Modify model.properties

Signed-off-by: lijian <lijian6@sugon.com>

Python/README.md

@@ -53,11 +53,11 @@ Fine-tuning时可调整epoch参数来调整模型。
 
 | Engine | Model Path| Data | Accuracy(%) |
 | :------: | :------: | :------: | :------: |
-| Pythorch | models/model.onnx | daisy | 98.4 |
-| Pythorch | models/model.onnx | dandelion | 98.2 |
-| Pythorch | models/model.onnx | roses | 90.0 |
-| Pythorch | models/model.onnx | sunflowers | 97.4 |
-| Pythorch | models/model.onnx | tulips | 95.4 |
+| Pytorch | models/model.onnx | daisy | 98.4 |
+| Pytorch | models/model.onnx | dandelion | 98.2 |
+| Pytorch | models/model.onnx | roses | 90.0 |
+| Pytorch | models/model.onnx | sunflowers | 97.4 |
+| Pytorch | models/model.onnx | tulips | 95.4 |
 | MIGraphX | models/model.onnx | daisy | 98.4 |
 | MIGraphX | models/model.onnx | dandelion | 98.8 |
 | MIGraphX | models/model.onnx | roses | 91.3 |

Python/infer_pytroch_migraphx.py

@@ -77,11 +77,11 @@ def main(intputdir):
 
         for i in range(len(predict)):
             if(predict[i].numpy() >= 0.5):
-                print("pythorch class: {:10}   prob: {:.3}".format(class_indict[str(i)], predict[i].numpy()))
+                print("pytorch class: {:10}   prob: {:.3}".format(class_indict[str(i)], predict[i].numpy()))
                 if intputdir.find(class_indict[str(i)]):
                     pytorch_match_cnt += 1
 
-    print("Pythorch Img_cnt: {:<5} match_cnt: {:<5} acc:{:.3}".format(Img_cnt, pytorch_match_cnt, pytorch_match_cnt/Img_cnt))
+    print("Pytorch Img_cnt: {:<5} match_cnt: {:<5} acc:{:.3}".format(Img_cnt, pytorch_match_cnt, pytorch_match_cnt/Img_cnt))
     print("Migraphx Img_cnt: {:<5} match_cnt: {:<5} acc:{:.3}".format(Img_cnt, migraphx_match_cnt, migraphx_match_cnt/Img_cnt))
 
 

model.properties

@@ -3,6 +3,6 @@ modelName=Vision_Transformer
 # 模型描述
 modelDescription=ViT是一个基于transformer的视觉图像分类模型
 # 应用场景(多个标签以英文逗号分割)
-appScenario=训练,推理,train,inference,Pythorch,MIGraphX,图像分类,C++
+appScenario=训练,推理,train,inference,Pytorch,MIGraphX,图像分类,C++
 # 框架类型(多个标签以英文逗号分割)
-frameType=MIGraphX,Pythorch
+frameType=MIGraphX