Project 1 – Matthew Xie

For Project 1, I created a self-generated melody & drone patch.

First off, a wav file of single piano notes played consecutively is analyzed. While Max randomly selects portions of the wav file to play in snippets, the frequency of the audio being played is analyzed and triggers the 1st higher-pitched drones in intervals. Meanwhile, the 2nd drone patch can be triggered by using the keyboard as a midi-keyboard.

The drone is achieved via subtractive synthesis. The pink noise generator is send through filters, only letting pass certain frequency bands. Then, the subtractive synthesis is done with a handful of inline reson~ objects.

The ‘analyzer~’ object is referenced from the maxobject.com website.

Delay is added to all sound effects. Piano melody can also go through a noise gate at will. The speed of the piano sampling can also be manipulated, which will immediately also effect the speed of the self-generated higher pitched drones.

Here is an example of the music being played:

Code is Here:

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view raw Project 1 _ Matthew Xie hosted with ❤ by GitHub

Reactive Visuals in Max for Live (Project 1) — Jonathan Cavell

For our first longer term project, I created a patch which resulted in a more stylistic visual which reacted to midi and audio data from Ableton Live session information. Within the patch, gl objects are set to render and erase based of midi information from each instrument and are manipulate by the amplitude of the audio signal generated by each instrument. The end result is a set of shapes/objects, each assigned to their own instrument, which are turned on and off by that instrument and manipulated by its audio signal.

The patch automates the movement, transparency, and rotation of objects within the video window in direct proportion to the amplitude signal of each midi instrument in Live. For the shapes associate with the synth, I created an image in Adobe Illustrator which was then imported into Max and layered to create a new object. The drum kit uses clearly defined geometric shapes to contrast the more amorphous shape generated by the synth.

Midi Send Portions of the Patch

Synth Visual Portion of the Patch

Drum Visual Portion of the Patch

The patch itself, while it is rather large (and divided into a set of four patches within the Live session) is built on a series of smaller patches to execute a simple, but polished concept. My personal goal for this project was to become familiar with a set of techniques which I had not utilized in a previous project and familiarize myself with the Max for Live environment which operates with a unique set of limitations. I wanted to create a patch that generated a stylistic visual element which could be replicated for live performance which came across as a more polished visualization with smoother transitions than what I was able to achieve in previous projects.

Of these techniques, the ones I was most concerned about ended up being the easiest (ex. creating a unique shape/image in Adobe Illustrator and converting it into an .obj for use by jit.gl since I do not have a visual media background) and the ones I thought I should be able to complete easily proved more complicated when working in the Max for Live environment (ex. automating the transparency of different jit.gl objects and creating smooth movement across the video window).

I would like to experiment further with the automation to create a much more experimental version of the visual elements, but I am pleased with how this first version turned out.

Drum Visualization Patch

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view raw dumviz.maxpat hosted with ❤ by GitHub

Synth Visualization Patch

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view raw synthvid2.maxpat hosted with ❤ by GitHub

Midi Send Patches

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view raw drummidisend.maxpat hosted with ❤ by GitHub
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view raw synthmidisend.maxpat hosted with ❤ by GitHub

Project 1 – 3x Oscillator – Will Walters

For this project, I created a synthesizer instrument called a 3x Oscillator. It does more or less what it says on the tin, the user can control three oscillators which can be played via midi input. When a note is played, the oscillators produce sound in tandem, creating a far fuller sound than a single tone. The oscillators can be tuned and equalized relative to each other, and the waveform of each can be selected – sinusoid, sawtooth, or square. Other options for customization include total gain of the instrument; independent control of the attack, decay, sustain, and release; and a filter with both type and parameters customizable.

Here’s a video of me noodling around with it:

(sorry about the audio in some places, it’s my capture, not the patch itself)

The main patch can be found here.

The patch used inside poly~ can be found here.

Project 1 – Kinect Depth Projection Mapping – Adam J. Thompson

This project was an exploration of how the Kinect might be used to map pre-rendered and generative audio-responsive projections onto the faces of instruments.

The patch uses adjustable maximum and minimum Kinect depth map thresholds to isolate the desired object/projection surface, and subsequently uses the created depth map as a mask. This forces the video content to show through only in the shape of the isolated surface.

The patch is less precise on instruments which expose a large part of the body, as, for example, legs tend to inhabit similar depth thresholds as the face of a guitar; it is better suited to instruments with larger faces that obscure most of the body, such as cellos and upright basses.

In attempting to map to the surface of a guitar, I also toyed around with other uses for the patch, which include this animated depth shadow, which places the video mapped shadow of the performer on the wall, creating the potential for visual duets between any number of performers and mediated versions of their bodies.

I plan to continue exploring how to make this patch more precise on a variety of instruments, possibly by pairing this existing process with computer vision, motion tracking, and/or IR sensor elements.

The gist is here.

Jonathan Namovic Project 1- Launch Pad

For my project 1 I decided to try and make an instrument out of my computer. I separated out the keys into distinct regions and assigned them midi values based on where they were on the keyboard. I then used these note values in different modes to produce different sounds. I also included a boomerang effect that allows the user to record a short piece of audio and then the patch loops it and repeatedly plays it. I created ten drum sound effects by filtering noise in different ways. The main instrument portion is a square wave filtered in a similar way to make the note sound less harsh. The last mode is a saw tooth tremolo that repeated plays the same not so long as it is held. The launch pad is polyphonic and can export the sound in the loop buffer.

A short example piece that has been layered three times

Audio Player

main patch code:

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tqltzgcqClA4DYy3pgYIkOAmdbZsYC4j30lW91RaxeOA4DMl91+ccyOfLATb
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Kcc1ym72uYeunrB8+1GxsPX+yapMRnbNj+O++ncrTl.
-----------end_max5_patcher-----------
</code></pre>
view raw Namovic project 1 main patch hosted with ❤ by GitHub

note maker code:

<pre><code>
----------begin_max5_patcher----------
1282.3oc0Z01aihCD9yYk1+CH93cYY86Fe+UVspxk31xdIPDP51pUW9seFaH
caaJYHmcSuJEHwDX7yyLyy3wo+5yeZQ500OXZSS9qjukrXwurirvMV+HKFGX
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FKPlAKvi.KXVaQrULXR0.hRjIsIDRmNffCsz3xPjWbLpfINep35ccc0UPfKF
6x+IrwiWjkBPTg2s+GSVjjw7JdJuiV4zBIPpQFEQPEJBw8E50l8InDbhjaAG
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fxpoCv80E8+tjTzEC5rWou4MiqszW9CU6fQ+EdAgzVuqoXbdN10is+9CS3Ul
1txJsqaue6akmdhlXfavgG0ILnHbFT.xfHOODBCxgXv.BPFHWHMbFjBhQIgy
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vUbAFlwx2.ygvySAIWQCm9HEzRFFcEAvfDPEbTpHRx.mBrHFaigU1EEL+LFT
cWb3VKJV.csuwREE1L.yioaV3WHJroPHLHHMyvUcFyduiiIf6gKPFDCBgGuJ
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32JgGDC+iTjto1F1VsqbL4wMGrG9WyCwE8A
-----------end_max5_patcher-----------
</code></pre>
view raw Namovic project 1 note maker patch hosted with ❤ by GitHub

drum patch code:

<pre><code>
----------begin_max5_patcher----------
3187.3oc2cssaiajD8YGf7OHHf8kccH5aUeI+JAACnsYbTVaICI4ISPv5u8s
uPIQ40RrnmpU2ZeXrGSJwhc0UcpCqpql+8O9C2L+tUeqay7Y+7reY1M2729i
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PZrD5VfBowRGRikgVfzLBMnb7Mz43aP43anyw2fxwWSmiuQiVfz33aP43qoy
w2fxwWSmieXmr.gUJcN9FTN9FBMZ3nlCczIPFZARiUpFEoFMcHMZTHMZEcBz
fxsfNnMMNjF5hVnAzygzDOTiJhulNGeMNGe5h3qYnEHQiPTOaAcxCP42CzEc
Jr25NtaHXnSfnXX.DpRQMGBzEr..zBjlfE.p.9.c98.J+dEcQm.TA7IzHkgQ
iJoiQCtPEjYwnPAynnSgprnEHQiPTvLB575UZzI0mnQHfwFUQGiscWpQDHcv
LJT7YTzELTIPKPhlCQgqonCmQgh.kjNV2Jr.azHNIpLzHoKxjDEvljNjToAs
ICMbtknvYjzgyHQYyHoCmQhBmQRGNiTfVfzfyHQgyHHzs.WAmoCXC0THcOTg
.WQmnysWXwUkK5DHp7yHnC5Vfi.Egyg.ZmBZPREnxDrftLAKvsPSnCIUHPy5
lHUZvf2NZwlem25p0OzsNtNktb2BpSbKvn5VvLZgvxtVX7agrqEziljfrqEF
+VH6ZA0n2BxbqEF8VPaxsV.FkOfM2ZA4n2BYehXbs.K2SDhQebEH2ZgQuEjt
bqEFmve10BiGZN6Nki5QHxN533TvxtGga7GMJ6woPbOT9oBdN0BnxxOmtbDi
hcLmtGohi6oTo6w94Vz0KkF9+bbEnktjSw0nrYTjk5FNpmRkvU2JGU52f28r
rj5Xh6V38UbgTzINpmUmxFlfavkgGJaKDbqXSBEH+RuVsSwQGehjQ3njgCEj
QHPOCmwCiQnH03EIQPgLbXgLBcQX3vAXDBDvv05TLJcRvwLgQXfaFCuHoZTh
dsUQzXDUgylel9Lr8kW9Z25M8eijjl+b6erJFmyba5uWrL82xzeut6qK18UR
MU47102+6K11c+1WWmZayuo6eMPM+4U9nlKecwtX2w6A+O9u.BVtZdB
-----------end_max5_patcher-----------
</code></pre>
view raw Namovic project 1 drum patch hosted with ❤ by GitHub

saw tooth tremolo code:

<pre><code>
----------begin_max5_patcher----------
1063.3ocyXE1aaCBD8yYR6+.xebJyiCvX79qLMEQbnsdyAGYS5Z0zxu8gg3j
s0LGbGVYUJl5CiOdu633g+9aeyhj0MOo5RPeD8IzhEe2ZYgyVukECFVjrU9T
Ysry8fIZ02ZV+kjkG6yndx3ruUYZaPPF9TW6jlxGpz2upUUZ7NgvHoYKQTRQ
JdIhm0ekPRwnOOLnl8lZkw77NkeDIqk56SN2em44ZWWIm7id+1JscPt4G4Wr
5eWNyvf4pMtAagv6oPhy3Od6a5asMKClEVu2XZziAUfI5QGP4NPxFtFOnBgC
Uh30C0+V.+cGFC9BVJwFoIYTGvK5C6WIR2UcuVVOOwZBDeBnqTVqNfvHv8iL
FcPY4trgBWSAOfD+ISG7IPG33SG0UZ0gP3.NougNANXYrJCPt.W.+CqMtaut
zTMdg.hfmxs+kwsvEbfFicDQeyHf+t5FooG6C+ds0G1Iak1xyp1UJsbseL3K
SPrKPPhSud4lM6ZpzliaYXQCImmUXAFNsPXwXtEbKQ4Eo4hbBk0aOicxNgwR
4BrHC56fRbFy7jANE39A+aOD3eHgfjV3dmtWo2XgMEBxwDvYLevOnO+pCmaU
ccx6UuL298vXQXlu5N8XzMjZcySUNnHI9XeTnSKf+SfNaFJvqps.EgCf.H4N
EMYjPUzrLFDwkJmUDednE8XSUoUn3XxcndENhv4gIfeb3IByPdf0infVEj4.
OM+kf+UpkCeoL8y4icxGUaVYMZmIqjFSakUWpWP+hyfzV2110pxlsaUZOh7b
z.IEUx5CGPvnqXDNEgTe9BULGJglxg.he5xGP.IOcTIAXW9BPbKSXP.bfWLv
7T5LO9bfbSW6AKNQLrcuYQujmQIDf6kF5UHBhIoM77+MwxpYgKBB3wmjLOT0
sqo94QUMSNdXApuvZHLiUgVOQz27OWA5hJlyliSShBnpwwsWnjabUC9rrIyg
w2kwSALeISFad2jYFTSI+1g.hvXeDt3FGgAR7Yfsll6tNCLb9XVbkPMguVDL
CQ+85cxxudczKb6.vJ9OnL2LjAToCZItiCn3aVB.6EE38tw8Md9yuWrCF8c7
GDRWy91xg4o+jI1j6yy2MpNSkV597ImeHn+ovicF9I4O7U8GKZ9SDD9DQye7
PvGMZtylTDf+HwyegBOHJtiBAAu3E9nAkdFM2MLyG2ewCdjf3Sd77GNn3GDs
DFxTxWNU.ucip0I5JRyfqWvIOdTbPYrveAwPDlAPP0zo29o.fmw3NDzR4gED
wvg4Ag43sXF3gV7.lqvbPy.HaNCy8SARnSgX3vrPJnDOAZ.61uZlc6WMSBdi
qHQ6AsyLbYkbGOHfb2tGUscGGh2W1i.8kFGsjuzeek1eO0eeq5wpgg3+FaIx
V6QfL1y+ru0e1km3rjiitwRx58UCgZ2bvd4m.abXdEA
-----------end_max5_patcher-----------
</code></pre>
view raw Namovic project 1 saw tremello patch hosted with ❤ by GitHub

Project 1 – Isha Iyer

For project 1, I used a Kinect to control the motion of a particle system using my hand. I am very interested in different applications of motion tracking and I think this was a good introduction to help me learn how the Kinect works. Here is a download link to a video showing my project in real time: IMG_1479

I used this tutorial to help me create particles from an image that I would then control using input from the Kinect. To control the Kinect I used output from the object dp.kinect2. This took me a while to set up initially. I wanted to have the system use real-time image input from the Kinect as the image – that did not end up working quite like I wanted so I stuck to using one preset image.

Here is the gist for my code:

<pre><code>
----------begin_max5_patcher----------
3662.3oc6c01bahjD9ydqZ+OLkp7or1Nya71U2cU159Yr6VpvRijIAA5.jiS
159ueyaHAHALHCXLwURrhADSOO8L8zSyS272+5ubyhGhelkt.7O.+A3la9a9
QtQdLwQtI+.2rXm+yqB8SkW3hUw61whxVbq9jYrmyjmH8wfMYfUgAq9JHKFj
5+DC7je3AdCjesQG1EeHKjkIuUv7CGrVdChe3K2YgNdw68yV8XPz1kIrUYJY
zxCdO7V.11Q7AxR8a7eB9q7uUZ12CYxaWwVMHJuQQxC9+90eQ7I+iaMtiGw9
FWBOueGF6udGKMEfpoehtP+j50T+zFp6fXwGNxehwszMUsX122yT2jEKNc48
DDrOgkxxpoaRuT2z0ftIFRj8VnTcRgcselKUfEAQxOJef5PgiBl7pWt1OyOe
lvo9u5a8.Ko3WgevSWs0sptJVzdYwa2xk2ihB51imG4HN7lvX98S++7EWxcv
6cOcUX3kuJNnXA8v1EtRRs2OHB63T3Jst7UhtGRcbJdOonKek1VBMywqplVl
duUgKplFEiKcqbpq6h.+kFr0iPqQmfeWmLZ5DrKwPsB40SqbG5dOrEFYfZAd
uMkZ60tVQbgVDLc5OSQ++uFi6426KZbGeIi6NMYbmpVq1V1IfFsB1l3jc9xu
tc8Kpw66O3GssfY889I96XYrjkrH+GT2TXOuxW2AGqFAGjiXHvOsfCoIvgPI
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jkEG0kdYiNViwdxAIxgJXZ9O6VurxngdRgK1oj+V14ZbVheJa4p3v3DvGPfO
fAef.9.sKXhcSXBRMwwUM8gB6WUO9pAD+rrjCAcoaRadOUhw2JMO5R1GDsWU
.ewq61JqyHP5J+PlvsOrv4StmccZK1jFWjA4IgHBFp16oS+Ndvd3Ai6s5Fbf
aDNTlBUfBB8FAM3qMHfg6DNAi6zhDMtFqixIdndng2TGLR.+nC8cbitsqBsF
0FVXoidqqCGft926RWu44.TWUmF8Vou+bG56NMu3Xg3pN8646AeMHhK72klc
XylNDdYZy6XUNSmHAAGWi.gxczR2bUjPJFgjEaBBYOwRRC395ULdhK72uuvw
qDVkc9eIVdubNEUEdqFWMRKIrmBxuEzSG1Og2Qy38xCIJg+Y6ivf3NEulkDw
8.43R3JkTtnUb9gxfnsbQBa0uQcKFuVtFcaX7puxVWDO3iU1yhBhjQZMJyOS
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JJ87yJMqsnssxmnQabU7x4zB6pAEBqdwGhxJG46ZM8U07GBV51cIWefxI2Th
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.GtsAGVpMTRUAn6sCbHdDsxvYTOlfpASnsgIpvzq1+jMrSHRKgbYLPsxQmTG
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swiKZKCM13B1s5AExRErOMX67VBrax1xOBAoby8rgx1Rc9r5ZY5ZsTOIILb5
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wItuuS4QUiz5.dBz4cMxXpQPFZB58XWLkhcAgZpZ6mjXW7e4CSRh4yQ.O9iw
02UaSenCROWcQC6Scn+8iJO4O5tS8lAL1xGe.97zCrS3RojGaxa6X896UjhA
C9rvATVVbjxTI.c5HC0dBrqKfnFNRVmiizW3CP6KAYK483jfmE1SL+2Zy405
TkEHIh3YyWGU.j8awETiRNM9Pxp79P9Vo3psRBzZVZVPzQxy7GGiuI.dLCfL
XnV2kEhoxhTpGVgwV0BsKKnAWTrlRxh0DRVLUTt.9EmrVmpsSAAD2f.BGPAj
Zp.N7y2DNEBvlHKzQRXLxRDkLNBiQZI5vOmiXprjK0CrrXjRRlmuCqrfMUVx
MlOvxhYypG9YR4PuAJI6wQXLaDyHgLFYvCM7SqQF6hg6vKKFuro2vKKHiG9B
GdgQjP+FoiZdQo7Sbh78KD7sd8REEyWJRbufGNjo1kQo7JnizedaX7C9gZpM
ebKdMyE5STl9nTd0o0QskPnfnOw2RG3Oi1GmFjE7DC7u.AQ+YTDaqu9W4m+3
2qDcnIlmEHDnAIJpUdp.nSygwoHCUKzbX+mVG+snNjqKXZyI7mUgL9S+n3fu
xcRYdK7IQpOzg9Ixt8DajfkwHyxZJTvn9RP18pPO.dhEFCH.YfOIX.EBE+6x
CvwlWBAvMlc3JFNoSQXUsWpDE+MJYupD+jQKmfq.dcntJfarv.Pop7A1wqlP
p9VAUBiW0EPowIOXWocAhqbHiCcZBJctBafar1rfrT47Aj9SZAHA2bhyicKZ
Q8mP3AZv5MT57u9rvE6UrqoDsfnMW7RTbeCWnn.NEpQK0V4Rj3vuuaO3Ccod
LfHlXDhHGN43MUpVIMs.zVVctmRtT+uwUigpD.R8.Noj9XgGyVFBOuygaWcg
9.5pxWME9ZUNGtYq4a9hqOpRu6aK7Cz6Y886Y886Y88P7j7kqqCNtpREd.YF
QIZO+wH15R9ipTggHCG8mgiJQH9z0.WsyLeUpPfbU9iHIv7bfr3e7ZPq1YJl
BlPNj4EZExh1xsCcEPV6zxVgUHBsFWd5MHab4kzGAUp5DFBXXCALOUHJvyG7
h6ek00fXsx0JhJBNHWo6NzYCjIdlA3ECQ4PgnhXLw18JRQnWQD42thwOsVLT
PDcUPAMuLpeMfUqkJEjdO6jYFX8wiNldEnliodYoV9yANWrPc2PPBbMXo4g+
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pJ7bCtD9YgtB+rZc6hn7BMGbnbyZnHpumwj.c34oeW3mE5Uf20tckzViNwqM
mUjSnLcv4UhF8lm9CuV7nuqYhvTf7uiAqRslPrJk1oobngUXLlF8WRrGkIcc
TDQuBy5PlOVmLgXJr6vO7piDnd7Gb0E6kccnUA5MOdulbvM+tTRE6XO3z60j
Si7rH79crzGAYGxffOuNw+aKED..rONHJKE7Y06PGj5OcfXSnFIHIQsIYKUv
iwtjgjLfdCLCIafysFfSMxtVhkJheJpShbfyDRShbL30oilUwu848Vsj8J6w
D9bu3v0cjsWMR4TMcbzu+Mbbday1qKN5ow27JDcktq1m8YeNkYdSvKa0qxE8
y3yUsplE09cBd8NAudmfWSIBdcZkjqhgWsSnDuhOKMDBMWBC8SrUW8CFpcdw
4QUzOWY3b.q.qjQ941dGZXHFmNGgTDVG6MWdjsoeK3GM9Rk45YGmlVbDj87h
pWRH64AgcbtySD6tq6o01N23vZxDplNZMeHGGdPXFGV8ZuxdlAWaqV9gMDuf
sSEL0N707hiNWJc1+6SdkMDjBSwbNcrRlOra5pYEsig.1biSzQwI6FDFgo.J
0KsNh6bwg+Te9tzFjxEpJPkpQYTu4hUrghDXJzRO55cVMY1NIop4jukH0j6D
p5J4Lc3pfcWJKinIMibPScF43LgpsZzIDibP1COMEnSHVv0A9tLBEpPbmLLh
lJ0.O7viLvdg4TvogHRl57uwxzBI3PRihynPA3y9q82mA5DWJPF7bgQZxl.c
d6UUtzuROPfOGuYSJSVL9+xgc6AjtfRvlQI0i7knKk9NuUqcYc.Q7L.PTU1.
KqoIbTKCSB1sONIaW7SAraAEeqka.MSLgYRpW2NH3aiZJT38hWjZm18uAiMZ
tdPpJ4Mt3SPwUfAi6HBA+Jx5vn.KC..UluQdSP0nuEmDtVS2wM6SA1hOS88E
1RkqAw6g0xzwKU6oZrzaoWyQU4svDqqeHx4u0S6qgJkeA5XBQXauGqmLbkzf
szKKmW.E8T2ixwyPiIU8mJGYZIorLI1EWTGXb64ZR640aMmiIMGA2asmsQsW
u0bVlzb18VyQMZzB0s+ZPyzeBwhzOMnkwMHteZPhwMHpeZPjwMX+nCIFMngz
eiRIticCNxy5IFMlA2iMH1nFr+VkfXzfTrU+0fkBCccsWkAVUBzwHHAn5j.X
OHAXyL1h5MPGajwVT+MNFazDGDs2rtiMZhCoG6gFMwA0i5PnwPZ+r9Edbs0h
LZwDjWMyKwiqHPFHSCFJBCn4QjQFmP82JBHiLNgGz9rY1GwC3ZBUdDDF7hR7
E1djQt8LxbBp+1QCB0EcZezfvQdEAjQtR40qsW6ySur295HnTIa0jMU0rTqZ
FpcgrSqgLS6rrRSJC7e7+APqZOfB
-----------end_max5_patcher-----------
</code></pre>
view raw Project 1 hosted with ❤ by GitHub

