Object-Detection

This is a Streamlit web application that uses a pre-trained Faster R-CNN model to detect and draw bounding boxes around people in images.

Setup

1. Clone the Repository

Clone this repository to your local machine using the following command:

git clone https://github.com/your-username/object-detection.git

2.Navigate to the Project Directory

Change your current directory to the project directory

cd object-detection

3. Install Dependencies

Make sure you have Python installed. Install the required Python packages using the following command:

pip install -r requirements.txt

4.Run the App

To run the app, execute the following command in your terminal:

streamlit run main.py

Usage

1.Visit the deployed Streamlit app or run it locally.

2.Upload an image using the provided file uploader.

3.The app will display the uploaded image with bounding boxes drawn around detected people.

Dependencies

Streamlit
Pillow
NumPy
Matplotlib
PyTorch
Torchvision

Model

The app uses a Faster R-CNN model with a ResNet50 backbone for person detection. The model is pre-trained and comes with default weights.