animl 1.1.3

Tools for classifying camera trap images

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

1. Installation
2. 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