|
|
| Line 45: |
Line 45: |
| | This will ask for your git credentials, so have them ready. | | This will ask for your git credentials, so have them ready. |
| | | | |
| − | = The MouseTrap Program =
| |
| − |
| |
| − | '''Here is a complete dissection of the hierarchy done by gnome:''' http://gnome-mousetrap.sourcearchive.com/documentation/0.3plus-psvn17-2ubuntu1/main.html
| |
| − |
| |
| − | ==Definitions==
| |
| − | ; Haar wavelet: First proposed by Alfred Haar, the Haar wavelet is a series of square-shaped functions that when shown together form a basis otherwise known as a wavelet family and expressed in terms of an orthonormal function basis. For more information, see: [[http://en.wikipedia.org/wiki/Haar_wavelet]]
| |
| − | ; Haar-like features: Uses adjacent rectangular regions in a specified detection window, sums up the pixel intensities and calculates the difference between those sums. They are called Haar-like features because they are computed using similar coeffients in the Haar wavelet transforms. These regions can then be concatenated with ''boosted classifiers'' into a ''classifier cascade'' to cross reference these regions with other positive samples to form a model for object detection. For more information, see [[http://en.wikipedia.org/wiki/Haar-like_features]] [[http://opencv.willowgarage.com/wiki/FaceDetection]]
| |
| − | ; Boosted Classifiers: The result of increasing the accuracy of a classifier cascade through the means of positive object recognition of scaled images.
| |
| − | ; Boosting: Attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. [[http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume11/opitz99a-html/node4.html]]
| |
| − | ; Classifier Cascade: Proposed by Paul Viola and refined by Rainer Lienhart, a classifier cascade
| |
| − | ; ROI (Region of Interest): This is usually a subset of the original frame represented as a rectangle. It is most often compared to a classifier cascade to determine a positive match.
| |
| − | ; Ocvfw (OpenCV FrameWork): A MouseTrap in house framework that manages OpenCV methods and includes functions to initiate the camera and detect further Haar-like features.
| |
| − | ; Optical flow: Detecting the pattern of motion of moving objects. [[http://www.youtube.com/watch?v=WS3naWwfToI]] [[http://robots.stanford.edu/cs223b05/notes/CS%20223-B%20T1%20stavens_opencv_optical_flow.pdf]]
| |
| − | ; Lucas-Kanade method: Differential method to estimate optical flow, it combines several nearby pixels to resolve the ambiguity of the optical flow equation [[http://en.wikipedia.org/wiki/Lucas%E2%80%93Kanade_method]].
| |
| − | ; Singleton: Restricts the instantiation of a class to one object so coordination over program actions can be achieved.
| |
| − |
| |
| − | == Classes ==
| |
| − |
| |
| − | === app ===
| |
| − | ==== main.py ====
| |
| − | * Loads the Image Detection Module (idm)
| |
| − | *
| |
| − | ==== commons.py ====
| |
| − | * Stores global variables for Ocvfw
| |
| − | * cv: OpenCV related variables
| |
| − | * hg: OpenCV.highgui related variables. Set in ocvfw/idm/ color.py to be used in the creation of the Window and Trackbar
| |
| − | * abs_path: the absolute path to the commons file
| |
| − | * haar_cds: array with the haar xml file paths
| |
| − | * colors: array with the types of colors the image can appear in
| |
| − | * singleton: class instance to be passed through program globally
| |
| − |
| |
| − | * '''Methods:'''
| |
| − | get_ch(color): returns channel corresponding to the color given (rgb, bgr, gray)
| |
| − |
| |
| − | ==== environment.py ====
| |
| − |
| |
| − | ==== debug.py ====
| |
| − | * This is used to display messages to the command line
| |
| − | * Very helpful to troubleshoot
| |
| − |
| |
| − | === ui ===
| |
| − |
| |
| − | ==== main.py ====
| |
| − |
| |
| − | === lib ===
| |
| − |
| |
| − | === addons ===
| |
| − |
| |
| − | == OpenCV Framework (ocvfw) ==
| |
| − | * This is the wrapper around OpenCV
| |
| − | * View diagram here: [[https://github.com/amberheilman/mousetrap/blob/master/docs/MouseTrap.jpeg]]
| |
| − |
| |
| − |
| |
| − | === ocvfw/ _ocv.py ===
| |
| − | * Contains three classes:
| |
| − |
| |
| − | OcvfwBase: direct copy of backends/ OcvfwBase
| |
| − | OcvfwPython: direct copy of backends/ OcvfwPython
| |
| − | OcvfwCtypes: direct copy of backends/ OcvfwCtypes
| |
| − |
| |
| − | === ocvfw/ idm ===
| |
| − | * Detects features based on an xml file
| |
| − |
| |
| − | === ctypesopencv ===
| |
| − | * This is used instead of the python bindings for OpenCV
| |
| − |
| |
| − | === pocv.py ===
| |
| − | * Returns an instance of the idm
| |
| − |
| |
| − | === ocvfw/ haars ===
| |
| − | * Used thousands of samples to concatenate an xml file to predict features
| |
| − |
| |
| − | ===dev/ camera===
| |
| − | * checks for gtk
| |
| − | * loads the camera backend
| |
| − | * sets Camera as a singleton with backend as the base
| |
| − | * Class Capture
| |
| − | ** first gets a region of interest and then matches it against a haar classifier
| |
| − | ** Sets all variables associated with video capture
| |
| − | **'''Methods:'''
| |
| − | set_async(fps, async): sets the frames per second and whether the image should have asynchronous querying.
