Cuestionario vinculado a una guía · Medio Nivel

Prueba de generación de imágenes con IA

Pruebe los conceptos básicos de difusión, opciones de flujo de trabajo de imágenes, limitaciones visuales, inspección del tamaño final, límites de ampliación y uso teniendo en cuenta la procedencia.

Rutas de guía relacionadasGeneración de imágenes de IA
Pregunta 1 de 8

Which learned process characterizes diffusion image models?

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  1. Which learned process characterizes diffusion image models?
    • They learn a denoising process
    • They retrieve a finished stock image for every prompt
    • They copy one training image pixel for pixel
    • They use only hand-written drawing rules
  2. A product combines image generation, editing, upscaling and postprocessing. What should a team evaluate?
    • Only the prompt field, since later stages cannot change the image
    • The complete workflow and final artifact
    • The model name without inspecting the output
    • Only the first generated preview
  3. Which details can help communicate a visual goal in a prompt?
    • A guarantee that every tiny feature will render correctly
    • The legal status of the model’s training data
    • Subject, composition, lighting, palette and needed empty space
    • The final output’s provenance after publication
  4. A diagram requires exact small labels and repeated geometry. What should the creator do?
    • Assume the prompt guarantees every label is correct
    • Judge only the overall style
    • Skip review if the resolution is high
    • Inspect the details directly and rebuild unreliable elements as editable shapes or text
  5. Why inspect an image at its intended display size?
    • A thumbnail can hide distortions or unreadable text that appear in the final layout
    • Every image becomes accurate when enlarged
    • It proves the depicted event occurred
    • A small preview always has more detail than the full image
  6. What does upscaling guarantee about depicted details?
    • It restores the original object’s physically correct structure
    • Nothing about accuracy; more pixels do not necessarily recover accurate detail
    • It converts every image into a vector
    • It verifies the source and rights of each object
  7. When should an illustration be labeled as synthetic?
    • Only when it is low resolution
    • Never, because realistic images are documentary evidence
    • When the context requires preventing it from being mistaken for documentary evidence
    • Only if the AI tool is named in the file name
  8. What should a team preserve to help reproduce or review a final generated asset?
    • Only the prompt, while deleting the delivered file
    • The model’s training dataset regardless of rights
    • A screenshot of the first preview only
    • The actual final asset and relevant generation settings