https://github.com/shamspias/yolo-box-visualizer
A Streamlit app to upload images and YOLO annotations, visualizing bounding boxes easily.
https://github.com/shamspias/yolo-box-visualizer
python steamlit yolo
Last synced: 3 months ago
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A Streamlit app to upload images and YOLO annotations, visualizing bounding boxes easily.
- Host: GitHub
- URL: https://github.com/shamspias/yolo-box-visualizer
- Owner: shamspias
- Created: 2025-01-06T14:09:02.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-01-06T15:25:57.000Z (5 months ago)
- Last Synced: 2025-01-27T11:19:22.127Z (4 months ago)
- Topics: python, steamlit, yolo
- Language: Python
- Homepage:
- Size: 5.34 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# YOLO Box Visualizer
## Overview
YOLO Box Visualizer is a Streamlit-based web app that allows you to:
- Upload (or drag-and-drop) images.
- Upload (or drag-and-drop) YOLO annotation files (txt).
- Parse and visualize red bounding boxes over the uploaded image.## Installation
1. **Clone the repository**:
```bash
git clone https://github.com/your-username/YOLO-Box-Visualizer.git2. **Navigate to the project folder**:
```bash
cd YOLO-Box-Visualizer
```
3. **Set up a virtual environment** (optional but recommended):
```bash
python3 -m venv venv
source venv/bin/activate
```
4. **Install dependencies**:
```bash
pip install -r requirements.txt
```
## Usage
Run the Streamlit application:
```bash
streamlit run src/app.py```
Open the provided URL in your browser. You can now:
1. Upload an image (jpg, jpeg, png).
2. Upload a YOLO annotation file (txt).
3. Click "Show Annotation" to see the bounding box on your image.## Example



## Contributing
1. Fork the repository.
2. Create a feature branch.
3. Commit your changes.
4. Submit a pull request.