I had a look and the image exists as does its corresponding xml file. I searched for the error on google and found a github conversation that I now cannot find again!! typical, but the person mentioned if they have one label and it is set to difficult then they can recreate the error every time. They said you need to set keep_difficult to true. I dont know where this needs to be set. And I cannot find the convo again to ask!
I checked the xml file and low and behold it had difficult in the xml. Do you know where I need to turn this keep_difficult setting on in the code?
Thanks :)
EDIT: I set difficult to 0 in the xml and it processed that file fine until next one with difficult. Is difficult setting really that big a impact on the training do you think? If not I can write a quick script to simply go through all xmls and change it to 0. But I don’t want to do that if it will really impact the training of hard to discern labels.
EDIT: found your answer to this here: https://forums.developer.nvidia.com/t/successful-training-with-train-ssd-py-using-small-custom-data-set-but-error-on-full-data-set/156921/6
it now trains thank you so much for your help, is there any info generated by this trainer that can be loaded into tensorboard or would I have to code that into it myself?
Once again, thank you!!
Edit: FYI for future reference I had to set num workers to 0 for it to run. Otherwise the multiprocessor error would happen.