This section introduces the deployment of PaddleOCR on Jeston NX, TX2, nano, AGX and other series of hardware.
This section introduces the deployment of PaddleOCR on Jetson NX, TX2, nano, AGX and other series of hardware.
## 1. Prepare Environment
You need to prepare a Jeston development hardware. If you need TensorRT, you need to prepare the TensorRT environment. It is recommended to use TensorRT version 7.1.3;
You need to prepare a Jetson development hardware. If you need TensorRT, you need to prepare the TensorRT environment. It is recommended to use TensorRT version 7.1.3;
1. Install PaddlePaddle in Jeston
1. Install PaddlePaddle in Jetson
The PaddlePaddle download [link](https://www.paddlepaddle.org.cn/inference/user_guides/download_lib.html#python)
Please select the appropriate installation package for your Jetpack version, cuda version, and trt version. Here, we download paddlepaddle_gpu-2.3.0rc0-cp36-cp36m-linux_aarch64.whl.
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@@ -32,11 +32,11 @@ cd PaddleOCR
pip3 install -r requirements.txt
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*Note: Jeston hardware CPU is poor, dependency installation is slow, please wait patiently*
*Note: Jetson hardware CPU is poor, dependency installation is slow, please wait patiently*
## 2. Perform prediction
Obtain the PPOCR model from the [document](https://github.com/PaddlePaddle/PaddleOCR/blob/dygraph/doc/doc_ch/ppocr_introduction.md#6-%E6%A8%A1%E5%9E%8B%E5%BA%93) model library. The following takes the PP-OCRv3 model as an example to introduce the use of the PPOCR model on jeston:
Obtain the PPOCR model from the [document](https://github.com/PaddlePaddle/PaddleOCR/blob/dygraph/doc/doc_ch/ppocr_introduction.md#6-%E6%A8%A1%E5%9E%8B%E5%BA%93) model library. The following takes the PP-OCRv3 model as an example to introduce the use of the PPOCR model on Jetson: