This repository contains model code and technical report by team Tiny_MONO for the Scalable and High-Performance TinyML Solutions for Plant Disease Detection Challenge by ITU.
We have attached the Tensorflow lite libraries which can be directly imported into the microcontroller based devices, the files along with their Edge Impulse project ID is provided below: ei-crop-disease---apple :293067 ei-crop-disease---corn : 293499 ei-crop-disease---grape : 306987 ei-crop-disease---potato : 293549
The live Testing using the pre trained Model deployed in Arduino Nano 33 BLE Sense with OV7675 Cam Module is recorded and can be accessed through this link: https://drive.google.com/drive/folders/1lv9VB_PKtQA60QRmCKNdEIZHZCiPrps_?usp=sharing
The dataset used for this study is: https://paperswithcode.com/dataset/plantvillage Additionally, the Custom Model developed using Pytorch Framework is attached (PV disease detection.ipynb).