9/26/2023 0 Comments Goodsync raspberry pi![]() ![]() When you click through from our site to a retailer and buy a product or service, we may earn affiliate commissions. And we pore over customer reviews to find out what matters to real people who already own and use the products and services we’re assessing. We gather data from the best available sources, including vendor and retailer listings as well as other relevant and independent reviews sites. Right_img_msg.ZDNET's recommendations are based on many hours of testing, research, and comparison shopping. Signal.signal(signal.SIGINT, signal_handler)įor frame in camera.capture_continuous(stream, format="rgb", use_video_port=True): # this is supposed to shut down gracefully on CTRL-C but doesn't quite work: Left_img_id = 'stereo_camera' # TF frame Right_img_pub = rospy.Publisher('right_camera/image_color', Image, queue_size=1) Left_img_pub = rospy.Publisher('left_camera/image_color', Image, queue_size=1) #_stabilization = True # fussy about res? # using several camera options can cause instability, hangs after a while This works quite well, though it doesn't have the camera_info incorporated yet: #!/usr/bin/env pythonĬamera = PiCamera(stereo_mode = 'top-bottom',stereo_decimate=False)Ĭamera.resolution = (res_x, res_y*2) # top-bottom stereo As for the speed issues, it's reading the stream into a 3d array then laboriously flattening it again, which is pointless unless I need to do OpenCV stuff with the image in this node. (more)ĭoing antishake, video stabilisation and AWB all at once makes it unstable for some reason. # picamera stereo ROS node using dual CSI. Revised code after advice in this thread: #!/usr/bin/env python Right_img_msg.data = right_image.flatten().tolist() Left_img_msg.data = left_image.flatten().tolist() Left_img_msg.step = res_x*3 # bytes per row: pixels * channels * bytes per channel (1 normally) # clear the stream in preparation for the next frame # grab the raw NumPy array representing the image and split it ![]() Right_img_pub = rospy.Publisher('right_camera/image_color', Image, queue_size=10)įor frame in camera.capture_continuous(rawCapture, format="rgb", use_video_port=True): Left_img_pub = rospy.Publisher('left_camera/image_color', Image, queue_size=10) # queue_size should be roughly equal to FPS? RawCapture = PiRGBArray(camera, size=(res_x*2, res_y)) # picamera struct, a numpy array? # x must be multiple of 128: 640, 512, 384Ĭamera = PiCamera(stereo_mode = 'side-by-side',stereo_decimate=False) # modified from code by Adrian Rosebrock, įrom sensor_msgs.msg import CameraInfo, Image # picamera stereo ROS node using dual CSI Pi CS3 board I suspect I'm going to have to redo it in C++ but I'd rather avoid that because python is quick to use.Ĭan someone tell me what I'm doing wrong, or a better way? #!/usr/bin/env python I think sensor_msgs is the only way to do it as I need to set identical timestamps, but I'm a novice.Īlso the publish rate is pretty slow. This brings in both cameras as one image with good sync (better than 1/60 sec anyway) which i then split up and publish using sensor_msgs. I'm using the picamera library so I can access the cameras as if I was using raspivid. I have cameras plugged into the 2 CSI ports on the standard Raspberry Pi Compute Module breakout board. My Python script to publish the images consistently stops after ~500 images, with no errors. I'm trying to make a stereo camera for visual odometry. ![]()
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