Open source technology for agriculture, farming, and gardening
FarmVibes.AI: Multi-Modal GeoSpatial ML Models for Agriculture and Sustainability
Robust and efficient coverage paths for autonomous agricultural vehicles. A modular and extensible Coverage Path Planning library
A system that uses ESP-NOW, LoRa, and other protocols to transport sensor data in remote areas without relying on WiFi.
A PHP based, free, and open source farming management system.
Open source Farm management Information System (FMIS) - Connecting farms to the world
An open-source, low-cost, image-based weed detection device for in-crop and fallow scenarios.
Factura Electrónica AFIP y otros servicios web (proyecto software libre) — Interfases, tools and apps for Argentina's gov't. webservices (soap, com/dll simil-ocx, pdf, dbf, xml, json, etc.) #python
[IROS24] Offical Code for "FruitNeRF: A Unified Neural Radiance Field based Fruit Counting Framework" - Inegrated into Nerfstudio
Building the Coffee Quality Institute Database
Agricultural Supply Chain Dapp With Micro-Finance
AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.
PyTorch implementation of the model presented in "Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention"
The core repository for the FOODON food ontology project. This holds the key classes of the ontology; larger files and the results of text-mining projects will be stored in other repos.
The official repository for the EuroCrops dataset.
One stop application for farmers. 📱👨🌾 It provides E-commerce, social media, reading articles, APMC statistics, weather forecasting, etc. This application uses the best technologies and practices and serves the need very well. 🚜
A PyTorch Implementation of Jiaxuan You's Deep Gaussian Process for Crop Yield Prediction
PyTorch implementation of U-TAE and PaPs for satellite image time series panoptic segmentation.
The world’s first community-led, not-for-profit, digital platform joining farmers and scientists together for participatory assessment of social, environmental and economic outputs of farming systems.
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