Uhlolojikelele
I-SPADE (I-Spatially-Adaptive Normalization) iphendula isakhiwo esinelebula esilula, njengemephu yencwadi yombala yengane ethi 'isibhakabhaka lapha, utshani laphaya, isihlahla lapha', ibe isithombe esithatha izithombe. Kubalulekile ngoba kunikeza amaciko nabaklami ukulawula okunembayo kwendawo phezu kwalokho okuvela lapho esigcawini esikhiqiziwe.
I-SPADE Semantic Image Synthesis ingeyokugeleza komsebenzi okubonwa ngekhompyutha okuhumusha noma okukhiqiza imidiya ebonakalayo ukuze ihlaziywe, isebenze, futhi isungule.
I-Deep Dive
I-SPADE, eyethulwa abacwaningi be-NVIDIA uPark, Liu, Wang, noZhu ngo-2019 (ngohlelo lokusebenza lwedemo i-GauGAN), ikhiqiza izithombe ezingokoqobo kusuka kumamephu wesegimenti ye-semantic, lapho iphikseli ngayinye inemibala ngesigaba sayo (amanzi, umgwaqo, isakhiwo, isibhakabhaka). Amajeneretha angaphambilini adlise imephu yokuhlukaniswa ngezendlalelo zokujwayela ezazivame 'ukugeza' ulwazi lwesakhiwo, zikhiqize imiphumela engacacile noma engahambisani. Ukuqonda kwe-SPADE ukuthi isakhiwo kufanele siqhubeke siqondisa inethiwekhi kuzo zonke izigaba zokukhiqiza, hhayi nje kokokufaka. Ilungisa ukwenza kusebenze okujwayelekile kusetshenziswa amapharamitha afundwe ngokuqondile kumephu yokuhlukanisa endaweni ngayinye yendawo. Umphumela uba ukwakheka okucijile, okulawulekayo lapho ungapenda khona imephu yelebula futhi ubuke indawo ekholekayo, egcwele ukuboniswa kanye nokuthungwa, okwenziwe.
I-Technical Insight
Iqoqo elijwayelekile noma izikali zesibonelo zokujwayela kanye nokwenza kusebenze ngamanani afundiwe angawodwa esiteshini, kulahla imininingwane yendawo. I-SPADE esikhundleni salokho ibikezela isikali (i-gamma) kanye no-shift (i-beta) njengezithako ezigcwele zendawo ezihlanganiswe ngezendlalelo ezincane ezisetshenziswa kumaski wesegimenti. Lawa mapharamitha ahlukahlukayo ngendawo ajovwa ngokulungiswa okuningi kuyo yonke ijeneretha, ngakho ukwakheka kwe-semantic kuyaqhubeka nokubeka obala okukhiphayo futhi kuvimbele ulwazi ukuthi lungasuswa.
I-Mastering SPADE Semantic Image Synthesis
I-SPADE (I-Spatially-Adaptive Normalization) iphendula isakhiwo esinelebula esilula, njengemephu yencwadi yombala yengane ethi 'isibhakabhaka lapha, utshani laphaya, isihlahla lapha', ibe isithombe esithatha izithombe. Kubalulekile ngoba kunikeza amaciko nabaklami ukulawula okunembayo kwendawo phezu kwalokho okuvela lapho esigcawini esikhiqiziwe. I-SPADE Semantic Image Synthesis ingeyokugeleza komsebenzi okubonwa ngekhompyutha okuhumusha noma okukhiqiza imidiya ebonakalayo ukuze ihlaziywe, isebenze, futhi isungule. Ukuze wakhe ukuqonda okujulile, phatha i-SPADE Semantic Image Synthesis njengemodeli yokusebenza, hhayi isici esisodwa: chaza imiphumela efiselekayo, ucacise ukucabanga, futhi uhlukanise lokho uhlelo olungakwenza ngokwethembeka kulokho okusadinga ukwahlulela kochwepheshe.
Empeleni, amaqembu aqinile asebenzisa ukunemba kwebhalansi ye-SPADE Semantic Image Synthesis namaqiniso okusebenza njengekhwalithi yedatha, ukuhluka kokukhanya, nokuvumelana kwamalebula. Babhala imibandela yempumelelo ecacile, ukuhlola okuqhathaniswa nedatha engokoqobo nokugeleza komsebenzi, futhi baphindaphinde ngokusekelwe kumaphethini okuhluleka aqashiwe esikhundleni sokuwina kwebhentshimakhi yesikhathi esisodwa. Yilapho ukuqonda kwethiyori kuguquka kube amandla ahlala njalo kuwo wonke umkhiqizo, inqubomgomo, kanye nokusebenza.
I-Visual AI ingakwazi ukuhlola, ukutholwa, nokumaka imisebenzi esikalini. Ngesikhathi esifanayo, amalungelo ezithombe kanye nemvume kungaba ubungozi bomthetho uma ukutholakala kungacacile. Indlela eqine kakhulu iwukuhlanganisa isivinini sokuhlola nesiyalo sokuphatha: qhuba abashayeli bezindiza, bamba ubufakazi, ushicilele amalogi ezinqumo, futhi ubuyekeze izivikelo ngokuqhubekayo njengoba imodeli yokuziphatha, okulindelwe ngabasebenzisi, kanye nezimfuneko zokulawula zishintsha.
I-Strategic Impact
I-Visual AI ingakwazi ukuhlola, ukutholwa, nokumaka imisebenzi esikalini.
