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John D. Pope's Projects

audioplayermanager icon audioplayermanager

Small Swift Wrapper and Queue-Manager around AVPlayer which let you play MediaPlayer items and stream songs from URLs.

audioplaylistcontroller icon audioplaylistcontroller

A configurable playlist controller that uses MPMediaPickerController to create a playlist and display the selected songs and play them. It also provides a player control view for controlling the playback. Supports persistence of the playlist created within a single app session

audiorecognizer icon audiorecognizer

Roy van Rijn has written wonderful post about Shazam algorithm and how to implement it on our own. To do this he placed many chunks of his project source code, but he did not upload all source code of his application because as he stated: The Shazam patent holders lawyers are sending me emails to stop me from releasing the code and removing this blogpost. It occurred that core of this algorithm is very simple. I have analyzed his post and as weekend project I have written simple Proof-Of-Concept application which outputs its findings to console. It gives surprisingly correct answers. For now I have tested 10 different mp3 audio files and this application was able to recognize each of them. Application is learning basing on path to mp3 file on your local disk or http stream of mp3 file from any source and recognize by sound from microphone.

audiostreamer icon audiostreamer

A Swift 4 framework for streaming remote audio with real-time effects using AVAudioEngine

augmentkit icon augmentkit

A framework that provides an easy way to use ARKit without relying on SceneKit. Made with app developers in mind.

augmentor icon augmentor

Image augmentation library in Python for machine learning.

authelia icon authelia

The Single Sign-On Multi-Factor portal for web apps

auto2bot icon auto2bot

An automatic bot similar to Shapeshift and Changelly

autocoding icon autocoding

Easily have an object serialized and deserialized automatically in Swift

autoencoder icon autoencoder

This repository contains code for vectorized and unvectorized implementation of autoencoder. The autoencoder has been trained on MNIST dataset. I implemented the autoencoder exercise provided in http://deeplearning.stanford.edu/wiki/index.php/UFLDL_Tutorial. The entire code is written in Matlab.

autoencoder-1 icon autoencoder-1

Implementation of Semantic Hashing. Modified from Ruslan Salakhutdinov and Geoff Hinton's code of training Deep AutoEncoder

autoencodersynthesis icon autoencodersynthesis

Performs interactive audio synthesis using a previously trained auto encoder. VIsualizes hidden layer and allows for interaction with hidden units. W/ Andy Sarroff. See Andy's github (woodshop) for more interesting projects using Deep Learning and audio synthesis.

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