Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Ray | 28,919 | 80 | 363 | 7 hours ago | 95 | December 04, 2023 | 3,474 | apache-2.0 | Python | |
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads. | ||||||||||
Gradio | 24,498 | 1 | 229 | 7 hours ago | 534 | December 05, 2023 | 445 | apache-2.0 | Python | |
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work! | ||||||||||
Bentoml | 5,953 | 12 | 12 hours ago | 119 | November 20, 2023 | 182 | apache-2.0 | Python | ||
Build Production-Grade AI Applications | ||||||||||
Fate | 5,313 | 1 | 12 hours ago | 33 | September 20, 2023 | 812 | apache-2.0 | Python | ||
An Industrial Grade Federated Learning Framework | ||||||||||
Seldon Core | 4,009 | 13 | 7 | 8 days ago | 48 | August 17, 2023 | 113 | apache-2.0 | HTML | |
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models | ||||||||||
Production Level Deep Learning | 3,957 | 20 days ago | 7 | |||||||
A guideline for building practical production-level deep learning systems to be deployed in real world applications. | ||||||||||
Orchest | 3,876 | 6 months ago | 19 | December 13, 2022 | 125 | apache-2.0 | TypeScript | |||
Build data pipelines, the easy way 🛠️ | ||||||||||
Opyrator | 2,964 | 8 days ago | 11 | May 04, 2021 | 5 | mit | Python | |||
🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more. | ||||||||||
Transformer Deploy | 1,542 | a month ago | 53 | apache-2.0 | Python | |||||
Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀 | ||||||||||
Seldon Server | 1,420 | 4 years ago | 44 | June 28, 2017 | 26 | apache-2.0 | Java | |||
Machine Learning Platform and Recommendation Engine built on Kubernetes |
EcoAssist is an application designed to streamline the work of ecologists dealing with camera trap images. Its an AI platform that allows you to analyse images with machine learning models for automatic detection, offering ecologists a way to save time and focus on conservation efforts.
Please use the following citations if you used EcoAssist in your research.
@article{van_Lunteren_EcoAssist_2023,
author = {van Lunteren, Peter},
doi = {10.21105/joss.05581},
journal = {Journal of Open Source Software},
month = aug,
number = {88},
pages = {5581},
title = {{EcoAssist: A no-code platform to train and deploy custom YOLOv5 object detection models}},
url = {https://joss.theoj.org/papers/10.21105/joss.05581},
volume = {8},
year = {2023}
}
@article{Beery_Efficient_2019,
title = {Efficient Pipeline for Camera Trap Image Review},
author = {Beery, Sara and Morris, Dan and Yang, Siyu},
journal = {arXiv preprint arXiv:1907.06772},
year = {2019}
}