Created by Shubham Kumar and other contributors
My Article in TowardsDataScience
Models are trained on the preprocessed dataset which can be downloaded here.
- It is recommended to set up the project inside a virtual environment to keep the dependencies separated.
- 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.
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.
-
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
-
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
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.
When using any part of this repo, please cite: Plant Village Paper.