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shape_predictor: allow dpoint as training input #2183
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This isn't supported by the current API. There isn't any particularly good reason, it's just how the code is setup. It could use floating point coordinates. I am somewhat skeptical that someone can label landmarks to sub-pixel accuracy though. Do you really have a problem domain where humans, or whatever it is that generates the labels, somehow really knows the location of the landmarks to sub-pixel accuracy? |
Thanks for getting back. I am using this dataset, which supplies float coordinates. The images are quite small, therefore I assumed it might make a difference. |
Were they annotated at a higher resolution and then downsampled?
In any case, if you want to put up a PR that switches the
full_object_detection to use dpoint instead of point (but in a way that's
reasonably backwards compatible so existing users are not bothered) that
would be cool with me.
|
Warning: this issue has been inactive for 35 days and will be automatically closed on 2020-11-30 if there is no further activity. If you are waiting for a response but haven't received one it's possible your question is somehow inappropriate. E.g. it is off topic, you didn't follow the issue submission instructions, or your question is easily answerable by reading the FAQ, dlib's official compilation instructions, dlib's API documentation, or a Google search. |
Warning: this issue has been inactive for 43 days and will be automatically closed on 2020-11-30 if there is no further activity. If you are waiting for a response but haven't received one it's possible your question is somehow inappropriate. E.g. it is off topic, you didn't follow the issue submission instructions, or your question is easily answerable by reading the FAQ, dlib's official compilation instructions, dlib's API documentation, or a Google search. |
Notice: this issue has been closed because it has been inactive for 45 days. You may reopen this issue if it has been closed in error. |
Hi ! |
Yeah this would be a reasonable thing to upgrade. If someone wants to go replace |
Currently, the shape predictor training example showcases how to provide training and test data using integer coordinates.
Hoever, I would like to train a shape predictor using float coordinate pairs. I hope to gain increased precision by doing so. Since the shape predictor is also giving float numbers as output, I would assume that this should be possible.
However, there is no documentation to be found on the input format.
I'm happy to extend the documentation as soon as I know how this works.
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