Cuestionario vinculado a una guía · Medio Nivel

Prueba de segmentación de imágenes

Distinga las tareas de segmentación y revise las máscaras mediante reglas de anotación, métricas de superposición, comprobaciones de límites y pruebas de canalización de imagen completa.

Rutas de guía relacionadasSegmentación de imágenes
Pregunta 1 de 8

A project labels every road pixel as road. Which segmentation type is this?

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  1. A project labels every road pixel as road. Which segmentation type is this?
    • Segmentación semántica
    • Instance segmentation
    • Clasificación de imágenes
    • Object detection only
  2. A project must distinguish each car from other cars of the same category. Which task fits?
    • Semantic segmentation only
    • Instance segmentation
    • Clasificación de imágenes
    • Agrupación
  3. Why document how reviewers label uncertain boundaries?
    • Annotation rules replace testing
    • All boundaries are always objectively obvious
    • Different reviewers may draw different masks, affecting evaluation
    • Only image colors matter
  4. An image has 950 background pixels and 50 target pixels; a prediction labels everything background. What pixel accuracy results?
    • 50%, with balanced classes
    • 5%, with perfect target recall
    • 100%, with perfect segmentation
    • 95%, despite detecting none of the target
  5. Why can overlap metrics such as IoU be more informative than pixel accuracy?
    • They guarantee accurate boundaries
    • They assess overlap of predicted and reference regions
    • They ignore class balance
    • They prove the mask is safe to use
  6. A mask looks correct before export but shifts when placed back on the original image. What should the team inspect?
    • The class name alphabetically
    • The model’s training company
    • Cropping, resizing, and coordinate conversion
    • Only the overall pixel score
  7. Why inspect segmentation overlays at the scale where they will be used?
    • Boundary errors can matter differently depending on the application
    • A thumbnail always shows every boundary accurately
    • Overlay scale changes the ground truth
    • Pixel accuracy proves usability
  8. What should be preserved when transforming an image for segmentation?
    • An average color value
    • Only the compressed thumbnail
    • The user interface theme
    • Source dimensions and coordinate alignment