Maswali ya Uchoraji na Upakaji rangi

Majibu na maelezo huonekana unapojibu maswali.

1. Uchoraji hufanya nini?
   • Huzalisha upya eneo lililofunikwa ndani ya picha
   • Hupanua picha zaidi ya mipaka yake
   • Hubadilisha maandishi kuwa hotuba
   • Inasisitiza faili za picha
2. Upakaji rangi nje hufanya nini?
   • Huondoa rangi kutoka kwa picha
   • Huzalisha maudhui mapya zaidi ya kingo asili
   • Hutambua nyuso
   • Hunoa pikseli za ukungu
3. How does RePaint use the known region during diffusion-based inpainting?
   • It permanently freezes every unmasked pixel with no resampling
   • It removes the mask before denoising
   • It repeatedly resamples and conditions generation on known pixels during reverse diffusion
   • It trains a new model from scratch for each image
4. What architecture does LaMa introduce for large-mask image inpainting?
   • A language-only transformer
   • A nearest-neighbor search over captions
   • A fixed-color fill with no learned model
   • Fast Fourier Convolutions with a receptive field that supports image-wide context
5. Ni nini huongoza maudhui ambayo yanaonekana katika eneo lililofunikwa kwa uso?
   • Kidokezo cha maandishi na pikseli zinazozunguka
   • Jina la faili pekee
   • Saa ya kifaa
   • Kiwango cha mgandamizo wa picha
6. Kwa nini uchoraji wa nje ni muhimu kwa kuunda upya?
   • Inafuta mada
   • Inaweza kubadilisha uwiano wa picha kwa kuongeza mandhari
   • Inasimba picha kwa njia fiche
   • Inapunguza azimio
7. Besides Fourier Convolutions, what two components does the LaMa paper identify in its large-mask inpainting method?
   • A speech decoder and image captioner
   • A fixed image palette and nearest-neighbor lookup
   • A high receptive-field perceptual loss and large training masks
   • A video tracker and optical-flow classifier
8. What does a mask specify in an inpainting task?
   • The image’s camera model
   • The order of training examples
   • The output file’s copyright status
   • Which image region is to be modified or synthesized