Example Programs in CVB Installation

The CVB installation includes several standalone example programs that can be executed directly. These programs are installed under %CVB%Tutorial (Windows) or $CVB/tutorial (Linux). Select your preferred programming language from the links below to access a list of available examples along with the corresponding code:

C++

.NET

Python

Example Code in C++, .NET and Python

Below, you will find a collection of both larger code examples and smaller code snippets in C++, .NET and Python, each accompanied by explanations.

Device Discovery
Discovery in CVB
Access Discovery Information
Select Gig-E Vision Driver
Example - Discovering GIG-E Vision Devices
Example - Discovering USB3 Vision Devices
Example - Discovering USB3 Vision Devices
Example - Discovering USB3 Vision Devices

Configuration
Configuration in CVB
Quick Configuration
Example - Software Trigger
VinDevice Node Map and VinBuffer Node Map

Acquisition and Streaming
Starting Acquisition
Accessing an Image Stream
Accessing a Point Cloud Stream
Accessing a Composite Stream
Example - Cancellation
Example - Event Callbacks
Example - User Managed Memory
Example - Multiple Components
Example - Multiple Streams
Example - Resize Flow Set Pool
Example - Single Stream

GenApi
Direct Register Access
File Download

GigE Vision
Setting/Modifying the Packet Size for GEV Cameras
Setting/Modifying the Inter Packet Delay for GEV Cameras
Enabling the Packet Resend for GEV Cameras
GEV MultiStream
Interface Discover
Device Discover
Temporary IP Setting
Persistent IP Setting

Image Data Handling
Example - Reinterpreting Images as PFNC Buffer
Pixel Access (C++): Fast Contiguous Access
Pixel Access (C++): Fast Linear Access
Pixel Access (C++): VPAT Access
Pixel Access (C++): Access Using Iterators
Pixel Access (C++): Flexible Pixel Access Using Cvb::Visit
Pixel Access (.NET): Fast Linear Access
Pixel Access (.NET): VPAT Access
Pixel Access (Python): Mapping Image to NumPy Array Without Copying
Pixel Access (Python): Copying Image to NumPy Array and Mapping it to a Wrapped Image
Example - Image Loading / Saving
Example - Image Creation
Efficiently Writing Image and Point Cloud Algorithms Using Visit (C++)

Search and Classification
Search and Classify

Shape Recognition
Shapefinder-Chippins-Train
Shapefinder-Chippins-Search

3D Camera Calibration
Applying Intrinsic Calibration - Static Factors for ZMaps
Applying Intrinsic Calibration - Using a Calibration File
Applying Intrinsic and Extrinsic Calibration to Range Maps
Applying Extrinsic Calibration to Point Clouds
AQS12 - Defining and Fixing AQS12 Reference Points
Extrinsic Calibration
Extrinsic Calibration - Rigid-Body Transformation
Intrinsic and Extrinsic Calibration
AQS12 - Segmentation and Point Extraction

Linescan Camera Calibration
Preprocessing Step 1 - Detecting the Stripe Target
Preprocessing Step 2 - Detecting Calibration Points
Calibration - Estimating Calibration Coefficients
Creating a Calibrated Image

3D Point Clouds
Analyze a CVB Composite (C++/.NET)
Convert a Composite to a PointCloud (C++/.NET)
Generic Data Access to a Composite (C++/.NET)
Analyze a CVB Composite (Python)
Convert a Composite to a PointCloud (Python)
Generic Data Access to a Composite (Python)
Accessing Point Cloud Values (C++/.NET)
Point Cloud Access (C++): Flexible Point Cloud Access Using Cvb::Visit
Point Cloud Access (Python): Mapping a Point Cloud to NumPy Array
Load and Save Point Clouds
Rectifying Point Clouds (ZMaps)
Fill Gaps in ZMaps

Alignment of Point Clouds
Match3D-ICP: Alignment of Point Clouds