https://github.com/nneji123/flask-client-camera
https://github.com/nneji123/flask-client-camera
docker docker-compose flask gitpod html javascript medium-article python railway render webcam websocket
Last synced: about 1 month ago
JSON representation
- Host: GitHub
- URL: https://github.com/nneji123/flask-client-camera
- Owner: Nneji123
- License: mit
- Created: 2023-02-22T16:50:04.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-03-29T05:52:03.000Z (about 2 years ago)
- Last Synced: 2025-05-04T21:57:10.402Z (about 1 month ago)
- Topics: docker, docker-compose, flask, gitpod, html, javascript, medium-article, python, railway, render, webcam, websocket
- Language: Python
- Homepage: https://medium.com/p/97fb4a0a764f/edit
- Size: 58.6 KB
- Stars: 26
- Watchers: 2
- Forks: 6
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# Real-time Image Processing using Flask and OpenCV
## About
**This is a real-time image processing application built using Flask and OpenCV. The application receives a video stream from the client and processes it using OpenCV. The processed video is then sent back to the client for display.**
## Repository Structure
```bash
├── Dockerfile
├── README.md
├── app.py
├── docker-compose.yml
├── requirements.txt
└── templates
├── index.html
└── static
└── logo.ico
```
## Tools Used
The application was built using the following tools:
- Flask: A micro web framework written in Python.
- Socket.IO: A library that enables real-time, bidirectional communication between web clients and servers.
- OpenCV: A computer vision library with Python bindings.
- Docker: A tool designed to make it easier to create, deploy, and run applications by using containers.
## How to run the application (using virtual environment)
1. Clone the repository:
`git clone https://github.com/Nneji123/flask-client-camera.git`
2. Create a virtual environment: `python3 -m venv env`
3. Activate the virtual environment: `source env/bin/activate` or `source env/Scripts/activate` if you use windows os.
4. Install the required packages: `pip install -r requirements.txt`
5. Start the application: `python app.py`
## How to run the application (using gitpod)
[](https://gitpod.io/#https://github.com/Nneji123/flask-client-camera)
## How to run the application (using Docker and Docker Compose)
1. Clone the repository: `git clone https://github.com/your_username/real-time-image-processing.git`
2. Install Docker and Docker Compose on your machine
3. Build the Docker image: `docker build -t image-processing .`
4. Start the Docker container: `docker run -p 5000:5000 -it image-processing`
Alternatively, you can use Docker Compose to start the application: `docker-compose up -d --build`
## How to deploy the application
Click the button below to deploy the application to `render.com`
[](https://render.com/deploy)
## License
[MIT](./README.md)