imadarsh9686/bone_fracture_detection

System where X ray images of fracture and non-fracture images of the whole body, If there is a fracture present it create a boundary box showing the fracture

Bone Fracture Detection with YOLOv8 and Streamlit

This repository contains a Streamlit web application for bone fracture detection using YOLOv8. Follow the instructions below to run the application.

Prerequisites

• Python 3.9
• Git

Installation

1. Clone the repository to your local machine:

   git clone https://github.com/imadarsh9686/bone_fracture_detection.git
   

2. Navigate to the project directory:

   cd your-repo
   

3. Create a conda environment (optional but recommended):

   conda create --name your_env_name python=3.9.18
   

4. Activate the conda environment:

   conda activate your_env_name
   

5. Install the required Python packages:

   pip install -r requirements.txt
   

Running the Application

1. Detecting Fractures in a Single Image

1. Make sure your virtual environment is activated.

2. Run the following command to start the Streamlit app:

      streamlit run app.py
   

3. Open your web browser and go to http://localhost:8501.

4. Upload an X-ray image and click the "Detect" button to view the fracture detection results.

2. Creating a CSV File of Fracture Predictions in a Folder

1. Follow steps 1-4 from the "Detecting Fractures in a Single Image" section.

2. Navigate to the "Image Folder Detection" page in the Streamlit app.

3. Enter the path of the folder containing X-ray images.

4. Click the "Detect in Folder" button to generate a CSV file with detection results.