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59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
# This work is licensed under the MIT license.
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# Copyright (c) 2013-2023 OpenMV LLC. All rights reserved.
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# https://github.com/openmv/openmv/blob/master/LICENSE
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#
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# Iris Detection 2 Example
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#
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# This example shows how to find the eye gaze (pupil detection) after finding
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# the eyes in an image. This script uses the find_eyes function which determines
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# the center point of roi that should contain a pupil. It does this by basically
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# finding the center of the darkest area in the eye roi which is the pupil center.
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#
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# Note: This script does not detect a face first, use it with the telephoto lens.
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import sensor
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import time
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import 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(3)
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sensor.set_gainceiling(16)
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# Set resolution to VGA.
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sensor.set_framesize(sensor.VGA)
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# Bin/Crop image to 200x100, which gives more details with less data to process
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sensor.set_windowing((220, 190, 200, 100))
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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 stages is faster but less accurate.
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eyes_cascade = image.HaarCascade("/rom/haarcascade_eye.cascade", stages=24)
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print(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 eyes !
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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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eyes = img.find_features(eyes_cascade, threshold=0.5, scale_factor=1.5)
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# Find iris
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for e in eyes:
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iris = img.find_eye(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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