Please refer to installation guideline at Python Installation
Please refer to the instructions at Building from Source
These Examples demonstrate how to use the python wrapper of the SDK.
Link to GitHub
This example demonstrates how to start streaming depth frames from the camera and display the image in the console as an ASCII art.
Rendering depth and color with OpenCV and Numpy
This example demonstrates how to render depth and color images using the help of OpenCV and Numpy
Align & Background Removal
Demonstrate a way of performing background removal by aligning depth images to color images and performing simple calculation to strip the background.
Example of the advanced mode interface for controlling different options of the D400 ??? cameras
Read Bag File
Example on how to read bag file and use colorizer to show recorded depth stream in jet colormap.
Export Point Cloud to PLY
This example shows how to export pointcloud to ply format file
Frame Queue management
This example shows How to manage frame queues to avoid frame drops when multi streaming
Box measurement and multi-cameras Calibration
Simple demonstration for calculating the length, width and height of an object using multiple cameras.
Self Calibration: On Chip + Tare
This example Demonstrates how to run On Chip calibration and Tare
Demonstrates how to retrieve pose data from a T265 camera
This example shows how to change coordinate systems of a T265 pose
Sparse Stereo Depth (FishEye Passive)
This example shows how to use T265 intrinsics and extrinsics in OpenCV to asynchronously compute depth maps from T265 fisheye images on the host.
T265 Wheel Odometry
This example shows how to fuse wheel odometry measurements on the T265 tracking camera
Stream over Ethernet
This example shows how to stream depth data from RealSense depth cameras over ethernet.
PointCloud with OpenCV
This sample is mostly for demonstration and educational purposes.
PointCloud with PyGlet
OpenGL Pointcloud viewer with http://pyglet.org
TensorFlow Machine Learning
Tutorial showing how TensorFlow-based machine learning can be applied with Intel RealSense Depth Cameras.
- Distance to Object - This notebook offers a quick hands-on introduction to Intel RealSense Depth-Sensing technology. Please refer to Distance to Object for further information. Click to experience
- Depth Filters - This notebook is intended to showcase effect of post processing filters. Please refer to Depth Filters for further information. Click to experience
Updated almost 2 years ago