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Update README.md

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@@ -73,11 +73,11 @@ val: val2017.txt # val images (relative to 'path') 5000 images
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  ### Test & Evaluation
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- - Code snippet from [`onnx_inference.py`](onnx_inference.py) on how to use
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  ```python
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  args = make_parser().parse_args()
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- onnx_path = args.model
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- onnx_model = onnxruntime.InferenceSession(onnx_path)
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  grid = np.load("./grid.npy", allow_pickle=True)
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  anchor_grid = np.load("./anchor_grid.npy", allow_pickle=True)
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  path = args.image_path
@@ -86,8 +86,8 @@ val: val2017.txt # val images (relative to 'path') 5000 images
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  img0 = cv2.imread(path)
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  img = pre_process(img0)
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- onnx_input = {onnx_model.get_inputs()[0].name: img}
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- onnx_output = onnx_model.run(None, onnx_input)
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  onnx_output = post_process(onnx_output)
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  pred = non_max_suppression(
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  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
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  - Run inference for a single image
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  ```python
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- python onnx_inference.py -m ./yolov5s_qat.onnx -i /Path/To/Your/Image --ipu --provider_config /Path/To/Your/Provider_config
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  ```
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  *Note: __vaip_config.json__ is located at the setup package of Ryzen AI (refer to [Installation](#installation))*
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  - Test accuracy of the quantized model
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  ```python
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- python onnx_eval.py -m ./yolov5s_qat.onnx --ipu --provider_config /Path/To/Your/Provider_config
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  ```
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  ### Performance
 
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  ### Test & Evaluation
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+ - Code snippet from [`infer_onnx.py`](infer_onnx.py) on how to use
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  ```python
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  args = make_parser().parse_args()
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+ onnx_path = args.onnx_model
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+ onnx_weight = onnxruntime.InferenceSession(onnx_path)
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  grid = np.load("./grid.npy", allow_pickle=True)
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  anchor_grid = np.load("./anchor_grid.npy", allow_pickle=True)
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  path = args.image_path
 
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  img0 = cv2.imread(path)
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  img = pre_process(img0)
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+ onnx_input = {onnx_weight.get_inputs()[0].name: img}
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+ onnx_output = onnx_weight.run(None, onnx_input)
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  onnx_output = post_process(onnx_output)
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  pred = non_max_suppression(
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  onnx_output[0], conf_thres, iou_thres, classes, agnostic_nms, max_det=max_det
 
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  - Run inference for a single image
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  ```python
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+ python infer_onnx.py --onnx_model ./yolov5s.onnx -i /Path/To/Your/Image --ipu --provider_config /Path/To/Your/Provider_config
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  ```
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  *Note: __vaip_config.json__ is located at the setup package of Ryzen AI (refer to [Installation](#installation))*
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  - Test accuracy of the quantized model
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  ```python
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+ python eval_onnx.py --onnx_model ./yolov5s.onnx --ipu --provider_config /Path/To/Your/Provider_config
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  ```
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  ### Performance