例程讲解04-Image-Filters->advanced_frame_differencing高级帧间差分
# 高级帧间差分例子
#
# 注意: 为了运行这个程序，你需要插入SD卡。
#
# 这个例子示范了OpenMV的帧间差分算法。
# 之所以叫做高级的帧间查分，是因为背景图片会实时更新
import sensor, image, pyb, os, time
BG_UPDATE_FRAMES = 50 # How many frames before blending.
BG_UPDATE_BLEND = 128 # How much to blend by... ([0-256]==[0.0-1.0]).
sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.GRAYSCALE) # or sensor.RGB565
sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
sensor.skip_frames(time = 2000) # Let new settings take affect.
sensor.set_auto_whitebal(False) # Turn off white balance.
clock = time.clock() # Tracks FPS.
if not "temp" in os.listdir(): os.mkdir("temp") # Make a temp directory
print("About to save background image...")
sensor.skip_frames(time = 2000) # Give the user time to get ready.
sensor.snapshot().save("temp/bg.bmp")
print("Saved background image - Now frame differencing!")
frame_count = 0
while(True):
clock.tick() # Track elapsed milliseconds between snapshots().
img = sensor.snapshot() # Take a picture and return the image.
frame_count += 1
if frame_count > BG_UPDATE_FRAMES:
frame_count = 0
# Blend in new frame. We're doing 256-alpha here because we want to
# blend the new frame into the backgound. Not the background into the
# new frame which would be just alpha. Blend replaces each pixel by
# ((NEW*(alpha))+(OLD*(256-alpha)))/256. So, a low alpha results in
# low blending of the new image while a high alpha results in high
# blending of the new image. We need to reverse that for this update.
img.blend("temp/bg.bmp", alpha=(256-BG_UPDATE_BLEND))
img.save("temp/bg.bmp")
# Replace the image with the "abs(NEW-OLD)" frame difference.
img.difference("temp/bg.bmp")
print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while
# connected to your computer. The FPS should increase once disconnected.
