bias 位置 0-1
组中值是上下限之间的中点数值，以代表各组标志值的一般水平。 0.0 : 最小值滤波 0.25 : 0.5 : 中值滤波 0.75 : 1.0 : 最大值滤波
# Midpoint Filter Example # # This example shows off midpoint filtering. Midpoint filtering replaces each # pixel by the average of the min and max pixel values for a NxN neighborhood. import sensor, image, time sensor.reset() # Initialize the camera sensor. sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE sensor.set_framesize(sensor.QQVGA) # or sensor.QVGA (or others) sensor.skip_frames(time = 2000) # Let new settings take affect. clock = time.clock() # Tracks FPS. while(True): clock.tick() # Track elapsed milliseconds between snapshots(). img = sensor.snapshot() # Take a picture and return the image. # The first argument is the kernel size. N coresponds to a ((N*2)+1)^2 # kernel size. E.g. 1 == 3x3 kernel, 2 == 5x5 kernel, etc. Note: You # shouldn't ever need to use a value bigger than 2. The "bias" argument # lets you select between min and max blending. 0.5 == midpoint filter, # 0.0 == min filter, and 1.0 == max filter. Note that the min filter # makes images darker while the max filter makes images lighter. img.midpoint(1, bias=0.5) print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while # connected to your computer. The FPS should increase once disconnected.