---
title: Yolo V3
emoji: 👀
colorFrom: gray
colorTo: blue
sdk: gradio
sdk_version: 3.40.1
app_file: app.py
pinned: false
license: mit
---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference


# YoloV3 object detection model- Interactive Interface
    
This project Impliments a simple Gradio interface to perform inference on YoloV3 object detection.

## Task : 

The task involves performing detection on the Pascal voc dataset using the YoloV3 model built with PyTorch and PyTorch Lightning. 

## Files :

1. `requirements.txt`: Contains the necessary packages required for installation.
2. `model.py`: Contains the YoloV3 model architecture.
3. `YoloV3.pth`: Trained model checkpoint file containing model weights.
4. `examples/`: Folder containing example images (e.g., car.jpg, home.jpg, etc.).
5. `app.py`: Contains the Gradio code for the interactive interface. Users can select input images or examples of the model that detects objects.


## Implementation

The following features are implemented using Gradio:

1. **Upload and Select Images:** Users can upload new images or select from a set of example images.


## Usage

1. Run the `app.py` script to launch the interactive Gradio interface.