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SimBAxTF or SimBA?

!!! IMPORTANT !!! You can choose to install SimBA as a standalone package or install SimBA with TensorFlow integration.

  1. If you would like to be able to call DeepLabCut or DeepPoseKit commands via the SimBA interface (whuch requires a local GPU), please install SimBAxTF from the master branch. Please see full instructions below.

  2. If you do not want to use TensorFlow through SimBA on your local machine, and instead have DeepLabCut/DeepPoseKit installed elsewhere, please install SimBA from the SimBA_no_TF branch. This does not require a GPU, or local installations of DeepLabCut or DeepPoseKit. Please see full instructions below. This version of SimBA includes all functionalities of SimBAxTF, except for the ability to generate pose-estimation models through the SimBA GUI. Pose-estmation model results can still be imported and analysed.

Requirements

  1. Python 3.6 <-- VALIDATED WITH 3.6.0
  2. Git
  3. FFmpeg

Installing SimBA

Install SimBAxTF with integrated TensorFlow (use this installation method when running DeepLabCut or DeepPoseKit locally using a GPU)

Open bash or command prompt and run the following commands on current working directory

git clone -b master https://github.com/sgoldenlab/simba.git

pip3 install -r simba/simba/requirements.txt

Install SimBA standalone package (without TensorFlow or integrated DeepLabCut/DeepPoseKit support)

Open bash or command prompt and run the following commands on current working directory

git clone -b SimBA_no_TF https://github.com/sgoldenlab/simba.git

pip3 install -r simba/SimBA/requirements.txt

How to launch SimBA

  1. Open up command prompt in the SimBA folder

  2. In the command prompt type

python SimBA.py
  1. Hit Enter.

Note: For this launch to work you need to add python to the environmental path.

python dependencies

package ver.
Pillow 5.4.1
deeplabcut 2.0.9
eli5 0.10.1
imblearn 0.5.0
imutils 0.5.2
matplotlib 3.0.3
Shapely 1.6.4.post2
deepposekit 0.3.5
dtreeviz 0.8.1
opencv_python 3.4.5.20
numpy 1.18.1
imgaug 0.4.0
pandas 0.25.3
scikit_image 0.14.2
scipy 1.1.0
seaborn 0.9.0
sklearn 1.1.0
scikit-learn 0.22.1
tensorflow_gpu 0.14.1
scikit-learn 0.22.1
tqdm 4.30.0
yellowbrick 0.9.1
xgboost 0.9
tabulate 0.8.3
tables ≥ 3.5.1