| |
| − | If it is true, then it will set a gobject timeout of the specified frames per second
| |
| − | sync(): Synchronizes the Capture image with the Camera image
| |
| − | set_camera(key, value): sets the Camera object with key and value specified
| |
| − | image(new_img): sets the self.__image variable to specified value
| |
| − | resize(width, height, copy): manipulates the self.__image variable and resizes it using cv.Resize() and width
| |
| − | and height given, will not replace the self.__image if copy is True.
| |
| − | to_gtk_buff(): Converts image to gtkImage and returns it
| |
| − | points(): returns self.__graphics["point"], a list with rectangles that have been added?
| |
| − | rectangles(): returns self.__graphics["rect"], a list with rectangles that have been added
| |
| − | show_rectangles(rectangles): draws the rectangles onto the self.__image
| |
| − | original(): returns the Capture object with the self.__image_orig image, setting the Capture to the original image
| |
| − | rect(*args): uses the args (a rectangle) to get a sub-part of the self.__image using cv.GetSubRect()
| |
| − | flip(flip): flip is a string that can contain 'hor' 'ver' or 'both' to use cv.Flip() to manipulate the
| |
| − | self.__image. Returns self.__image
| |
| − | color(new_color, channel, copy): if new_color is true it will set the image to the new channel provided.
| |
| − | If copy is set, it will only manipulate a new image and keep the
| |
| − | existing image as is.
| |
| − | change(size, color, flip): will set self.__color_set to the new color value and set self.__flip
| |
| − | to the new flip value. Does not currently support the change in image size.
| |
| − | add(graphic): has checks to see if the capture is locked or if the graphic exists already. Otherwise
| |
| − | it will add the graphic passed to it to the image using set_lkpoint()
| |
| − | remove(label): removes a graphic object from self.__graphics[] by its label.
| |
| − | get_area(haar_csd, roi, orig): uses the haartraining file (haar_csd) to it will use get_haar_points()
| |
| − | or get_haar_roi_points() depending whether roi is set. It can also get
| |
| − | the area within an area using the roi and setting the origin point.
| |
| − | message(message): does nothing, just pass
| |
| − | lock(): sets the self.__lock to true, which is used in add() and remove()
| |
| − | unlock(): sets self.__lock to false
| |
| − | is_locked(): returns self.__lock
| |
| − |
| |
| − | *'''Classes'''
| |
| − | '''Graphic()'''
| |
| − | init(): x and y stored in a list coords[x, y]
| |
| − | size: list [width, height]
| |
| − | type: could be a point
| |
| − | label: string
| |
| − | color: rgb color or tuple
| |
| − | follow: used for optical flow
| |
| − | parent: what is the parent class
| |
| − | is_point(): checks if type is true
| |
| − |
| |
| − | '''Point(): contains a graphic and additional variables and methods'''
| |
| − | init(): graphic(**args)
| |
| − | __ocv: opencv attribute
| |
| − | last: opencv attribute
| |
| − | diff: difference between two points
| |
| − | abs_diff: difference between original and current
| |
| − | rel_diff: difference between last and current
| |
| − | orig: an opencv Point objec
| |
| − | set_opencv(opencv): updates the current attributes, updates the points in abs_diff and rel_diff
| |
| − | and sets self.__ocv to opencv given
| |
| − | opencv(): returns the graphic object with the opencv attributes (__ocv)
| |
| − |
| |
| − | ===backend===
| |
| − | * link to image on how the backend distributes variables [[http://gnome-mousetrap.sourcearchive.com/documentation/0.4-2/classmousetrap_1_1ocvfw_1_1__ocv_1_1OcvfwBase__inherit__graph.png"]]
| |
| − |
| |
| − | * Contains three classes:
| |
| − |
| |
| − | ====backend/ OcvfwBase====
| |
| − | * sets image variables
| |
| − | * '''Methods:'''
| |
| − | set(key, value): sets the key (image variables) to the value specified
| |
| − | lk_swap(set): switches the boolean of the Lucas-Kanade points, if true, it will append current to last
| |
| − | new_image(size, num, ch): Will CreatImage(size, depth, channel) using a Size(width, height), depth and channel
| |
| − | set_camera_idx(idx): sets the global var self.idx to specified idx number
| |
| − | wait_key(num): uses cv WaitKey() and inputs number specified
| |
| − | start_camera(params): grabs the video capture and sets it as a global variable
| |
| − | query_image: grabs the first frame and creates self.img, the pyramids and grey images for optical flow.
