streamlit-ml-app

About Project

An application that facilitates farmers, scientists and botanists to detect the type of plant or crops, detect any kind of diseases in them. The app sends the image of the plant to the server where it is analysed using CNN classifier model. Once detected, the disease and its solutions are displayed to the user.

Model

Trained to identify 5 classes for Disease Detection and 24 classes for Disease Classification

       - Disease Classification Classes

                   - Apple___Apple_scab
                   - Apple___Black_rot
		   - Apple___Cedar_apple_rust
		   - Apple___healthy
		   - Blueberry___healthy
		   - Cherry___healthy
		   - Cherry___Powdery_mildew
		   - Grape___Black_rot
		   - Grape___Esca_Black_Measles
		   - Grape___healthy
		   - Grape___Leaf_blight_Isariopsis_Leaf_Spot
		   - Orange___Haunglongbing
		   - Peach___Bacterial_spot
		   - Peach___healthy
		   - Pepper,_bell___Bacterial_spot
		   - Pepper,_bell___healthy
		   - Potato___Early_blight
		   - Potato___healthy
		   - Raspberry___healthy
		   - Soybean___healthy
		   - Squash___Powdery_mildew
		   - Strawberry___healthy
		   - Strawberry___Leaf_scorch
		
        - Disease Detection Classes
        
		   - Cherry___healthy
		   - Cherry___Powdery_mildew
		   - Grape___Black_rot
		   - Grape___Esca_Black_Measles
		   - Grape___healthy
		   - Grape___Leaf_blight_Isariopsis_Leaf_Spot 

Usage

1. Install the required dependencies

	pip install -r requirements.txt 

2. Command for running app

	streamlit run app.py

Images

Enviornments

1. This app is deployed on Heroku

Note: The tensorflow model load into the memory and hence can be slow on heroku as compared to the local enviornment

Developer

Hi there, I'm Ameya Upalanchi

I'm a Project Enthusiast, Developer, and Life long learner!

• I am currently learning everything
• 2020 Goals: Contribute more to Open Source projects
• Fun fact: I love to play table tennis and guitar / drums

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