# Dlib Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/dlib
> Markdown URL: https://aitinkerers.org/technologies/dlib.md
> Technology record last updated: 2026-03-02T07:13:09Z
> Generated: 2026-08-24T06:48:02Z

Dlib is the high-performance C++ toolkit for real-world machine learning (ML), computer vision, and data analysis applications.

Dlib, a robust, cross-platform C++ library, delivers a comprehensive suite of tools for solving complex problems in ML and data analysis. Developed by Davis E. King since 2002, it is used across industry and academia (robotics, embedded devices, HPC) under the permissive Boost Software License. Key features include state-of-the-art algorithms: structural Support Vector Machines (SVMs), deep learning (CNNs for object detection), and efficient image processing (HOG-based face detection). The library emphasizes high-quality, portable code, complete documentation, and robust Python bindings, making it a reliable choice for production systems.

- Official technology site: https://dlib.net
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Face Morphing through DL and Convex Combinations](https://medellin.aitinkerers.org/talks/rsvp_GW1J70Ocieo)

Demostraré un pipeline para hacer morphing entre dos imágenes de entrada que contienen rostos.. Este pipeline consta de dos pasos: 1. Detección de rostros y de puntos de referencia en rostros usando dos modelos de Deep learning disponibles libremente. 2. Generación de una nueva imagen como una interpolación convexa entre las dos imágenes de entrada, informalmente "alpha * Img1 + (1-alpha) * Img2". Cada pixel de esta imagen se calcula a partir de una combinación convexa de pixeles correspondientes las imagenes de entrada.

- Event context: Lanzamiento de AI Tinkerers #1 — 2024-04-25 — Medellín
- Public talk page: https://medellin.aitinkerers.org/talks/rsvp_GW1J70Ocieo

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