修改python代码使用migraphx后端推理

Python/Classifier.py

@@ -3,6 +3,7 @@
 分类器示例
 """
 import cv2
+import argparse
 import numpy as np
 import onnxruntime as ort
 
@@ -57,20 +58,19 @@ def postprocess(scores,pathOfImage):
     text = 'class=%s ' % (labels[a[0]])
     saveimage(pathOfImage,text)
 
-def ort_seg_dcu(model_path,image):
+def ort_seg_dcu(model_path,image,staticInfer,dynamicInfer):
     
-    #创建sess_options
-    sess_options = ort.SessionOptions()
+    provider_options=[]
+    if staticInfer:
+        provider_options=[{'device_id':'0','migraphx_fp16_enable':'true','dynamic_model':'false'}]
 
-    #设置图优化
-    sess_options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_BASIC
+    if dynamicInfer:
+        provider_options=[{'device_id':'0','migraphx_fp16_enable':'true','dynamic_model':'true', 'migraphx_profile_max_shapes':'data:1x3x224x224'}]
 
-    #是否开启profiling
-    sess_options.enable_profiling = False
-    dcu_session = ort.InferenceSession(model_path,sess_options,providers=['ROCMExecutionProvider'],)
+    dcu_session = ort.InferenceSession(model_path, providers=['MIGraphXExecutionProvider'], provider_options=provider_options)
     input_name=dcu_session.get_inputs()[0].name
 
-    results = dcu_session.run(None, input_feed={input_name:image })
+    results = dcu_session.run(None, input_feed={input_name:image})
     scores=np.array(results[0])
     print("ort result.shape:",scores.shape)
 
@@ -88,13 +88,24 @@ def saveimage(pathOfImage,text):
     cv2.destroyAllWindows()
 
 if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--imgPath', type=str, default='../Resource/Images/ImageNet_01.jpg', help="image path")
+    parser.add_argument('--staticModelPath', type=str, default='../Resource/Models/resnet50_static.onnx', help="static onnx filepath")
+    parser.add_argument('--dynamicModelPath', type=str, default='../Resource/Models/resnet50_dynamic.onnx', help="dynamic onnx filepath")
+    parser.add_argument("--staticInfer",action="store_true",default=False,help="Performing static inference")
+    parser.add_argument("--dynamicInfer",action="store_true",default=False,help="Performing dynamic inference")
+    args = parser.parse_args()
 
-    pathOfImage ="../Resource/Images/ImageNet_01.jpg"
-    image = Preprocessing(pathOfImage)
-    model_path = "../Resource/Models/resnet50-v2-7.onnx"
+    # 数据预处理
+    image = Preprocessing(args.imgPath)
 
-    # 推理
-    result = ort_seg_dcu(model_path,image)
+    # 静态推理
+    if args.staticInfer:
+        result = ort_seg_dcu(args.staticModelPath,image,args.staticInfer,args.dynamicInfer)
+
+    # 动态推理
+    if args.dynamicInfer:
+        result = ort_seg_dcu(args.dynamicModelPath,image,args.staticInfer,args.dynamicInfer)
     
     # 解析分类结果
-    postprocess(result,pathOfImage)
+    postprocess(result,args.imgPath)