A neural network that transforms a design mock-up into a static website.
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
🔥💥RxFFmpeg 是基于 ( FFmpeg 4.0 + X264 + mp3lame + fdk-aac + opencore-amr + openssl ) 编译的适用于 Android 平台的音视频编辑、视频剪辑的快速处理框架，包含以下功能：视频拼接，转码，压缩，裁剪，片头片尾，分离音视频，变速，添加静态贴纸和gif动态贴纸，添加字幕，添加滤镜，添加背景音乐，加速减速视频，倒放音视频，音频裁剪，变声，混音，图片合成视频，视频解码图片，抖音首页，视频播放器及支持 OpenSSL https 等主流特色功能
Simple Binary Encoding (SBE) - High Performance Message Codec
🔥🔥🔥自定义Android相机(仿抖音 TikTok)，其中功能包括视频人脸识别贴纸，美颜，分段录制，视频裁剪，视频帧处理，获取视频关键帧，视频旋转，添加滤镜，添加水印，合成Gif到视频，文字转视频，图片转视频，音视频合成，音频变声处理，SoundTouch，Fmod音频处理。 Android camera(imitation Tik Tok), which includes video editor,audio editor,video face recognition stickers, segment recording,video cropping, video frame processing, get the first video frame, key frame, vi…
Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
Convert images of LaTex math equations into LaTex code.
🤖 PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
Sequence-to-sequence framework with a focus on Neural Machine Translation based on PyTorch
Declarative binary reading and writing: bit-level, symmetric, serialization/deserialization
Fantastic toolkit for CTFers and everyone.
FFmpegCommand适用于Android的FFmpeg命令库，实现了对音视频相关的处理，能够快速的处理音视频，大概功能包括：音视频剪切，音视频转码，音视频解码原始数据，音视频编码，视频转图片或gif，视频添加水印，多画面拼接，音频混音，视频亮度和对比度，音频淡入和淡出效果等
This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai
Tensorflow seq2seq Implementation of Text Summarization.
最新版ffmpeg3.3-android，并通过CMake方式移植到Android中,并实现编解码，转码，推拉流，滤镜等各种功能
BERT for Multitask Learning
Decode All Bases - Base Scheme Decoder
Multiple implementations for abstractive text summurization , using google colab
Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"
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