagList(imgList,nameList,gray=False,showTitle=True,showticks=True):
             ax.set_yticks([])
             ax.set_xticks([])
 
+        ax.set_aspect('equal')
         #ax.margins(0, 0) 
         #ax.xaxis.set_major_locator(plt.NullLocator())
         #ax.yaxis.set_major_locator(plt.NullLocator())

faceIdentification.py

@@ -21,7 +21,7 @@ def CascadeDetect(cascPath=r'./res/haarcascade_frontalface_default.xml'):
 
 def main():
     cv2.useOptimized()
-    file =  r'./res/trump.jpg'#r'./res/Lenna.png' #obama.jpg
+    file =  r'./res/trump.jpg'##obama.jpg #r'./res/Lenna.png'  #
 
     print('Number of parameter:', len(sys.argv))
     print('Parameters:', str(sys.argv))
@@ -32,25 +32,26 @@ def main():
     img = loadImg(file,mode=cv2.IMREAD_COLOR) # IMREAD_GRAYSCALE IMREAD_COLOR
 
     faceROI = CascadeDetect()
-    faceR=faceROI.getDetectImg(img)
-    face = faceROI.detecvFaceImgOne(img)
+    faceR=faceROI.getDetectImg(img) #reSize=(newW,newH)
+    #print('faceR.shape=',faceR.shape)
+    face = faceROI.detecvFaceImgOne(img.copy()) #reSize=(newW,newH)
     faceGray = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
 
     img = changeBgr2Rbg(img)
     faceR = changeBgr2Rbg(faceR)
-    #face = changeBgr2Rbg(face)
-    #faceGray = changeBgr2Rbg(faceGray)
+    face = changeBgr2Rbg(face)
+    faceGray = changeBgr2Rbg(faceGray)
 
     ls,names = [],[]
     ls.append(img),names.append('orignal')
     ls.append(faceR),names.append('faceR')
     ls.append(face),names.append('face')
     ls.append(faceGray),names.append('faceGray')
 
-    plotImagList(ls,names)
+    plotImagList(ls,names,showTitle=False,showticks=True)
 
     #faceGray = resizeImg(faceGray,newW,newH)
-    writeImg(face,'./res/myface_.png')
+    writeImg(face,'./res/Lenna1.png')
     #writeImg(faceGray,'./res/myface_gray.png')
 
 if __name__=="__main__":

makeDB.py

@@ -22,12 +22,13 @@ def UpdatePtsToLocation(pts,H,W):
         pts[i][1] = pts[i][1]*H
     return pts
 
-def calculateFeature(pts,H,W,file=r'test.pts'):
+def calculateFeature(pts,H,W,file=r'./res/test.pts'):
     pts = UpdatePtsToLocation(pts,H,W)
 
     #print(pts)
 
-    writeAnotationFile(file,pts)
+    #writeAnotationFile(file,pts)
+
     pts = np.array(pts)
     #print(pts.shape)
 

predictPerson.py

@@ -48,7 +48,7 @@ def main():
 
     showimage(testFaceLabelPts(img,pts,locCod=False))
     if 1:
-        feature = np.array(calculateFeature(pts,H,W,'predict.pts'))
+        feature = np.array(calculateFeature(pts,H,W,r'./res/predict.pts'))
     else:
         feature = pts.reshape(1,136)
     print('feature=',len(feature),feature)

testLabel.py

@@ -113,8 +113,8 @@ def showPredictImage():
     plotImagList(imgList,nameList,showticks=False,showTitle=False)
 
 def showPredictOutdatasetImage():
-    file1 = r'.\res\\' + 'Lenna.png'
-    file2 = r'.\res\\' + 'obama.png' #obama.png
+    file1 = r'.\res\\' + 'anna.png'
+    file2 = r'.\res\\' + 'trump.png' #obama.png
 
     predictImg1 = testFaceLabelPredict(file1)   
     predictImg2 = testFaceLabelPredict(file2)