Update README.md

README.md

@@ -73,11 +73,11 @@ 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()
-    onnx_path = args.model
-    onnx_model = onnxruntime.InferenceSession(onnx_path)
+    onnx_path = args.onnx_model
+    onnx_weight = onnxruntime.InferenceSession(onnx_path)
     grid = np.load("./grid.npy", allow_pickle=True)
     anchor_grid = np.load("./anchor_grid.npy", allow_pickle=True)
     path = args.image_path 
@@ -86,8 +86,8 @@ val: val2017.txt  # val images (relative to 'path') 5000 images
 
     img0 = cv2.imread(path)
     img = pre_process(img0)
-    onnx_input = {onnx_model.get_inputs()[0].name: img}
-    onnx_output = onnx_model.run(None, onnx_input)
+    onnx_input = {onnx_weight.get_inputs()[0].name: img}
+    onnx_output = onnx_weight.run(None, onnx_input)
     onnx_output = post_process(onnx_output)
     pred = non_max_suppression(
         onnx_output[0], conf_thres, iou_thres, classes, agnostic_nms, max_det=max_det
@@ -112,12 +112,12 @@ val: val2017.txt  # val images (relative to 'path') 5000 images
 
  - Run inference for a single image
   ```python
-  python onnx_inference.py -m ./yolov5s_qat.onnx -i /Path/To/Your/Image --ipu --provider_config /Path/To/Your/Provider_config
+  python infer_onnx.py --onnx_model ./yolov5s.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 ./yolov5s_qat.onnx --ipu --provider_config /Path/To/Your/Provider_config
+  python eval_onnx.py --onnx_model ./yolov5s.onnx --ipu --provider_config /Path/To/Your/Provider_config
   ```
 
 ### Performance