Open Source Computer Vision Library
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Updated
Nov 22, 2021 - C++
Digital image processing is the use of algorithms to make computers analyze the content of digital images.
As reported by deepsource in here we abuse from using built-in input function in our functionality.
We target to have a clean and healthy source code free of risk.
Replace variable names whether it makes sense e.g. for image based functionality input -> image ; in l
Originally posted by stefanv July 11, 2017
RANSAC was implemented in scikit-image & scikit-learn around the same time, by the same @ahojnnes. In the mean time, some improvements have landed on either side.
We should compare the two implementations, and port fixe
Enhancement
A discussion in #614 revealed a good place for improvement - we should ensure that input image is continuous upon start of the augmentation pipeline. This could be implemented by adding
image = np.ascontiguousarray(image)to image and mask targets.A proposed place to add this call - somewhere at the beginning of
A.Compose.__call__.