README.md

metadata

title: MRI Orientation
emoji: 🐠
colorFrom: yellow
colorTo: gray
sdk: gradio
sdk_version: 6.2.0
app_file: app.py
pinned: false

MRI Orientation Predictor

This is a simple web application for predicting the orientation of MRI images using a YOLOv11 classification model that is already pretrained on several MRI datasets. It classifies images into axial, coaxial, or sagittal orientations and provides a confidence score.

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Features

• Predict MRI orientation for uploaded images.
• Display confidence score for the prediction.
• Easy-to-use web interface powered by Gradio.
• Supports .jpg, .jpeg, and .png images.

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Model

The model is a YOLOv11 classification model saved as best.pt. The model outputs short labels:

• ax → axial
• co → coaxial
• sa → sagittal

The application maps these short labels to full orientation names for easier understanding.

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Installation

Install required packages:

pip install -r requirements.txt

Requirements.txt

The requirements.txt should include at least:

ultralytics
torch
torchvision
gradio
Pillow

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Usage

1. Place your YOLOv11 model file best.pt in the project directory.
2. Run the Gradio app:

python app.py

3. Upload an MRI image in the interface.
4. The predicted orientation and confidence will be displayed.

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Example Output

Orientation: axial | Confidence: 0.95
Orientation: coaxial | Confidence: 0.87
Orientation: sagittal | Confidence: 0.92

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Notes

• Make sure your model is a YOLOv11 classification model saved as .pt.
• The model should return labels "ax", "co", "sa" which are mapped to full names.
• Confidence is reported as a float between 0 and 1.

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