Installation
Important
We currently only support Linux/MacOS installations
Note
Please do not forget to install the other optional dependencies if you would like to use them:
-
MMCV+MMDetection, and/or
-
YOLOv5
A- Installation using pip
Option 1: Installing from pypi repository [Stable Version]
To install icevision package together with almost all dependencies:
$ pip install icevision[all]
Option 2: Installing an editable package locally [For Developers]
Note
This method is used by developers who are usually either:
-
actively contributing to
icevision
project by adding new features or fixing bugs, or -
creating their own extensions, and making sure that their source code stay in sync with the
icevision
latest version.
Then, clone the repo and install the package:
$ git clone --depth=1 https://github.com/airctic/icevision.git
$ cd icevision
$ pip install -e .[all,dev]
$ pre-commit install
Option 3: Installing a non-editable package from GitHub:
To install the icevision package from its GitHub repo, run the command here below. This option can be used in Google Colab,
for example, where you might install the icevision latest version (from the master
branch)
$ pip install git+git://github.com/airctic/icevision.git#egg=icevision[all] --upgrade
B- Installation using conda
Creating a conda environment is considered as a best practice because it avoids polluting the default (base) environment, and reduces dependencies conflicts. Use the following command in order to create a conda environment called icevision
$ conda create -n icevision python=3.8 anaconda
$ conda activate icevision
$ pip install icevision[all]
Optional dependencies
MMDetection Installation
We need to provide the appropriate version of the mmcv-full
package as well as the cuda
and the torch
versions. Here are some examples for both the CUDA and the CPU versions
Torch and CUDA version
For the torch version use torch.__version__
and replace the last number with 0.
For the cuda version use: torch.version.cuda
.
Example: TORCH_VERSION = torch1.8.0
; CUDA_VERSION = cu101
CUDA-Version Installation Example
$ pip install mmcv-full=="1.3.3" -f https://download.openmmlab.com/mmcv/dist/CUDA_VERSION/TORCH_VERSION/index.html --upgrade
$ pip install mmdet
CPU-Version Installation
$ pip install mmcv-full=="1.3.3+torch.1.8.0+cpu" -f https://download.openmmlab.com/mmcv/dist/index.html --upgrade
$ pip install mmdet
YOLOv5 Installation
$ pip install yolov5-icevision --upgrade
Troubleshooting
MMCV is not installing with cuda support
If you are installing MMCV from the wheel like described above and still are having problems with CUDA you will probably have to compile it locally. Do that by running:
pip install mmcv-full
If you encounter the following error it means you will have to install CUDA manually (the one that comes with conda installation will not do).
OSError: CUDA_HOME environment variable is not set. Please set it to your CUDA install root.
sudo apt install nvidia-cuda-toolkit
nvcc --version
Error: Failed building wheel for pycocotools
If you encounter the following error, when installation process is building wheel for pycocotools:
unable to execute 'gcc': No such file or directory
error: command 'gcc' failed with exit status 1
sudo apt install gcc
gcc --version
gcc (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Copyright (C) 2019 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.