Overview
Vision Transformers (ViTs) inoshandisa dhizaini yetransformer inopa simba ChatGPT kumifananidzo, ichitora mufananidzo senhevedzano yezvigamba pachinzvimbo chegridi yemapikisi. Vakaratidza kuti haudi convolutions kuti uwane kucherechedzwa kwemufananidzo.
Vision Transformers ndeyekombuta-yekuona workflows inodudzira kana kugadzira midhiya yekuona yekuongorora, mashandiro, uye kugadzira.
Deep Dive
Kwemakore, convolutional neural network (CNNs) yaitonga komputa kuona nekutarisa mafirita madiki pamufananidzo. Bepa ra2020 'Mufananidzo Wakakodzera 16x16 Mazwi' kubva Google rakapikisa izvi nekucheka chifananidzo kuita mapechi akagadzika, kazhinji 16x16 pixels, kupepeta rimwe nerimwe kuita vector, uye kudyisa zvakatevedzana kuita mushanduri wakajairwa. Chigamba chimwe nechimwe chinova 'chiratidzo,' sezwi riri mumutsara. Iyo modhi inozoshandisa kuzvidzora kuitira kuti chigamba chega chega chigone kuenderana kune chimwe chigamba, kutora hukama hurefu-refu diki sefa isingaone munhanho imwe. Kubata: ViTs vane nzara-data nekuti vanoshaya yakavakirwa-mukati fungidziro dzeCNNs. Vakadzidziswa pamaseti akakura seJFT-300M, vaifananidza kana kurova maCNN akanakisa, vachigadzirazve tsvakiridzo yechiono chazvino.
Technical Insight
A ViT inotsemura chifananidzo kuita chigamba chisina kupindirana, mutsara mapurojekiti chimwe nechimwe mukumisikidza, uye inowedzera maencodings kuitira kuti modhi izive pakagara chigamba chega chega mumufananidzo wekutanga. Yakakosha inodzidzwa 'class token' inofanogadzirirwa; kumiririra kwayo kwekupedzisira kunofambisa kupatsanurwa. Akaturikidzana ega ega ega matinji rega rega rega riyere ruzivo kubva kune mamwe ese, ichipa yepasi rose inogashira munda kubva kune imwe layer. Nekuti kutarisisa kunoyera quadratically nenhamba yezvigamba, mifananidzo yakakwira-resolution inodhura, ndosaka ukuru hwechigamba uye kutarisisa kwakasiyana kunokosha.
Mastering Vision Transformers
Vision Transformers (ViTs) inoshandisa dhizaini yetransformer inopa simba ChatGPT kumifananidzo, ichitora mufananidzo senhevedzano yezvigamba pachinzvimbo chegridi yemapikisi. Vakaratidza kuti haudi convolutions kuti uwane kucherechedzwa kwemufananidzo. Vision Transformers ndeyekombuta-yekuona workflows inodudzira kana kugadzira midhiya yekuona yekuongorora, mashandiro, uye kugadzira. Kuti uvake kunzwisisa kwakadzama, bata Vision Transformers semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodiwa, kujekesa fungidziro, uye patsanura zvinogona kuitwa nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Vision Transformers kuenzanisa kurongeka nezvinoitika zvekushanda semhando yedata, kusiyana kwemwenje, uye kuenderana kwemazita. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Panguva imwecheteyo, kodzero dzeMufananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana hunhu husina kujeka. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Google's image classification and search ranking systems dzakatora transformer backbones mushure mekunge ViT yaratidza kukwikwidzana neCNNs.
CLIP uye mamwe emifananidzo-mameseji mamodheru anoshandisa ViT encode mifananidzo kuitira kuti mafoto nemifananidzo zvienderane munzvimbo yakagovaniswa.
Tsvagiridzo yekufungidzira yekurapa uchishandisa ViTs kuona mapatani mukati mese scansheni kwete chete maumbirwo enzvimbo
Kuzvityaira uye marobhoti ekuona akaturikidzana anosanganisa ViT-maitiro kutarisisa kwekunzwisisa kwechiitiko munzvimbo yakazara yekuona.
Maitiro Ekuita
Vision Transformers mukuita
Google's image classification and search ranking systems zvakatora matransformer backbones mushure mekunge ViT yaratidza kukwikwidzana neCNNs.
Google's image classification and search ranking systems dzakatora matransformer backbones mushure mekunge ViT yaratidza kukwikwidzana neCNNs Teams inowanzowana mibairo iri nani painotsanangura mabhindauko emhando kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuronda zvese zvakawanikwa mukubudirira uye kukanganisa mutengo nekufamba kwenguva.
Vision Transformers mukuita
CLIP uye mamwe emifananidzo-mameseji mamodhi anoshandisa ViT kukodha mifananidzo kuitira kuti mapikicha nemifananidzo zvienderane munzvimbo yakagovaniswa.
CLIP uye mamwe emifananidzo-zvinyorwa modhi anoshandisa ViT encode mifananidzo kuitira kuti mapikicha nemifananidzo zvienderane munzvimbo yakagovaniswa Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Vision Transformers mukuita
Tsvagiridzo yekufungidzira yekurapa uchishandisa ViTs kuona mapatani mukati mese scansheni kwete chete maumbirwo enzvimbo.
Tsvagiridzo yekufungidzira yezvokurapa uchishandisa maViTs kuona mapatani pane yese scan kwete chete maumbirwo enzvimbo Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura hunhu hwepamberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Vision Transformers mukuita
Kuzvityaira uye marobhoti ekuona akaturikidzana anosanganisa ViT-maitiro kutarisisa kwekunzwisisa kwechiitiko munzvimbo yakazara yekuona.
Kuzvityaira uye marobhoti ekuona akaturikidzana anosanganisa ViT-maitiro kutarisisa kwekunzwisisa kwechiitiko munzvimbo yakazara yekuona Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye kukanganisa mutengo nekufamba kwenguva.
Njodzi & Guardrails
Kodzero dzemifananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana provenance isina kujeka.
Kuita kwemuenzaniso kunogona kusiyanisa kupenya, huwandu hwevanhu, uye nharaunda.
Manyepo enhema anogona kusacherechedzwa kunze kwekunge zvikumbaridzo zvekuvimba zvikatariswa.
Implementation Roadmap
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa.
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.