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On April 20, 2012, Google announced that they were deprecating Picasa for Linux and will no longer maintain it for Linux. [13] To use latest version of Picasa on Linux, Linux users can use Wine and install Picasa for Windows. [14] Linux users can use other programs to upload to Picasa Web Albums, including Shotwell and Digikam. [15]
Bob Amstadt, the initial project leader, and Eric Youngdale started the Wine project in 1993 as a way to run Windows applications on Linux.It was inspired by two Sun Microsystems products, Wabi for the Solaris operating system, and the Public Windows Interface, [10] which was an attempt to get the Windows API fully reimplemented in the public domain as an ISO standard but rejected due to ...
Starting with version 2.0, digiKam has introduced face recognition allowing you to automatically identify photos of certain people and tag them. DigiKam's photo manager was the first free project to feature similar functionality, with face recognition previously implemented only in proprietary products such as Google Picasa, Apple's Photos, and Windows Live Photo Gallery.
Face detection is gaining the interest of marketers. A webcam can be integrated into a television and detect any face that walks by. The system then calculates the race, gender, and age range of the face. Once the information is collected, a series of advertisements can be played that is specific toward the detected race/gender/age.
Facial recognition software at a US airport Automatic ticket gate with face recognition system in Osaka Metro Morinomiya Station. A facial recognition system [1] is a technology potentially capable of matching a human face from a digital image or a video frame against a database of faces.
Snap is a software packaging and deployment system developed by Canonical for operating systems that use the Linux kernel and the systemd init system. The packages, called snaps, and the tool for using them, snapd, work across a range of Linux distributions [3] and allow upstream software developers to distribute their applications directly to users.
This comparison of optical character recognition software includes: OCR engines, that do the actual character identification; Layout analysis software, that divide scanned documents into zones suitable for OCR; Graphical interfaces to one or more OCR engines
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