4. 在眼睛识别实例中会有 OSError: Could not find the file报错如何解决？
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    • 在眼睛识别实例中会有 OSError: Could not find the file报错如何解决？

    • 6

      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

      Face Eye Detection Example

      This script uses the built-in frontalface detector to find a face and then

      the eyes within the face. If you want to determine the eye gaze please see the

      iris_detection script for an example on how to do that.

      import sensor
      import time
      import image

      Reset sensor

      sensor.reset()

      Sensor settings

      sensor.set_contrast(1)
      sensor.set_gainceiling(16)
      sensor.set_framesize(sensor.HQVGA)
      sensor.set_pixformat(sensor.GRAYSCALE)

      Load Haar Cascade

      By default this will use all stages, lower satges is faster but less accurate.

      face_cascade = image.HaarCascade("frontalface", stages=25)
      eyes_cascade = image.HaarCascade("eye", stages=24) #是这一行报错
      print(face_cascade, eyes_cascade)

      FPS clock

      clock = time.clock()

      while True:
      clock.tick()

      # Capture snapshot
img = sensor.snapshot()

# Find a face !
# 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.
objects = img.find_features(face_cascade, threshold=0.5, scale_factor=1.5)

# Draw faces
for face in objects:
    img.draw_rectangle(face)
    # Now find eyes within each face.
    # Note: Use a higher threshold here (more detections) and lower scale (to find small objects)
    eyes = img.find_features(
        eyes_cascade, threshold=0.5, scale_factor=1.2, roi=face
    )
    for e in eyes:
        img.draw_rectangle(e)

# Print FPS.
# Note: Actual FPS is higher, streaming the FB makes it slower.
print(clock.fps())
      0