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  • My USB 3.1 camera does not achieve full frame rate

    This article explains some basic factors that may affect the frame rate of your USB 3.1 device.

  • Overview of multithreading optimizations in Ladybug library.

    This article discusses the addition of multithreading to the Ladybug library and its interaction with dual- and quad-core CPUs.

  • Product Change Notifications (PCN)

    Product Change Notifications (PCN) are issued in order to communicate to customers any changes to a product that impact fit, form, function, or availability.

  • Setting up Multiple GigE Cameras with Spinnaker

    This application notes describes how to set up multiple FLIR machine vision GigE cameras using Spinnaker.

  • Storing Data in On-Camera Flash Memory

    The Applicable Product(s) provide the user with flash memory on-board the camera for the purposes of non-volatile data storage. This Technical Application Note explains what flash memory is and provides an example of using flash memory to store image data.

  • Streaming Cameras on Embedded Systems

    This technical application note provides a summary and instructions for streaming FLIR machine vision cameras using FlyCapture2 on ARM-based embedded boards. It includes examples of some of the more commonly used embedded boards: ODROID-XU; Samsung Exynos 5250 Arndale; and NVIDIA Jetson TK1, TX1, TX2 and DRIVE PX. The benchmark results show that embedded boards are able to support high-speed machine vision applications.

  • Streaming USB2 and USB3 Cameras with libdc1394 in OS X

    This application note provides information on how to set up, configure, and stream USB2 and USB3 cameras in Apple’s OS X operating system, using open source libdc1394 and libusb libraries. Please note that FLIR does not support libdc1394 and libusb.

  • Synchronizing a Blackfly or Grasshopper3 GigE Camera’s Time to PC Time

    This application note describes how to synchronize a Point Grey BFLY-PGE or GS3-PGE camera’s internal time to system (PC) time. This is useful for users that need to find out when images are being captured relative to real world time.

  • Synchronizing Ladybug Cameras

    This application note describes how to synchronize Ladybug cameras over USB3 by determining the relationship between the image timing and the camera’s current time. This is useful for Ladybug users who need to correlate their images with external information such as LIDAR or GPS.

  • Training a classification model for Firefly-DL using TensorFlow framework

    This application note describes how to setup your computer and train a custom classification model that is compatible with Firefly-DL cameras. We use TensorFlow (TF) framework to train a custom model.

  • Understanding Color Interpolation

    The two critical items to consider when choosing interpolation methods are false color artifacts and image sharpness. These two parameters are important because they are used in edge detection algorithms and to ensure accurate color reproduction.

  • Updating Ladybug Calibration Files

    Ladybug cameras have calibration files that provide settings used for stitching and rectifiying images. If an update to the calibration file is necessary, use the UpdatorGUI utility provided in the Ladybug SDK to upload the file.