Tools for classifying camera trap images
Project description
animl-py
AniML comprises a variety of machine learning tools for analyzing ecological data. This Python package includes a set of functions to classify subjects within camera trap field data and can handle both images and videos. This package is also available in R: animl
Table of Contents
- Installation
- Usage
Installation Instructions
It is recommended that you set up a conda environment using the included environment.yml folder. See Dependencies below for more detail. You will have to activate the conda environment first each time you want to run AniML from a new terminal.
git clone https://github.com/conservationtechlab/animl-py.git
cd animl-py
conda env create --file environment.yml
conda activate animl-gpu
pip install -e .
From PyPi
conda create -n animl-gpu python=3.7
conda activate animl-gpu
conda install cudatoolkit=11.3.1 cudnn=8.2.1
pip install animl
Dependencies
We recommend running AniML on GPU-enabled hardware. **If using an NVIDIA GPU, ensure driviers, cuda-toolkit and cudnn are installed. The /models/ and /utils/ modules are from the YOLOv5 repository. https://github.com/ultralytics/yolov5
Python Package Dependencies
- pandas = 1.3.5
- tensorflow = 2.6
- torch = 1.13.1
- torchvision = 0.14.1
- numpy = 1.19.5
- cudatoolkit = 11.3.1 **
- cudnn = 8.2.1 **
A full list of dependencies can be found in environment.yml
Verify Install
With the conda environment active:
python3 -m animl /path/to/example/folder
Usage
Inference
Training
Project details
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