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Tried to emulate Arduino's 11 folders... I'd perfer to have all the shield scripts in one folder... but, that might not make sense. I don't really want one script per folder however. So, I might merge some more stuff in the future. I have a grand idea here that will become evident as I work though the examples. Anyway, the current structure is not final. It will be in flux for a little while. As for Git History, folder history is the best we're going to get. Git and GitHub don't seem to deal with moves too well.
45 lines
1.3 KiB
Python
45 lines
1.3 KiB
Python
import sensor, time, image
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# Reset sensor
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sensor.reset()
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# Sensor settings
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sensor.set_contrast(1)
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sensor.set_gainceiling(16)
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sensor.set_framesize(sensor.QVGA)
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sensor.set_pixformat(sensor.GRAYSCALE)
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# Load Haar Cascade
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# By default this will use all stages, lower satges is faster but less accurate.
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face_cascade = image.HaarCascade("frontalface", stages=25)
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eyes_cascade = image.HaarCascade("eye", stages=24)
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print(face_cascade, eyes_cascade)
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# FPS clock
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clock = time.clock()
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while (True):
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clock.tick()
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# Capture snapshot
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img = sensor.snapshot()
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# Find a face !
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# Note: Lower scale factor scales-down the image more and detects smaller objects.
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# Higher threshold results in a higher detection rate, with more false positives.
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objects = img.find_features(face_cascade, threshold=0.5, scale=1.5)
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# Draw faces
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for face in objects:
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img.draw_rectangle(face)
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# Now find eyes within each face.
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# Note: Use a higher threshold here (more detections) and lower scale (to find small objects)
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eyes = img.find_features(eyes_cascade, threshold=0.5, scale=1.2, roi=face)
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for e in eyes:
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iris = img.find_eyes(e)
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img.draw_rectangle(e)
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img.draw_cross(iris[0], iris[1])
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# Print FPS.
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# Note: Actual FPS is higher, streaming the FB makes it slower.
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print(clock.fps())
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