 

Project 1 – Automated Lighting System

This patch analyzes audio in three ways and represents the information through a LED light pattern.
The 30 LED lights are grouped into three subgroups, where there’s an inner layer consist of two lights, a middle layer consist of a ring of 10 lights, and an outer layer of 18 lights. Changes of colors or brightness happen from the inner ring to the outer ring, so that the light propagates outwards.
The audio amplitude controls the brightness(saturation) of the colors. The ratio of lower frequency to higher frequency controls a color picker, which determines the RGB values. Then the values are being sent to the three layers with different amount of delay.

Code:


----------begin_max5_patcher----------
6718.3oc6csrjiiakccVeEJz3UyjEGbwaLgWXGyV2q7JGU3nBlRLyhcSIpQh
pdXG1e6C.3akjTfRfJUWIqtCUpHHE.N7fKtu.v+7COr7ozuGcX4h+mEeZwCO
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6siKtZ9kx9wtn75Re6KV9T31WVt3uWbKOmteSXloXdwU1Els5Kwae4y6iVkk
+b.kSBjDBQPebAkfB3bk7wERT.5wEXR.p5mKdssYk9zu9Q7xpev8gahxh1+4
nsgOk2vQ0s63skMavbs+0G9f4iGcDX1F8MckUVUYQe21jWdXWTz5j3M5lNxU
TC5E0p5dcgMLFJPQkTI+wE.HDABEhgEOtPIFBd..srKP.OEf.ZxAAIKfV.BR
IwzwGt6yX2tdO9V16ADQSAvBrhcNLfJlZLHIMb8lnCGtAL.fRM8UNBEv3JAB
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L2Yl68JyU+L+qO7+Csz5s3.
-----------end_max5_patcher-----------

Project 1: Enhance It! – Anish Krishnan

As I make a lot of videos and short films in my free time, anything related to processing videos excites me, so I really wanted to learn how to use the computer vision object built into Max. For this project I used the cv.jit.faces object to be able to alter a face in a movie by either blurring it or placing a virtual spotlight on it. First, I downscale the image to 1/5th of its original size, then convert it to greyscale, and run it through the cv.jit.faces object. I use the output matrix to determine the positions of the face and accordingly place a blurred image with an alpha layer that I made on top of the face or add a spotlight. I hope you like my project!

Original Image:

Blurred Face:

Enhanced Face/Spotlight

Google Drive Link to Code AND Necessary Media:

https://drive.google.com/drive/folders/0B_T97VaALHA0U1Z6bVllU0MzWEE?usp=sharing

 

The code:

<pre><code>
----------begin_max5_patcher----------
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4f2jKvhrkI01Mkj+k27a.z6GU0B
-----------end_max5_patcher-----------
</code></pre>
view raw gistfile1.txt hosted with ❤ by GitHub

The helper patch “process”:

<pre><code>
----------begin_max5_patcher----------
947.3oc0X10aZCCEF9Z3WgUDWlFh+Hesqlz1sSZZa8pooJCwhZVvAEaZopp6
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PM3w9FZS7BNLyvDax7EAYb7l42tgb36A4CjAKYY5mDf+IAN5PfOgJl43dDC.
El3g0eHDsAPpNOp7bTaI6PhEcA0sb4x7rG9G.dRqlOnQvEpRen7GsYEvnPyR
9cRIBiayERrnITVLC1WEyRhdIXsWKK1hfwE.7Iw06agMDBKID6u83gnMxtzh
t.zFBMyrgjtQ76pF1jUJUtnefyTpp05zvHORRRRXhKHNzTflXHjreBC9vQHA
h2PX8rWqDRr4VuRlhlkA7q95RrOLAuo0CjtmKXccpnj1xiwPatMDXxkJ4dW3
CR1.ecBvgZ3LxlY.oRUJegTQKTfQPvHjKnJDSjBFgAiHWfrBBJbiwfIaaNEl
z59xX76wYlyUdKumKRyu2FMcbzNuvAXSQ6RfH58iafiX5BgP7B16rtM2atD4
ETUAeMf.ldKs.Dg7Me+4URV07ee0TlV6apztCNUzFmBmr8bDr0pCnvOBoAAA
3sK3gHCbQnlJeIGn5OB2KoAW9o5cdETn98wf0tQPPqyzHK5FY4zzxpj.9hk4
EpE42wYfwWKYExwTAWd6eKzGDTw3ulOckt9nRN9Ke65w+5dtTwR+IelflIG+
8h74ZrfiWvR4zwyJnO7Cp9rLj2xx2K6r2i3tMXT0BUP6kQQP61XL7B.M5s0X
7yH1L.mLt3k+2pL5TF+41fLeUwzlmpp2OzErUlTlTwETEW2h41wf7qFzdc52
hPviHj9U1Ocgh5BQgVPnvNHTfEzInC577ow7hTVgIgr2EVWVauJ6eRJS5hxP
K3s51vNSYKX34RITWVAfsg6g5xRf39H0rSJih6ibyWjwe.oi1uznyfzg8hg2
Iow8hgCeC0gNIkL6+bzMoRrkRGiInMpFzEyqoJ3qZrftb4c5dJqGsQCcmTyy
MypQtlK4hpKwlKKX2waFOwDgVna3Qo61YUQUCUqiCcpt0bc9gXEuN6Tq7SC+
O3jI9.G
-----------end_max5_patcher-----------
</code></pre>
view raw gistfile1.txt hosted with ❤ by GitHub

Project 1 – Sarika Bajaj

This project allows a person via the Kinect to use their hand to move around balls in a virtual ball pit. Much of this patch has been built upon some of the dp.kinect2 reference patches as well as a reference from https://cycling74.com/tutorials/00-physics-patch-a-day, integrating the two by creating a kinect system that uses the closest player’s right hand to move around the main movable physics force. Most of the work in this project involved figuring out what good bounding boxes would be in the physical world and in the virtual world/how the user would actually interact with the Kinect (I wanted the output animation to be very obviously user controlled – almost painfully so). Additionally, I had some fun changing the aesthetics of the actual ball system.

Video of the system working:

Gist of code: https://gist.github.com/anonymous/9ddab8deb04b40090d8efeb8cd0b5f06

Assignment 4 – Matthew Xie

For assignment 4, I decided to utilize the fft object and create an audio effect patch that would mimic the sound of recent favorite music genre ‘Vaporwave’.

I created a noise reduction subpatch. Furthermore, a degrading fft subpatch is also used and linked to the output, playing along with the other signal. After these two subpatches, the audio signal is then run through the original patch where it is stretched out in real time (slowed down). This is done by using the delay effect.

I also added another simple visual presentation, that is very similar to the one we made in class. A japanese city pop song was used in demonstration, to achieve that ‘vaporwave aesthetic’.

Another demo: https://soundcloud.com/thewx/assignment4-demo/s-K8iMc

 

Top level patch:

<pre><code>
----------begin_max5_patcher----------
2272.3oc0aszaiiiD9bxuBAg8zhD2hjh5wdJCvbXuLmVr.KPiFFzVz1raIQM
TzIwyfI+1W9PRVxQVVwRiQ5zwJxTEYw5iUUrphp+y6uycE+UZoqy+x4qN2c2
ed+c2YZR2vcUe+N2LxqqSIkFxby2mshJdy8A6y36koTo7PA0NHtkrs4jT2Gb
b2jxIRWmuUQYAQtdGKe6RAcszRL.iWfevI.4uv6AGbr9JDsvqoOrDCO4q99i
XbMK2vyk4jLCCc+EASyspIJOwzJr56p4h9qdpwspA4gTa+ZOXaHqMMVSkRDY
4Jopr8XoIrj8GFBAnEsn0BAVh0M9W2eu9xCiDPk7saUSpygmr7Kfgg5IiieT
nA87qu1KFF31LPBEBJohkzbxpzNh+6AoN.BndHDzRZtjHY77VyGHvyNEhNy7
oKhAtBDKiVVR11.YR5qRqHVPyOKNNHHF5o0Cww.8rEEMjdHBdY8vKffeHUpq
AfxounlpuCeJ2njXtH4MG3kLeGiUqGTiSfvfAgKzOsvUwlMx2bH4b4NpfmSc
G.RPFMGer4OwVEHX+HB.69wLz5JfdWi.Z7YedSCky5Uj7sCtpisNoQPiWZr2
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prINGHg7GoYf+7YmOC5A..x3uy2GMBEgeJzCH+vQvs6i+5g+PEsj82qamTfm
uYaAL.LFkfauNP+fv2YxEaSWrijmjRcdhrWxWZ.E5.lDZElgCqHvFXqMhB.N
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rhCrgKBGzH.+YxFP4PHaepjUnbITVnDHw9LmmjDwVpIRVm06WQO37TBsTtLg
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ZwBDAMuiU91yENvdnP9fESdtMhoFbN.A+aDXiFCifyg5yIqX8yILdN3DbxJP
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fyvZuoyZvHY8z3zn1JYN75.wickDNUNMJuNygHMFmN5R+pWKmFm.2JW1PuOt
iz4xfazrFL6FbixGcT+Rs+Mh08H0na.qw8K0vow5wrT2uLeaXLb10tGIiQys
tMverdolpuC.ZDaaEOGLBN1slmpiW.Xr6ONYNMJiQ3bfdiQe38LxldLon3Yp
nrhZCObyHemaTTMmuq9Xrse0TTUWA8YVM8lydykHVuiIopz3E1hC8Zjsbklx
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DcOhiwn.T2dnKOpoOKY4Z.k1ptGGuztGc3fGHvKN1PE.DgAl67PHr+oSrMrz
zlt1txc0Eqz07B5qj75xo0kSvXOPbfd7QdwQd916TMA5vopdAZp2zCcubBcv
5gOJ.F5iM3ZnGNJxdWjO5zgmju0V4RXqi7zsPvK3hZkW0LKtg98RdijU6Dso
fOOTYwHTO8zZh5ZdoLq6ioVQ+08+eR.cCaC
-----------end_max5_patcher-----------
</code></pre>
view raw Top level Patch hosted with ❤ by GitHub

Noise Reduction Patch:

<pre><code>
----------begin_max5_patcher----------
713.3ocyW0zaaBCF9L4WAhiSoQ1FLX1gcX6vNse.SUSStDmLWQri.Sa5pZ9s
O6WCsoQsDRgIkbffeiMOOOueRdbVPzM5ch5nvOGdcXPviyBB.SNCAsqCh1v2
UTxqgsEoD2qu41n49exH1Y.yeYeHZAsyrtwTJLlG1J7O5nZ4ZEuLJ7WsaXK2
T7GoZ8uqDEF+dRvwKPyCwXh6qDp6Jwd+ymQtDPxh9U3rNjpMOTBfD0YQ0rQp
rnCzk7hQOm.qXmwmlMycY93zsTERdWU2udIHPnL20XTuxMcfxE++VtqVYrO3
8g3n2WXjberKEhmzjdUFcTARzzors5RitfWs+T4vyGT1LIuMhBYyo8GdSFkS
fLcNgOseLUvwwXnBllApMeAsGMStTpfGmlIrrgqYzkhls44FsMiepR1YPodJ
8z454WJo51NYR0AMxNsGXnE99wX9oXY84KXipqd7A9B3oGUJUGOKGHny9qcP
05lphNg1FVBegiKE0VmC2H0pC1ian6AaRWsTT89MgOGjwmBYhG4QCzIkH5sk
HdTHyF.x4SfBYCvU15tGENGkHzSLCO0YKCCZzaC83hhtWBaX0Hi1+lLDjnSP
FCfDdHHMZMQFhlRlBjPCEoW6878P4a2dmnptc2.H1wI2pgDnr4vRoxuLFVVI
tS1s+DvBuxNTvXmHzT46pui4eA9nMZapnpQ1lMZk2r1t+G02Vw2HNX50WKaD
W0NpxpnU7lRyqcC7hBgxTnK8T6Z6+FKFmkljYk4hTZRNh3tK2YBacxKdV7ya
8tU1ye7fnnMVfjcksGFMNhfe6At5rIHx9OERRczJKKNl.TkQvXb7zSvuWIDe
.F5nDM18wcGNkk5n4TStevWaON+roGKAklBLCkhrjCbko43b5zyweJJK02e9
TjPwPfMigYXfpTaTuifsEoqzVlI+aaYr6cmn4HD6iH.6YdZ1+7LLS6G
-----------end_max5_patcher-----------
</code></pre>
view raw noisereduction patch hosted with ❤ by GitHub

Degrading Patch

<pre><code>
----------begin_max5_patcher----------
705.3oc6X10aZCCEF95vuhHe4DqJ9qDX2seGSUn.XXth3fbbXzUU9sO+QfUl
1RLyVz0QuIQ93C4094bL4EdZTBXd8dVCH8SoeIMI4oQII1Pl.IciS.Uk6Wro
rwlFPv9V87G.icSoX6U1vKYqkkKYGNNQcqZCSodbKy8vAM70hxMfz66RXaoZ
wW4h0yjrEJWN37r6xFmRwDysbj4JRe8zmguzpkV+OBOJzpZgRTVYkA7YIWqQ
2LMpG23BeLhnshKzKK6NA+hGPC+61LgFMOkqaOXSFZB97nQlKiCiTe3PJ7tP
vDASMjgflZtgy6CSnfwD5UBSaq2npWTJGriZ7kzaU.c8VY8AM70EZn3AMMuT
0ZxEWngmNcXnQdyBsUqT5Gr9TIX31GpkDTRejfdcIQVTIAWbHE4e2yk0G43F
onO5kGL8fWB8vwidbQJ4ORtd4SQF08U4Sr258bVw0kOGStobGa4L8BPunmUp
TR97Vky4PxILk.LyLaQcUES3fBvNgEvwCy3+NLm20FhmNLlmbqi4XXnqnynR
1v94vY2tF5fTWeIjNrgN76N5Nq4JOKyCCcu6n6LnglP8.Z+e6nqq8gPG1PG9
MuiNXrcz00GQxF1PG9VzQW267PtFq9sZft1dM9WvKFtqCBQ8.PSe8.jc8.1v
E+5+RlcOYheN0ZpakKNRfNijo+bWsj0nOPVp30hWji93YJL89eacwWcJ7TGT
f5j6gNDWNAqCzCcBkaDOzAEg8Cwy5Sn5f8o.gIwRInOJEZMB6SQBGipD1mxj
42pDtRXeThFKkf9nTv0IjO6IbLTJyWkBlddHDMR5.8PmPIm4ko90gGrRS7Uo
PemjWscQXGA8Tmy6EbVHJ2tcGS1zkrUBsEqGpklgEisC4B2P6+jAPx1wOlOw
FoTpsQozdnZkNuN6m3LWCppWxjhVdm8EsxOO5GPXSdVm
-----------end_max5_patcher-----------
</code></pre>
view raw Degrading Patch hosted with ❤ by GitHub

Visual Patch:

<pre><code>
----------begin_max5_patcher----------
750.3ocyXssbaBCE7Y7WACO153pK.F2ekNcxfcjSkKHwHDoNSl3u8JjvMwsf
rpEjgWhBGKyd1U6Q5H+xhfns7ij5nvuF9svffWVDDnC0FHn64fnx7i6Jxq0S
KhQ9Ee6gnklORRNJ0gqeZ+ovL.37GvajEDo74Jh4kGUSejkWDsz5+E98tudU
tb2OnrGuWP1IMuAX1JvxPDF1Njjpe.sB7muB8AchnRt6fImSiZ4yE5LH5bDV
SIkoRMMavuEzjv5nwsAecwh1+rzOY4.Utph+Sxov5JESDMk2UlKEzigvPzfZ
kUc.uQq.3zj1AnYXPkH1Qk.0qR.+XTB3soDH.Z05DmkB7bQJ97IKL1kJATrl
u3MZifUVmNWH8mN4CkQFOuY.sYUxvLNY1v3PvJ7fjdeAOWZeYFn4YW4tcuMZ
tPZQ3VJq91pm6HbBtkpw.qDF5HgASMg+hW95jMlJY7080PvbYM1OJCcmxalK
Lt9BWceGJi010LcaIwHaV2LGIErWRAtER0TtkHFtlT0+01b1i165vPPSsYh0
Zy0uoSh7RhjHtmvx2Z3JvGxiFuUz86kT1d9vNYJS1JL+6f0ioRiMMo1oRV71
wdYC9fZQEbiajm89NTWCs4VlMcksKWH4U7hSteElqqAvTsUH0ZAieGdO1EEN
zb5+6U2PlMDgFEIy5A6dUVfemVne6QET1ee+VcB1F+RApl2H1clncm9D9VN9
.oVIN4RJm8t4fLyo2k.WwI0AbTM0pJG8CmDGvAewb3hGTmaLnGaLAt8hp8gL
X5Qd.NC8B4V5ftBxYSAkcA30SAiQtn0IiP8BLwwBFuAxEJswTYNtZoSH2dgf
9f1O+S6MqtNziw9d572kMX8ciOniKifQ.mqU5k1eoGdxAF2uYAM4.q2Ye7so
tfLdRpMu3kZoz7R6jocj7ppmHh5tYqwP0Y1AtNuVuT+HkYdT+iSGIHOQOO+X
cjbgp+Jop4pFgoAoiYlekunRthgrFZGIUH+5heyZsAGc
-----------end_max5_patcher-----------
</code></pre>
view raw visual patch hosted with ❤ by GitHub