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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.