Search Results for "linux h264 decoder" - Page 4
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Showing 370 open source projects for "linux h264 decoder"
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nxtvepg is a decoder and browser for Nextview EPG - a subscription-free electronic TV program guide in the analog domain. Up to ~2012, Nextview was broadcasted in Germany, Austria, Switzerland, Turkey, Belgium and France and covered all major TV networks. Due to shut-down of analog transmission Nextview is defunct now. nxtvepg can still be used as browser for XMLTV files and EPG grabber from teletext.
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PNG_IO
An Ada 2012 library for reading and writing PNG image files
PNG_IO is an Ada2012 coder/decoder for Portable Network Graphics, allowing Ada2012 programs to read and write PNG files. It is portable across machines and operating systems. It depends on Zlib and Zlib_Ada to perform lossless compression and decompression. Versions prior to v5 were in Ada95. -
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VABlog
YUV/PCM/H264/H265/AAC/FFmpeg/Opengl
VABlog is a full-stack web application project that combines blogging functionality with multimedia and video-related features. It is designed as a learning-oriented system that demonstrates how to build a modern web platform with both frontend and backend components. The project includes user authentication, content publishing, and media management capabilities, allowing users to create and manage posts with embedded video content. It integrates database storage for handling user data,... -
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Amazon Kinesis Video Streams Parser Lib
Easy to work with the output of video streams
Amazon Kinesis Video Streams parser library is for developers to include in their applications that makes it easy to work with the output of video streams such as retrieving frame-level objects, metadata for fragments, and more. The Amazon Kinesis Video Streams Parser Library for Java enables Java developers to parse the streams returned by GetMedia calls to Amazon Kinesis Video. A streaming Mkv Parser called StreamingMkvReader that provides an iterative interface to read the MkvElements in... -
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FasterTransformer
Transformer related optimization, including BERT, GPT
FasterTransformer is a high-performance inference library designed to accelerate transformer-based models such as BERT, GPT, and T5 on NVIDIA GPUs. It provides optimized implementations of transformer encoder and decoder layers using CUDA, cuBLAS, and custom kernels to maximize throughput and minimize latency. The library supports multiple deep learning frameworks, including TensorFlow, PyTorch, and Triton, allowing developers to integrate it into existing pipelines without major changes. It... -
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NÜWA - Pytorch
Implementation of NÜWA, attention network for text to video synthesis
Implementation of NÜWA, state of the art attention network for text-to-video synthesis, in Pytorch. It also contains an extension into video and audio generation, using a dual decoder approach. It seems as though a diffusion-based method has taken the new throne for SOTA. However, I will continue on with NUWA, extending it to use multi-headed codes + hierarchical causal transformer. I think that direction is untapped for improving on this line of work. In the paper, they also present a way... -
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Lyra
A Very Low-Bitrate Codec for Speech Compression
lyra is a neural audio codec designed to deliver intelligible, natural-sounding speech at extremely low bitrates, making real-time communication viable on constrained networks. It replaces hand-engineered codecs with learned models that capture speech characteristics more efficiently and reconstruct waveforms with a neural vocoder. The system targets mobile-class hardware, balancing latency and quality so it can run in real-time on phones. Its architecture is resilient to packet loss and... -
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wdesea
RTMPServer, FDM, chocolate 3D Print
Android RTMP Server(H264Stream) JNI FDM chocolate 3D Print -
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Karlo
Text-conditional image generation model based on OpenAI's unCLIP
Karlo is a text-conditional image generation model based on OpenAI's unCLIP architecture with the improvement over the standard super-resolution model from 64px to 256px, recovering high-frequency details only in the small number of denoising steps. We train all components from scratch on 115M image-text pairs including COYO-100M, CC3M, and CC12M. In the case of Prior and Decoder, we use ViT-L/14 provided by OpenAI’s CLIP repository. Unlike the original implementation of unCLIP, we... -
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CPT
CPT: A Pre-Trained Unbalanced Transformer
A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation. We replace the old BERT vocabulary with a larger one of size 51271 built from the training data, in which we 1) add missing 6800+ Chinese characters (most of them are traditional Chinese characters); 2) remove redundant tokens (e.g. Chinese character tokens with ## prefix); 3) add some English tokens to reduce OOV. Position Embeddings We extend the max_position_embeddings from 512 to 1024. We... -
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LightSeq
A High Performance Library for Sequence Processing and Generation
Lightseq is a high-performance library focused on efficient inference and training for deep learning models, especially large language models (LLMs) and transformer-based architectures. Its goal is to optimize both memory usage and computational throughput, enabling faster training or inference on limited hardware while maintaining model quality. Lightseq provides optimized CUDA kernels, quantization strategies, and runtime optimizations tailored for transformer operations — which often are... -
