This is a web application🌐 which could help easily diagnose diseases in plants 🌱 using Machine Learning all on the web, powered by TensorFlow JS.
You can use and test the latest web app from below 👇
- Creates a TensorFlow Model for identifying plant diseases
- Creates optimized TensorFlow JS Models
- Uses TensorFlow JS to perform inferences on-device
- Creates a fully functional web app using React
- Exposes a hosted API built with TensorFlow Serving for inferences from the TensorFlow Model
Click to View Plant AI web app Design from below
This notebook contains the code to train a model on the PlantVillage dataset
to identify diseases from plant images. Here we provide a subset of our
experiments on working with this data. Finally we export our model as a
TensorFlow SavedModel
.
This notebook shows the the process of converting the TensorFlow SavedModel
we built in the prequel notebook to the TFJS format for the Plant AI model. It
also shows performing optimizations on this.
This notebook shows the the process of converting the TensorFlow SavedModel
we built in the prequel notebook to the TF Lite format for the Plant AI model.
To get up and running with this web-app, run the following commands, make sure you have Node.js installed. This runs the app in development mode:
git clone https://github.com/Rishit-dagli/Greenathon-Plant-AI # or clone your own fork
cd Greenathon-Plant-AI
npm install
npm start
Your app should now be running on localhost:3000 🚀.
This project uses GitHub Super Linter which is Combination of multiple linters to install as a GitHub Action.
Following Linters are used internally by super linter (enabled for this project):
Awesome! If you want to contribute to this project, you're always welcome! See Contributing Guidelines. You can also take a look at Greenathon-Plant-AI's Project Status Tracker for getting more information about current or upcoming tasks.
Have any questions, doubts or want to present your opinions, views? You're always welcome. You can start discussions.
@misc{hughes2016open,
title={An open access repository of images on plant health to enable the development of mobile disease diagnostics},
author={David. P. Hughes and Marcel Salathe},
year={2016},
eprint={1511.08060},
archivePrefix={arXiv},
primaryClass={cs.CY}
}
Copyright 2020 Rishit Dagli
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.