我也是,怎么解决啊
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人眼识别示例代码报错 OSError: Could not find the file 如何解决?
回复: 人眼识别示例代码报错 OSError: Could not find the file 如何解决?
# 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) 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())