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mAP mean average precision for 4 object per image . Can you explain it?


How to predict on part of image after training on other part of image?Can we train a neural network to tell if an object is present or not in an Image?Are there pretrained models on the ImageNet Bounding Boxes dataset?Space between an object and the ground truth bounding boxTraining of Region Proposal Network (RPN)What does the co-ordinate output in the yolo algorithm represent?Bounding Boxes in YOLO ModelTraining detector without bounding box dataExtracting metrics from multiple classes of clustered objectsUsing a discriminator to distinguish ground truth and predicted boxes for FRCNN













0












$begingroup$


I need a little help.
I have 4 ground-truth object on image.
I have 3 prediction object.



I understed IoU. But I don't understed how to compute mAP for more bounding boxes.










share|improve this question









$endgroup$
















    0












    $begingroup$


    I need a little help.
    I have 4 ground-truth object on image.
    I have 3 prediction object.



    I understed IoU. But I don't understed how to compute mAP for more bounding boxes.










    share|improve this question









    $endgroup$














      0












      0








      0





      $begingroup$


      I need a little help.
      I have 4 ground-truth object on image.
      I have 3 prediction object.



      I understed IoU. But I don't understed how to compute mAP for more bounding boxes.










      share|improve this question









      $endgroup$




      I need a little help.
      I have 4 ground-truth object on image.
      I have 3 prediction object.



      I understed IoU. But I don't understed how to compute mAP for more bounding boxes.







      deep-learning






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked 17 mins ago









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