未验证 提交 d14d72e3 编写于 作者: D Double_V 提交者: GitHub

Merge pull request #2030 from LDOUBLEV/lite_doc

fix lite doc
......@@ -24,15 +24,7 @@ Paddle Lite是飞桨轻量化推理引擎,为手机、IOT端提供高效推理
### 1.2 准备预测库
预测库有两种获取方式:
- 1. 直接下载,预测库下载链接如下:
|平台|预测库下载链接|
|-|-|
|Android|[arm7](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.6.3/inference_lite_lib.android.armv7.gcc.c++_shared.with_extra.with_cv.tar.gz) / [arm8](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.6.3/inference_lite_lib.android.armv8.gcc.c++_shared.with_extra.with_cv.tar.gz)|
|IOS|[arm7](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.6.3/inference_lite_lib.ios.armv7.with_cv.with_extra.with_log.tiny_publish.tar.gz) / [arm8](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.6.3/inference_lite_lib.ios.armv8.with_cv.with_extra.with_log.tiny_publish.tar.gz)|
注:1. 上述预测库为PaddleLite 2.6.3分支编译得到,有关PaddleLite 2.6.3 详细信息可参考[链接](https://github.com/PaddlePaddle/Paddle-Lite/releases/tag/v2.6.3)。
- 2. [推荐]编译Paddle-Lite得到预测库,Paddle-Lite的编译方式如下:
- 1. [推荐]编译Paddle-Lite得到预测库,Paddle-Lite的编译方式如下:
```
git clone https://github.com/PaddlePaddle/Paddle-Lite.git
cd Paddle-Lite
......@@ -45,6 +37,9 @@ git checkout release/v2.7
更多编译命令
介绍请参考[链接](https://paddle-lite.readthedocs.io/zh/latest/user_guides/Compile/Android.html#id2)
- 2. 直接下载预测库,下载[链接](https://github.com/PaddlePaddle/Paddle-Lite/releases/tag/v2.7.1)
直接下载预测库并解压后,可以得到`inference_lite_lib.android.armv8/`文件夹,通过编译Paddle-Lite得到的预测库位于
`Paddle-Lite/build.lite.android.armv8.gcc/inference_lite_lib.android.armv8/`文件夹下。
预测库的文件目录如下:
......@@ -88,11 +83,11 @@ Paddle-Lite 提供了多种策略来自动优化原始的模型,其中包括
|-|-|-|-|-|-|-|
|V1.1|超轻量中文OCR 移动端模型|8.1M|[下载地址](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_det_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_cls_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_rec_opt.nb)|v2.7|
|【slim】V1.1|超轻量中文OCR 移动端模型|3.5M|[下载地址](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_det_prune_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_cls_quant_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_rec_quant_opt.nb)|v2.7|
|V1.0|轻量级中文OCR 移动端模型|8.6M|[下载地址](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.0_det_opt.nb)|---|[下载地址](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.0_rec_opt.nb)|v2.7|
注意:V1.1 3.0M 轻量模型是使用PaddleSlim优化后的,需要配合Paddle-Lite最新预测库使用。
如果直接使用上述表格中的模型进行部署,可略过下述步骤,直接阅读 [2.2节](#2.2与手机联调)
如果直接使用上述表格中的模型进行部署没有问题,可略过下述步骤,直接阅读 [2.2节](#2.2与手机联调)
如果要部署的模型不在上述表格中,则需要按照如下步骤获得优化后的模型。
......@@ -184,7 +179,7 @@ wget https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn_infer.tar && tar
```
git clone https://github.com/PaddlePaddle/PaddleOCR.git
cd PaddleOCR/deploy/lite/
# 运行prepare.sh,准备预测库文件、测试图像和使用的字典文件,并放置在预测库中的demo/cxx/ocr文件夹下
# 按照如下命令运行prepare.sh,将预测库文件、测试图像和使用的字典文件到预测库中的demo/cxx/ocr文件夹下
sh prepare.sh /{lite prediction library path}/inference_lite_lib.android.armv8
# 进入OCR demo的工作目录
......@@ -255,6 +250,7 @@ use_direction_classify 0 # 是否使用方向分类器,0表示不使用,1
adb shell
cd /data/local/tmp/debug
export LD_LIBRARY_PATH=${PWD}:$LD_LIBRARY_PATH
# ./ocr_db_crnn 检测模型文件 方向分类器模型文件 识别模型文件 测试图像路径 字典文件路径
./ocr_db_crnn ch_ppocr_mobile_v1.1_det_prune_opt.nb ch_ppocr_mobile_v1.1_rec_quant_opt.nb ch_ppocr_mobile_cls_quant_opt.nb ./11.jpg ppocr_keys_v1.txt
```
......
......@@ -22,15 +22,7 @@ deployment solutions for end-side deployment issues.
## 3. Prepare prebuild library for android and ios
### 3.1 Download prebuild library
|Platform|Prebuild library Download Link|
|-|-|
|Android|[arm7](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.6.3/inference_lite_lib.android.armv7.gcc.c++_shared.with_extra.with_cv.tar.gz) / [arm8](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.6.3/inference_lite_lib.android.armv8.gcc.c++_shared.with_extra.with_cv.tar.gz)|
|IOS|[arm7](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.6.3/inference_lite_lib.ios.armv7.with_cv.with_extra.with_log.tiny_publish.tar.gz) / [arm8](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.6.3/inference_lite_lib.ios.armv8.with_cv.with_extra.with_log.tiny_publish.tar.gz)|
note: The above pre-build inference library is compiled from the PaddleLite `release/v2.7` branch. For more information about PaddleLite 2.6.3, please refer to [link](https://github.com/PaddlePaddle/Paddle-Lite/releases/tag/v2.6.3).
### 3.2 Compile prebuild library (Recommended)
### 3.1 Compile prebuild library (Recommended)
```
git clone https://github.com/PaddlePaddle/Paddle-Lite.git
cd Paddle-Lite
......@@ -66,6 +58,11 @@ inference_lite_lib.android.armv8/
| `-- java
```
### 3.2 Download prebuild library
PaddleLite also provides a compiled [prediction library](https://github.com/PaddlePaddle/Paddle-Lite/releases/tag/v2.7.1), developers can try on their own.
## 4. Inference Model Optimization
......@@ -80,7 +77,6 @@ You can directly download the optimized model.
| - | - | - | - | - | - | - |
| V1.1 | extra-lightweight chinese OCR optimized model | 8.1M | [Download](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_det_opt.nb) | [Download](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_cls_opt.nb) | [Download](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_rec_opt.nb) | develop |
| [slim] V1.1 | extra-lightweight chinese OCR optimized model | 3.5M | [Download](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_det_prune_opt.nb) | [Download](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_cls_quant_opt.nb) | [Download](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.1_rec_quant_opt.nb) | develop |
| V1.0 | lightweight Chinese OCR optimized model | 8.6M | [Download](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.0_det_opt.nb) | - | [Download](https://paddleocr.bj.bcebos.com/20-09-22/mobile/lite/ch_ppocr_mobile_v1.0_rec_opt.nb) | develop |
If the model to be deployed is not in the above table, you need to follow the steps below to obtain the optimized model.
......
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