添加检测正常时的输出

handler.py

@@ -52,6 +52,7 @@ class PersonPosture():
                 cv2.line(self.orin_img,tuple(map(int,self.pred[12][:2])),tuple(map(int,self.pred[13][:2])),(0,0,255),thickness=3)
                 print("斜肩")
             # 检查O型腿
+            flag = 0
             if feet_distance != None and knee_distance != None:
                 if feet_distance / knee_distance < 0.8:
                     cv2.line(self.orin_img, tuple(map(int,self.pred[2][:2])), tuple(map(int,self.pred[1][:2])), (0, 0, 255), thickness=3)
@@ -59,6 +60,7 @@ class PersonPosture():
                     cv2.line(self.orin_img, tuple(map(int,self.pred[3][:2])), tuple(map(int,self.pred[4][:2])), (0, 0, 255), thickness=3)
                     cv2.line(self.orin_img, tuple(map(int,self.pred[4][:2])), tuple(map(int,self.pred[5][:2])), (0, 0, 255), thickness=3)
                     print("膝盖间距较大，O形腿")
+                    flag = 1
             # 检查 X型腿
             # 如果两个膝盖和两个脚四个点都检测到了
             if feet_distance!=None and knee_distance!=None:
@@ -69,6 +71,9 @@ class PersonPosture():
                     cv2.line(self.orin_img, tuple(map(int,self.pred[3][:2])), tuple(map(int,self.pred[4][:2])), (0, 0, 255), thickness=3)
                     cv2.line(self.orin_img, tuple(map(int,self.pred[4][:2])), tuple(map(int,self.pred[5][:2])), (0, 0, 255), thickness=3)
                     print("双脚间距较大,X形腿")
+                    flag = 1
+            if flag == 0:
+                print("腿部没有检测到O型腿或X型腿，正常 ")
             # 检查歪头
             if head_slope!=None and abs(head_slope)<CROOKED_HEAD_THRE:
                 cv2.line(self.orin_img, self.pred[8][:2], self.pred[9][:2], (0, 0, 255), thickness=3)
@@ -171,7 +176,7 @@ def main():
             pred.append({'keypoints': ans[i,:,:]})
         return pred
 if __name__ == '__main__':
-    image_path = "data/custom/膝盖超伸2.png"
+    image_path = "data/custom/wenjin正脸.jpg"
     from train import init
     func, config = init()
 
@@ -224,7 +229,7 @@ if __name__ == '__main__':
 
 
     person = PersonPosture(pred,orig_img)
-    orig_img = person.analysis(False)
+    orig_img = person.analysis(True)
     cv2.imshow("test", orig_img)
     cv2.waitKey()
 

readme.md

@@ -12,6 +12,3 @@ yolo5模型目前是调用yolo5项目的restapi获取的，自带的models里面
 
 
 
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