Metadata-Version: 2.1
Name: animl
Version: 1.1.2
Summary: Tools for classifying camera trap images
Author-email: Kyra Swanson <tswanson@sdzwa.org>
Project-URL: Homepage, https://github.com/conservationtechlab/animl-py
Keywords: camera trap,ecology,conservation,zoo,SDZWA,conservationtechlab
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: wget
Requires-Dist: humanfriendly
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: tqdm
Requires-Dist: pyyaml
Requires-Dist: pillow
Requires-Dist: opencv-python <=4.8.1.78
Requires-Dist: numpy <=1.19.5
Requires-Dist: pandas <=1.3.5
Requires-Dist: protobuf <=3.19.4
Requires-Dist: termcolor <=1.1.0
Requires-Dist: tensorboard <=2.6.0
Requires-Dist: tensorboard-data-server <=0.6.1
Requires-Dist: tensorboard-plugin-wit <=1.8.1
Requires-Dist: tensorflow-estimator <=2.6.0
Requires-Dist: tensorflow-gpu <=2.6.2
Requires-Dist: tensorflow-io-gcs-filesystem <=0.24.0
Requires-Dist: tf-estimator-nightly <=2.8.0.dev2021122109
Requires-Dist: torch <=1.13.1
Requires-Dist: torchvision <=0.14.1

# 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](https://github.com/conservationtechlab/animl)

Table of Contents
1. Installation
2. [Usage](#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
