Please use one (or more) of the supplied Anaconda environments for a fast and easy installation process.
(0) Be sure you have Anaconda 3 installed! https://www.anaconda.com/distribution/, and get familiar with using "cmd" or terminal!
(1) Either go to www.deeplabcut.org (at the bottom of the page) to download the correct environment file:
or download or git clone this repo (in the terminal/cmd program, while in a folder you wish to place DeepLabCut
type git clone https://github.com/AlexEMG/DeepLabCut.git).
Now, always in Terminal (or Command Prompt), go to the folder named conda-environments using the command "cd" (which stands for change directory). For example, if you downloaded or cloned the repo onto your Desktop, the command may look like:
cd C:\Users\YourUserName\Desktop\DeepLabCut\conda-environments
To get the location right, a cool trick is to drag the folder and drop it into Terminal. Alternatively, you can (on Windows) hold SHIFT and right-click > Copy as path, or (on Mac) right-click and while in the menu press the OPTION key to reveal Copy as Pathname.
(2) Now, depending on which file you want to use (if with GPUs, see extra note below!!!), open the program terminal or cmd where you placed the file (i.e. cd conda-environments) and then type:
conda env create -f DLC-CPU.yaml
or
conda env create -f DLC-GPU.yaml
(3) You can now use this environment from anywhere on your comptuer (i.e. no need to go back into the conda- folder). Just enter your environment by running:
- Ubuntu/MacOS:
source/conda activate nameoftheenv(i.e. on your Mac:conda activate DLC-CPU) - Windows:
activate nameoftheenv(i.e.activate DLC-GPU)
Now you should see (nameofenv) on the left of your teminal screen, i.e. (dlc-macOS-CPU) YourName-MacBook...
NOTE: no need to run pip install deeplabcut, as it is already installed!!! :)
However, if you ever want to update your DLC, just run pip install --upgrade deeplabcut once you are inside your env. You can check the version by running import deeplabcut deeplabcut.__version__. Don't be afraid to update, DLC is backwards compatable with your 2.0+ projects and peformance continues to get better and new features are added nearly monthly.
Great, that's it!
Simply run ipython or pythonw (macOS only) to lauch the terminal, jupyter notebook to lauch a browser session, or ipython/pythonw, import deeplabcut, deeplabcut.launch_dlc() to use our Project Manager GUI! Many more details here!
Some users might want to create their own env. Here is an example. In the terminal type:
conda create -n DLC python=3.7 tensorflow=1.13.1
(this would be for CPU-based tensorflow; for GPU support use tensorflow-gpu=1.13.1).
The only thing you then need to add to the env is deeplabcut (pip install deeplabcut) and wxPython, which is OS dependent.
For Windows and MacOS, you just run pip install -U wxPython but for linux you need the specific wheel (https://wxpython.org/pages/downloads/index.html).
Now just follow the user guide to get DeepLabCut up and running in no time!
Just as a reminder, you can exit the environment anytime and (later) come back! So the environments really allow you to manage multiple packages that you might want to install on your computer.
Here are some conda environment management tips: https://kapeli.com/cheat_sheets/Conda.docset/Contents/Resources/Documents/index
GPUs: The ONLY thing you need to do first if you have an NVIDIA GPU, NVIDIA driver installed, and CUDA <=10 (currently, TensorFlow 1.13.1 is installed inside the env, so you can install up to CUDA 10 and an appropriate driver). Please note that only NVIDA GPUs are supported.