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View Code? Open in Web Editor NEWcode for Universal Barcode Detector via Semantic Segmentation https://arxiv.org/abs/1906.06281
License: Apache License 2.0
code for Universal Barcode Detector via Semantic Segmentation https://arxiv.org/abs/1906.06281
License: Apache License 2.0
Hello,
I am unable to start training. Is there a possibility that you can help with versions of packages that you use. It's probably that I need some specific versions of tensorflow.
Thanks for sharing such a great work. I read the base paper its quite fascinating. I am trying to reproduce the results with my own custom training data.
I would like to know the detail format and folder structure of the train/validation data.
Thanks for your sharing.
I found that when you calculate the loss, the K you use seems to be based on batchsize, not a single image. Did you decide to do this based on relevant considerations? For example, there is little difference between batchsize and single image.
Maybe it is better if I calculate K separately for each picture?
for your paper:
L = Ldetection + αLclassification (1)
Detection loss Ldetection itself is a weighted sum of three components: mean binary crossentropy loss on positive pixels Lp, mean binary crossentropy loss on negative pixels Ln, and mean binary crossentropy loss on worst predicted k negative pixels Lh, where k is equal to the number of positive pixels in image.
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