# This work is licensed under the MIT license. # Copyright (c) 2013-2023 OpenMV LLC. All rights reserved. # https://github.com/openmv/openmv/blob/master/LICENSE # # Iris Detection 2 Example # # This example shows how to find the eye gaze (pupil detection) after finding # the eyes in an image. This script uses the find_eyes function which determines # the center point of roi that should contain a pupil. It does this by basically # finding the center of the darkest area in the eye roi which is the pupil center. # # Note: This script does not detect a face first, use it with the telephoto lens. import sensor import time import image # Reset sensor sensor.reset() # Sensor settings sensor.set_contrast(3) sensor.set_gainceiling(16) # Set resolution to VGA. sensor.set_framesize(sensor.VGA) # Bin/Crop image to 200x100, which gives more details with less data to process sensor.set_windowing((220, 190, 200, 100)) sensor.set_pixformat(sensor.GRAYSCALE) # Load Haar Cascade # By default this will use all stages, lower stages is faster but less accurate. eyes_cascade = image.HaarCascade("/rom/haarcascade_eye.cascade", stages=24) print(eyes_cascade) # FPS clock clock = time.clock() while True: clock.tick() # Capture snapshot img = sensor.snapshot() # Find eyes ! # Note: Lower scale factor scales-down the image more and detects smaller objects. # Higher threshold results in a higher detection rate, with more false positives. eyes = img.find_features(eyes_cascade, threshold=0.5, scale_factor=1.5) # Find iris for e in eyes: iris = img.find_eye(e) img.draw_rectangle(e) img.draw_cross(iris[0], iris[1]) # Print FPS. # Note: Actual FPS is higher, streaming the FB makes it slower. print(clock.fps())