Example: 02-Image-Processing/03-Frame-Differencing/in_memory_basic_frame_differencing.py

# 本作品采用MIT许可证授权。
# 版权所有 (c) 2013-2023 OpenMV LLC。保留所有权利。
# https://github.com/openmv/openmv/blob/master/LICENSE
#
# In Memory Basic Frame Differencing 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
import time

TRIGGER_THRESHOLD = 5

sensor.reset()  # 初始化相机传感器。
sensor.set_pixformat(sensor.RGB565)  # 或 sensor.GRAYSCALE
sensor.set_framesize(sensor.QVGA)  # 或传感器.QQVGA（或其他规格）
sensor.skip_frames(time=2000)  # 让新设置生效。
sensor.set_auto_whitebal(False)  # 关闭白平衡。
clock = time.clock()  # 跟踪FPS。

# Take from the main frame buffer's RAM to allocate a second frame buffer.
# There's a lot more RAM in the frame buffer than in the MicroPython heap.
# However, after doing this you have a lot less RAM for some algorithms...
# So, be aware that it's a lot easier to get out of RAM issues now. However,
# frame differencing doesn't use a lot of the extra space in the frame buffer.
# But, things like AprilTags do and won't work if you do this...
extra_fb = sensor.alloc_extra_fb(sensor.width(), sensor.height(), sensor.RGB565)

print("About to save background image...")
sensor.skip_frames(time=2000)  # 给用户时间准备。
extra_fb.replace(sensor.snapshot())
print("Saved background image - Now frame differencing!")

while True:
    clock.tick()  # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot()  # 拍照并返回图像。

    # Replace the image with the "abs(NEW-OLD)" frame difference.
    img.difference(extra_fb)

    hist = img.get_histogram()
    # This code below works by comparing the 99th percentile value (e.g. the
    # non-outlier max value against the 90th percentile value (e.g. a non-max
    # value. The difference between the two values will grow as the difference
    # image seems more pixels change.
    diff = hist.get_percentile(0.99).l_value() - hist.get_percentile(0.90).l_value()
    triggered = diff > TRIGGER_THRESHOLD

    print(clock.fps(), triggered)  # 注意：您的 OpenMV Cam 在连接到
    # 计算机时运行速度会减半。断开连接后，FPS 应该会增加。