| |
| − | Uses wait_key(). returns true
| |
| − | set_lkpoint(point): uses cv.Point, sets the self.img_lkpoints image, uses dev/ camera.set_opencv()
| |
| − | to manipulate the graphic object (made my Mousetrap), sets the ["current"] using FindCornerSubPix()
| |
| − | and if ["last"] exists, it appends current, appends point to ["points"]
| |
| − | clean_lkpoints(): sets self.img_lkpoints current, last and points to empty
| |
| − | show_lkpoints(): calculates the optical flow and assigns it to the ["current"] lkpoints if it resolves.
| |
| − | Recursively goes through ["points"] and draws them, then sets ["current"] back to points
| |
| − | swap_lkpoints(): only after the new points were shown, swap prev with original and current with last
| |
| − |
| |
| − | ====backend/ OcvfwPython====
| |
| − | * inherits from OcvfwBase
| |
| − | * imports global and local variables from Commons.hg (highgui related variables) and Commons.cv(Opencv) variables
| |
| − | * has the ability to get_motion_points but is not used
| |
| − | * has the ability to add_message to the image shown but is not used
| |
| − | * '''Methods:'''
| |
| − | get_haar_roi_points: finds regions of interest within the entire frame image and returns the matches against the classifier cascade
| |
| − | using the ''HaarDetectObjects()'' OpenCV function.
| |
| − | get_haar_points: resizes the image by 1.5
| |
| − |
| |
| − | ====backend/ OcvfwCtypes====
| |
| − | * imports global and local variables from Commons.hg (highgui), Commons.cv(which is a CV common lib), and OcvfwBase
| |
| − |
| |
| − | == Files affected by OpenCV 2.4.3 upgrade ==
| |
| − | * main.py
| |
| − | * ocvfw
| |
| − | ** _ocv.py
| |
| − | ** ocvfw/ idm
| |
| − | *** eyes.py
| |
| − | *** finger.py
| |
| − | *** forehead.py
| |
| − | *** color.py
| |
| − | ** commons.py
| |
| − | ** ocvfw/ dev
| |
| − | *** camera.py
| |
| − | ** ocvfw/ backends
| |
| − | *** OcvfwBase.py
| |
| − | *** OcfwCtypes.py
| |
| − | *** OcvfwPython.py
| |
| − |
| |
| − | = Opencv =
| |
| − |
| |
| − | == General 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=
| |
| − |
| |
| − | ===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
| |
| − | * A good source for this is: http://code.opencv.org/projects/opencv/wiki/Working_with_OpenCV_git_repository
| |
| − | * The rest of the history plus matches between git commits and SVN revisions are stored at a separate "OpenCV Attic" repository: git://code.opencv.org/opencv_attic.git.
| |
| − | * Also OpenCV Extra was put to a separate repository: git://code.opencv.org/opencv_extra.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." NEED A REF OR LINK
| |
| − |
| |
| − | ----
| |
| − | So what is OpenCV?
| |
| − | * OpenCV is a computer vision library in C++.
