Created with the support of the IoT-Ngin 2nd Open Call
This repository contains helpfull utility scripts and notebooks for the ML analysis of the data generated from the LEEAF IoT-Ngin OC2 project.
A helper notebook used to review and parse the datasets used in the project.
A jupyter notebook to train a leaf detection model using the trainYOLO platform.
An AWS lambda function to check newly collected images for leafs and generate cropped leaf images from them using a YOLO-based ML model.
Classification contains a benchmark file and ML models that can be used to test the speed of the classification process on different systems.
Edge contains the implementation of the edge server of LEEAF. An application that is designed to process image files and upload the extracted leaves with their characterization to the cloud.