ACM_FARM_HEALTH'24
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Farm_Heath is specially decined platform for farmers , it uses neural networks to predict the disease of potato plant by just unploading the photo of leaf from your device, with the help of NLP it will also be providing insides on analysing the growth of fertiliser product using sentimental analysis and summary of huge reviews in 5 lines . This website also be providing some useful farming laws and schemes given by our government which are available on regional languages such as hindi, english, & tamil .
In this section you should provide instructions on how to use this repository to recreate your project locally.
- Clone the repo
git clone https://github.com/Adityapratapsingh28/ACM_FARM_HEALTH-24.git
Here, list all libraries, packages and other dependencies that need to be installed to run your project. Include library versions and how they should be installed if a special requirement is needed.
Make sure you make requirements.txt having all the dependencies required to run the code
For example, this is how you would list them:
- Installing all dependencies
pip install -r requirements.txt
- Example of requirements.txt
tensorflow==2.5.0 fastapi uvicorn python-multipart pillow tensorflow-serving-api==2.5.0 matplotlib numpy
farmheathvdeo.mp4
Farmers in india due to lack of knowledge and awareness about plant disesae did'nt know that from which disesae thier plant is suffering from and which lead them to the huge ecomonic loss and crop wastage , many websites are there to help them but these websites are only available on English language , but since majorty of the farmers only knows thier regional and local languages.This language issue create more complication to communicate with them and to help them using usefull technology.
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Plant disease prediction
- Our Deep learning model will take the image of plant from user and predict the disease from which thbe plant is suffering from.
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Fertilizer analysis summarization
- NLP model using webscrapping and month on month sentimental analysis on amazon reviews of each year given by user and it will provide the summary of all the reviews so the farmer can get a idea that how is the product is that product is going to help him or not.
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Multilingual website
- Our website is available on three languages right now that are hindi , english & tamil. This will provide ease of communication and readability to farmers.
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Farmers laws/schemes
- Since many farmers are unaware about the farmer laws given by our goverment and schemes provided by the goverment to help farmers, so on our website we have provided the laws & schemes in a very easy simple language so the farmer can understand easily.
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Website Interface:
- User-friendly website interface for easy interaction and navigation.
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Enhanced Model Training:
- Our deep learning model is trained and tested and the accuracy is 98% , while our summarization analysis model is also performing good.
Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
Nilesh Kanti - Linkedin
Aditya Pratap Singh - Linkedin
Srijan Sarkar - Linkedin
Sai Ganeshan M - Linkedin
You can acknowledge any individual, group, institution or service.