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Bee or Wasp

Bee or Wasp

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数据结构 ? 558.83M

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Hand-curated, close-up photos of bees, wasps, and other insects. The challenge is primarily to distinguish bees from wasps.

    Excerpt from labels.csv :

    id,path,is_bee,is_wasp,is_otherinsect,is_other,photo_quality,is_validation,is_final_validation
    1,bee110007154554_026417cfd0_n.jpg,1,0,0,0,1,0,0
    2,bee110024864894_6dc54d4b34_n.jpg,1,0,0,0,1,0,1
    3,bee110092043833_7306dfd1f0_n.jpg,1,0,0,0,1,1,0
    6842,wasp2I00101.jpg,0,1,0,0,0,0,0
    6843,wasp2I00102.jpg,0,1,0,0,0,0,0
    6844,wasp2I00103.jpg,0,1,0,0,0,1,0
    

    Dataset totals

    we have:
     bees..........: 3183
     wasps.........: 4943
     other insects.: 2453
     other.........: 845
    
    in that, there is:
     training photos : 7942
     hyperparameter tuning (1st level validation) photos : 1719
     final validation (brag about your result with these) photos : 1763
    
    In the final validation, there is 504 bees and 753 wasps, meaning that the resolution of the result is 0.08%
    

    Labels:

    in labels.csv :

    • id - ordinal - unique index
    • path - string - relative path to the photo, including extension
    • is_bee - nominal - 1 if there is a bee in the photo
    • is_wasp - nominal - 1 if there is a wasp in the photo
    • is_otherinsect - nominal - 1 if there is other insect prominently in the centre of the photo, but it is not a wasp and not a bee. It might be a fly, but there are other things there too, like beetles
    • is_other - random photos not containing any insects
    • photo_quality - 1 for photos where I have very high confidence that it is bee, wasp, or other. 0 for photos of generally low quality or where I am not very confident that it is what it says it is. You can use this to initially reduce the size of the training set
    • is_validation - you can use this for your training validation, or you can combine these with the training data and split your training/validation differently
    • is_final_validation - do NOT use these photos for training - use them to compute your final score. This will enable comparing results by different kagglers. Optionally, if you want to deploy an app to actually serve the model, you can then use these for final training too.

    Data Collection

    This image dataset collates and refines upon several sources:

    The photos have been hand-curated by our expert biologist, Callum Robertson https://www.linkedin.com/in/callum-robertson-358014109/

    Collator and Kaggle competitor: George Rey

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