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Old_Scallion2173 OP t1_j95a3nm wrote

Reply to comment by Morteriag in [D] bounding box or instance segmentation by Old_Scallion2173

I see, currently I'm using roboflow as it is convenient and does have a polygonal labelling tool. By the way, Do you think I should do transfer learning and/or k-fold cross validation too since my dataset is small (325 images)?

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Morteriag t1_j95aodr wrote

That size would do well as a PoC, not much more, and you should be able to annotate all the data within a day or two. Automation does not make that much sense at this scale. I love Roboflow for bounding boxes, but LabelBox has superior tools for segmentation. Sure, with this small data set you can use cross validation, although a hold out test set is also preferable. I would almost consider hand-picking the test set at this scale to make sure you get a sense of how it performa on challenging examples. What is the pixel size of your images? I know microscopy/histology images typically can cover large areas and one image could in fact be considered a mosaic of many “normal” sized images.

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Morteriag t1_j95b954 wrote

Last I checked Roboflow only had point-to-point vector masks for segmentation. In my experience that makes getting quality annotations a pain. In Labelbox, you can also hold in the mouse button. Hasty.ai focus on auto annotations, and by the look of the image you posted, it might be a good fit for your usecase.

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