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Update face detection example
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@ -6,12 +6,12 @@ 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.QCIF)
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sensor.set_framesize(sensor.HQVGA)
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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=16)
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face_cascade = image.HaarCascade("frontalface", stages=25)
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print(face_cascade)
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# FPS clock
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@ -26,16 +26,12 @@ while (True):
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# Find objects.
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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=0.65, scale=1.65)
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objects = img.find_features(face_cascade, threshold=0.5, scale=1.5)
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# Draw objects
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for r in objects:
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img.draw_rectangle(r)
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if (len(objects)):
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# Add a small delay to see the drawing on the FB
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time.sleep(100)
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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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