raulftang Goto Github PK
Name: Raulftang
Type: User
Location: Beijing, China
Name: Raulftang
Type: User
Location: Beijing, China
A simple, decentralized dependency manager for Cocoa
Data Logger Application.
A simple chat system, supports text/voice/video chat, including a native iOS WebRTC client and a signaling system based on socket.io & Node.js
clb team contribute
Web-based Cloud Gaming service for Retro Game
Asynchronous socket networking library for Mac and iOS
This is a Chinese translation of the CUDA programming guide
DeDRM tools for ebooks
This is tensorflow implementation for paper "Deep Image Matting"
Deep Multi-scale CNN for Dynamic Scene Deblurring
https://serveo.net is an alternative for ngrok. taichunmin/serveo-server can let you host your own serveo. And taichunmin/serveo can let you secure URL to your localhost server through any NAT or firewall in Docker.
Dolphin is a GameCube / Wii emulator, allowing you to play games for these two platforms on PC with improvements.
dotEngine ios sdk
Doubango VoIP framework
WebRTC Plugin for Internet Explorer
Build cross platform desktop apps with JavaScript, HTML, and CSS
如何优雅地上网-科学上网小工具
The aim of this work is to recognize the six emotions (happiness, sadness, disgust, surprise, fear and anger) based on human facial expressions extracted from videos. To achieve this, we are considering people of different ethnicity, age and gender where each one of them reacts very different when they express their emotions. We collected a data set of 149 videos that included short videos from both, females and males, expressing each of the the emotions described before. The data set was built by students and each of them recorded a video expressing all the emotions with no directions or instructions at all. Some videos included more body parts than others. In other cases, videos have objects in the background an even different light setups. We wanted this to be as general as possible with no restrictions at all, so it could be a very good indicator of our main goal. The code detect_faces.py just detects faces from the video and we saved this video in the dimension 240x320. Using this algorithm creates shaky videos. Thus we then stabilized all videos. This can be done via a code or online free stabilizers are also available. After which we used the stabilized videos and ran it through code emotion_classification_videos_faces.py. in the code we developed a method to extract features based on histogram of dense optical flows (HOF) and we used a support vector machine (SVM) classifier to tackle the recognition problem. For each video at each frame we extracted optical flows. Optical flows measure the motion relative to an observer between two frames at each point of them. Therefore, at each point in the image you will have two values that describes the vector representing the motion between the two frames: the magnitude and the angle. In our case, since videos have a resolution of 240x320, each frame will have a feature descriptor of dimensions 240x320x2. So, the final video descriptor will have a dimension of #framesx240x320x2. In order to make a video comparable to other inputs (because inputs of different length will not be comparable with each other), we need to somehow find a way to summarize the video into a single descriptor. We achieve this by calculating a histogram of the optical flows. This is, separate the extracted flows into categories and count the number of flows for each category. In more details, we split the scene into a grid of s by s bins (10 in this case) in order to record the location of each feature, and then categorized the direction of the flow as one of the 8 different motion directions considered in this problem. After this, we count for each direction the number of flows occurring in each direction bin. Finally, we end up with an s by s by 8 bins descriptor per each frame. Now, the summarizing step for each video could be the average of the histograms in each grid (average pooling method) or we could just pick the maximum value of the histograms by grid throughout all the frames on a video (max pooling For the classification process, we used support vector machine (SVM) with a non linear kernel classifier, discussed in class, to recognize the new facial expressions. We also considered a Naïve Bayes classifier, but it is widely known that svm outperforms the last method in the computer vision field. A confusion matrix can be made to plot results better.
The Flutter engine
Shell scripts to build FFmpeg for iOS and tvOS
A set of tutorials that demonstrates how to write a video player based on FFmpeg
A proxy software to help circumventing the Great Firewall.
Performant animated GIF engine for iOS
A fast reverse proxy to help you expose a local server behind a NAT or firewall to the internet.
SensorFusion for iOS
A utility for fundamentals data of China commodity futures
glsl photoshop blending modes. glslify formatted.
A performant Grid-View for iOS (iPhone/iPad) that allows sorting of views with gestures (the user can move the items with his finger to sort them) and pinching/rotating/panning gestures allow the user to play with the view and toggle from the cellview to a fullsize display.
An open source iOS framework for GPU-based image and video processing
GPUImage 2 is a BSD-licensed Swift framework for GPU-accelerated video and image processing.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.