The OGN is A Community Project > 자유게시판

Welcome to the OGN venture! The objective of the Open Glider Network is to create and maintain a unified monitoring platform for gliders, drones and other aircraft. The tracking knowledge is freely out there to anyone so long as they follow OGN data usage guidelines. Today FLARM is mainly utilized in gliders, however different small aircraft (planes, helicopters, deltas, para-gliders and even drones) are increasingly typically geared up with it, especially if working within the areas intensively utilized by gliders, such because the Alps. Contrary to FLARM, OGN proposes an open transmission protocol and has an ambition to affect (or better) impose a normal. The OGN is a community challenge. It relies on software program, hardware, receivers and different contributions from people and iTagPro bluetooth tracker the open supply community. APRS linux based mostly servers that obtain and ahead information. Data includes system location information, status of receivers and the standing of the OGN APRS community. A system database (aircraft).

Register your aircraft/drone with tracking device within the OGN system database right here in case you wish to affect the best way how it’s going to be seen within the system (anonymous vs recognized). OGN ground receivers, primarily based at airfields, gliding clubs, iTagPro bluetooth tracker summits of mountains or private homes of our community members. They pay attention and decode the placement knowledge of aircraft in their vicinity and ship place experiences via community to the APRS servers. Software for Linux that may be installed on a Pc or small mini-board computers (such as the Raspberry Pi, Cubieboard2, Odroid U3, etc.). It drives a USB DVB-T radio receiver and listens for, decodes, sends the place reviews and participates within the OGN community. Websites and applications that may use and display the information. The OGN is rising and evolving. It is a work in progress and there remains to be much work to be accomplished. Funding, installing and running a receiver at your gliding club, at your home or wherever the OGN has a ‘hole’ in its coverage. The price of receiver is probably less than two aerotows for many glider pilots. Contributing your time to replace, expand and maintain this Wiki, or improve the applications that use/ show/ share the OGN knowledge or write your own application for the community. OGN should evolve! You may be a part of us by subscribing to our discussion group.

Object detection is broadly used in robotic navigation, intelligent video surveillance, industrial inspection, aerospace and lots of different fields. It is an important branch of picture processing and pc vision disciplines, and can be the core a part of clever surveillance systems. At the same time, goal detection can also be a fundamental algorithm in the sector of pan-identification, which plays an important position in subsequent duties such as face recognition, gait recognition, crowd counting, and instance segmentation. After the first detection module performs target detection processing on the video frame to obtain the N detection targets within the video body and the first coordinate data of each detection target, the above methodology It also contains: displaying the above N detection targets on a screen. The first coordinate info corresponding to the i-th detection goal; acquiring the above-talked about video body; positioning within the above-mentioned video body based on the primary coordinate data corresponding to the above-mentioned i-th detection goal, acquiring a partial picture of the above-talked about video frame, and determining the above-talked about partial image is the i-th picture above.

The expanded first coordinate information corresponding to the i-th detection target; the above-mentioned first coordinate information corresponding to the i-th detection goal is used for positioning within the above-talked about video body, including: in response to the expanded first coordinate data corresponding to the i-th detection goal The coordinate data locates in the above video frame. Performing object detection processing, best bluetooth tracker if the i-th picture includes the i-th detection object, iTagPro features acquiring position data of the i-th detection object within the i-th image to acquire the second coordinate information. The second detection module performs goal detection processing on the jth picture to find out the second coordinate info of the jth detected target, the place j is a optimistic integer not larger than N and not equal to i. Target detection processing, acquiring a number of faces in the above video body, and first coordinate info of every face; randomly acquiring target faces from the above multiple faces, and intercepting partial images of the above video body in keeping with the above first coordinate info ; performing target detection processing on the partial picture by way of the second detection module to acquire second coordinate information of the target face; displaying the target face based on the second coordinate data.