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  # Diabetic Retinopathy Detection: Utilizing Multiprocessing for Processing Large Datasets and Transfer Learning to Fine-Tune Deep Learning Models
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  Efficiently process large datasets & develop advanced model pipelines for diabetic retinopathy detection. Streamlining diagnosis.
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- ## Gradio App
 
 
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  <!--
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  <iframe src="https://bhimrazy-diabetic-retinopathy-detection.hf.space" frameborder="0" width="1920" height="1080"></iframe>
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- [![Gradio App](https://github.com/bhimrazy/diabetic-retinopathy-detection/assets/46085301/4e0788dd-84a1-427e-a38a-e22c2aa86c50)](https://bhimrazy-diabetic-retinopathy-detection.hf.space)
 
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+ ![diabetic-retinopathy-detection](https://github.com/bhimrazy/diabetic-retinopathy-detection/assets/46085301/bb45b4cf-9441-435f-819a-176226e1ac00)
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  # Diabetic Retinopathy Detection: Utilizing Multiprocessing for Processing Large Datasets and Transfer Learning to Fine-Tune Deep Learning Models
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  Efficiently process large datasets & develop advanced model pipelines for diabetic retinopathy detection. Streamlining diagnosis.
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+ ## Gradio Diabetic Retinopathy Detection App
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  <!--
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  <iframe src="https://bhimrazy-diabetic-retinopathy-detection.hf.space" frameborder="0" width="1920" height="1080"></iframe>
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  -->
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+ ### Overview
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+ Welcome to our Diabetic Retinopathy Detection App! This app utilizes deep learning models to detect diabetic retinopathy in retinal images. Diabetic retinopathy is a common complication of diabetes and early detection is crucial for effective treatment.
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+ ### Try It Out
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+ Use the interactive interface below to upload retinal images and get predictions on diabetic retinopathy severity.
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+ [Open Diabetic Retinopathy Detection App](https://bhimrazy-diabetic-retinopathy-detection.hf.space)
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+ [![Gradio App](https://github.com/bhimrazy/diabetic-retinopathy-detection/assets/46085301/4e0788dd-84a1-427e-a38a-e22c2aa86c50)](https://bhimrazy-diabetic-retinopathy-detection.hf.space)
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+ ### How to Use
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+ 1. Click on the "Open Diabetic Retinopathy Detection App" button above.
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+ 2. Upload a retinal image by clicking on the "Upload Image" button.
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+ 3. Once the image is uploaded, the model will process it and provide predictions on the severity of diabetic retinopathy.
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+ 4. Interpret the results provided by the model.