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@@ -9,5 +9,63 @@ app_file: app.py
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  license: apache-2.0
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
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  pinned: false
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  license: apache-2.0
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  ---
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+ # Alzheimer MRI Classification
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+
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+ This repository contains a Gradio application for classifying Alzheimer's disease stages from MRI images using a fine-tuned ResNet50 model. The application is deployed on Hugging Face Spaces.
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+ ## Table of Contents
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+ - [Introduction](#introduction)
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+ - [Model Details](#model-details)
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+ - [Setup](#setup)
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+ - [Usage](#usage)
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+ - [Contributing](#contributing)
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+
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+ ## Introduction
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+ This application uses a convolutional neural network (ResNet50) to classify MRI images into one of four stages of Alzheimer's disease:
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+ - Mild Demented
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+ - Moderate Demented
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+ - Non-Demented
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+ - Very Mild Demented
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+
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+ The model is fine-tuned on a custom dataset and can be accessed through a user-friendly web interface powered by Gradio.
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+
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+ ## Model Details
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+ The model architecture is based on ResNet50, with the final fully connected layer adjusted to output predictions for 4 classes. The model is trained using PyTorch and fine-tuned on a dataset of MRI images.
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+
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+ ## Setup
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+ To run the application locally, follow these steps:
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+ 1. Clone the repository:
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+ ```bash
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+ git clone https://github.com/your_username/alzheimer_mri_classification.git
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+ cd alzheimer_mri_classification
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+ ```
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+
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+ 2. Install the required dependencies:
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+ ```bash
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+ pip install -r requirements.txt
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+ ```
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+ 3. Ensure you have the model file (`alzheimer_model_resnet50.pth`) in the root directory of the project. You can download it from [Hugging Face Hub](https://huggingface.co/your_username/alzheimer_model_resnet50).
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+ 4. Run the application:
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+ ```bash
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+ python app.py
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+ ```
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+ 5. The Gradio interface will launch and can be accessed in your web browser at `http://127.0.0.1:7860`.
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+
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+ ## Usage
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+ Once the application is running, you can upload an MRI image through the web interface and get the predicted classification.
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+
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+ ### Example Usage
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+ 1. Open the application in your browser.
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+ 2. Click on "Upload an MRI Image" to upload an image.
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+ 3. The application will display the predicted classification for the uploaded image.
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+
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+
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+ ## Contributing
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+ Contributions are welcome! If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request.
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference