Skip to content

Latest commit

 

History

History
77 lines (59 loc) · 2.05 KB

INSTALL.md

File metadata and controls

77 lines (59 loc) · 2.05 KB
Raw

Installation

Requirements

  • Linux (tested on Ubuntu 16.04 and CentOS 7.2)
  • Python 3.4+
  • PyTorch 1.0
  • Cython
  • mmcv >= 0.2.2

Install mmdetection

a. Install PyTorch 1.0 and torchvision following the official instructions.

b. Clone the mmdetection repository.

git clone https://github.com/open-mmlab/mmdetection.git

c. Compile cuda extensions.

cd mmdetection
pip install cython  # or "conda install cython" if you prefer conda
./compile.sh  # or "PYTHON=python3 ./compile.sh" if you use system python3 without virtual environments

d. Install mmdetection (other dependencies will be installed automatically).

python(3) setup.py install  # add --user if you want to install it locally
# or "pip install ."

Note: You need to run the last step each time you pull updates from github. The git commit id will be written to the version number and also saved in trained models.

Prepare COCO dataset.

It is recommended to symlink the dataset root to $MMDETECTION/data.

mmdetection
├── mmdet
├── tools
├── configs
├── data
│   ├── coco
│   │   ├── annotations
│   │   ├── train2017
│   │   ├── val2017
│   │   ├── test2017
│   ├── VOCdevkit
│   │   ├── VOC2007
│   │   ├── VOC2012

Scripts

Just for reference, Here is a script for setting up mmdetection with conda.

Notice

You can run python(3) setup.py develop or pip install -e . to install mmdetection if you want to make modifications to it frequently.

If there are more than one mmdetection on your machine, and you want to use them alternatively. Please insert the following code to the main file

import os.path as osp
import sys
sys.path.insert(0, osp.join(osp.dirname(osp.abspath(__file__)), '../'))

or run the following command in the terminal of corresponding folder.

export PYTHONPATH=`pwd`:$PYTHONPATH