Pinned Repositories
-smacktalk
openfire+smack写的基于android的即时聊天软件
09-ZombieRunner
First person shooter with Unity terrain and AI pathfinding
3DMapVisualization
Multiplatform application building 3D models from contour input (OpenOrienteering files)
aaf-easyphotomap
:camera: Easy Photo Map is a photomap application that displays the location of the photo on the map using the location information included in the photo.
accordion
Android accordion emulator
Activiti
Activiti is a light-weight workflow and Business Process Management (BPM) Platform targeted at business people, developers and system admins. Its core is a super-fast and rock-solid BPMN 2 process engine for Java. It's open-source and distributed under the Apache license. Activiti runs in any Java application, on a server, on a cluster or in the cloud. It integrates perfectly with Spring, it is extremely lightweight and based on simple concepts.
adempiere
ADempiere Business Suite ERP/CRM/MFG/SCM/POS done the Bazaar way in an open and unabated fashion. Focus is on the Community that includes Subject Matter Specialists, Implementors and End-Users.
akaunting
Free and Online Accounting Software
android-chat-ui
A messages UI library for Android
Kalkun
Open Source Web based SMS Management
ahmadRMusa's Repositories
ahmadRMusa/sqlitebrowser
Official home of the DB Browser for SQLite (DB4S) project. Previously known as "SQLite Database Browser" and "Database Browser for SQLite". Website at:
ahmadRMusa/oTplayer
Audio (and video) player for oTranscribe
ahmadRMusa/HERO
A CrossFit Gym Management Application (ASP.NET MVC 5)
ahmadRMusa/Emotion-Recognition-Using-SVMs
A software which detect a human face through live webcam feed and identifies the emotion of the person (i.e. the person is happy or sad).
ahmadRMusa/laravel-books-api
Books API Built in Laravel 5
ahmadRMusa/Simple-Instant-Articles-for-Facebook
Add support for Facebook Instant Articles to your WordPress site.
ahmadRMusa/p2p-lib
a p2p library, we can share our books to friends
ahmadRMusa/bookstore
An online bookstore using Laravel framework
ahmadRMusa/HappyNet
Convolutional neural network that does real-time emotion recognition. HappyNet detects faces in video and images, classifies the emotion on each face, then replaces each face with the correct emoji for that emotion. Based on Caffe and the "Emotions in the Wild" network available on Caffe model zoo.
ahmadRMusa/liby.io
Database website for organizing large volumes of books.
ahmadRMusa/Vector-Pinball-Editor
GUI editor for Vector Pinball
ahmadRMusa/Ball-Game
A simple game in libGDX
ahmadRMusa/getmybooks
its books site
ahmadRMusa/3DMapVisualization
Multiplatform application building 3D models from contour input (OpenOrienteering files)
ahmadRMusa/power-up-template
A static GitHub pages hosted sample Power-Up
ahmadRMusa/Emotion-Detection-in-Videos
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.
ahmadRMusa/Shamarly
Shamarly Mushaf for Android مصحف الشمرلي للأندرويد
ahmadRMusa/shamraly-images
Shamraly Quran Mushaf for developers
ahmadRMusa/tafseer-sqlite-db
Quran Tafseer Sqlite database (8 tafseer books)
ahmadRMusa/leaf-identification
A Leaf Identification System
ahmadRMusa/augmented-reality-example
Android Implementation of Augmented Reality
ahmadRMusa/Ruby-on-Rails-gym-management-system
Gym online management system in Ruby on Rails
ahmadRMusa/UberClone
ahmadRMusa/opencbs
Open-source core banking system for microfinance institutions
ahmadRMusa/bookshare
share books in campus
ahmadRMusa/staunton
The massive multiplayer Chess game slash :sparkles: ReactiveCocoa tutorial :sparkles:
ahmadRMusa/xmpp-muc-android
XMPP MUC androud client example using Smack
ahmadRMusa/oTinput
A dynamic media input form developed for oTranscribe
ahmadRMusa/OnlineChess
Here is a cross-platform (Android/Desktop) Chess game for playing with your friends
ahmadRMusa/android-piano
Piano for Android