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EnCodec
State-of-the-art deep learning based audio codec
Encodec is a neural audio codec developed by Meta for high-fidelity, low-bitrate audio compression using end-to-end deep learning. Unlike traditional codecs (like MP3 or Opus), Encodec uses a learned quantizer and decoder to reconstruct complex waveforms with remarkable accuracy at bitrates as low as 1.5 kbps. It employs a convolutional encoder–decoder architecture trained with perceptual loss functions that optimize for human auditory quality rather than raw waveform distance. The model can... -
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This is a research project to possible improve compression using LZ77, LZSS or bwt, bwt is used on the bzip2 compression library, the v28 from 04/dec/2022 is the first version to almost beat lzma, indeed it is a tweak of lzma, the decoder for v28 will follow in a few days
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BCConvert
Converts h264 to avi and mp4 for BC platform CCTV
H264 to AVI and H264 to MP4 conversion tool for BC platform CCTV. BC platform CCTV includes: Reolink RLN8-410, RLN16-410 Swann NVR-7400, NVR-7300, NVR-7285, NVR-7085, NVR-7072 iNewCam DVR7904 Amcrest DVR-960H Dripstone 400503, 400505 eSSL NVR-PoE-9304, NVR-PoE-9308, B Series VisionNet 185033 - 185040 This app can split h264 files to video and audio then uses ffmpeg to create mp4 or avi. Or it can use BCNetSDK.dll from official clients for h264 to mp4 or avi. -Works best if... -
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DiffSinger
Singing Voice Synthesis via Shallow Diffusion Mechanism
DiffSinger is an open-source PyTorch implementation of a diffusion-based acoustic model for singing-voice synthesis (SVS) and also text-to-speech (TTS) in a related variant. The core idea is to view generation of a sung voice (mel-spectrogram) as a diffusion process: starting from noise, the model iteratively “denoises” while being conditioned on a music score (lyrics, pitch, musical timing). This avoids some of the typical problems of prior SVS models — like over-smoothing or unstable GAN... -
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LaMDA-pytorch
Open-source pre-training implementation of Google's LaMDA in PyTorch
Open-source pre-training implementation of Google's LaMDA research paper in PyTorch. The totally not sentient AI. This repository will cover the 2B parameter implementation of the pre-training architecture as that is likely what most can afford to train. You can review Google's latest blog post from 2022 which details LaMDA here. You can also view their previous blog post from 2021 on the model. -
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JSON Parser
JSON Parser written in C that outputs JSON into D-List list objects
JSON parser is a highly efficient JSON data decoder written in C, that parses JSON data into a form that is very easy to use from within C code. You only need to include the json-parser.h file in your source code. If your project does not already incorporate D-List, you will also need to include dlist.h The JSON parser package also includes a JSON validator that does not parse or create resources, but allows the caller to validate JSON data from unknown sources, prior to any parsing... -
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Mask2Former
Code release for "Masked-attention Mask Transformer
Mask2Former is a unified segmentation architecture that handles semantic, instance, and panoptic segmentation with one model and one training recipe. Its core idea is to cast segmentation as mask classification: a transformer decoder predicts a set of mask queries, each with an associated class score, eliminating the need for task-specific heads. A pixel decoder fuses multi-scale features and feeds masked attention in the transformer so each query focuses computation on its current spatial... -
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Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
Example image Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series... -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the... -
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pcdtojpeg converts PCD (Kodak Photo CD) image files into high quality JPEG images. Conversions are at the maximum available PCD resolution, and are fully color managed - no blown highlights or color casts. A C++ PCD decoder library is also available.
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Logisim Italian Fork
in progress...
Github: https://github.com/LogisimIt/Logisim -
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Reformer PyTorch
Reformer, the efficient Transformer, in Pytorch
This is a Pytorch implementation of Reformer. It includes LSH attention, reversible network, and chunking. It has been validated with an auto-regressive task (enwik8). -
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SEZEII
Plugin-based video converter
SEZE is a plugin-based video converter for Windows/Linux. You can write your video filter in C++ (see section "How to make video effect"). Output video is a lossless H264 RGB24 format and not contain audio. -
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fairseq-lua
Facebook AI Research Sequence-to-Sequence Toolkit
fairseq-lua is the original Lua/Torch7 version of Facebook AI Research’s sequence modeling toolkit, designed for neural machine translation (NMT) and sequence generation. It introduced early attention-based architectures and training pipelines that later evolved into the modern PyTorch-based fairseq. The framework implements sequence-to-sequence models with attention, beam search decoding, and distributed training, providing a research platform for exploring translation, summarization, and...
