Skip to content

A plant disease detector (classifier) based on the PlantVillage dataset

License

Notifications You must be signed in to change notification settings

Mobasherah12/Detection-of-Plant-Disease

 
 

Repository files navigation

Detection of Plant Disease

Plant Image

Introduction

Getting affected by a disease is very common in plants due to various factors such as fertilizers, cultural practices followed, environmental conditions, etc. These diseases hurt agricultural yield and eventually the economy based on it. 

Any technique or method to overcome this problem and getting a warning before the plants are infected would aid farmers to efficiently cultivate crops or plants, both qualitatively and quantitatively. Thus, disease detection in plants plays a very important role in agriculture.

The PlantVillage Dataset

We use a publicly available and quite famous, the PlantVillage Dataset. The dataset was published by crowdAI during the "PlantVillage Disease Classification Challenge"

The dataset consists of about 54,305 images of plant leaves collected under controlled environmental conditions. The plant images span the following 14 species:

Apple, Blueberry, Cherry, Corn, Grape, Orange, Peach, Bell Pepper, Potato, Raspberry, Soybean, Squash, Strawberry, and Tomato.

The dataset contains a total of 38 classes of plant disease and 1 class of background images listed below:

  1. Apple Scab
  2. Apple Black Rot
  3. Apple Cedar Rust
  4. Apple healthy
  5. Blueberry healthy
  6. Cherry healthy
  7. Cherry Powdery Mildew
  8. Corn Gray Leaf Spot
  9. Corn Common Rust
  10. Corn healthy
  11. Corn Northern Leaf Blight
  12. Grape Black Rot
  13. Grape Black Measles
  14. Grape Leaf Blight
  15. Grape healthy
  16. Orange Huanglongbing
  17. Peach Bacterial Spot
  18. Peach healthy
  19. Bell Pepper Bacterial Spot
  20. Bell Pepper healthy
  21. Potato Early Blight
  22. Potato healthy
  23. Potato Late Blight
  24. Raspberry healthy
  25. Soybean healthy
  26. Squash Powdery Mildew
  27. Strawberry Healthy
  28. Strawberry Leaf Scorch
  29. Tomato Bacterial Spot
  30. Tomato Early Blight
  31. Tomato Late Blight
  32. Tomato Leaf Mold
  33. Tomato Septoria Leaf Spot
  34. Tomato Two Spotted Spider Mite
  35. Tomato Target Spot
  36. Tomato Mosaic Virus
  37. Tomato Yellow Leaf Curl Virus
  38. Tomato healthy

Due to the limited computational power, it is difficult to train the classification model locally on a majority of normal machines. Therefore, we use the processing power offered by Google Colab notebook as it connects us to a free TPU instance quickly and effortlessly.

💻Tech Stacks


Jupyter Python HTML5


Contributing Guidelines 👷

  • Fork the project.
  • Create your Feature Branch
git checkout -b '<your_branch_name>'
  • Stage your changes
git add .
  • Commit your changes
git commit -m '<your_commit_message>'
  • Check for Status to be sure everything is added
git status
  • Check for your remote
git remote -v
  • Push changes to remote
git push origin '<your_branch_name>'

📌 Opensource Programs

This project is a part of following Open Source Program



Useful Links

  1. The PlantVillage dataset paper can be found here.


Project Admin👨‍:


    


✨Our valuable Contributors :



License:

MIT License

📜 Code Of Conduct:

Click to read

About

A plant disease detector (classifier) based on the PlantVillage dataset

Resources

License

Code of conduct

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 80.7%
  • Python 18.8%
  • HTML 0.5%