sarra831/Plant_Disease_Detection

Plant Disease Detector Web Application

Plant Disease Detector

_{Created by Shubham Kumar and other contributors}

---

My Article in TowardsDataScience

Models are trained on the preprocessed dataset which can be downloaded here.

Local Set-Up

Local:

• It is recommended to set up the project inside a virtual environment to keep the dependencies separated.
  • Python
  • Conda
• Activate your virtual environment.
• Install dependencies by running pip install -r requirements.txt.
• Start up the server by running python app/server.py serve.
• Visit http://localhost:8080/ to explore and test.

Docker:

Make Sure the Docker is installed in your local Machine. Click Here to know that how to install Docker.

• Mac:

  $ git clone https://github.com/imskr/Plant_Disease_Detection.git
  $ cd Plant_Disease_Detection
  $ docker build -t fastai-v3 .
  $ docker run --rm -it -p 8080:8080 fastai-v3

  Go to http://localhost:8080/ to test your app.

• Windows:

  $ git clone https://github.com/imskr/Plant_Disease_Detection.git
  $ cd Plant_Disease_Detection
  $ docker build -t fastai-v3 .
  $ docker run --rm -it -p 8080:8080 fastai-v3

  Go to http://localhost:8080/ to test your app.

  Note: Windows 10 Pro required.

• Linux:

  $ git clone https://github.com/imskr/Plant_Disease_Detection.git
  $ cd Plant_Disease_Detection
  $ docker build -t fastai-v3 .
  $ docker run --rm -it -p 8080:8080 fastai-v3
  

  Note: If this doesn't work use --no-cache flag in the build command.

  Go to http://localhost:8080/ to test your app.

Deployment

• Google Cloud Platform:

  The complete guideline to deploy the Plant Disease Detection App can be found here

• AWS Elastic BeanStalk:

  The complete guideline to deploy the Plant Disease Detection App can be found here

Server Set-Up (For Training)

• Google Cloud Platform (Intermediate) - The complete tutorial can be found here

• Gradient (Easy) - The complete tutorial can be found here

• AWS EC2 (Advance) - The complete tutorial can be found here

Dataset Description:

Name	No of Classes	Class Names
Apple	04	'Apple___Apple_scab','Apple___Black_rot','Apple___Cedar_apple_rust' 'Apple___healthy'
Blueberry	01	'Blueberry___healthy'
Cherry	02	'Cherry_(including_sour)Powdery_mildew', 'Cherry(including_sour)_healthy'
Corn	04	'Corn___Cercospora_leaf_spot', 'Corn___Common_rust','Corn___Northern_Leaf_Blight','Corn___healthy'
Grape	04	'Grape___Black_rot','Grape___Esca_(Black_Measles)','Leaf_blight_(Isariopsis_Leaf_Spot)','Grape___healthy'
Orange	01	'Orange___Haunglongbing_(Citrus_greening)'
Peach	02	'Peach___Bacterial_spot','Peach___healthy'
Pepper	02	'Pepper,_bell___Bacterial_spot','Pepper,_bell___healthy'
Potato	03	'Potato___Early_blight','Potato___Late_blight','Potato___healthy'
Raspberry	01	'Raspberry___healthy'
Soyabean	01	'Soybean___healthy'
Squash	01	'Squash___Powdery_mildew'
Strawberry	02	'Strawberry___Leaf_scorch','Strawberry___healthy'
Tomato	10	Tomato: 'Bacterial_spot','Early_blight', 'Late_blight', 'Leaf_Mold', 'Septoria_leaf_spot', 'Spider_mites','Target_Spot', 'Yellow_Leaf_Curl_Virus', 'Mosaic_virus', 'Healthy'

Before making your valuable contribution to this project do check CONTRIBUTING.md file.

Citation

When using any part of this repo, please cite: Plant Village Paper.