MouseTrap Dev Help

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* http://docs.opencv.org/doc/tutorials/tutorials.html -> tutorials on opencv
 
* http://docs.opencv.org/doc/tutorials/tutorials.html -> tutorials on opencv
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* http://docs.scipy.org/doc/numpy/reference/arrays.ndarray.html#array-attributes -> structure of numpy arrays
  
 
==== A cv2 example ====
 
==== A cv2 example ====

Revision as of 18:38, 14 February 2013

Contents

Opencv

Great Resources

cv 2.4.3

A cv2 example

Here is a little program that will capture video from the webcam and display it (you might have to CTRL+C) 

"""
This module is used for testing the opencv2 capabilities
"""
import cv2
#get webcam feed
capture = cv2.VideoCapture(0)
while True:
    #combines VideoCapture.grab() and VideoCapture.retrieve()
    retrieval_value, image = capture.read()
    #shows captured image in a window
    cv2.imshow("webcam", image)
    #will stop capture with capatible webcam
    if cv2.waitKey(10) == 27:
        break

cv 2.1

Concerns

Here we place all of the concerns when migrating to a newer version of opencv or the repercussions of not upgrading.

Migration to Python 3

  • Opencv 2.4.3 does not support Python 3

Camera drivers

  • Currently, only some camera drivers are supported with the new version of opencv, leading to problems regarding capture. One issue is the inability to cancel the program webcam capture.

Yum repo

  • Right now, only the 2.3.1 version of opencv is available in the yum repository

OpenCV Info (WIP)

Basics and Source Code

OpenCV (Open Source Computer Vision) is a library of programming functions for the realtime computer vision. OpenCV is released under the liberal BSD license and hence it's free for both academic and commercial use. It has C++, C, Python and Java (Android) interfaces and supports Windows, Linux, Android and Mac OS. The library has more than 2500 optimized algorithms. Adopted all around the world, OpenCV has more than 47 thousand people of user community and estimated number of downloads exceeding 5 million. Usage ranges from interactive art, to mines inspection, stitching maps on the web or through advanced robotics.

To access the OpenCV repository directly: git clone git://github.com/itseez/opencv.git

History

"OpenCV was started at Intel in 1999 by Gary Bradski for the purposes of accelerating research in and commercial applications of computer vision in the world and, for Intel, creating a demand for ever more powerful computers by such applications. Vadim Pisarevsky joined Gary to manage Intel's Russian software OpenCV team. Over time the OpenCV team moved on to other companies and other Research. Several of the original team eventually ended up working in robotics and found their way to Willow Garage. In 2008, Willow Garage saw the need to rapidly advance robotic perception capabilities in an open way that leverages the entire research and commercial community and began actively supporting OpenCV, with Gary and Vadim once again leading the effort."

So what is OpenCV?

The full name is "Open Source Computer Vision Library." It is a library of programming functions aimed at real-time computer vision. It was developed by Intel and now Willow Garage and Itseez support it. It is free for use under the open source BSD license. Also, it can cross-platform.

Where did it come from?

OpenCV emerged from the Intel Research Initiative; it is related to Intel's Performance Library, which today is called Integrated Performance Primitives (IPP). The project launched in 1999. It was looking for CPU-intensive applications. The project goals were to:

  1. advance vision research by open and optimized infrastructure
  2. disseminate vision knowledge with readable code
  3. and advance commercial applications

Version List: 

alpha-release at CVPR 2000 
five beta-releases 2001-2005 
Version 1.0 2006 
Continuation of development by Willow Garage 2008 (pre-release version 1.1) 
Version 2.0 2009 
Versions 2.1, 2.2 2010 
Version 2.3 2011 
Version 2.4.0 May 2012 
Version 2.4.1 June 2012 
Version 2.4.2 July 2012

Application Use: 

2D and 3D Feature Toolkits
Egomotion Estimation
Facial Recognition System
Gesture Recognition
Human-Computer Interaction (HCI)
Mobile Robotics
Motion Analysis
Object Detction and Recognition
Segmentation
Stereo Vision: Depth Perception from 2 Cameras
Structure from Motion (SFM)
Motion Tracking

(http://www.cvl.isy.liu.se/education/graduate/opencv/Lecture1_History.pdf)

Definitions

Modules Available

*core: a compact module defining basic data structures, including the dense multi-dimensional array Mat and basic functions
used by all other modules
*imgproc: an image processing module that includes linear and non-linear image filtering, geometrical image transformations
(resize, affine and perspective warping, generic table-based remapping), color space conversion, histograms, and so on
*video: a video analysis module that includes motion estimation, background subtraction, and object tracking algorithms
*calib3d: basic multiple-view geometry algorithms, single and stereo camera calibration, object pose estimation, stereo
correspondence algorithms, and elements of 3D reconstruction
*features2d: salient feature detectors, descriptors, and descriptor matchers
*objdetect: detection of objects and instances of the predefined classes (for example, faces, eyes, mugs, people, cars, and so on)
*highgui: an easy-to-use interface to video capturing, image and video codecs, as well as simple UI capabilities
*gpu: GPU-accelerated algorithms from different OpenCV modules
*some other helper modules, such as FLANN and Google test wrappers, Python bindings, and others

(http://docs.opencv.org/)

Good Link Resources

OpenCV Community

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