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Quick_Deploy: PyTorch: Clarify client.py usage #134

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Quick_Deploy: PyTorch: Clarify client.py usage #134

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6 changes: 4 additions & 2 deletions Quick_Deploy/PyTorch/README.md
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Expand Up @@ -71,8 +71,10 @@ docker run -it --net=host -v ${PWD}:/workspace/ nvcr.io/nvidia/tritonserver:<yy.
pip install torchvision

wget -O img1.jpg "https://www.hakaimagazine.com/wp-content/uploads/header-gulf-birds.jpg"
python ./client.py
```
Building a client requires three basic points. Firstly, we setup a connection with the Triton Inference Server.

Let's take a look at the contents of `client.py`. Building a client requires three basic points. Firstly, we setup a connection with the Triton Inference Server.
```
client = httpclient.InferenceServerClient(url="localhost:8000")
```
Expand All @@ -95,4 +97,4 @@ The output of the same should look like below:
[b'12.468750:90' b'11.523438:92' b'9.664062:14' b'8.429688:136'
b'8.234375:11']
```
The output format here is `<confidence_score>:<classification_index>`. To learn how to map these to the label names and more, refer to our [documentation](https://github.com/triton-inference-server/server/blob/main/docs/protocol/extension_classification.md). The client code above is available in `client.py`.
The output format here is `<confidence_score>:<classification_index>`. To learn how to map these to the label names and more, refer to our [documentation](https://github.com/triton-inference-server/server/blob/main/docs/protocol/extension_classification.md).