mirror of
https://github.com/openmv/openmv.git
synced 2025-11-04 14:49:50 +08:00
These two new classes allow you to record image data for later viewing at the same speed the image data was recorded. Unlike GIF/MJPEG the image data is stored on the file system completely uncompressed in native frame buffer format making super fast reading and writing possible. Recording VGA Grayscale at ~13 FPS is possible along with playing it back. (That's about 30 Mb/s folks). ... The motivation for writing these scripts is so that you can record video of something like a line following track, take that video home, and work on computer vision algorithms for that data. These classes should make it a lot easier to use the camera at home now.
26 lines
775 B
Python
26 lines
775 B
Python
# Image Reader Example
|
|
#
|
|
# USE THIS EXAMPLE WITH A USD CARD!
|
|
#
|
|
# This example shows how to use the Image Reader object to replay snapshots of what your
|
|
# OpenMV Cam saw saved by the Image Writer object for testing machine vision algorithms.
|
|
|
|
import sensor, image, time
|
|
|
|
snapshot_source = False # Set to true once finished to pull data from sensor.
|
|
|
|
sensor.reset()
|
|
sensor.set_pixformat(sensor.RGB565)
|
|
sensor.set_framesize(sensor.QQVGA)
|
|
sensor.skip_frames(time = 2000)
|
|
clock = time.clock()
|
|
|
|
img_reader = None if snapshot_source else image.ImageReader("/stream.bin")
|
|
|
|
while(True):
|
|
clock.tick()
|
|
img = sensor.snapshot() if snapshot_source else img_reader.next_frame(copy_to_fb=True, loop=True)
|
|
# Do machine vision algorithms on the image here.
|
|
|
|
print(clock.fps())
|