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Getting Started with OpenCV
OpenCV is an open-source computer vision library that allows you to perform image processing on FLIR machine vision cameras. This application note provides information on how to install and use OpenCV in Visual Studio. OpenCV does not support machine vision standards such as USB3 Vision and GigE Vision, therefore it is not recommended to grab images using OpenCV functions. Instead, we recommend using FlyCapture 2 SDK or Spinnaker SDK to grab images and convert them to OpenCV images.
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Getting Started with Spinnaker SDK on MacOS
This application note describes how to install and use the Spinnaker® SDK in MacOS.
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How to upload a neural network to the Firefly DL
Once a neural network file has been successfully converted into a Firefly DL format, users can upload that neural network file onto the camera using SpinView, or through the Spinnaker SDK.
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Image Tearing Causes and Solutions
This application note explains image tearing, how to detect it, its causes, and recommended solutions.
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Low Noise Imaging in the GS3-U3-15S5 Camera
This application note describes the low noise imaging in the GS3-U3-15S5 camera, including: Description and use of optimized mode. Comparison of imaging metrics, including saturation capacity, temporal dark noise, and temperature, between standard and optimized imaging modes. Comparison of images between standard and optimized modes.
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Optimized Modes for Low Light Imaging in the Grasshopper2 FireWire Camera
This application note describes the optimized modes for low light imaging available in Grasshopper2 FireWire cameras, including: 1. Description and use of optimized modes. 2. Comparison of imaging metrics, including full well depth, read noise, dark noise, dark current and temperature, between standard and optimized imaging modes. 3. Comparison of images between standard and optimized modes.
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Overview of the Ladybug Image Stitching Process
The purpose of this Technical Application Note is to: Explain how the Ladybug API creates a single panoramic image from six separate raw images that are output from a Ladybug camera. Explain why stitching is an imperfect process and how to work with stitching errors.
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Saving Custom Settings on FLIR Machine Vision Cameras
This application note describes how to save custom image settings onto a FLIR machine vision camera. Using FLIR machine vision software (whether through a GUI or through working directly with our API), it’s possible to change a variety of settings, such as frame rate, region of interest, pixel format, or gain. The complete list of settings that are stored are found in your camera's Technical Reference manual, available from the downloads page. By default, once a camera has been power-cycled (disconnected from its power source and reconnected), the camera starts up with its factory default settings. Using the FlyCapture®2 SDK, or the Spinnaker® SDK, it’s possible to save custom settings to the camera so that even after a power-cycle occurs, the camera starts up with the settings that were saved. Each camera is capable of saving up to two custom profiles.
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Saving Images at High Bandwidth
This Technical Application Note provides an analysis of the challenge of saving images at high bandwidth and offers methods to solve the issues. The FlyCapture2 SDK includes a GUI application (FlyCap2) for capturing and saving images as well as an API for writing applications. Using one of FLIR’s fastest Grasshopper3 USB 3.1 cameras, we demonstrate how to stream and save images to disk at a speed of 373 MB/s.
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Teledyne Machine Vision Cameras are Headed to Mars!
For the first-ever filming of a spacecraft landing, the engineers included 6 Teledyne cameras.
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3D Imaging, Lasers, and Fish Lice
Mestec’s software identifies the location of lice on fish exterior, then fires a laser from the unit which removes the lice from the fish.
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Capturing Consistent Color
Whether you're sorting fruits and vegetables or inspecting sneakers, capturing accurate color and rich details at high speed with guaranteed reliability calls for certain characteristics in a camera.