chanyn/zed-opencv

ZED SDK interface sample with OpenCV 3.1

Stereolabs ZED - OpenCV

This sample shows how to interface the ZED SDK and OpenCV to acquire and display ZED stereo images and depth map.

Getting started

• First, download the latest version of the ZED SDK on stereolabs.com.
• Make sure you have OpenCV installed.
• For more information, check out this blog post and read the ZED API documentation.

Prerequisites

• Windows 7 64bits or later, Ubuntu 16.04
• ZED SDK and its dependencies (CUDA, OpenCV 3.1)

Build the program

Download the sample and follow these instructions:

Build for Windows

• Create a "build" folder in the source folder
• Open cmake-gui and select the source and build folders
• Generate the Visual Studio Win64 solution
• Open the resulting solution and change configuration to Release
• Build solution

Build for Linux

Open a terminal in the sample directory and execute the following command:

mkdir build
cd build
cmake ..
make

Run the program

• Navigate to the build directory and launch the executable file

• Or open a terminal in the build directory and run the sample :

    ./ZED\ with\ OpenCV [path to SVO file]
  

You can optionally provide an SVO file path (recorded stereo video of the ZED)

Features

This sample is the perfect place to get started coding with the ZED. It shows how to use the basic functions of the ZED SDK:

• Capture stereo video from the ZED or an SVO file.
• Capture depth map as a compatible 32bits float OpenCV matrix.
• Display stereo video in several viewing modes: raw, rectified, grayscale, anaglyph, overlay, difference and side-by-side.
• Display disparity and depth map.
• Adjust several depth parameters: depth sensing mode, max range, depth confidence.

To learn how to add camera tracking capabilities, see the dedicated tracking sample.

Keyboard shortcuts

This table lists keyboard shortcuts that you can use in the sample application.

Parameter	Description	Hotkey
Left image view	Display left rectified RGB image.	'0'
Right image view	Display right rectified RGB image.	'1'
Side by Side view	Display the left and right images side by side.	'2'
Overlay view	Display overlay view.	'3'
Difference view	Display difference view.	'4'
Anaglyph view	Display anaglyph view.	'5'
Depth view	Toggle between disparity / depth map display.	'd'
Confidence view	Display depth map confidence. The confidence value is mapped between 0 (high confidence threshold, sparse data) and 100 (low confidence threshold, dense data).	'c'
Confidence threshold	Increase/Decrease depth map confidence threshold.	'b'/'n'
Sensing mode	Toggle between STANDARD sensing mode (faster, should be used by most applications) / FILL (fully dense and filtered depth map).	's'
Exit	Quit the application.	'q'

Limitations

• For simplicity's sake, this sample uses GPU->CPU data transfer to retrieve and display the images with OpenCV.
• For optimal performance, we recommend using a direct device to device copy of the ZED SDK GPU buffer to OpenGL buffer, rather than using the CPU as an intermediate.