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https://github.com/flofriday/ttf-2024
Our entry for the tourism tech festival 2.0 (2024)
https://github.com/flofriday/ttf-2024
Last synced: 1 day ago
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Our entry for the tourism tech festival 2.0 (2024)
- Host: GitHub
- URL: https://github.com/flofriday/ttf-2024
- Owner: flofriday
- License: mit
- Created: 2024-11-09T09:08:50.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-11-09T18:31:21.000Z (3 months ago)
- Last Synced: 2024-11-09T18:32:08.609Z (3 months ago)
- Language: TypeScript
- Homepage:
- Size: 446 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# TTF-2024 - SlopeFlow
Our entry for the [Tourism Tech Festival 2.0](https://tourism-technology.com/) (2024)
Snowflow is a delightful webapp to discover the slopes in your ski resort with
the least people and the most fun. For accurate live-reporting we process webcam
feeds and detect the number of people waiting at the ski-lifts with machine
learning to precisely estimate the waiting times.
## Build and run with Docker
```bash
docker compose up --build
```
This will build the frontend which is accessible at http://localhost:3000 and backend at http://localhost:8000.
## Build and run locally
You will need the following requirements for the local build:
- [Python 3.12+](https://www.python.org/downloads/) and [Pip](https://pip.pypa.io/en/stable/installation/)
- [Node.js](https://nodejs.org/) and [npm](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm)
### Backend Setup
1. Set up Python environment:
```bash
cd backend
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
```
2. Download required YOLO model files:
```bash
# Download YOLOv3 weights
wget https://pjreddie.com/media/files/yolov3.weights -P models/
# Download configuration file
wget https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov3.cfg -P models/
# Download COCO class names
wget https://raw.githubusercontent.com/pjreddie/darknet/master/data/coco.names -P models/
```
3. Adapt the `backend/data/ski_resorts.json` file to your liking. By default it already includes some of the best known resorts in Austria. Example schema:
```json
{
"resorts": [
{
"name": "Obertauern",
"location": "Salzburg, Austria",
"description": "One of Austria's most snow-sure winter sports destinations",
"website": "https://www.obertauern.com"
}
]
}
```
4. Load resort data
```bash
python scripts/load_resort_data.py
```
5. Finally start the server with
```bash
uvicorn app.main:app --reload
```
The backend will be available at http://localhost:8000.
### Frontend Setup
In a new terminal run:
```bash
cd frontend
npm install
npm run dev
```
The frontend will be available at http://localhost:3000.
## Development
### Code Style
We maintain a consistent code style through automated formatting:
- **Python**: We use either [ruff](https://github.com/astral-sh/ruff)
- **TypeScript/HTML/CSS**: We use [prettier](https://prettier.io/)
To further improve the code quality we use linters like [ESLint](https://eslint.org/) for TypeScript and [ruff](https://docs.astral.sh/ruff/) for Python.
Run the formatters before submitting any changes.
## Contributing
Contributions are quite welcome! You are awesome 😊✨