lingbot-map: A feed-forward 3D foundation model for reconstructing scenes from streaming data

lingbot-map

本周 GitHub 最热门开源项目深度解析 项目地址: Robbyant/lingbot-map 生成时间: 2026-04-20 14:31:37

项目概览

Robbyant/lingbot-map 是本周 GitHub 上最受关注的开源项目之一,在短时间内积累了大量关注。

基本信息

指标数据
作者@Robbyant
编程语言Python
Star 数2754 ⭐
Fork 数214
创建时间2026-04-15
最后更新2026-04-20

项目简介

A feed-forward 3D foundation model for reconstructing scenes from streaming data

Python 是一门简洁优雅的编程语言,广泛应用于数据科学、人工智能、Web 开发等领域。

核心特性

根据项目 README 分析,lingbot-map 的主要特点包括:

  • 高关注度:2754 个 Star,说明开发者社区对此项目高度认可
  • 活跃开发:214 个 Fork,社区参与度高
  • 快速成长:自 2026-04-15 创建以来持续获得关注
  • 开源免费:完全开源,可自由使用和二次开发

技术架构

lingbot-map 基于 Python 技术栈构建:

  1. 编程语言:Python
  2. 项目规模:2754 个 Star,获得广泛认可
  3. 社区活跃度:214 个 Fork,开发者积极参与

README 原文摘要

<<R<[[[[[[h#L##`ccdho/d!!!!!!/t#i#*`ooi<1bdi[[[[[[dt#n1`nnvi>bivPPPHMLipg***I.`ddmLyvaDruoivs🗺BGHSnbaaagia>apFogdc>:oeitQsCalnnle]jgee/togautrscaisgtir(eiln/M-mhtiaehrcgrBg]hcnSsgeMe-eclaetncoTn(ttgceieatE-kltai==te=ht]Fo]ttprfoaetv""-a"tp(ap(hiffSteacaMmctshcehuLhci-tictesaep:te]tbiactaoo-enspns/t](t.nsCihrnnnte:t:p(hpcgoeetdleteishtsoBfnn-alirsGr/m:tt:mootcAin"/e"igtp//tceyreng>to>m./ps/u-uxtngbemgsis:isMstSvboae.hm:meaetRiotstsiggrpdTrert-erhe.i.-!reco-mriilsimsaoaaonma.cedhmghtWnnmnmapplsig.ite:sisepnCd.e.sea'fntngosilshlcvogrtp"n.odhidheru*ytisiesmmIc*twes.el.ebenthix/tildinurfiodtsaodsoti*eonttt/s./sl*rn=hTaib.ib/t:e*3=rtcaioaan*."ai/dodsaAc:11ncgsgsre00s/1esteefc*S0fv?/ta/teh*u-%o1lPatLsei:py"r?artii/dte>mlboiccf-eAreaejceefcirblevn3otfoe=cv1s9ruerflPt1?eewreo=a-?l-0aadprPpWlaA9rl-eaeeabp5dlfrSprbbea-yofte&selca3rorrmil=hfDuwre&et=%e2namamse%F-cfirames-F0--ofdnisab0%24uicnsgl%9.eneaegaeu9F0cdsrg=eF%-9aco3eP)%Ag-tchnD=D]A4rbioiaF(4%e6ootdRr&h%9e8nreieXct96nddcvciot7%)-miteovlp%2]aonurn&os20(8darsscr:0MLbeteeto=/MoIalerlr/odC9wbuoetdeE7fgiecrdeelNeortnt=&cl&S5rohcirlh&mE0uhoeonme.5snpmndgoestatdaa<&olssxbrigr/l=osatenekhoagag)agds1gdygem,>oo.e=iKc=br=MndVoaeoHogemrabudncpxcbge3saairyglDecrvoaiShe)bnncrged]atgoee(t.Fpcoathrcaeomtoteoc&nettamecstebpd/&otrnoselclritt:riooucih/)nlrco/]go=tcnea(brpiu,xrlo=uoeixitornsesin-rp!,ntvgmalai.bane🏗abnoopg)nlgrt)e]🌍dig-)(ns/m]hlgtaa(torbphtnses_tpgta/pts-am2ap:rbi6ps/aln0e:neg4rwg../weia1phwnn4du.dfd1fgmre4)goiri1idfet)netneglcrfsceaacotcoraieprtv.eeec.c~oct2o/ni0protmnFiboPmbdwSiyeizaltoanshnttiiRn5olo1niba8-nb×bgys3abai7sonn8ettgd-/lrmleeaaisppnsop)gtlrbruooetataic-mohmineanspg.)vferramleownogrksetqhureonucgehsaenxccheoerdicnognt1e0x,t0,00pofsrea-mreesf.erencewindow,andtrajectorymemory.

2. Install PyTorch (CUDA 12.8)

`

##l----#1234#l***##i#....#inn*****g访g22222bAb00000ooO::22222tf[RItp66666-PeGEs-e[2-----myeiAsPmnG000000aAtdtDuRaCi244444pIh-HMeplt6-----ofuEsaH-11111nobwu088777rIb4*****ws]-*****as(2:::::Wr]uGh0ed(eiGtuuuuubh使tit1ppppp3tHtp4dddddDtuHs:aaaaapbu:3tttttfsb/1eeeeeo:/:u/Ag3rrn/Pi7eedgIt*aaaihddttummihbeeou.nbc.omcmoo*/dmRe/olR2bo7bfb5yob4arynatrn/etSlc/tiolannirgsnbtgorbtuo-ctmt-aimpna)gp*)scenesfromstream2i0n2g6-d0a4t-a15