This dataset is taken from Kaggle and below the link is given.
https://www.kaggle.com/emmarex/plantdisease
- Early blight is one of the most common tomato diseases, occurring nearly every season wherever tomatoes are grown.
- It affects leaves, fruits and stems and can be severely yield limiting when susceptible cultivars are used and weather is favorable.
- Severe defoliation can occur and result in sunscald on the fruit.
- Early blight is common in both field and high tunnel tomato production in Minnesota.
(Source credit : NC State Extension Publications - NC State University)
- Late blight is a potentially devastating disease of tomato and potato, infecting leaves, stems, tomato fruit, and potato tubers.
- The disease spreads quickly in fields and can result in total crop failure if untreated.
- Late blight does not occur every year in Minnesota.
- Late blight of potato was responsible for the Irish potato famine of the late 1840s.
(Source credit : Open Access Goverment and Paplauski Vital)
- Developing deep learning model to predict image of tomato leaves which will be having a disease.
- Creating User Interface using Gradio Library
- Python = 3.7.12
- Tensorflow (with Keras) = 2.5.0
- Seaborn = 0.11.2
- Jupyter=1.0.0
- Gradio=2.6.3
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Create an anaconda environment "myenv" with mentioned Python version. "conda create -n myenv python=3.7.12".
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Run command "pip install -r requirements.txt" on your prompt.
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Run "Tomato_Disease_Prediction.ipynb" this file at the end "h5.file" will generate which will be later used by another file "User_Interface.ipynb"
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Now, Run "User_Interface.ipynb", at the end you will see public url, click on it check the model prediction!
- NC State Extension Publications - NC State University
- Open Access Goverment and Paplauski Vital
- This dataset was gotten from spMohanty's GitHub Repo