ECE597 Project Music Visualizer

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thumb‎ Embedded Linux Class by Mark A. Yoder


Team members: Zhihao Xue, Ying Ying Zhou

Grading Template

I'm using the following template to grade. Each slot is 10 points. 0 = Missing, 5=OK, 10=Wow!

09 Executive Summary
09 Installation Instructions 
08 User Instructions
09 Highlights
09 Theory of Operation
10 Work Breakdown
09 Future Work
10 Conclusions
10 Demo
10 Not Late
Comments: Nice demo.  Thanks for fixing up the wiki

Score:  93/100

Executive Summary

This project is a music visualizer implemented on a 10x10 LED matrix controlled by Beaglebone Black, where a pattern that corresponds to the spectrum of a wav file is displayed on the LED. We are able to compute the spectrum of slices of the given wavefile, convert the spectrum to a 10 by 10 matrix, and display the spectrum on the LED matrix. Currently, the LEDs updates every 0.1 second. Depending on the size of the file, it may take a long time (about 1 minute for a 7M wav file) to parse the file. Once the file is loaded, the software will play the wav file and synchronize it with the LED display. Adjustments can be made to change the design of the display pattern, and how often the screen is updated.

Packaging

The LED matrix is a 3-pin device that connects directly to the beaglebone. LED-Matrix.jpg

Installation Instructions

Hardware

Connect 10x10 Neopixel LED matrix to P9_22 on Beaglebone, Black is GND, Red is VCC and White is DIN, the schematic is below:

Schem.jpg

Connect USB sound card to Beagle

The sound card we using is CREATIVE SOUND BLASTER X-FI GO! PRO The sound card driver is included in our git repo

Beagle-main.jpg

Connect Beagle to host computer

Beagle-all.jpg

Software

Download and install LEDscape from git repository

bone$: git clone https://github.com/Yona-Appletree/LEDscape.git

Please following the instruction [1] under LEDscape repo to install LEDscape and disable HDMI ports

Download and install scipy and numpy package

bone$: sudo apt-get update
bone$: sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose
bone$: sudo apt-get install build-essential
bone$: pip install cython
bone$: git clone git://github.com/numpy/numpy.git numpy
bone$: cd numpy
bone$: python setup.py build
bone$: python setup.py install --prefix=$HOME/local

After installing LEDscape, scipy and numpy packages, get the project git repo

bone$: git clone https://github.com/xHa0z/musicvisualizer.git

Then make USB sound card as default output

bone$: cd musicvisualize
bone$: cp asoundrc ~/.asoundrc

User Instructions

Enter musicvisualizer directory

bone$: cd musicvisualizer

Enable PRU and LEDscape service

bone$: cd musicvisualizer
bone$: ./setup.sh

Run visualizer

bone$: python final.py

Highlights

Here is our YouTube video

This video shows how the LED matrix works with Super Mario theme song. The right most column is low frequency while the left most column is high frequency.

The spectrum is update every 0.1 second.

https://www.youtube.com/watch?v=gEa0vO2T--I

Theory of Operation

The software reads a wave file, and obtains the amplitude and the sampling frequency. The amplitude is stored in an array, while the sampling frequency will be used to determine how many samples in the amplitude array represents 1 second.

Most wav files are written with a sampling frequency of 44100 Hz, indicating 44100 samples in a second, which is a lot more than what we need to compute a 10x10 spectrum. We downsample the amplitude array by a factor of 4, to decrease the number of computation needed.

The amplitude array (downsampled to 11025 Hz) is then sliced into 0.1 second segments, each with a length of 1102 samples. First array is sample 0-1102, second array is 1103-2205, and so on. Each new array represents 0.1 second of the original wav file. Fast Fourier transform is used to obtain the spectrum of each 0.1 second segment.

To map the spectrum onto a 10x10 grid, the frequency component is divided into ten columns, by finding the average of all amplitude values for every 1/10 of the length of the Fourier transform. This gives us a 1-D array of 10 elements, where the length of the x-axis of the spectrum is compressed down to 10. The amplitude in the 1-D array is then normalized to a value between 0-10, therefore compressing the y-axis of the spectrum down to 10.

This array is converted to a 10x10 matrix, and is displayed on the LED matrix using open pixel control.

The sound and display component of the software runs simultaneously so that the display is synchronized with the sound.

Work Breakdown

Major tasks 1. Install and test LEDscape; drive the LED matrix using default test programs in LEDscape. -Zhihao

2. Install and test open pixel control; make a custom pattern in open pixel control and display it on the LED matrix. -Ying Ying

3. Read a wav file, compute its spectrum, and map it to a 10x10 matrix. -Ying Ying

4. Display the spectrum using open pixel control. -Zhihao

5. Play wav file and synchronize sound with display. -Zhihao

6. Test other sound files. -Ying Ying


Future Work

Currently we only have one pattern for the spectrum, which displays red, blue, green, and white. More complicated design patterns could be implemented to explore the capabilities of LEDscape(fading, color changing, etc). Minor adjustments could be made to the software to make it more versatile, and work more smoothly. Some issues we currently have are with the size of the input file (only works if size of original file is divisible by 4), and the display can be delayed depending on the input file.

Conclusions

We have implemented a music visualizer using Beaglebone Black, by displaying the spectrum of a given wav file on a 10x10 LED matrix.

Although the original scope was to make a music visualizer that displays a pattern for a given sound file, to make the project more interactive, a recording element could be added, and the spectrum could be updated in real time. Another expansion of the project is to stack several LED matrices, add a third variable, and create a 3-D music visualizer.



thumb‎ Embedded Linux Class by Mark A. Yoder