Hi all, I have been successfully playing around with a few toy language models for OCRopus. I'm unsure of how to set the weights in the model because I'm not sure how the costs from the optical part of the recognition are determined. I think I read somewhere that they should aim to be negative log likelihoods? Any particular base?
I suppose the answer to this may also depend on the model(s) you're using. Right now, I'm still just using the character/line model. But I noticed that there are some parameters in plain text in that model (e.g. below). Is there any documentation or information on what these mean, etc? If not, perhaps you could point me to the relevant source code? Best, Ben From, ocropus/data/models/default.model: <object> linerec linerecverbose=0 grouper=SimpleGrouper use_reject=1 use_priors=0 invert=1 space_fractile=0.5 space_min=0.2 minheight=10 maxheight=300 space_max=1.1 space_yes=1 maxaspect=1 segmenter=DpSegmenter classifier=latin space_multiplier=2 extractor=scaledfe cpreload=none space_no=5 minclass=32 maxcost=20 maxrange=5 minprob=1e-06 END_OF_PARAMETERS=HERE -- You received this message because you are subscribed to the Google Groups "ocropus" group. To post to this group, send email to [email protected]. To unsubscribe from this group, send email to [email protected]. For more options, visit this group at http://groups.google.com/group/ocropus?hl=en.
