
Architecture of Mask RCNN – A PyTorch Implementation - rohithasrk
https://github.com/wannabeOG/Mask-RCNN
======
zorkw4rg
[https://github.com/wannabeOG/Mask-
RCNN/blob/master/model.py](https://github.com/wannabeOG/Mask-
RCNN/blob/master/model.py)

yeah dumping it all in a single 2098 line file, why not? Here is a clean
documented implementation of faster rcnn for comparison:
[https://github.com/chenyuntc/simple-faster-rcnn-
pytorch](https://github.com/chenyuntc/simple-faster-rcnn-pytorch)

~~~
wannabeOG
Thanks, I will work on incorporating these changes. In my defense it was my
first project and I was solely focused on getting the results and didn't focus
much on making the code "accessible"

~~~
targafarian
This is a good summary of a large portion of code written in academia. "Didn't
know how to program," "wrote it for myself," and "just trying to get a
result." I've heard that a billion times. Not such a big deal if it's just for
yourself and not shared with the world. Unfortunately in larger academic
collaborations these mentalities end up slowing down research more than
enabling it. (And if you intend on making your research public, the
"collaboration" should be seen as anyone who views your github.)

Academics are great at finding "local optima," but rarely do they see beyond
their next result, and then others have the onerous task of trying to verify
the previous results or worse still using the previous work to build towards
"larger" results.

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edshiro
Nice one! I don't remember all that much from reading the Mask-RCNN paper last
year and have not seen many implementations so it's nice to be presented with
this Pytorch implementation.

From what I recall about Faster R-CNN, the Regions Of Interest (ROI) are pre-
determined via Selective Search, right? So I presume you would need to do the
same thing with Mask-RCNN? I think this is the part I am the most confused
with since I have never implemented Selective Search myself. Could you point
me to introductory material on it?

Lastly, I can see the author of this work has read my blog post on
understanding SSD MultiBox - glad it helped in some way :).

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mliker
RCNN uses selective search to generate the ROIs. What makes Faster RCNN faster
is not having to spend time on selective search.

~~~
wannabeOG
It uses an RPN to generate the region proposals so it completely does away
with the selective search which was the bottleneck for speed in fast RCNN

