• Hardware
  • Low cost camera with PC interface

Hi @SwapnilBhole
Same thing but instead of IP, you use MXID for identification. No extra steps are needed for usb (like making sure devices are not on the same IP), just plug and play.

Thanks,
Jaka

    jakaskerl I have to keep this camera on for 22 hours per day. This will be in industrial environment 0 degree to max 55 degree. will this camera sustain for this?

      22 days later

      Where I can find getting started for OAK-1 Lite camera.
      I found this. but, this is for PoE

      11 days later

      I have purchase OAK-1 Lite.
      I have to capture only image. Its working, but I have to do it very fast.
      What are different optimization for capturing image only?

      import depthai as dai
      import cv2

      pipeline = dai.Pipeline()

      cam_rgb = pipeline.createColorCamera()
      cam_rgb.setBoardSocket(dai.CameraBoardSocket.RGB)
      cam_rgb.setResolution(dai.ColorCameraProperties.SensorResolution.THE_1080_P)
      #cam_rgb.setAutoExposureEnable(True)

      xout = pipeline.createXLinkOut()
      xout.setStreamName("video")
      cam_rgb.video.link(xout.input)

      with dai.Device(pipeline) as device:
      while True:
      frame = device.getOutputQueue(name="video", maxSize=4, blocking=False).get()
      img = frame.getCvFrame()
      cv2.imshow("OAK Image", img)


          cv2.imwrite("C:\depthai\demo_code\save_image\captured_image.jpg", img)
          
          break
      
          if cv2.waitKey(1) == ord('q'):
              break
      
      cv2.destroyAllWindows()

      Hi @SwapnilBhole
      What do you mean by "very fast".
      If you want to do it any faster than you have it currently, you would need to put the saving part in a separate process/(maybe thread would work as well).

      Thanks,
      Jaka

        jakaskerl
        "very fast" meaning is I have to capture image in minimum possible time.
        Can I reduce any line of above code?
        or is there any another method to capture image as fast as I can?
        Threading I will use. But, need some direction or sample code.

          SwapnilBhole
          It's pretty much as minimal as you can make it without reducing frame size.
          perhaps setting pipeline.setXLinkChunkSize(0) could help with latency.

          cv2.imshow("OAK Image", img) also takes additional time to display, so removing it would speed up the host loop.

          Thanks,
          Jaka

          We are using this OAK-1-Lite inside industrial machine (machine vision system). since, CPU is kept below machine & camera is at top, distance from camera to CPU is 3 meter approx. Can you suggest any good USB cable which can send data upto 3 meter?
          I am using camera only for capturing image & later on for OCR.

          Hi @SwapnilBhole
          We've seen some problems with longer standard USB cables. I'd suggest you get one that says "active" USB cable. Those ones can carry data up to 10m or more.

          Thanks,
          Jaka

          14 days later

          Hi @jakaskerl ,
          We have OAK-1-Lite. our task is to capture image from this.
          task-1: keep camera on in streaming mode & capture image.
          in this, we are getting clear image. distance between object & camera is 10cm & we changed to 12 cm.

          task-2: we have capture image directly. no streaming mode.
          in this case, image is blur. how can we resolve this.

          task-3: This is autofocus, we have to change it to fixed focus. any reference?

          @SwapnilBhole ,
          it's not in focus because camera isn't producing frames to run 3A (auto focus, exposure, whitebalance). You can create Script node and just discard preview frames so 3A is run and frames are in focus.

          script_discard.setProcessor(dai.ProcessorType.LEON_MSS)
          script_discard.setScript("""
          while True:
              node.io['preview'].get()
          """)
          cam.preview.link(script_discard.inputs['preview'])
          1. See here: https://docs.luxonis.com/hardware/platform/sensors/focus-type/#Manual%20Focus