Search Results for "mac steganography decoder"
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Showing 280 open source projects for "mac steganography decoder"
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Generic Image Decoder
A standalone, portable generic Ada package for decoding images
The Generic Image Decoder is a package for decoding a broad variety of image formats, from any data stream, to any kind of medium. Unconditionally portable code: OS-, CPU-, compiler- independent code. More information on... http://gen-img-dec.sf.net Alire crate: https://alire.ada.dev/crates/gid Mirror: https://github.com/zertovitch/gid -
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Pytorch-toolbelt
PyTorch extensions for fast R&D prototyping and Kaggle farming
A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images. Every-day common routines (fix/restore random seed, filesystem utils, metrics). Losses:... -
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go-json
Fast JSON encoder/decoder compatible with encoding/json for Go
Fast JSON encoder/decoder compatible with encoding/json for Go. -
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simplejson
simplejson is a simple, fast, extensible JSON encoder/decoder
simplejson is a simple, fast, complete, correct and extensible JSON <http://json.org> encoder and decoder for Python 3.3+ with legacy support for Python 2.5+. It is pure Python code with no dependencies but includes an optional C extension for a serious speed boost. simplejson is the externally maintained development version of the json library included with Python (since 2.6). This version is tested with the latest Python 3.8 and maintains backward compatibility with Python 3.3+ and the... -
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Pilipala
Recommendations, live streams, video playback
PiliPala is a GPL‑licensed, Flutter-built third-party Bilibili client that works on Android, iOS, desktop, and web. It includes recommendations, live streams, video playback with gestures, adjustable playback speed, AV quality and decoder controls, bullet comments, subtitles, snapshots, fullscreen modes, UI theming, blacklists, and more. -
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Whisper
Robust Speech Recognition via Large-Scale Weak Supervision
OpenAI Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. A Transformer sequence-to-sequence model is trained on various speech processing tasks, including multilingual speech recognition, speech translation, spoken language identification, and voice activity detection. These tasks are jointly represented... -
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Phase1
Decoding Image Steganography: Finding images hidden in the last bits o
The Phase1 program decodes hidden messages (text or images) embedded within a source image assuming common steganography techniques. It supports decoding text and images by extracting least significant bits (LSBs) from various combinations of pixel channels. -
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Typia
Super-fast/easy runtime validations and serializations
Super-fast/easy runtime validations and serializations through transformation. -
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Solidity
The Smart Contract Programming Language
Solidity is a statically-typed curly-braces programming language designed for developing smart contracts that run on Ethereum. Solidity 0.8.4 adds custom structured errors, allows more flexible configuration of the SMTChecker and fixes a bug in the Solidity ABI decoder v2. Read more about the bug here. With v0.8.4, errors can be defined inside and outside of contracts (including interfaces and libraries). This provides a convenient and gas-efficient way to explain to users why an operation... -
Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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Segment Anything
Provides code for running inference with the SegmentAnything Model
Segment Anything (SAM) is a foundation model for image segmentation that’s designed to work “out of the box” on a wide variety of images without task-specific fine-tuning. It’s a promptable segmenter: you guide it with points, boxes, or rough masks, and it predicts high-quality object masks consistent with the prompt. The architecture separates a powerful image encoder from a lightweight mask decoder, so the heavy vision work can be computed once and the interactive part stays fast. A... -
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nghttp2
HTTP/2 C Library and tools
nghttp2 is an implementation of HTTP/2 and its header compression algorithm HPACK in C. The framing layer of HTTP/2 is implemented as a form of reusable C library. On top of that, we have implemented HTTP/2 client, server and proxy. We have also developed a load test and benchmarking tool for HTTP/2. We have participated in httpbis working group since HTTP/2 draft-04, which is the first implementation draft. Since then we have updated nghttp2 library constantly to the latest specification... -
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far2l
Linux port of FAR v2
Linux fork of FAR Manager v2. Works also on OSX/MacOS and BSD (but the latter is not tested on a regular manner). Plug-ins that are currently working: NetRocks (SFTP/SCP/FTP/FTPS/SMB/NFS/WebDAV), colorer, multiarc, tmppanel, align, autowrap, drawing, edit case, SimpleIndent, Calculator, Python (optional scripting support). -
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Granite Code Models
A Family of Open Foundation Models for Code Intelligence
Granite Code Models are IBM’s open-source, decoder-only models tailored for code tasks such as fixing bugs, explaining and documenting code, and modernizing codebases. Trained on code from 116 programming languages, the family targets strong performance across diverse benchmarks while remaining accessible to the community. The repository introduces the model lineup, intended uses, and evaluation highlights, and it complements IBM’s broader Granite initiative spanning multiple modalities.... -
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GLM-OCR
Accurate × Fast × Comprehensive
