How to Detect Tea Leaf Diseases with Dash and Roboflow

Published: 01 January 1970
on channel: Pyresearch
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#Pyresearch #ComputerVision #opencv #DeepLearning #TeaPlantation #AIinAgriculture #MachineLearning #Roboflow #CropProtection #Innovation

deploying a deep learning model for tea plantations is transforming the way we manage and protect crops. Here's how:

📸 Collect & Preprocess: Start by gathering a diverse dataset of tea plant images, capturing both healthy and diseased conditions. This step is crucial for teaching the model to distinguish between different plant states.

💻 Train the Model: Utilize a powerful computing platform to train the model, focusing on achieving high accuracy. This is where deep learning shines, learning complex patterns from the data.

🚀 Deploy & Integrate: Once the model is trained, deploy it to a cloud or on-premises server. Integrate it seamlessly with the plantation management system for real-time monitoring and insights.

🔄 Monitor & Update: Continuously monitor the model's performance. Keep it up-to-date with new data to ensure ongoing accuracy and efficiency in detecting plant diseases.


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code: https://github.com/noorkhokhar99/How-...


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