Building A Mask R-CNN From Scratch in TensorFlow and Keras

Building A Mask R-CNN From Scratch in TensorFlow and Keras

In this post, we'll explanation of how to build a basic Mask R-CNN for learning purposes, without the hustle and bustle.

If you ever wanted to implement a Mask R-CNN from scratch in TensorFlow, you probably found Matterport’s implementation¹. This is a great one, if you only want to _use _a Mask R-CNN. However, as it is very robust and complex, it can be hard to thoroughly understand every bit of it. And the even bigger problem is, that it doesn’t run with new versions of TensorFlow.

And if you would have given a chance to a PyTorch implementation, the most frequently used one is the Detectron2², which is also very hard to understand because of its complexity.

From all the descriptions of how Mask R-CNN works, it always seems very easy to implement it, but somehow you still can’t find a lot of implementations.

object-detection tensorflow keras mask-r-cnn machine-learning

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