Tools for detecting wildlife in aerial images using active learning
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Updated
Jul 25, 2024 - Python
Tools for detecting wildlife in aerial images using active learning
A Raspberry Pi camera system with a live video feed, motion detection system, H.264 mp4 recording capabilities and a storage management system with support for remote storage. The recorder supports pre-motion frame recording and no internet environments (e.g. Wildlife cameras).
Hypraptive BearID project. FaceNet for bears.
Code for paper "From Crowd to Herd Counting: How to Precisely Detect and Count African Mammals using Aerial Imagery and Deep Learning?"
Distance Estimation for Estimating Animal Abundance
Pytorch implementation for "Iterative Human and Automated Identification of Wildlife Images" (Nature -Machine Intelligence, 2021)
The Image Level Label to Bounding Box (IL2BB) pipeline automates the generation of labeled bounding boxes by leveraging an organization’s previous labeling efforts.
Outil d'import de données entre instances GeoNature (côté client)
Code and supplementary material for "SOCRATES: Introducing Depth in Visual Wildlife Monitoring using Stereo Vision" (WIP)
Code for training and evaluating a detector for the USGS Izembek goose survey dataset
Determine the 🐦 from its 🎵
A Python package to download and interact with the CITES trade database
Simple Python program with a GUI built using tkinter that tests your knowledge of identifying species. Inspired by a course I took in university where I had to learn to identify species but forgot most of them. Currently, only bird species found in Ontario are available in the Images directory. You can contribute to this if you happen to stumble…
Reserve Design Optimizing Functional Connectivity and Animal Density
CycleGAN Model in PyTorch for translating animal image to other domain irrespective of the pairing between two images.
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