| |
| − | * OpenCV 2 was released in 2009 with additional functionality and increased performance
| |
| − | * CV is a Python wrapper for OpenCV
| |
| − | * CV2 is a Python wrapper for OpenCV 2 and includes CV
| |
| − | ** If you want CV functions you have to
| |
| − |
| |
| − | import cv2.cv as cv
| |
| − |
| |
| − | 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:
| |
| − | #advance vision research by open and optimized infrastructure
| |
| − | #disseminate vision knowledge with readable code
| |
| − | #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/)
| |
| − |
| |
| − | === OpenCV - Great Resources===
| |
| − | * http://www.cvl.isy.liu.se/education/graduate/opencv/Lecture1_History.pdf
| |
| − | * http://docs.opencv.org/
| |
| − | * http://docs.opencv.org/opencv_tutorials.pdf (Tutorial)
| |
| − | * http://opencv.org/documentation.html
| |
| − | * http://www.pages.drexel.edu/~nk752/tutorials.html (Tutorials)
| |
| − | * http://www.laganiere.name/opencvCookbook/ (Companion Site to an OpenCV2 Book)
| |
| − | * http://stackoverflow.com/questions/10417108/what-is-different-between-all-these-opencv-python-interfaces (Difference between CV and CV2)
| |
| − | * http://opencv-users.1802565.n2.nabble.com/ (OpenCV mailing list archive)
| |
| − | * http://pr.willowgarage.com/wiki/OpenCVMeetingNotes (OpenCV meeting minutes)
| |
| − | ** As of May 22, 2012, the meetings notes moved to: http://code.opencv.org/projects/opencv/wiki/Meeting_notes
| |
| − | * http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs (OpenCV Change Logs)
| |
| − |
| |
| − | =Opencv 2 Info=
| |
| − |
| |
| − | ==Some Differences Between cv and cv2==
| |
| − |
| |
| − | * single import of all of OpenCV using <big>import cv</big>
| |
| − | * OpenCV functions no longer have the "cv" prefix
| |
| − | * simple types like CvRect and CvSca,lar use Python tuples
| |
| − | * sharing of Image storage, so image transport between OpenCV and other systems (e.g. numpy and ROS) is very efficient
| |
| − | * complete documentation for the Python functions
| |
| − |
| |
| − | == OpenCV 2 - Great Resources ==
| |
| − |
| |
| − | === cv 2.4.3 ===
| |
| − | * http://docs.opencv.org -> documentation
| |
| − |
| |
| − | * http://docs.opencv.org/opencv2refman.pdf / http://cvhci.anthropomatik.kit.edu/download/visionhci09/opencv.pdf -> pdf documentation resources
| |
| − |
| |
| − | * http://fossies.org/dox/OpenCV-2.4.3/index.html -> Complete Hierarchical guide to opencv
| |
| − |
| |
| − | * http://docs.opencv.org/doc/tutorials/tutorials.html -> tutorials on opencv
| |
| − |
| |
| − | * http://docs.scipy.org/doc/numpy/reference/arrays.ndarray.html#array-attributes -> structure of numpy arrays
| |
| − |
| |
| − | * Books:
| |
| − | Author: Laganière, Robert.
| |
| − | Title: OpenCV 2 computer vision application programming cookbook [electronic resource] :
| |
| − | over 50 recipes to master this library of programming functions for real-time computer vision / Robert Laganière.
| |
| − | Imprint Birmingham, U.K. : Packt Open Source Pub., 2011.
| |
| − | Availability: eBook in the Drexel Library.
| |
| − |
| |
| − | Author: Gary Bradski; Adrian Kaehler
| |
| − | Title: Learning OpenCV
| |
| − | Publisher: O'Reilly Media, Inc.
| |
| − | Pub. Date: September 24, 2008
| |
| − | Availability: ACM Safari books collection for anyone who is a member.
| |
| − |
| |
| − | ==== 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 ===
| |
| − | * http://opencv.willowgarage.com/documentation/python/index.html -> documentation
| |
| − | * http://nullege.com/codes/search/cv -> code samples
| |
| − |
| |
| − | =OpenCV Community=
| |
| − | * The #opencv IRC channel on Freenode -- currently 'Un-official'
| |
| − | * http://opencv.willowgarage.com/wiki/FullOpenCVWiki#Welcome.2FPeople.People
| |
| − | * http://tech.groups.yahoo.com/group/OpenCV/ -> User Group on Yahoo
| |
| − | * http://answers.opencv.org/questions/ -> Q&A
| |
| − | * http://code.opencv.org/projects/opencv/issues -> Bugs
| |
| − |
| |
| − | =Code Meeting Notes=
| |
| − | * '''Meetings occur on Wednesday's at noon (starting on 2/20) on irc.gnome.org #mousetrap - holiday and other circumstances permitting.'''
