waruguru/deep-learning-in-agriculture

Deep learning in agriculture

Deep Learning Based Plant Diseases Recognition

This simple website uses a CNN to predict the disease on a plant leaf. It consists of 38 classes of different healthy and diseased plant leaves. These 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/waruguru/Plant-Disease-Detector.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:

   python 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.

install Python3.6 (Ubuntu)

1. Open terminal via Ctrl+Alt+T or searching for “Terminal” from app launcher. When it opens, run command to add the PPA:

   sudo add-apt-repository ppa:jonathonf/python-3.6

2. Then check updates and install Python 3.6 via commands:

   • sudo apt-get update
   • sudo apt-get install python3.6

3. Check if python 3.6 was installed properly python3 -V

Get sample pictures

1. You can get sample pictures from here: https://www.kaggle.com/abdallahalidev/plantvillage-dataset

Screenshots