Auto Image Segmentation using YOLO11 and SAM2

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  • Опубликовано: 2 фев 2025

Комментарии • 14

  • @Ibn_Sulaimaan
    @Ibn_Sulaimaan Месяц назад

    Very clear explanation. Thanks for the good work.

  • @stanley4869
    @stanley4869 Месяц назад

    can YOLO do delineation(segmentation) alone?

  • @sozno4222
    @sozno4222 Месяц назад

    Is there a reason you’re not just using segmentation from YOLO 11? There’s a version of the model for that. Are you doing it this way because you have the classification dataset but not the segmentation dataset?

  • @user-rp9iis1en6h
    @user-rp9iis1en6h 3 дня назад

    You are a very good teacher.
    I have one question, how can we create a new image of the segmented part only ?

  • @biz8015
    @biz8015 3 месяца назад +1

    Is it possible to use this technique to detect the defects in industrial products? like defects in bike engine parts ?

    • @aireferat
      @aireferat 2 месяца назад

      yes working on similar now for car manufacturing'

  • @kevinkibebe5397
    @kevinkibebe5397 21 день назад

    How to create segmentations on large image datasets

  • @arpitpathak7276
    @arpitpathak7276 3 месяца назад

    Hi sir can you provide the code so that when we sam2 segment the images also show the class label on above the bounding box

  • @deveshsharma4361
    @deveshsharma4361 3 месяца назад +1

    Sir please make a video on helmet detection using yolo

    • @BingeWatcher247
      @BingeWatcher247 3 месяца назад +1

      Kindly Make this Video

    • @aireferat
      @aireferat 2 месяца назад

      that is already in the universe models PPE tracking

  • @afinaapayeva3421
    @afinaapayeva3421 3 месяца назад

    I don't understand, why would we use YOLO11, if we can directly fine tune SAM2 for image segmentation

    • @aryan.2763
      @aryan.2763 3 месяца назад

      Yes correct
      .. even SAM 2 has the feature to do automask as well or using pointwise, bounding box promt , we can perform it .
      Even using , Florence model also you can perform.