import sensor, time, image # Reset sensor sensor.reset() # Sensor settings sensor.set_contrast(1) sensor.set_gainceiling(16) sensor.set_framesize(sensor.QCIF) 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=16) print(face_cascade) # FPS clock clock = time.clock() while (True): clock.tick() # Capture snapshot img = sensor.snapshot() # Find objects. # 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=0.65, scale=1.65) # Draw objects for r in objects: img.draw_rectangle(r) if (len(objects)): # Add a small delay to see the drawing on the FB time.sleep(100) # Print FPS. # Note: Actual FPS is higher, streaming the FB makes it slower. print(clock.fps())