Book Image

Learning OpenCV 3 Computer Vision with Python (Update)

Book Image

Learning OpenCV 3 Computer Vision with Python (Update)

Overview of this book

Table of Contents (16 chapters)
Learning OpenCV 3 Computer Vision with Python Second Edition
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
6
Retrieving Images and Searching Using Image Descriptors
Index

Capturing frames from a depth camera


Back in Chapter 2, Handling Files, Cameras, and GUIs, we discussed the concept that a computer can have multiple video capture devices and each device can have multiple channels. Suppose a given device is a stereo camera. Each channel might correspond to a different lens and sensor. Also, each channel might correspond to different kinds of data, such as a normal color image versus a depth map. The C++ version of OpenCV defines some constants for the identifiers of certain devices and channels. However, these constants are not defined in the Python version.

To remedy this situation, let's add the following definitions in depth.py:

# Devices.CAP_OPENNI = 900 # OpenNI (for Microsoft Kinect)CAP_OPENNI_ASUS = 910 # OpenNI (for Asus Xtion)
# Channels of an OpenNI-compatible depth generator.CAP_OPENNI_DEPTH_MAP = 0 # Depth values in mm (16UC1)CAP_OPENNI_POINT_CLOUD_MAP = 1 # XYZ in meters (32FC3)CAP_OPENNI_DISPARITY_MAP = 2 # Disparity in pixels (8UC1)CAP_OPENNI_DISPARITY_MAP_32F...