190119CodeforIkoma_Mapillary

 190119CodeforIkoma_Mapillary

瀬戸寿一 (2019年1月)「オープンなストリート画像共有サービスMapillaryとは?」、Code for Ikoma定例会、市民活動推進センターららポート、2019年1月19日

E19e33bd30954fc1846f3d64863b7846?s=128

Toshikazu SETO

January 19, 2019
Tweet

Transcript

  1. 1.

    / 0 (2 !     " 

       G C I G 9 / S O M / S 1 / )/ /
  2. 2.

    C -- 0 : 1 A B 4 C 1

    :2 4 3460 2 /362 2 1 90 630 km 2
  3. 14.

    2 0 / 1 https://mapillary.github.io/mapillary_greenhouse/global-challenge/q2-2018/ Score = (total unique KM

    contributed + (images/1000)) * (1 + (count of local participants/10))
  4. 15.

    2 0 / 1 Mapillary images are available under the

    Creative Commons Attribution-ShareAlike 4.0 (CC BY-SA 4.0)
  5. 18.

    2 0 / 1 1 0 2 5 0 1

    0 The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes doi: 10.1109/ICCV.2017.534
  6. 19.

    12/ 0 - - - - ( - ( -

    - ) https://research.mapillary.com/lsun.html
  7. 20.

    12/ 0 Mapillary Vistas Dataset  25,000 & 100 

       https://research.mapillary.com/
  8. 21.

    12/ 0 0 2 1 , •Road markings: increased from

    6 classes to 21 classes including speed limits and direction arrows, which are essential classes for building navigation and HD maps. •Driveway: a new class that we’ve introduced to help enhance data extraction for last-mile •Barriers: increased from 6 to 11 classes. Detailed refinement of the barrier classes is the first step to enhance the perception capacity for autonomous driving under different scenarios. •Signages: the billboard class is now refined to advertisement, storefront, and general information signages. This facilitates automatic and in-depth location-aware data extraction for marketing, business, and point-of-interest analysis. •Traffic light states: dynamic properties are associated with static objects. In this case, we have refined 100K traffic light annotations with different state
  9. 25.

    2 0 / 1 3/ ) ( 0 . 3

    . https://github.com/mapillary/mapillary-js
  10. 27.

    67 wl k m 3 . ( https://github.com/enricofer/go2mapillary • 0

    1 ( o Qi tpI JS • x M e V i I • 0 x 0 1 G J 0375297 G • / 9 C.1QW d fV f M y • b a r Thanks! Christopher Beddow
  11. 28.

    4 : 2 kyh g . . / . •

    f f O S o 0 2 Oe d • 2 9 2 F 0 2 F19:9 492 P 9 : • r Mvs R tMO ipl mnwI • f c Waf 8 2 2 9 .9 2 .9 / C9 Thanks! Christopher Beddow
  12. 29.

    /0 1 4 • S P A • 9 90

    0 99 ad • 2. 9 • M O Ce k f c • ek m o C j i C I . . / . Thanks! Christopher Beddow