https://github.com/sudip-13/plant-disease-detection

Plant disease detection from leaf uses machine learning to identify diseases for early intervention
https://github.com/sudip-13/plant-disease-detection

cloudinary css docker jwt-token keras matplotlib-pyplot mongodb nodejs numpy reactjs tensorflow tensorflow-serving

Last synced: 9 days ago
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Plant disease detection from leaf uses machine learning to identify diseases for early intervention

• Host: GitHub
• URL: https://github.com/sudip-13/plant-disease-detection
• Owner: sudip-13
• Created: 2024-03-17T15:24:24.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2024-06-01T18:24:02.000Z (6 months ago)
• Last Synced: 2024-06-01T20:48:20.057Z (6 months ago)
• Topics: cloudinary, css, docker, jwt-token, keras, matplotlib-pyplot, mongodb, nodejs, numpy, reactjs, tensorflow, tensorflow-serving
• Language: Jupyter Notebook
• Homepage:
• Size: 42.6 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Plant-Disease-Classification

# powershell comand

# docker

docker pull tensorflow/serving

# To Start docker container

### This directory peeeper disease classification

docker run -it -v D:\plant\peeper-disease:/peeper-disease -p 8501:8501 --entrypoint /bin/bash tensorflow/serving

### This directory potato disease classification

docker run -it -v D:\plant\potato-disease:/potato-disease -p 8601:8601 --entrypoint /bin/bash tensorflow/serving

### This directory tomato disease classification

docker run -it -v D:\plant\tomato-disease:/tomato-disease -p 8701:8701 --entrypoint /bin/bash tensorflow/serving

# To serve only latest models

### peeeper disease classification

tensorflow_model_server --rest_api_port=8501 --model_name=peeper-disease --model_base_path=/peeper-disease/Models/

### potato disease classification

tensorflow_model_server --rest_api_port=8601 --model_name=potato-disease --model_base_path=/potato-disease/Models/

### tomato disease classification

tensorflow_model_server --rest_api_port=8701 --model_name=tomato-disease --model_base_path=/tomato-disease/Models/

 ## here’s a brief description of how disease detection works for tomato, potato, and pepper plants using leaf images:

## Tomato:-

 Deep learning techniques, particularly Convolutional Neural Networks (CNNs), have been used to detect and classify diseases in tomato plants.For instance, a CNN-based technique was used to detect diseases in tomato crops. Another study used a deep learning-based system utilizing the plant leaves image data

 ## Potato:-

 Similar to tomato plants, potato leaf diseases have also been detected using deep learning techniques345. A study used a CNN model to classify potato leaf diseases .

## Peeper:-

For pepper plants, an enhanced lightweight model based on GoogLeNet architecture was introduced for disease detection.

[![Watch the video](https://vimeo.com/929143932)](https://vimeo.com/929143932)