Understanding mean Average Precision for Object Detection (with Python Code)

Shubham Chauhan March 17, 2021

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https://shubhamchauhan125.medium.com/map-mean-average-precision-for-object-detection-with-simple-python-demonstration-dcc7b3850a07

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5 Comments

  1. Karuna Sree13 February 2021 at 19:29

    Can you please explain the formula of FN in the above program ..

    Thanks,
    Karuna Sree

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  2. Karuna Sree13 February 2021 at 19:32

    Thanks for the blog ... I couldn't understand the formula FN = len(eval_table['TP/FP']== 'TP') .... can you please help me ..

    Thanks,
    Karuna Sree

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    Replies
    1. Shubham Chauhan14 February 2021 at 12:50

      It is mentioned above that if IOU>0.5 then it will be true positive and also if IOU>0.5 but object is miss classified then it will be flase negative(FN). So FN is the number of count for IOU>0.5 which is TP.

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    2. Karuna Sree4 March 2021 at 07:52

      Thank you .. But how are you getting the misclassified ... Not all true positives are not FN right ? Are you comparing that classification difference here ?

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    3. Shubham Chauhan4 March 2021 at 21:19

      Yes, you are right that all TP are not FN but finding FN will complicate the code. So, just for simplicity we are considering them equal to TP. You can make it zero or you can replace some TP with FN in the data for your calculation and understanding. For better understanding I will mention this assumption in the article.

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