Update Python/Classifier.py

Python/Classifier.py

@@ -42,7 +42,7 @@ def Preprocessing(pathOfImage):
     norm_img_data = norm_img_data.reshape(1, 3, 224, 224).astype('float32')
     return norm_img_data
 
-def postprocess(scores):
+def postprocess(scores,pathOfImage):
     '''
     Postprocessing with mxnet gluon
     The function takes scores generated by the network and returns the class IDs in decreasing order
@@ -54,6 +54,9 @@ def postprocess(scores):
     a = np.argsort(preds)[::-1]
     print('class=%s ; probability=%f' %(labels[a[0]],preds[a[0]]))
 
+    text = 'class=%s ' % (labels[a[0]])
+    saveimage(pathOfImage,text)
+
 def ort_seg_dcu(model_path,image):
     
     #创建sess_options
@@ -73,6 +76,17 @@ def ort_seg_dcu(model_path,image):
 
     return scores
 
+def saveimage(pathOfImage,text):
+    iimage = cv2.imread(pathOfImage, cv2.IMREAD_COLOR)
+    font = cv2.FONT_HERSHEY_SIMPLEX
+    font_scale = 0.5
+    font_color = (255, 0, 0)  
+    font_thickness = 1
+    text_position = (5, 10)
+    cv2.putText(iimage, text, text_position, font, font_scale, font_color, font_thickness)
+    cv2.imwrite("./output_image.jpg", iimage)
+    cv2.destroyAllWindows()
+
 if __name__ == '__main__':
     
     pathOfImage ="../Resource/Images/ImageNet_01.jpg"
@@ -83,4 +97,4 @@ if __name__ == '__main__':
     result = ort_seg_dcu(model_path,image)
     
     # 解析分类结果
-    postprocess(result)
+    postprocess(result,pathOfImage)