fix comment

deploy/jeston/readme.md

 
-# Jeston
+# Jeston部署PaddleOCR模型
 
 本节介绍PaddleOCR在Jeston NX、TX2、nano、AGX等系列硬件的部署。
 
@@ -8,7 +8,7 @@
 
 需要准备一台Jeston开发板，如果需要TensorRT预测，需准备好TensorRT环境，建议使用7.1.3版本的TensorRT；
 
-1. jeston安装paddlepaddle
+1. jeston安装PaddlePaddle
 
 paddlepaddle下载[链接](https://www.paddlepaddle.org.cn/inference/user_guides/download_lib.html#python)
 请选择适合的您Jetpack版本、cuda版本、trt版本的安装包。
@@ -26,7 +26,7 @@ pip3 install -U paddlepaddle_gpu-*-cp36-cp36m-linux_aarch64.whl
 git clone https://github.com/PaddlePaddle/PaddleOCR
 ```
 
-其次，安装依赖：
+然后，安装依赖：
 ```
 cd PaddleOCR
 pip3 install -r requirements.txt
@@ -50,23 +50,35 @@ tar xf ch_PP-OCRv3_rec_infer.tar
 执行文本检测预测：
 ```
 cd PaddleOCR
-python3 tools/infer/predict_det.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/  --image_dir=./doc/imgs/  --use_gpu=True
+python3 tools/infer/predict_det.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/  --image_dir=./doc/imgs/french_0.jpg  --use_gpu=True
 ```
 
+执行命令后在终端会打印出预测的信息，并在 `./inference_results/` 下保存可视化结果。
+![](./images/det_res_french_0.jpg)
+
+
 执行文本识别预测：
 ```
-python3 tools/infer/predict_det.py --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/  --image_dir=./doc/imgs_words/ch/  --use_gpu=True
+python3 tools/infer/predict_det.py --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/  --image_dir=./doc/imgs_words/en/word_2.png  --use_gpu=True --rec_image_shape="3,48,320"
+```
+
+执行命令后在终端会打印出预测的信息，输出如下：
+```
+[2022/04/28 15:41:45] root INFO: Predicts of ./doc/imgs_words/en/word_2.png:('yourself', 0.98084533)
 ```
 
 执行文本检测+文本识别串联预测：
 
 ```
-python3 tools/infer/predict_system.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/ --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/ --image_dir=./doc/imgs/ --use_gpu=True
+python3 tools/infer/predict_system.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/ --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/ --image_dir=./doc/imgs/ --use_gpu=True --rec_image_shape="3,48,320"
 ```
 
+执行命令后在终端会打印出预测的信息，并在 `./inference_results/` 下保存可视化结果。
+![](./images/00057937.jpg)
+
 开启TRT预测只需要在以上命令基础上设置`--use_tensorrt=True`即可：
 ```
-python3 tools/infer/predict_system.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/ --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/ --image_dir=./doc/imgs/ --use_gpu=True --use_tensorrt=True
+python3 tools/infer/predict_system.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/ --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/ --image_dir=./doc/imgs/00057937.jpg --use_gpu=True --use_tensorrt=True --rec_image_shape="3,48,320"
 ```
 
 更多ppocr模型预测请参考[文档](../../doc/doc_ch/inference_ppocr.md)

deploy/jeston/readme_en.md

 
-# Jeston
+# Jeston Deployment for PaddleOCR
 
 This section introduces the deployment of PaddleOCR on Jeston NX, TX2, nano, AGX and other series of hardware.
 
 
-## 1. 环境准备
+## 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;
 
-1. jeston install paddlepaddle
+1. Install PaddlePaddle in Jeston
 
 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.
@@ -49,23 +49,35 @@ tar xf ch_PP-OCRv3_rec_infer.tar
 The text detection inference:
 ```
 cd PaddleOCR
-python3 tools/infer/predict_det.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/  --image_dir=./doc/imgs/  --use_gpu=True
+python3 tools/infer/predict_det.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/  --image_dir=./doc/imgs/french_0.jpg  --use_gpu=True
 ```
 
+After executing the command, the predicted information will be printed out in the terminal, and the visualization results will be saved in the `./inference_results/` directory.
+![](./images/det_res_french_0.jpg)
+
+
 The text recognition inference:
 ```
-python3 tools/infer/predict_det.py --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/  --image_dir=./doc/imgs_words/ch/  --use_gpu=True
+python3 tools/infer/predict_det.py --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/  --image_dir=./doc/imgs_words/en/word_2.png  --use_gpu=True --rec_image_shape="3,48,320"
+```
+
+After executing the command, the predicted information will be printed on the terminal, and the output is as follows:
+```
+[2022/04/28 15:41:45] root INFO: Predicts of ./doc/imgs_words/en/word_2.png:('yourself', 0.98084533)
 ```
 
 The text  detection and text recognition inference:
 
 ```
-python3 tools/infer/predict_system.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/ --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/ --image_dir=./doc/imgs/ --use_gpu=True
+python3 tools/infer/predict_system.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/ --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/ --image_dir=./doc/imgs/00057937.jpg --use_gpu=True --rec_image_shape="3,48,320"
 ```
 
+After executing the command, the predicted information will be printed out in the terminal, and the visualization results will be saved in the `./inference_results/` directory.
+![](./images/00057937.jpg)
+
 To enable TRT prediction, you only need to set `--use_tensorrt=True` on the basis of the above command:
 ```
-python3 tools/infer/predict_system.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/ --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/ --image_dir=./doc/imgs/ --use_gpu=True --use_tensorrt=True
+python3 tools/infer/predict_system.py --det_model_dir=./inference/ch_PP-OCRv2_det_infer/ --rec_model_dir=./inference/ch_PP-OCRv2_rec_infer/ --image_dir=./doc/imgs/  --rec_image_shape="3,48,320" --use_gpu=True --use_tensorrt=True
 ```
 
 For more ppocr model predictions, please refer to[document](../../doc/doc_en/inference_ppocr_en.md)