/Plant-Diseases-Recognition

CNN classifier for recognizing plant diseases using Keras

Primary LanguageJavaScript

Deep Learning Based Plant Diseases Recognition

This django based web application uses a trained convolutional neural network to identify the disease present on a plant leaf. It consists of 38 classes of different healthy and diseased plant leaves. The 38 classes are:

  1. Apple-> Apple scab
  2. Apple-> Black rot
  3. Apple-> Cedar apple rust
  4. Apple-> healthy
  5. Blueberry-> healthy
  6. Cherry-> Powdery mildew
  7. Cherry-> healthy
  8. Corn-> Cercospora leaf spot (Gray leaf spot)
  9. Corn-> Common rust
  10. Corn-> Northern Leaf Blight
  11. Corn-> healthy
  12. Grape-> Black rot
  13. Grape-> Esca (Black Measles)
  14. Grape-> Leaf blight (Isariopsis Leaf Spot)
  15. Grape-> healthy
  16. Orange-> Haunglongbing (Citrus greening)
  17. Peach-> Bacterial spot
  18. Peach-> healthy
  19. Pepper, bell-> Bacterial spot
  20. Pepper, bell-> healthy
  21. Potato-> Early blight
  22. Potato-> Late blight
  23. Potato-> healthy
  24. Raspberry-> healthy
  25. Soybean-> healthy
  26. Squash-> Powdery mildew
  27. Strawberry-> Leaf scorch
  28. Strawberry-> healthy
  29. Tomato-> Bacterial spot
  30. Tomato-> Early blight
  31. Tomato-> Late blight
  32. Tomato-> Leaf Mold
  33. Tomato-> Septoria leaf spot
  34. Tomato-> Spider mites (Two-spotted spider mite)
  35. Tomato-> Target Spot
  36. Tomato-> Tomato Yellow Leaf Curl Virus
  37. Tomato-> Tomato mosaic virus
  38. Tomato-> healthy

Requirements:

  1. Python
  2. Tensorflow
  3. Keras
  4. Django
  5. PIL
  6. Numpy

Steps to run the application:

This application requires Python 3.6 or higher

  1. Download the repository by clicking on the download button or type the following command in CMD to clone the repository:

    git clone https://github.com/saroz014/Plant-Diseases-Recognition.git

  2. Download model from the following link and paste it in the \plant_diseases\plant_app folder: https://drive.google.com/file/d/1FZXraDDPqbRTX-QeiQclfojgtoLddxQ_/view

  3. (Optional) Create a virtual enviourment. Refer this tutorial to learn how to create a virtual enviourment: https://www.youtube.com/watch?v=APOPm01BVrk If you create a virtual enviourment, make sure it is activated and you execute all commands from within the virtual enviournment. Skip this step if you are unsure about how it works.

  4. Install required packages:

    pip install -r requirements.txt

  5. Navigate to \plant_diseases directory and run the application with the following command:

    py manage.py runserver

  6. A link will appear in your command prompt. Copy this link and paste it in your browser, press enter.

  7. Your application is running. Choose any infected image to get results.

Screenshots