This repository contains Crop Monitoring models developed with drone images and computer vision
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Within this repository, you'll discover various models and computational tools designed for crop monitoring purposes. These resources can be used for predicting the health status of vineyards using images captured by drones.
The repository folders are structured as follow:
- data: here you should add the UC1 GITHUB DATA FOLDER that you could download from Zenodo.
- top_view: it has some top-view level calculations for vegetation analysis.
- calculate_vegetation_indexes
- create_grid
- extract_vineyard_data
- top_level_detection
- models: models developed for crop monitoring
- platform.json: organized information about the models
The models developed are the following:
This model has been trained with YOLOv8 and is able to detect the plants and provide information about its health status from a plant-view level.
This algorithm contains the complete workflow from detecting a plant in a row-view image to locate this plant in the global-view orthomosaic to visualize its health status at a global scope. It also locates the drone positions.
- Esther Vera - Noumena - Esther Vera
This project is funded by the European Union, grant ID 101060643.
