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* Fix links in readme * Fix links in readme * Update PPOCRv2/v3 examples * Update auto compression configs
75 lines
2.8 KiB
Markdown
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75 lines
2.8 KiB
Markdown
Executable File
# FastDeploy Toolkit
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FastDeploy provides a series of efficient and easy-to-use tools to optimize the deployment experience and improve inference performance.
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- [1.Auto Compression Tool](#1)
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- [2.Model Conversion Tool](#2)
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<p id="1"></p>
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## One-Click Model Auto Compression Tool
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Based on PaddleSlim's Auto Compression Toolkit (ACT), FastDeploy provides users with a one-click model automation compression tool that allows users to easily compress the model with a single command. This document will take FastDeploy's one-click model automation compression tool as an example, introduce how to install the tool, and provide the corresponding documentation for usage.
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### Environmental Preparation
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1.Install PaddlePaddle 2.4 version
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```
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https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/develop/install/pip/linux-pip.html
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```
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2.Install PaddleSlim 2.4 version
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```bash
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pip install paddleslim==2.4.0
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```
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3.Install fastdeploy-tools package
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```bash
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# Installing fastdeploy-tools via pip
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# This tool is included in the python installer of FastDeploy, so you don't need to install it again.
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pip install fastdeploy-tools==0.0.1
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```
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### The Usage of One-Click Model Auto Compression Tool
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After the above steps are successfully installed, you can use FastDeploy one-click model automation compression tool, as shown in the following example.
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```bash
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fastdeploy compress --config_path=./configs/detection/yolov5s_quant.yaml --method='PTQ' --save_dir='./yolov5s_ptq_model/'
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```
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For detailed documentation, please refer to [FastDeploy One-Click Model Auto Compression Tool](./common_tools/auto_compression/README_EN.md)
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<p id="2"></p>
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## Model Conversion Tool
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Based on X2Paddle, FastDeploy provides users with a model conversion tool. Users can easily migrate external framework models to the Paddle framework with one line of commands. Currently, ONNX, TensorFlow and Caffe are supported, and most mainstream CV and NLP model conversions are supported.
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### Environmental Preparation
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1. Install PaddlePaddle, refer to the following documents for quick installation
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```
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https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/develop/install/pip/linux-pip.html
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```
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2. Install X2Paddle
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To use the stable version, install X2Paddle via pip:
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```shell
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pip install x2paddle
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```
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To experience the latest features, you can use the source installation method:
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```shell
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git clone https://github.com/PaddlePaddle/X2Paddle.git
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cd X2Paddle
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python setup.py install
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```
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### How to use
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After successful installation according to the above steps, you can use the FastDeploy one-click conversion tool. The example is as follows:
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```bash
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fastdeploy convert --framework onnx --model yolov5s.onnx --save_dir pd_model
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```
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For more details, please refer to[X2Paddle](https://github.com/PaddlePaddle/X2Paddle)
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