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English | [简体中文](INSTALL_cn.md)
# Installation
This document covers how to install PaddleDetection and its dependencies
(including PaddlePaddle), together with COCO and Pascal VOC dataset.
For general information about PaddleDetection, please see [README.md](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.6).
## Requirements:
- PaddlePaddle 2.2
- OS 64 bit
- Python 3(3.5.1+/3.6/3.7/3.8/3.9/3.10)，64 bit
- pip/pip3(9.0.1+), 64 bit
- CUDA >= 10.2
- cuDNN >= 7.6
Dependency of PaddleDetection and PaddlePaddle:
| PaddleDetection version | PaddlePaddle version | tips |
| :----------------: | :---------------: | :-------: |
| develop | >= 2.3.2 | Dygraph mode is set as default |
| release/2.6 | >= 2.3.2 | Dygraph mode is set as default |
| release/2.5 | >= 2.2.2 | Dygraph mode is set as default |
| release/2.4 | >= 2.2.2 | Dygraph mode is set as default |
| release/2.3 | >= 2.2.0rc | Dygraph mode is set as default |
| release/2.2 | >= 2.1.2 | Dygraph mode is set as default |
| release/2.1 | >= 2.1.0 | Dygraph mode is set as default |
| release/2.0 | >= 2.0.1 | Dygraph mode is set as default |
| release/2.0-rc | >= 2.0.1 | -- |
| release/0.5 | >= 1.8.4 | Cascade R-CNN and SOLOv2 depends on 2.0.0.rc |
| release/0.4 | >= 1.8.4 | PP-YOLO depends on 1.8.4 |
| release/0.3 | >=1.7 | -- |
## Instruction
### 1. Install PaddlePaddle
```
# CUDA10.2
python -m pip install paddlepaddle-gpu==2.3.2 -i https://mirror.baidu.com/pypi/simple
# CPU
python -m pip install paddlepaddle==2.3.2 -i https://mirror.baidu.com/pypi/simple
```
- For more CUDA version or environment to quick install, please refer to the [PaddlePaddle Quick Installation document](https://www.paddlepaddle.org.cn/install/quick)
- For more installation methods such as conda or compile with source code, please refer to the [installation document](https://www.paddlepaddle.org.cn/documentation/docs/en/install/index_en.html)
Please make sure that your PaddlePaddle is installed successfully and the version is not lower than the required version. Use the following command to verify.
```
# check
>>> import paddle
>>> paddle.utils.run_check()
# confirm the paddle's version
python -c "import paddle; print(paddle.__version__)"
```
**Note**
1. If you want to use PaddleDetection on multi-GPU, please install NCCL at first.
### 2. Install PaddleDetection
**Note:** Installing via pip only supports Python3
```
# Clone PaddleDetection repository
cd <path/to/clone/PaddleDetection>
git clone https://github.com/PaddlePaddle/PaddleDetection.git
# Install other dependencies
cd PaddleDetection
pip install -r requirements.txt
# Compile and install paddledet
python setup.py install
```
**Note**
1. If you are working on Windows OS, `pycocotools` installing may failed because of the origin version of cocoapi does not support windows, another version can be used used which only supports Python3:
```pip install git+https://github.com/philferriere/cocoapi.git#subdirectory=PythonAPI```
2. If you are using Python <= 3.6, `pycocotools` installing may failed with error like `distutils.errors.DistutilsError: Could not find suitable distribution for Requirement.parse('cython>=0.27.3')`, please install `cython` firstly, for example `pip install cython`
After installation, make sure the tests pass:
```shell
python ppdet/modeling/tests/test_architectures.py
```
If the tests are passed, the following information will be prompted:
```
.......
----------------------------------------------------------------------
Ran 7 tests in 12.816s
OK
```
## Use built Docker images
> If you do not have a Docker environment, please refer to [Docker](https://www.docker.com/).
We provide docker images containing the latest PaddleDetection code, and all environment and package dependencies are pre-installed. All you have to do is to **pull and run the docker image**. Then you can enjoy PaddleDetection without any extra steps.
Get these images and guidance in [docker hub](https://hub.docker.com/repository/docker/paddlecloud/paddledetection), including CPU, GPU, ROCm environment versions.
If you have some customized requirements about automatic building docker images, you can get it in github repo [PaddlePaddle/PaddleCloud](https://github.com/PaddlePaddle/PaddleCloud/tree/main/tekton).
## Inference demo
**Congratulation!** Now you have installed PaddleDetection successfully and try our inference demo:
```
# Predict an image by GPU
export CUDA_VISIBLE_DEVICES=0
python tools/infer.py -c configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml -o use_gpu=true weights=https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams --infer_img=demo/000000014439.jpg
```
An image of the same name with the predicted result will be generated under the `output` folder.
The result is as shown below：
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