Update README.md

README.md

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+
 title: MRI Orientation
 emoji: 🐠
 colorFrom: yellow
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 pinned: false
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-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 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.
+
+---
+
+## 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.
+
+---
+
+## 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.
+
+---
+
+## Installation
+
+Install required packages:
+
+```bash
+pip install -r requirements.txt
+```
+
+### Requirements.txt
+
+The `requirements.txt` should include at least:
+
+```
+ultralytics
+torch
+torchvision
+gradio
+Pillow
+```
+
+---
+
+## Usage
+
+1. Place your YOLOv11 model file `best.pt` in the project directory.
+2. Run the Gradio app:
+
+```bash
+python app.py
+```
+
+3. Upload an MRI image in the interface.
+4. The predicted orientation and confidence will be displayed.
+
+---
+
+## Example Output
+
+```
+Orientation: axial | Confidence: 0.95
+Orientation: coaxial | Confidence: 0.87
+Orientation: sagittal | Confidence: 0.92
+```
+
+---
+
+## 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.
+
+---
+
+