/Plant_Disease_Prediction

An end to end application which predicts whether the cotton plant is a diseased plant or leaf or a fresh cotton plant or leaf.

Primary LanguageJupyter NotebookMIT LicenseMIT

Plant Disease Prediction

An end to end application which predicts whether the cotton plant belongs to the following set of classes.

  • Diseased Cotton Leaf.
  • Diseased Cotton Plant.
  • Fresh Cotton Leaf.
  • Fresh Cotton Plant.

Training

  • For Training Purpose Refer to the following Notebooks.
  • Click Here to view the training notebooks
  • The training is done on Google Colab , if you have your own GPU you can train on your local machine.
  • Dataset can be downloaded from here.Click Here
  • After Downloading the dataset Unzip it and place it under the Dataset Folder , all the path in the colab notebook is according to my relative path so it needs to be changed accordingly.

Inference

  • For Inference Purpose, create a virtual environment and install requirements.txt .

  • After performing the above step, run main.py.

  • After running the script Flask Server will start at http://127.0.0.1:5001/ , Copy this URL and open it in your browser.

  • Your flask application is now up and running and should look something like this. Image of Landing Page.

  • Click on the Choose button and upload the plant image , after uploading the image the page will look something like this. Image of Landing Page.

  • After Uploading the Image, click on the Predict button, after few seconds the output will appear something like this. Image of Landing Page.