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45 lines
1.1 KiB
Python
45 lines
1.1 KiB
Python
import sensor, time, image
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sensor.reset()
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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.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=25)
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print(face_cascade)
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# Skip a few frames to allow the sensor settle down
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# Note: This takes more time when exec from the IDE.
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for i in range(0, 30):
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img = sensor.snapshot()
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img.draw_string(0, 0, "Please wait...")
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d0 = None
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#d0 = image.load_descriptor(image.LBP, "/desc.lbp")
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clock = time.clock()
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while (True):
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clock.tick()
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img = sensor.snapshot()
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objects = img.find_features(face_cascade, threshold=0.5, scale=1.25)
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if objects:
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face = objects[0]
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d1 = img.find_lbp(face)
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if (d0 == None):
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d0 = d1
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else:
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dist = image.match_descriptor(image.LBP, d0, d1)
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img.draw_string(0, 10, "Match %d%%"%(dist))
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img.draw_rectangle(face)
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# Draw FPS
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img.draw_string(0, 0, "FPS:%.2f"%(clock.fps()))
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