def play_depth(bag_file: Bag, camera: str, depth: str) -> None:
"""
Play the ZED data in a bag file.
Args:
bag_file: the bag file to play
camera: the topic to use to read compressed or raw camera data
depth: the topic to use to read 32-bit floating point depth measures
Returns:
None
"""
# open windows to stream the camera and depth image data to
camera_window = None
depth_window = None
# iterate over the messages
for topic, msg, _ in bag.read_messages(topics=[camera, depth]):
# if topic is depth, unwrap and send to the depth window
if topic == depth:
# if the depth window is not setup yet, open it
if depth_window is None:
# create a title for the window
title = '{} ({})'.format(bag_file.filename, depth)
# initialize the window
depth_window = Window(title, msg.height, msg.width)
# get a depth image from the data and dimensions
img = get_depth_image(msg.data, depth_window.shape)
# show the image on the depth window
depth_window.show(img)
# if topic is camera, unwrap and send to the camera window
elif topic == camera:
# if the camera window is not setup yet, open it
if camera_window is None:
# create a title for the window
title = '{} ({})'.format(bag_file.filename, camera)
# initialize the window
camera_window = Window(title, msg.height, msg.width)
# get an image from the data and dimensions
img = get_camera_image(msg.data, camera_window.shape)
# show the image on the camera window
camera_window.show(img)
# shut down the viewer windows
camera_window.close()
depth_window.close()
def play_superpixel(bag_file: Bag, camera_info: str, camera: str, depth: str,
segmentation: str, downscale: int) -> None:
"""
Play the camera data in a bag file through a super pixel algorithm.
Args:
bag_file: the bag file to play
camera_info: the topic to use to read metadata about the camera
camera: the topic to use to read compressed or raw camera data
depth: the topic to use to read 32-bit floating point depth measures
segmentation: the algorithm to use for segmentation
downscale: the factor to downscale the image by before segmentation
Returns:
None
"""
# extract the camera dimensions from the bag
dims = get_camera_dimensions(bag, camera_info)
# open a window to stream the data to
window = Window('{} ({})'.format(bag_file.filename, camera), *dims)
# iterate over the messages
for topic, msg, _ in bag.read_messages(topics=[camera, depth]):
# if topic is camera, unwrap the camera data
if topic == camera:
camera_img = get_camera_image(msg.data, dims)
# if topic is depth, unwrap and calculate the segmentation
elif topic == depth:
depth_img = get_depth_image(msg.data, dims)
# combine the image with the depth channel (Red only)
img = np.concatenate([camera_img, depth_img[..., 0:1]], axis=-1)
# segment the image and get a copy of the segmented pixels
img = segment(img, method=segmentation, downscale=downscale)
# send the segmented image to the window
window.show(img)
# shut down the viewer windows
window.close()