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Optimized for real-time data processing, FlangerLens utilizes intelligent algorithms dynamically auto-scale video streams through a dedicated processor module.

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FlangerLens

Optimized for real-time data processing, FlangerLens utilizes intelligent algorithms dynamically auto-scale video streams through a dedicated processor module.

FlangerLens is aimed at developers who need a straightforward, dependable solution.

Highlights

  • Optimized for real-time data processing,
  • FlangerLens utilizes intelligent algorithms dynamically
  • auto-scale video streams through a

Key Features

  • Optimized for real-time data processing,
  • FlangerLens utilizes intelligent algorithms dynamically
  • auto-scale video streams through a

Technology Stack

  • javascript
  • javascript framework (Flask/Django/FastAPI or equivalent)
  • Pytest for testing

Installation

  1. Clone the repository: git clone https://github.com/karanjamoses/FlangerLens.git
  2. Install required dependencies: pip install -r requirements.txt

Configuration

FlangerLens is configured through environment variables (see .env.example). Key options:

  • APP_ENV: development or production.
  • PORT: Port the server listens on.
  • LOG_LEVEL: debug, info, or error.

Contributing

Contributions are welcome and appreciated. Please submit pull requests and issues through the GitHub interface.

License

This project is licensed under the MIT License. See the LICENSE file for details.

About

Optimized for real-time data processing, FlangerLens utilizes intelligent algorithms dynamically auto-scale video streams through a dedicated processor module.

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3 stars

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0 watching

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