I want to use an object detection model for some use case.

I started with the YOLOv3, because I need to be able to perform detection on multiple images in less than few seconds (Even if it is not for real-time / video).

So, I successfully loaded and generated predictions using a keras model with pretrained weights.

The problem is that the pre-trained weights for this model have been generated with the COCO dataset, which contains very few classes (80).

What really surprises me is that all the pre-trained weights I can found for this type of algorithms use the COCO dataset, and none of them use the Open Images Dataset V4 (which contains 600 classes).

Is there a reason for that ? And if there is not, is there a place where I can find such pre-trained weights ?


Darknet has a yolo implementation using Open Images check this page (scroll down up to the end, just before the citation)

You can simply use wget https://pjreddie.com/media/files/yolov3-openimages.weights

  • $\begingroup$ I tried to use these weights, but it look like there is only few classes. When I tried to do a detection with a turtle image, it is pretty confident that it is a bird (like with the weights trained with COCO, which have not been trained to recognize turtles), and with a pizza picture it give no prediction at all (with the weights trained with COCO the prediction is good). $\endgroup$
    – Nakeuh
    Apr 16 '19 at 15:59
  • $\begingroup$ Try retraining the last layer $\endgroup$ Apr 16 '19 at 16:00
  • $\begingroup$ How to pass labels to train last layer? model has to predict boundary boxes right? $\endgroup$
    – LUZO
    Jul 5 '19 at 14:31
  • $\begingroup$ learnopencv.com/… check this tutorial $\endgroup$ Jul 5 '19 at 15:06

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