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/2.5). ## Requirements: - PaddlePaddle 2.2 - OS 64 bit - Python 3(3.5.1+/3.6/3.7/3.8/3.9),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 | >= 2.2.2 | 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==2.2.2 -i https://mirror.baidu.com/pypi/simple # CPU python -m pip install paddlepaddle==2.2.2 -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 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: ![](../images/000000014439.jpg)