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Yolo #178
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Are you facing an isssue with labeling the different classes of image? |
I guess the question relates to "Did some test with annotation of the ball and robot, that worked fine. But when I selected to annotate a goal-post I got a different method. I could not find the option to change it and have goalposts the same way annotated as e.g. ball or robot?" |
Hi, I hope that I can answer your questions:
As far as I know, the formats you mentioned are not yet available. You can try to add them when defining a custom export format; the export format definition is pretty extensive. Generating multiple files is currently not possible, though. Maybe it would be possible to implement this feature directly in the ImageTagger that would probably be useful for a lot of people. I can look into that. The way we currently use the export format is that we export the data as yaml (there are already export formats for that) and then process the file locally.
There are a few different methods of annotating. The method for balls, robots and goals is the bounding box method. Goalposts however use the polygon method. That is a decision that we took for the publicly hosted instance because goal posts often are tilted in the image and we did not want to lose that information (it cannot be represented with bounding boxes).
Image segmentation is currently not supported and also not a planned feature. But if you would like to add it, feel free to ask for help!
There is currently no integration with labelimg but I guess improving an import/export flow to and from labelimg would be very nice. I see that labelimg saves the annotations in the PASCAL VOC format. Adding the option to upload this format should be doable. I can look into that sometime in the next weeks. I hope that this helped! |
Thank you for the quick answers! |
Hi,
Thank you for organizing this for Robocup. I did upload some test images to test the platform and see if it would benefit for us.
Some points I noticed, might be a feature request or maybe something I missed.
Thanks
MSL team VDL robotsports
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