Kedis ku xidhan hagaha · Dhexdhexaad Heerka
Waa maxay sababta Sawir-dhaliyeyaasha AI ay u helaan Kedis Qaldan Gacmaha
Tijaabooyin sababta ay gacmuhu uga hortagaan moodooyinka faafinta, oo ay ku jiraan xallinta daahsoon, kala duwanaanshaha iyo qoraallada kooban, iyo sida ControlNet iyo rinjiyeynta u hagaajiyaan iyaga.
Su'aal 1 ee 8
According to the guide, what does a diffusion model mainly learn from image-caption pairs?
Horudhac su'aal kasta8 su'aalo
Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.
- According to the guide, what does a diffusion model mainly learn from image-caption pairs?
- Local visual patterns such as texture and lighting
- Explicit anatomical rules about fingers
- A built-in 3D skeleton of the human body
- A counting procedure for body parts
- How does latent compression in Stable Diffusion make hands harder to draw?
- It removes color information
- It deletes hands from the training images
- It shrinks the image by a factor of eight in each dimension, leaving a hand only a few latent cells
- It converts the image into text
- Why do captions give models little help with hands?
- Captions are written in an obscure language
- Captions rarely mention hands or describe their pose
- Captions are removed before training
- Captions describe only hands and nothing else
- Which Midjourney version does the guide say was widely noted for better hands in 2023?
- Version 1
- Version 2
- Version 3
- Version 5
- What does an ADetailer-style detect-and-repaint workflow do?
- Finds hand regions, regenerates each one at higher effective resolution through inpainting, and blends it back
- Adds a watermark over the hands
- Replaces hands with gloves automatically
- Deletes the hands from the image
- Why do negative prompts like 'extra fingers' usually help little?
- They are too long for the encoder
- They only work on text rendering
- They switch off classifier-free guidance
- Few training captions described those errors, so the model has only a weak concept to steer away from
- What does a ControlNet OpenPose input provide when fixing hands?
- A color palette
- A new random seed
- A skeleton with hand keypoints that supplies the geometry
- A longer caption
- A suspected fake image has anatomically perfect hands. What should a fact-checker conclude?
- The image is definitely a real photograph
- Correct hands prove nothing either way, because newer generators often draw them correctly
- The image must come from Midjourney
- The image must carry a watermark