GLM-OCR is an open-source multimodal optical character recognition (OCR) model built on a GLM-V encoder–decoder foundation that brings robust, accurate document understanding to complex real-world layouts and modalities. Designed to handle text recognition, table parsing, formula extraction, and general information retrieval from documents containing mixed content, GLM-OCR excels across major benchmarks while remaining highly efficient with a relatively compact parameter size (~0.9B),... -
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x-transformers
A simple but complete full-attention transformer
A simple but complete full-attention transformer with a set of promising experimental features from various papers. Proposes adding learned memory key/values prior to attending. They were able to remove feedforwards altogether and attain a similar performance to the original transformers. I have found that keeping the feedforwards and adding the memory key/values leads to even better performance. Proposes adding learned tokens, akin to CLS tokens, named memory tokens, that is passed through... -
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IndexTTS2
Industrial-level controllable zero-shot text-to-speech system
IndexTTS is a modern, zero-shot text-to-speech (TTS) system engineered to deliver high-quality, natural-sounding speech synthesis with few requirements and strong voice-cloning capabilities. It builds on state-of-the-art models such as XTTS and other modern neural TTS backbones, improving them with a conformer-based speech conditional encoder and upgrading the decoder to a high-quality vocoder (BigVGAN2), leading to clearer and more natural audio output. The system supports zero-shot voice... -
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TorchAudio
Data manipulation and transformation for audio signal processing
The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch... -
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CTranslate2
Fast inference engine for Transformer models
CTranslate2 is a C++ and Python library for efficient inference with Transformer models. The project implements a custom runtime that applies many performance optimization techniques such as weights quantization, layers fusion, batch reordering, etc., to accelerate and reduce the memory usage of Transformer models on CPU and GPU. The execution is significantly faster and requires less resources than general-purpose deep learning frameworks on supported models and tasks thanks to many... -
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go-toml
Go library for the TOML file format
Go library for the TOML format. This library supports TOML v1.0.0. Full API, examples, and implementation notes are available in the Go documentation. As much as possible, this library is designed to behave similarly as the standard library's encoding/json. While go-toml favors usability, it is written with performance in mind. Most operations should not be shockingly slow. Decoder can be set to "strict mode", which makes it error when some parts of the TOML document was not present in the... -
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JSONLab
JSONLab: compact, portable, robust JSON/binary-JSON encoder
JSONLab is a free and open-source JSON/UBJSON/MessagePack encoder and decoder written in the native MATLAB language. It can be used to convert a MATLAB data structure (array, struct, cell, struct array, cell array, and objects) into JSON/UBJSON/MessagePack formatted strings and files, or to parse a JSON/UBJSON/MessagePack file into MATLAB data structure. JSONLab supports nearly all versions of MATLAB and GNU Octave (a free MATLAB clone). The development of JSONLab is currently funded by the... -
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Poison
An incredibly fast, pure Elixir JSON library
Poison is a fast and lightweight JSON library for Elixir focused on performance and idiomatic APIs. It provides straightforward encode and decode functions, along with a protocol-based encoder that lets you customize how your structs become JSON. Developers can derive or implement Poison.Encoder for domain types, control which fields are included, and map complex values into JSON-friendly forms. On the decoding side, it supports options for key handling and flexible parsing of JSON into... -
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ESPnet
End-to-end speech processing toolkit
ESPnet is a comprehensive end-to-end speech processing toolkit covering a wide spectrum of tasks, including automatic speech recognition (ASR), text-to-speech (TTS), speech translation (ST), speech enhancement, speaker diarization, and spoken language understanding. It uses PyTorch as its deep learning engine and adopts a Kaldi-style data processing pipeline for features, data formats, and experimental recipes. This combination allows researchers to leverage modern neural architectures while... -
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Step3-VL-10B
Multimodal model achieving SOTA performance
Step3-VL-10B is an open-source multimodal foundation model developed by StepFun AI that pushes the boundaries of what compact models can achieve by combining visual and language understanding in a single architecture. Despite having only about 10 billion parameters, it delivers performance that rivals or even surpasses much larger models (10×–20× larger) on a wide range of multimodal benchmarks covering reasoning, perception, and complex tasks, positioning it as one of the most powerful... -
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Wuffs
Wrangling Untrusted File Formats Safely
Wuffs is a memory-safe, zero-dependency library and domain-specific language for writing high-performance image codecs and related parsers. Instead of trusting ad-hoc C, Wuffs code is compiled to C with strong bounds, integer, and state checks inserted by construction, aiming to eliminate whole classes of security bugs without a heavy runtime. The design prioritizes predictable performance: decoders avoid dynamic allocation by default, return explicit “short read” signals, and run well in... -
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Multimodal
TorchMultimodal is a PyTorch library
This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference...
