Free camera repair shop software for linux

Camera Monitor is a little tray system icon that notifies you when your Webcam is on. The project is designed for the GNOME desktop, but will work as well on KDE and XFCE.
Camera Monitor is released under the terms of the GNU General Public License.
Installation:
tar xzf laptoptemp-0.2.tar.gz
cd cameramonitor-0.1
./configure
sudo make install
Enhancements:
- Added support for libnotify
- Ported to new gtk.StatusIcon
- Updated preferences panel
- Updated about information
- Removed notification on bad previous exit
- Added option to preferences for autostarting cameramonitor every session

Camera_AXIS is a Java application for viewing images generated by an AXIS 2100 network camera. The camera generates a video stream in MJPG format.

The java source code can be browsed online or downloaded in tgz format. The application uses the Base64 encoder from Robert Harder (distributed with Camera_AXIS). Installation is simple:

make

Start the application using te command:

make test

Configuration parameters are saved in .java.cfg. This file is created the first time you start the application and contains the URL of the camera and the user id and password of the camera administrator. Without the id and/or the password, you can still view images from the camera, but you wont be able to change its settings. Proxy settings are taken from the http_proxy environment variable (if present).

A precompiled jar-file is also available. Execute it with java -jar AXIS.jar.

FreeTpl PHP Shopping Cart supports Downloadable products with instant activation option, especially useful for software companies selling their products via the Internet & could be easily integrated into any system widely utilizing the power of templates and web-administration tools.

Shopping Basket with advanced Sales Mechanisms (Products reviews and ratings, Discounts mechanism, Shipping and Stock mechanisms, etc), Web-based Administration with Order Maintenance, Product Maintenance, User/Shopper Maintenance, multiple payment processing capabilities (including support of Verisign, Paypal and Authorize.net payment systems). The project provides an easy, quick and flexible web interface that allows adding high performance Shopping basket to your web site.

queue_repair is a toolkit for dealing with the qmail queue directory structure; it can create a new queue, move and properly rename a queue, dynamically change the conf-split value, convert big-todo queues to non-big-todo and vice versa, and repair a corrupted queue.

Playlist-repair scans music-playlists (PLS and M3U) for dead-links (moved or renamed files) and double entries.
The search-enginge finds moved and similar named files and replaces the wrong entrys in the playlist.
Enhancements:
- Missing: ID3Tag support

Python Traffic Analyzer is a Python base class and sample driver script written to retrieve and manipulate images from the TrafficLand cameras and calculate a numeric value representing the current traffic flow.

PyTrAn, an example driver script, an image collector and an image mask creator are available for download from the link shown at the bottom. To use the PyTrAn package begin by choosing a camera that you wish to analyze, for this example well use the camera captioned above.

We want to construct a mask over the area of the image that we are interested in, namely the road. In this particular example the road takes up the majority of the image but that is not always the case.

We will apply the mask over captured images to fine tune the area over which we are looking for movement. To create the mask we will first need to collect a sequential series of snapshots from the target camera. The image_collector.py script was written for this task:

$ mkdir mask_200003
$ cd mask_200003
$ ../image_collector.py 200003 30
Collecting 30 images...
30

Done.

The script is hard coded to capture images on a 2-second delay. The delay is necessary to ensure the image has changed. I believe 2-seconds to be the absolute minimum. Once complete, 30 images numbered 1 through 30 will be created in the current directory.

We construct a mask from these captured images by creating a diff-image for each sequential image pair and then adding each diff-image together. Naturally, a script was written to automate this task as well:

$ ../mask_maker.py 1 30
Creating a diff for each sequential image pair.
Diffing 29

Creating the initial mask from the first image pair.

Adding the rest of the diffs to the mask.
Masking 29

Done.

A number of .diff files are generated in this process. These files repesent the movement between individual sequence pairs.

The .diff files are simply intermediary files, the important bit is the mask file, which is generated as the sum of all differences.

The mask file may be dirty (as in this case) and require manual cleanup. The basic shape of the road however is clearly visible, evidence that we can with minimal effort automate the mask generation process. Also, this run was conducted at night, day-time images yield better results.

There are a few final steps we need to take before we can use the example PyTrAn driver script. First we need to convert the mask to ASCII (noraw) format:

$ pnmnoraw mask > mask_200003.ascii

Then we need to open an ImageMagick display window and get its X-window-ID using xwininfo. Finally, update camera_id and window_id in pytran_sampling.py and launch the driver:

$ ../pytran_sampling.py
DEBUG> grabbing frame from camera 200003
DEBUG> rotating image: pytran.this > pytran.last
DEBUG> refreshing image in 3 secs
taking a 5 minute sample at various thresholds.
DEBUG> grabbing frame from camera 200003
DEBUG> generating frame diff on pytran.last, pytran.this
DEBUG> displaying image: pytran.diff
DEBUG> converting pytran.diff to ascii
DEBUG> calculating traffic ratio...
ratio[5]: 55%
DEBUG> calculating traffic ratio...
ratio[10]: 52%
...
...
5 minute sample[5]: 67.88
5 minute sample[10]: 42.66
5 minute sample[15]: 30.57
5 minute sample[20]: 23.03
5 minute sample[25]: 18.39
5 minute sample[30]: 14.79
5 minute sample[35]: 12.42
5 minute sample[40]: 10.53
5 minute sample[45]: 9.06
5 minute sample[50]: 7.85