I-Visual AI ingakwazi ukuhlola, ukutholwa, nokumaka imisebenzi esikalini. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Amathimba aqanjiwe angakwazi ukulinganisa imiqondo ngokushesha ngezibuyekezo ezimbalwa ezenziwa mathupha.
Amathimba aqanjiwe angakwazi ukulinganisa imiqondo ngokushesha ngezibuyekezo ezimbalwa ezenziwa mathupha. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Imisebenzi ingasebenzisa amasiginali wesithombe nawevidiyo obekunzima ukuwenza ngaphambilini.
Imisebenzi ingasebenzisa amasiginali wesithombe nawevidiyo obekunzima ukuwenza ngaphambilini. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Ukuqaliswa Komhlaba Wangempela
Uhlelo lokusebenza lwe-NVIDIA lwe-GauGAN/Canvas, oluvumela abasebenzisi ukuthi bapende amamephu ahlukanisayo abe yizindawo ezinezithombe
Umcabango wezakhiwo nezinga legeyimu, lapho abaklami bedweba izindawo futhi bathole ukubuka kuqala kwesigcawu
Ikhiqiza izithombe zokuqeqeshwa zokwenziwa ezihlukene ezinamalebula ephikseli aziwayo okuthuthukiswa kwemodeli yokuhlukanisa
Amathuluzi okuhlela izithombe avumela abasebenzisi ukuthi babhale kabusha izifunda (baguqule utshani bube amanzi) futhi bahlanganise leyo ndawo ngendlela engokoqobo.
Amaphethini Okusebenzisa
I-SPADE Semantic Image Synthesis in practice
Uhlelo lokusebenza lwe-NVIDIA lwe-GauGAN/Canvas, oluvumela abasebenzisi ukuthi bapende amamephu ahlukanisayo ashintshashintsha abe yizindawo ezithatha izithombe.
Uhlelo lokusebenza lwe-NVIDIA lwe-GauGAN/Canvas, oluvumela abasebenzisi ukuthi bapende amamephu ahlukanisiwe amabi aba izindawo ezibonisa izithombe Amaqembu ngokuvamile athola imiphumela engcono lapho echaza izinga eliphezulu ngaphambili, agcine indlela yokukhuphuka yomuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-SPADE Semantic Image Synthesis in practice
Umqondo wezakhiwo kanye nezinga legeyimu, lapho abaklami bedweba izindawo futhi bathole ukubuka kuqala kwesigcawu esisheshayo.
Ukucabanga kwezakhiwo nezinga legeyimu, lapho abaklami bedweba izindawo futhi bathole ukubuka kuqala kwesigcawu esisheshayo Amaqembu ngokuvamile athola imiphumela engcono uma echaza izinga eliphezulu ngaphambili, egcina indlela yokukhuphuka yabantu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-SPADE Semantic Image Synthesis in practice
Ikhiqiza izithombe zokuqeqeshwa zokwenziwa ezihlukene ezinamalebula ephikseli aziwayo okuthuthukiswa kwemodeli yokuhlukanisa.
Ukukhiqiza izithombe zokuqeqeshwa zokwenziwa ezihlukene ezinamalebula ephikseli aziwayo okuthuthukisa imodeli yezigaba Amathimba ngokuvamile athola imiphumela engcono uma echaza izinga eliphezulu ngaphambili, egcina indlela yokukhuphuka yabantu yamakesi asemaphethelweni, futhi elandelela kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-SPADE Semantic Image Synthesis in practice
Amathuluzi okuhlela izithombe avumela abasebenzisi ukuthi balebule kabusha izifunda (baguqule utshani bube amanzi) futhi bahlanganise kabusha leyo ndawo ngendlela engokoqobo.
Amathuluzi okuhlela izithombe avumela abasebenzisi ukuthi balebule kabusha izifunda (baguqule utshani bube amanzi) futhi bahlanganise kabusha leyo ndawo ngendlela engokoqobo Amaqembu ngokuvamile athola imiphumela engcono uma echaza izinga eliphezulu ngaphambili, egcina indlela yokukhuphuka yabantu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
Izingozi & Guardrails
Amalungelo ezithombe kanye nemvume kungaba ubungozi bezomthetho uma ukuvela kungacacile.
Ukusebenza kwemodeli kungahluka kukho konke ukukhanya, izibalo zabantu, kanye nezindawo.
Okuhle okungelona iqiniso kungase kungabonakali ngaphandle uma izinga lokuzethemba liqashelwa.
Ukuqalisa Umhlahlandlela
Chaza indlela yokwamukela yokunemba, ukukhumbula, nezindleko zamaphutha.
Chaza indlela yokwamukela yokunemba, ukukhumbula, nezindleko zamaphutha. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Hlola ngedatha efana nezimo zangempela zokukhiqiza.
Hlola ngedatha efana nezimo zangempela zokukhiqiza. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Engeza isibuyekezo somuntu ukuze uthole ukuzethemba okuphansi noma izibikezelo zomthelela omkhulu.
Engeza isibuyekezo somuntu ukuze uthole ukuzethemba okuphansi noma izibikezelo zomthelela omkhulu. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Landelela ukukhukhuleka kwemodeli bese uqinisekisa kabusha ngemva kwezinguquko zekhamera noma zesethi yedatha.
Landelela ukukhukhuleka kwemodeli bese uqinisekisa kabusha ngemva kwezinguquko zekhamera noma zesethi yedatha. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.