This is a web application based on machine/deep learning models for crop disease detection and fertilizer/crop recommendation
Table of Contents
- Crop recommendation: By using the soil data such as: NPK ratios, moisture, temperature and amount of rainfall in the field region the model can recommend the best crop to grow
- Fertilizer recommendation: With the given soil data(type, temparture, Ph,...) and NPK ratios and the crop type, the app allow the user to know the best fertilzer to use for ensuring the good health of crops and thus maximazing the global yield of the field
- Crop diseases detection: The user need to give the crop image and it's type and the image recognition models will predict if the plant is healthy or not.
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To use this project you need to follow this steps:
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Make sure python3 is installed if not you can get it here
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Clone this repository:
git clone https://github.com/kaymen99/AgriGo.git cd AgriGo/AgriGo -
Install all the dependencies:
pip install -r requirements.txt
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And finally run this command:
python app.py
The datasets used for this project are from kaggle:
If you have any question or problem running this project just contact me: aymenMir1001@gmail.com
Distributed under the MIT License. See LICENSE.txt for more information.