Example: 01-Camera/02-Optical-Flow/differential-translation.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
#
# 差分光流平移
#
# 此示例展示了如何使用您的OpenMV摄像头测量 translation
# 通过比较当前与前一帧在X和Y方向上的
# image against each other. Note that only X and Y translation is
# 已处理 - 此模式下不支持旋转/缩放。
#
# To run this demo effectively please mount your OpenMV Cam on a steady
# 基准点，并快速向左、右、上、下移动，
# 观察数值变化。注意，你可以看到位移数值
# 在水平和垂直分辨率的一半范围内波动。
#
# NOTE You have to use a small power of 2 resolution when using
# find_displacement(). This is because the algorithm is powered by
# something called phase correlation which does the image comparison
# using FFTs. A non-power of 2 resolution requires padding to a power
# of 2 which reduces the usefulness of the algorithm results. Please
# use a resolution like B64X64 or B64X32 (2x faster).
#
# Your OpenMV Cam supports power of 2 resolutions of 64x32, 64x64,
# 128x64, and 128x128. If you want a resolution of 32x32 you can create
# it by doing "img.scale(x_scale=0.5, y_scale=0.5, hint=image.AREA)" on a 64x64 image.

import sensor
import time

sensor.reset()  # 重置并初始化传感器。
sensor.set_pixformat(sensor.RGB565)  # 将像素格式设置为RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.B64X64)  # Set frame size to 64x64... (or 64x32)...
sensor.skip_frames(time=2000)  # 等待设置生效。
clock = time.clock()  # 创建一个时钟对象来跟踪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.
extra_fb = sensor.alloc_extra_fb(sensor.width(), sensor.height(), sensor.RGB565)
extra_fb.replace(sensor.snapshot())

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

    displacement = extra_fb.find_displacement(img)
    extra_fb.replace(img)

    # Offset results are noisy without filtering so we drop some accuracy.
    sub_pixel_x = int(displacement.x_translation() * 5) / 5.0
    sub_pixel_y = int(displacement.y_translation() * 5) / 5.0

    if (
        displacement.response() > 0.1
    ):  # Below 0.1 or so (YMMV) and the results are just noise.
        print(
            "{0:+f}x {1:+f}y {2} {3} FPS".format(
                sub_pixel_x, sub_pixel_y, displacement.response(), clock.fps()
            )
        )
    else:
        print(clock.fps())