修改input/output代码

Python/PaddleOCR_infer_migraphx.py

@@ -296,9 +296,20 @@ class det_rec_functions(object):
         # 解析检测模型
         detInput = {"x":[1,3,2496,2496]}
         self.modelDet = migraphx.parse_onnx(self.det_file, map_input_dims=detInput)
-        self.inputName = self.modelDet.get_parameter_names()[0]
-        self.inputShape = self.modelDet.get_parameter_shapes()[self.inputName].lens()
 
+        # 获取模型输入/输出节点信息
+        print("det_inputs:")
+        inputs_det = self.modelDet.get_inputs()
+        for key,value in inputs_det.items():
+            print("{}:{}".format(key,value))
+
+        print("det_outputs:")
+        outputs_det = self.modelDet.get_outputs()
+        for key,value in outputs_det.items():
+            print("{}:{}".format(key,value))
+
+        self.inputName = self.modelDet.get_parameter_names()[0]
+        self.inputShape = inputs_det[self.inputName].lens()
         print("DB inputName:{0} \nDB inputShape:{1}".format(self.inputName, self.inputShape))
 
         # 模型编译
@@ -308,9 +319,20 @@ class det_rec_functions(object):
         # 解析识别模型
         recInput = {"x":[1,3,48,320]}
         self.modelRec = migraphx.parse_onnx(self.rec_file, map_input_dims=recInput)
-        self.inputName = self.modelRec.get_parameter_names()[0]
-        self.inputShape = self.modelRec.get_parameter_shapes()[self.inputName].lens()
 
+        # 获取模型输入/输出节点信息
+        print("rec_inputs:")
+        inputs_rec = self.modelRec.get_inputs()
+        for key,value in inputs_rec.items():
+            print("{}:{}".format(key,value))
+
+        print("rec_outputs:")
+        outputs_rec = self.modelRec.get_outputs()
+        for key,value in outputs_rec.items():
+            print("{}:{}".format(key,value))
+
+        self.inputName = self.modelRec.get_parameter_names()[0]
+        self.inputShape = inputs_rec[self.inputName].lens()
         print("SVTR inputName:{0} \nSVTR inputShape:{1}".format(self.inputName, self.inputShape))
 
         # 模型编译

Src/PaddleOCR/OcrDB.cpp

@@ -57,10 +57,21 @@ ErrorCode DB::Initialize(InitializationParameterOfDB InitializationParameterOfDB
     net = migraphx::parse_onnx(modelPath, onnx_options);
     LOG_INFO(stdout,"succeed to load model: %s\n",GetFileName(modelPath).c_str());
 
-    // 获取模型输入属性
-    std::unordered_map<std::string, migraphx::shape> inputMap=net.get_parameter_shapes();
-    inputName=inputMap.begin()->first;
-    inputShape=inputMap.begin()->second;
+    // 获取模型输入/输出节点信息
+    std::cout<<"DB_inputs:"<<std::endl;
+    std::unordered_map<std::string, migraphx::shape> inputs=net.get_inputs();
+    for(auto i:inputs)
+    {
+        std::cout<<i.first<<":"<<i.second<<std::endl;
+    }
+    std::cout<<"DB_outputs:"<<std::endl;
+    std::unordered_map<std::string, migraphx::shape> outputs=net.get_outputs();
+    for(auto i:outputs)
+    {
+        std::cout<<i.first<<":"<<i.second<<std::endl;
+    }
+    inputName=inputs.begin()->first;
+    inputShape=inputs.begin()->second;
     int N=inputShape.lens()[0];
     int C=inputShape.lens()[1];
     int H=inputShape.lens()[2];

Src/PaddleOCR/OcrSVTR.cpp

@@ -50,10 +50,22 @@ ErrorCode SVTR::Initialize(InitializationParameterOfSVTR InitializationParameter
     net = migraphx::parse_onnx(modelPath, onnx_options);
     LOG_INFO(stdout,"succeed to load model: %s\n",GetFileName(modelPath).c_str());
 
-    // 获取模型输入属性
-    std::unordered_map<std::string, migraphx::shape> inputMap=net.get_parameter_shapes();
-    inputName=inputMap.begin()->first;
-    inputShape=inputMap.begin()->second;
+    // 获取模型输入/输出节点信息
+    std::cout<<"SVTR_inputs:"<<std::endl;
+    std::unordered_map<std::string, migraphx::shape> inputs=net.get_inputs();
+    for(auto i:inputs)
+    {
+        std::cout<<i.first<<":"<<i.second<<std::endl;
+    }
+    std::cout<<"DSVTR_outputs:"<<std::endl;
+    std::unordered_map<std::string, migraphx::shape> outputs=net.get_outputs();
+    for(auto i:outputs)
+    {
+        std::cout<<i.first<<":"<<i.second<<std::endl;
+    }
+
+    inputName=inputs.begin()->first;
+    inputShape=inputs.begin()->second;
     int N=inputShape.lens()[0];
     int C=inputShape.lens()[1];
     int H=inputShape.lens()[2];