The sampling script will take 5 minute samples at varying color thresholds. The optimal threshold must be manually chosen. Furthermore, you will need to sample the traffic ratios during both heavy and light traffic times to get a good feel for your acceptable range. Also, keep in mind that the traffic ratio value is simply the percent change detected, or in other words the movement detected within the masked region. This means that a completely empty road will register similar values to a road so congested it looks like a parking lot. The time of day can be combined with the traffic ration to determine the logical truth.

With this task implemented and abstracted more complex systems can be built. When I find the time Id like to create a system that will take multiple potential travel routes and times, and during the travel time e-mail the traveler with the best route to take. Another idea I had would be to record the traffic flow values for each camera, for each day and for each half hour interval. Travelers and other interested parties can then analyze traffic patterns to determine the fastest route dependant on date/time.

reacTIVision is an open source, cross-platform computer vision framework for the fast and robust tracking of fiducial markers in a real-time video stream. reacTIVision project was mainly designed for the rapid development of table-based tangible user interfaces.

Its tracking core is using Ross Bencinas fidtrack library which is basically a newer high-performance implementation of Enrico Costanzas original d-touch concept. This framework was developed by Martin Kaltenbrunner et.al. at the Music Technology Group, IUA, UPF in Barcelona, Spain as part of the reacTable* project, a novel electro-acoustic musical instrument with a tangible user interface.

reacTIVision is a standalone application, which sends OpenSound Control messages via a UDP network socket to any connected client application. It implements the TUIO protocol, which was specially designed for transmitting the state of tangible objects on a table surface. This framework includes a set of free example client projects for various programming languages, which serve as a base for the easy development of tangible-user interface applications.

The reacTIVision application compiles and runs under the follwing operating systems: Win32, MacOS X and Linux. Under Win32 it suports any camera with a proper WDM driver, such as USB, USB2, FireWire and DV cameras. Equally under MacOS X any such camera supported by QuickTime will work in reacTIVision. Under Linux, FireWire cameras are best supported, as well as a few Video4Linux USB cameras.

NEW: Support the reacTIVision project and buy T-Shirts, posters and other merchandise featuring the reacTIVision fiducial symbols in our web-shop! All designs on these products can be recognized and tracked by the actual reacTIVision software.

Application Handling

Before starting the reacTIVision application make sure you have a supported camera connected to your system. The application can and will not work at all without a camera. Under Win32 and MacOS X the application will ask to select and configure the camera upon startup. Under Linux the camera will be selected automatically. Once configured the application will show a video window with the current camera image in black&white.

Pressing T will show the binary tresholded image, pressing the N key will turn the display off, which reduces its CPU usage significantly!

Pressing the S key will return to the original source image. For convenience and debugging porposes hitting the R key saves a raw image frame, while hitting the B key will save an image in the BMP format.

The P pauses the image analysis completely, hitting ESC will quit the application. The F key toggles the diplay of FPS info in the titlebar. In order to produce some more verbose debugging output, hitting the V key will print the currently recognized symbols to the console.

Command Line Options

The reacTIVision application per default sends the TUIO messages to port 3333 on localhost (127.0.0.1)

In order to change these parameters you can invoke the application with the -h [ip-address] and -p [port-no] options.

reacTIVision needs a so called "tree file" in order to function properly. The default "all.trees" is included and loaded automatically. If you want to use you own tree file you can invoke the application with the -t [tree-file] option.

Optionally if you dont want to analyze the complete image - for example in a square or round table setup - the application can mask a part of the video image with a black region, which speeds up the segmentation algorithm. In order to apply this mask You can invoke the application with the -m [square,circle] option.

Applying the -h or -help option will print a usage message to the console.

Calibration and Distortion

Some tables, such as the reacTable are using a convex mirror in order to increase the area visible to the camera at a minimal distance. This mirror as well as a fish-eye lens unfortunately distort the image. reactIVision includes a correction algorithm, which corrects this distortion with the help of a so called "grid file". These grid files can be generated during a prior calibration process.

To calibrate reacTIVision invoke the application with the option: reacTIVision -c 9 -g [grid_file]

In order to use the this calibration invoke the application with: reacTIVision -g [grid_file]

Kamera is a digital camera io_slave for KDE which uses gphoto2 and libgpio to allow access to your cameras pictures with the URL camera:/

This package is part of the official KDE graphics module.

KDE is a powerful Open Source graphical desktop environment for Unix workstations. It combines ease of use, contemporary functionality, and outstanding graphical design with the technological superiority of the Unix operating system.