| |
| − | == 2.19.2013 ==
| |
| − | === Agenda ===
| |
| − | # Status
| |
| − | # Go over git+mousetrap installation [[http://www.xcitegroup.org/foss2serve/index.php/MouseTrap_Dev_Help#Complete_Git_.2B_Mousetrap_Install]]
| |
| − | # Address any issues
| |
| − | # Go over mousetrap hierarchy [[http://www.xcitegroup.org/foss2serve/index.php/MouseTrap_Dev_Help#The_MouseTrap_Program]]
| |
| − | # Go over opencv integration methods [[http://www.xcitegroup.org/foss2serve/index.php/MouseTrap_Dev_Help#Files_affected_by_OpenCV_2.4.3_upgrade]]
| |
| − | # Next Steps
| |
| − |
| |
| − |
| |
| − | ===Meeting summary===
| |
| − | ---------------
| |
| − | '''Status'''
| |
| − | * LINK:
| |
| − | http://gnome-mousetrap.sourcearchive.com/documentation/0.4-2/main.html
| |
| − | (amber, 18:14:27)
| |
| − | * LINK:
| |
| − | http://gnome-mousetrap.sourcearchive.com/documentation/0.4-2/main.html
| |
| − | (amber, 18:14:29)
| |
| − | * LINK: http://code.opencv.org/projects/opencv/wiki/Meeting_notes
| |
| − | (Dark_Rose, 18:17:39)
| |
| − | * LINK:
| |
| − | http://www.xcitegroup.org/foss2serve/index.php/MouseTrap_Dev_Help#The_MouseTrap_Program
| |
| − | (amber, 18:20:24)
| |
| − |
| |
| − | '''Git and mousetrap installation'''
| |
| − | * creating your own branch in git: git checkout -b my_fantastic_branch
| |
| − | (Stoney, 18:29:24)
| |
| − | * LINK:
| |
| − | http://git-scm.com/book/en/Git-Branching-Basic-Branching-and-Merging
| |
| − | (amber, 18:32:31)
| |
| − |
| |
| − | '''Issues'''
| |
| − | * LINK: http://code.google.com/p/pyopencv/ (john, 18:46:37)
| |
| − | * ctypes-opencv is a package that brings Willow Garage's (formerly
| |
| − | Intel's) Open Source Computer Vision Library (OpenCV) to Python.
| |
| − | OpenCV is a collection of algorithms and sample code for various
| |
| − | computer vision problems. The goal of ctypes-opencv is to provide
| |
| − | Python access to all documented functionality of OpenCV. (amber,
| |
| − | 18:46:39)
| |
| − | * LINK: http://code.google.com/p/pyopencv/ (amber, 18:46:46)
| |
| − | * http://pythonhosted.org/pyopencv/2.1.0.wr1.2.0/ (amber, 18:51:37)
| |
| − | * LINK: http://pythonhosted.org/pyopencv/2.1.0.wr1.2.0/ (amber,
| |
| − | 18:51:45)
| |
| − |
| |
| − | '''Integration methods'''
| |
| − | * LINK:
| |
| − | http://gnome-mousetrap.sourcearchive.com/documentation/0.4-2/dir_9d66d24675e04ade776f5269c3621ea1.html
| |
| − | (amber, 18:58:53)
| |
| − | * LINK:
| |
| − | http://gnome-mousetrap.sourcearchive.com/documentation/0.3plus-psvn17-2ubuntu1/classmouseTrap_1_1ocvfw_1_1ocvfw.html
| |
| − | (amber, 19:02:40)
| |
| − | * ACTION: Create Module documentation for MouseTrap (amber, 19:14:55)
| |
| − |
| |
| − | Meeting ended at 19:16:36 CET.
| |
| − |
| |
| − | '''Action Items'''
| |
| − | ------------
| |
| − | * Create Module documentation for MouseTrap
| |
| − |
| |
| − | '''People Present (lines said)'''
| |
| − | ---------------------------
| |
| − | * amber (125)
| |
| − | * john (39)
| |
| − | * Stoney (31)
| |
| − | * logan_h (14)
| |
| − | * darci (8)
| |
| − | * Dark_Rose (5)
| |
| − | * tota11y (2)
| |
| − |
| |
| − | === Conclusions ===
| |
| − | * documentation on Mousetrap's OpenCV FrameWork is needed for further inspection.
| |
| − |
| |
| − | == 2.26.2013 ==
| |
| − | * Address meeting reschedule
| |
| | | | |
| | [[Category:Gnome_MouseTrap]] | | [[Category:Gnome_MouseTrap]] |
