差帧

basic frame difference

# Basic Frame Differencing Example
#
# Note: You will need an SD card to run this example.
#
# This example demonstrates using frame differencing with your OpenMV Cam. It's
# called basic frame differencing because there's no background image update.
# So, as time passes the background image may change resulting in issues.

import sensor, image, pyb, os, time

sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE
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!")

while(True):
    clock.tick() # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot() # Take a picture and return the image.

    # 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.

Advanced Frame Differencing

# Advanced Frame Differencing Example
#
# Note: You will need an SD card to run this example.
#
# This example demonstrates using frame differencing with your OpenMV Cam. This
# example is advanced because it preforms a background update to deal with the
# backgound image changing overtime.

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.
Copyright 杭州云江科技有限公司 2017 all right reserved,powered by Gitbook该文件修订时间: 2018-04-02 09:53:12

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