Rendering of an iPhone-based view camera, lasercut from cardboard.
You And I Are The Same
Recognizing The iPhone
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<?xml version="1.0"?> <opencv_storage> <cascade> <stageType>BOOST</stageType> <featureType>HAAR</featureType> <height>32</height> <width>32</width> <stageParams> <boostType>GAB</boostType> <minHitRate>9.9500000476837158e-01</minHitRate> <maxFalseAlarm>5.0000000000000000e-01</maxFalseAlarm> <weightTrimRate>9.4999999999999996e-01</weightTrimRate> <maxDepth>1</maxDepth> <maxWeakCount>100</maxWeakCount></stageParams> <featureParams> <maxCatCount>0</maxCatCount> <featSize>1</featSize> <mode>BASIC</mode></featureParams> <stageNum>3</stageNum> <stages> <!-- stage 0 --> <_> <maxWeakCount>1</maxWeakCount> <stageThreshold>1.</stageThreshold> <weakClassifiers> <_> <internalNodes> 0 -1 0 6.3478387892246246e-03</internalNodes> <leafValues> -1. 1.</leafValues></_></weakClassifiers></_> <!-- stage 1 --> <_> <maxWeakCount>1</maxWeakCount> <stageThreshold>1.</stageThreshold> <weakClassifiers> <_> <internalNodes> 0 -1 2 -6.0746502876281738e-01</internalNodes> <leafValues> 1. -1.</leafValues></_></weakClassifiers></_> <!-- stage 2 --> <_> <maxWeakCount>1</maxWeakCount> <stageThreshold>1.</stageThreshold> <weakClassifiers> <_> <internalNodes> 0 -1 1 -2.4005537852644920e-02</internalNodes> <leafValues> 1. -1.</leafValues></_></weakClassifiers></_></stages> <features> <_> <rects> <_> 0 0 12 3 -1.</_> <_> 4 0 4 3 3.</_></rects> <tilted>0</tilted></_> <_> <rects> <_> 0 0 16 4 -1.</_> <_> 0 0 8 2 2.</_> <_> 8 2 8 2 2.</_></rects> <tilted>0</tilted></_> <_> <rects> <_> 0 0 30 19 -1.</_> <_> 10 0 10 19 3.</_></rects> <tilted>0</tilted></_></features></cascade> </opencv_storage> |
I’m spending the month of July in Utrecht, Netherlands as artist-in-residence at Impakt, working on a project to let computers recognize other computers. For early testing, I’ve trained a computer vision “cascade file” (above) for recognizing front-facing iPhones.
The resulting cascade files, like above, will be released as a printed book, as well as on GitHub.
iPhone Camera Field Of View
The field of view of an iPhone’s camera: 1/4″ opening, expanded to 7.5 x 9″ at 8.5″ from the lens.
iPhone Stethoscope Attachment Finished
UPDATE: after quite a few tests, I’ve released a new version of the stethoscope attachment – download it here, have it printed here. Watch for a write-up and audio samples soon.
It’s done! After some more wrangling with shrinkage, my stethoscope attachment for the iPhone is complete. The MakerBot-printed piece slides onto the bottom of the phone and the stethoscope tube runs inside, allowing you to record sounds directly into the iPhone’s mics.
The part was printed in two pieces and welded together with plastic cement (which worked great on the MakerBot ABS). The fit is tight but doesn’t feel like it would damage the phone’s surfaces.
The sound is piped into the two mics by an internal chamber. Note the stop at the bottom hole – this prevents the stethoscope tube from being inserted too far and blocking the sound! Total build time was around 40-minutes per half, or about 90 minutes total counting GCode generation.
Files to be uploaded to Thingiverse later today
Now available for download on Thingiverse!
3d-Printed iPhone Stethoscope Attachment – Version 2
v2 of my 3d-printed iPhone stethoscope attachment – now with taller sides but shorter front/back… and it fits properly!
3d-Printed iPhone Stethoscope Attachment
Working on a related mic-building project (stethoscopes and the iPhone), I had a brainwave that it might be easier to essentially pipe the audio from the stethoscope head directly into the iPhone mics. About 90 minutes of MakerBot printing later, the first test was done. Though there were a few problems with the printing (tape is covering holes that ended up occurring), overall it works really well.
The next version will include an inner chamber to direct the sound to the mics better. Shrinkage was also less of an issue than with previous projects – a little tight on the sides but not the front/back. As a nice treat, the MakerBot ABS doesn’t seem to do any damage to the iPhone surface (knock on wood).
This sample is the stethoscope on my chest and clothes, then up against my neck, gulping, quiet talking, whispering, and ending with the stethoscope rubbed against my beard.
Thumb over the lens of my iPhone
