I found a new tool makesense who is trying to do the same thing that you're already doing. Probably with some new thoughts in mind. I recently asked the author how that tool is doing differently: SkalskiP/make-sense#23
The author responded that we need multiple clicks while labeling in imglab. Though I didn't understand it well as I can control most of the things with
Pretty much the title. A well documented notebook should do and can help people using this dataset. Comment below if you want to take this up or have any questions.
PhotoML is an Android App to demonstrate Firebase Vision ML-Kit Tasks like Label detection, Optical Character Recognition, Face detection and Barcode scanning
The basic idea of this generic interpolator for label images is to interpolate each label with an ordinary image interpolator, and return the label with the highest value. This is the idea used by the itk::LabelImageGaussianInterpolateImageFunction interpolator. Unfortunately, this class is currently limited to Gaussian interpolation. Using generic programming, our proposed interpolator extends this idea to any image interpolator. Combined with linear interpolation, this results in similar or better accuracy and much improved computation speeds on a test image.
I found a new tool makesense who is trying to do the same thing that you're already doing. Probably with some new thoughts in mind. I recently asked the author how that tool is doing differently: SkalskiP/make-sense#23
The author responded that we need multiple clicks while labeling in imglab. Though I didn't understand it well as I can control most of the things with