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69 lines
2.7 KiB
69 lines
2.7 KiB
# rs-capture Sample
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## Overview
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This sample demonstrates how to configure the camera for streaming and rendering Depth & RGB data to the screen.
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We use OpenGL for cross-platform rendering and GLFW for window management.
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If you are using OpenCV, `imshow` is a good alternative.
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## Expected Output
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## Code Overview
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First, we include the Intel® RealSense™ Cross-Platform API.
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All but advanced functionality is provided through a single header:
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```cpp
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#include <librealsense2/rs.hpp> // Include RealSense Cross Platform API
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```
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Next, we include a [very short helper library](../example.hpp) to encapsulate OpenGL rendering and window management:
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```cpp
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#include "example.hpp" // Include a short list of convenience functions for rendering
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```
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This header lets us easily open a new window and prepare textures for rendering.
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```cpp
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// Create a simple OpenGL window for rendering:
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window app(1280, 720, "RealSense Capture Example");
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```
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Depth data is usually provided on a 12-bit grayscale which is not very useful for visualization.
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To enhance visualization, we provide an API that converts the grayscale image to RGB:
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```cpp
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// Declare depth colorizer for enhanced color visualization of depth data
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rs2::colorizer color_map;
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```
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The sample prints frame rates of each enabled stream, this is done by rates_printer filter._
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```cpp
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// Declare rates printer for showing streaming rates of the enabled streams.
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rs2::rates_printer printer;
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```
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The SDK API entry point is the `pipeline` class:
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```cpp
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// Declare the RealSense pipeline, encapsulating the actual device and sensors
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rs2::pipeline pipe;
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// Start streaming with default recommended configuration
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// The default video configuration contains Depth and Color streams
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// If a device is capable to stream IMU data, both Gyro and Accelerometer are enabled by default
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pipe.start();
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```
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Next, we wait for the next set of frames, effectively blocking the program.
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Once a frameset arrives, apply both the colorizer and the rates_printer filters._
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```cpp
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rs2::frameset data = pipe.wait_for_frames(). // Wait for next set of frames from the camera
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apply_filter(printer). // Print each enabled stream frame rate
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apply_filter(color_map); // Find and colorize the depth data
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```
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Finally, render the images by the `window` class from [example.hpp](../example.hpp)
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```cpp
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// Show method, when applied on frameset, break it to frames and upload each frame into a gl textures
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// Each texture is displayed on different viewport according to it's stream unique id
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app.show(data);
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```
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