update for regression test

README.md

@@ -74,7 +74,7 @@ val: val2017.txt  # val images (relative to 'path') 5000 images
 
 ### Test & Evaluation
 
- - Code snippet from [`onnx_inference.py`](onnx_inference.py) on how to use
+ - Code snippet from [`infer_onnx.py`](./infer_onnx.py) on how to use
 ```python
 args = make_parser().parse_args()
 source = args.image_path 
@@ -106,12 +106,12 @@ for batch in dataset:
 
  - Run inference for a single image
   ```python
-  python onnx_inference.py -m ./yolov8m.onnx -i /Path/To/Your/Image --ipu --provider_config /Path/To/Your/Provider_config
+  python infer_onnx.py --onnx_model ./yolov8m.onnx -i /Path/To/Your/Image --ipu --provider_config /Path/To/Your/Provider_config
   ```
 *Note: __vaip_config.json__ is located at the setup package of Ryzen AI (refer to [Installation](#installation))*
  - Test accuracy of the quantized model
   ```python
-  python onnx_eval.py -m ./yolov8m.onnx --ipu --provider_config /Path/To/Your/Provider_config
+  python eval_onnx.py --onnx_model ./yolov8m.onnx --ipu --provider_config /Path/To/Your/Provider_config
   ```
 
 ### Performance

eval_onnx.py

@@ -271,7 +271,7 @@ def parse_opt():
     parser = argparse.ArgumentParser()
     parser.add_argument('--ipu', action='store_true', help='flag for ryzen ai')
     parser.add_argument('--provider_config', default='', type=str, help='provider config for ryzen ai')
-    parser.add_argument("-m", "--model", default="./yolov8m_qat.onnx", type=str, help='onnx_weight')
+    parser.add_argument("-m", "--onnx_model", default="./yolov8m.onnx", type=str, help='onnx_weight')
     opt = parser.parse_args()
     return opt
 
@@ -280,7 +280,7 @@ if __name__ == "__main__":
     opt = parse_opt()
     args = get_cfg(DEFAULT_CFG)
     args.ipu = opt.ipu
-    args.onnx_weight = opt.model
+    args.onnx_weight = opt.onnx_model
     args.provider_config = opt.provider_config
     validator = DetectionValidator(args=args)
     validator()

infer_onnx.py

@@ -75,9 +75,9 @@ def make_parser():
     parser = argparse.ArgumentParser("onnxruntime inference sample")
     parser.add_argument(
         "-m",
-        "--model",
+        "--onnx_model",
         type=str,
-        default="./yolov8m_qat.onnx",
+        default="./yolov8m.onnx",
         help="input your onnx model.",
     )
     parser.add_argument(
@@ -121,7 +121,7 @@ if __name__ == '__main__':
     dataset = LoadImages(
         source, imgsz=imgsz, stride=32, auto=False, transforms=None, vid_stride=1
     )
-    onnx_weight = args.model
+    onnx_weight = args.onnx_model
     if args.ipu:
         providers = ["VitisAIExecutionProvider"]
         provider_options = [{"config_file": args.provider_config}]