Metadata-Version: 2.4
Name: transparent-overlay
Version: 2.7.3
Summary: High-performance transparent graphics overlay for Windows
Home-page: https://github.com/IlyaYakko/transparent-overlay
Author: Илья Яковенко
Author-email: Илья Яковенко <ilya.a.yakovenko@gmail.com>
License: MIT
Keywords: overlay,graphics,transparent,windows,gdi,hud,performance
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.19.0
Requires-Dist: Pillow>=8.0.0
Requires-Dist: pywin32>=300; sys_platform == "win32"
Requires-Dist: numba>=0.56.0
Provides-Extra: examples
Requires-Dist: psutil>=5.8.0; extra == "examples"
Requires-Dist: pyautogui>=0.9.0; extra == "examples"
Dynamic: author
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python

# Transparent Overlay

![Hero](https://raw.githubusercontent.com/IlyaYakko/transparent-overlay/main/assets/images/hero_placeholder.png)

[![PyPI version](https://img.shields.io/pypi/v/transparent-overlay.svg)](https://pypi.org/project/transparent-overlay/)
[![Python versions](https://img.shields.io/pypi/pyversions/transparent-overlay.svg)](https://pypi.org/project/transparent-overlay/)
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE)
[![OS: Windows](https://img.shields.io/badge/OS-Windows-0078D6)](#requirements)

High-performance transparent graphics overlay for Windows.  
True per-pixel transparency, double buffering, cached sprites, thread-safe render loop, and **automatic Numba acceleration** (~10x faster rendering).

## Features

- True desktop transparency using layered windows (`UpdateLayeredWindow`)
- Smooth, flicker-free rendering with double buffering
- Cached sprites: shapes, lines, text, and custom NumPy RGBA arrays
- Thread-safe: separate logic and dedicated render thread
- Built-in diagnostics: FPS counter and per-frame statistics
- **Automatic Numba acceleration** (installed by default, with graceful NumPy fallback)

## Installation

```bash
pip install transparent-overlay
```

This installs the core library with **Numba included** for maximum performance.

For running the examples (additional dependencies):

```bash
pip install "transparent-overlay[examples]"
```

## Quick start

```python
from transparent_overlay import Overlay

with Overlay() as overlay:
    overlay.draw_circle(200, 150, 50, (255, 0, 0, 180))
    overlay.draw_rect(350, 100, 120, 80, (0, 0, 255, 160))
    overlay.draw_line(500, 100, 650, 180, (0, 255, 0, 255), thickness=3)
    overlay.draw_text(400, 50, "Basic Shapes", color=(255, 255, 255, 255), font_size=50)

    overlay.signal_render()
    input("Press Enter to exit...")
```

![Demo](https://raw.githubusercontent.com/IlyaYakko/transparent-overlay/main/assets/gifs/demo_basic_placeholder.gif)

## Use cases

- Real-time HUD overlays
- On-screen debugging for AI / computer vision applications
- Desktop widgets and transparent UI elements
- Streaming and recording overlays
- Graphics experiments and educational demos

## Documentation

- Full documentation: [DOCUMENTATION.md](https://github.com/IlyaYakko/transparent-overlay/blob/main/DOCUMENTATION.md)
- Examples and demos: [**examples/** folder on GitHub](https://github.com/IlyaYakko/transparent-overlay/tree/main/examples)
- Media assets (screenshots, GIFs, videos): [**assets/** folder on GitHub](https://github.com/IlyaYakko/transparent-overlay/tree/main/assets)

## Performance

The library automatically uses **Numba** for significantly faster pixel operations (up to 10x speedup).  
If Numba is unavailable for any reason, it seamlessly falls back to pure NumPy — functionality remains fully intact.

## Requirements

- **OS**: Windows 7 or later
- **Python**: 3.7 and above
- Hardware must support layered windows (all modern Windows systems do)

> Note: This package is Windows-only. Importing on other platforms will raise an error by design.

## License

[MIT License](LICENSE) — free for commercial and personal use.
