Search Results for "deep-live-cam"
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Showing 11 open source projects for "deep-live-cam"
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1
Pyro
Deep universal probabilistic programming with Python and PyTorch
Pyro is a flexible, universal probabilistic programming language (PPL) built on PyTorch. It allows for expressive deep probabilistic modeling, combining the best of modern deep learning and Bayesian modeling. Pyro is centered on four main principles: Universal, Scalable, Minimal and Flexible. Pyro is universal in that it can represent any computable probability distribution. It scales easily to large datasets with minimal overhead, and has a small yet powerful core of composable abstractions that make it both agile and maintainable. ... -
2
The Julia Programming Language
High-level, high-performance dynamic language for technical computing
Julia is a fast, open source high-performance dynamic language for technical computing. It can be used for data visualization and plotting, deep learning, machine learning, scientific computing, parallel computing and so much more. Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing. ... -
3
Triton
Development repository for the Triton language and compiler
Triton is a programming language and compiler framework specifically designed for writing highly efficient custom deep learning operations, particularly for GPUs. It aims to bridge the gap between low-level GPU programming, such as CUDA, and higher-level abstractions by providing a more productive and flexible environment for developers. Triton enables users to write optimized kernels for machine learning workloads while maintaining readability and control over performance-critical aspects like memory access patterns and parallel execution. ... -
4
Bend
A massively parallel, high-level programming language
Bend is an interactive programming environment (REPL) built on top of the Kotlin language, designed to allow users to explore, experiment, and learn Kotlin in a live, feedback-driven manner. The tool lets you define variables, functions, or values at the prompt and iteratively refine them—immediately seeing output and types—while preserving state across commands. It emphasizes discoverability and experimentation: users can inspect functions, call them on sample inputs, and evolve logic without a full project scaffold. ... -
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5
Tidal
Pattern language
Tidal Cycles (or just Tidal for short) is software for making patterns with code, whether live coding music at algoraves or composing in the studio. It includes a simple and flexible notation for rhythmic sequences and an extensive library of patterning functions for combining and transforming them. This allows you to quickly create complex patterns from simple ingredients. By default, sound is made with the featureful SuperDirt synth/sampler, but you can control other synths using Open Sound Control (OSC) or MIDI. ... -
6
OCaml
The core OCaml system: compilers, runtime system, base libraries
...The other is a native code compiler that produces more efficient machine code; its performance matches the highest standards of modern compilers. OCaml has great support for the most popular editors. VS Code is recommended for beginners, and for power users there is deep integration with Vim and Emacs. OCaml has a rich and dynamic community and best-in-class tooling. -
7
Quine Relay
An uroboros program with 100+ programming languages
quine-relay is an esoteric programming project that produces a single program which, when run, outputs the same program in another programming language; and that next-language version, when run, outputs itself in yet another language—and so on—cycling through many languages until returning to the original. It is effectively a “relay” of quines across dozens (or hundreds) of languages. The repository contains implementations, translation scaffolding, and carefully crafted code for each... -
8
The Acton programming language
The Acton Programming Language
...Built-in redundancy; Acton's transactional, high-performance distributed RTS can seamlessly resume application state after hardware failures. Never stop for an upgrade; Live upgrade your running application through compiler-supported code and data migration. Acton programs, and the actor model, work well from simple script-style applications on a single machine up to large distributed systems across a Data Center. Run at your scale. -
9
Ring
Simple and flexible programming language for applications development
The Ring is a practical general-purpose multi-paradigm language. The supported programming paradigms are imperative, procedural, object-oriented, declarative using nested structures, functional, meta programming and natural programming. The language is portable (MS-DOS, Windows, Linux, macOS, Android, WebAssembly, Microcontrollers, etc.) and can be used to create Console, GUI, Web, Games and Mobile applications. The language is designed to be simple, small and flexible. Ring is... -
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10
KAREL 3D C++ ( Karel the Robot in 3D )
Karel - 3D language interpreter
...First KAREL-3D is created in 1986 after Karel the Robot, in Slovakia ( before Czechoslovakia ) on 8 bit microcomputer PMD 85-2 for school kids to learn algorithm and what is programming, teach know how to solve a logical problem, like Spock and his children from the planet Vulcan ( live long and prosper ). because it's fun Actual WebGL version: https://sourceforge.net/projects/karel-3d-webgl/ -
11
Edward
A probabilistic programming language in TensorFlow
...Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilistic models, ranging from classical hierarchical models on small data sets to complex deep probabilistic models on large data sets. Edward fuses three fields, Bayesian statistics and machine learning, deep learning, and probabilistic programming. Edward is built on TensorFlow. It enables features such as computational graphs, distributed training, CPU/GPU integration, automatic differentiation, and visualization with TensorBoard. ...
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