capture

rs-capture Sample

Overview

This sample demonstrates how to configure the camera for streaming and rendering Depth & RGB data to the screen.
We use OpenGL for cross-platform rendering and GLFW for window management.
If you are using OpenCV, imshow is a good alternative.

Expected Output

Code Overview

First, we include the Intel® RealSense™ Cross-Platform API.
All but advanced functionality is provided through a single header:

#include <librealsense2/rs.hpp> // Include RealSense Cross Platform API

Next, we include a very short helper library to encapsulate OpenGL rendering and window management:

#include "example.hpp"          // Include a short list of convenience functions for rendering

This header lets us easily open a new window and prepare textures for rendering.

// Create a simple OpenGL window for rendering:
window app(1280, 720, "RealSense Capture Example");

Depth data is usually provided on a 12-bit grayscale which is not very useful for visualization.
To enhance visualization, we provide an API that converts the grayscale image to RGB:

// Declare depth colorizer for enhanced color visualization of depth data
rs2::colorizer color_map; 

The sample prints frame rates of each enabled stream, this is done by rates_printer filter._

// Declare rates printer for showing streaming rates of the enabled streams.
rs2::rates_printer printer;

The SDK API entry point is the pipeline class:

// Declare the RealSense pipeline, encapsulating the actual device and sensors
rs2::pipeline pipe;

// Start streaming with default recommended configuration
// The default video configuration contains Depth and Color streams
// If a device is capable to stream IMU data, both Gyro and Accelerometer are enabled by default 
pipe.start(); 

Next, we wait for the next set of frames, effectively blocking the program. Once a frameset arrives, apply both the colorizer and the rates_printer filters._

rs2::frameset data = pipe.wait_for_frames().    // Wait for next set of frames from the camera
                     apply_filter(printer).     // Print each enabled stream frame rate
                     apply_filter(color_map);   // Find and colorize the depth data

Finally, render the images by the window class from example.hpp

// Show method, when applied on frameset, break it to frames and upload each frame into a gl textures
// Each texture is displayed on different viewport according to it's stream unique id
app.show(data);