MATLAB Answers

Using a trained Faster RCNN Object Detector, expected LABEL to be nonempty

3 views (last 30 days)
jaida alsuhaibani
jaida alsuhaibani on 9 Feb 2020
Commented: jaida alsuhaibani on 14 Feb 2020
I’m using https://www.mathworks.com/help/vision/examples/object-detection-using-faster-r-cnn-deep-learning.html example to train it in my dataset.
the dataset contains 400 images and after it finish’s training "expected LABEL to be nonempty" error occur
What can I do?

  0 Comments

Sign in to comment.

Answers (1)

Sourav Bairagya
Sourav Bairagya on 12 Feb 2020
It seems that the labelling is not done properly.
It may be possible that some images are not labelled. So, it would be good to check the labelling of the input dataset once.
There is another possibility that if the bounding boxes present in input image are already small, then after resizing them, those small bounding boxes will become more smaller. Hence, while processing through first few layers of resNet50, all the useful labelling informations will be lost due to further downsampling of already small bounding boxes. To avoid such incident, you can crop the desired portions from the original image and adjust the bounding boxes accordingly so that after resize they don't become too small.

  1 Comment

jaida alsuhaibani
jaida alsuhaibani on 14 Feb 2020
Thank you for your answer I guess the problem is that the bounding boxes sometimes are really small Do you have any suggestions of how we can fix it without manually checking the images?

Sign in to comment.

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!