https://github.com/paramsiddharth/cotton-leaf-disease
An implementation of a cotton leaf disease prediction machine learning model in TensorFlow.
https://github.com/paramsiddharth/cotton-leaf-disease
Last synced: over 1 year ago
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An implementation of a cotton leaf disease prediction machine learning model in TensorFlow.
- Host: GitHub
- URL: https://github.com/paramsiddharth/cotton-leaf-disease
- Owner: paramsiddharth
- Created: 2020-10-16T07:37:17.000Z (almost 6 years ago)
- Default Branch: main
- Last Pushed: 2020-10-17T02:14:49.000Z (almost 6 years ago)
- Last Synced: 2024-05-22T20:22:52.917Z (about 2 years ago)
- Language: Python
- Size: 1.09 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Cotton Leaf Disease Prediction
An implementation of a cotton leaf disease prediction machine learning model in TensorFlow. The model was trained by Ritesh ([@DARK-art108](https://github.com/DARK-art108)). The application operates via a web interface where one may upload an image of a cotton plant/leaf and retrieve the prediction of whether or not it is infected.
## Execution
- Install all the PyPI requirements.
```
> pip3 install -r requirements.txt
```
- Manually place the model file `model_resnet.hdf5` in the application directory (optional).
- Start the Flask server.
```
> flask run
```
Make sure that the `FLASK_APP` enviroment variable is either empty or set to `app.py`. You can manually do that by executing `export FLASK_APP=app.py`.
The application will try to locate the model i. e. `model_resnet.hdf5` in the current directory, and if it is not found, download it.
Made with ❤ by [Ritesh](https://github.com/DARK-art108) and [Param](http://www.paramsid.com).