Overview

A Collaborative Deep Learning Framework for Conservation

👋 Welcome to Pytorch-Wildlife¶

PyTorch-Wildlife is an AI platform designed for the AI for Conservation community to create, modify, and share powerful AI conservation models. It allows users to directly load a variety of models including MegaDetector, DeepFaune, and HerdNet from our ever expanding model zoo for both animal detection and classification. In the future, we will also include models that can be used for applications, including underwater images and bioacoustics. We want to provide a unified and straightforward experience for both practicioners and developers in the AI for conservation field. Your engagement with our work is greatly appreciated, and we eagerly await any feedback you may have.

🚀 Quick Start¶

👇 Here is a brief example on how to perform detection and classification on a single image using PyTorch-wildlife

import numpy as np
from PytorchWildlife.models import detection as pw_detection
from PytorchWildlife.models import classification as pw_classification

img = np.random.randn(3, 1280, 1280)

# Detection
detection_model = pw_detection.MegaDetectorV6() # Model weights are automatically downloaded.
detection_result = detection_model.single_image_detection(img)

#Classification
classification_model = pw_classification.AI4GAmazonRainforest() # Model weights are automatically downloaded.
classification_results = classification_model.single_image_classification(img)

⚙️ Install Pytorch-Wildlife¶

pip install PytorchWildlife

Please refer to our installation guide for more installation information.

🖼️ Examples¶

Image detection using `MegaDetector`¶

animal_det_1
Credits to Universidad de los Andes, Colombia.

Image classification with `MegaDetector` and `AI4GAmazonRainforest`¶

animal_clas_1
Credits to Universidad de los Andes, Colombia.

Opossum ID with `MegaDetector` and `AI4GOpossum`¶

opossum_det
Credits to the Agency for Regulation and Control of Biosecurity and Quarantine for Galápagos (ABG), Ecuador.