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Since the matterport implementation is not available via a package manager, we want a way to consistently refer to the library from code.
One solution is to simply clone the repository as a subdirectory in this one, the license allows us to do this. The pro is that this is the simplest solution, the con is that it will bloat our own repo. We could strip out the parts that we don't need to alleviate that issue.
Another solution is to ensure that everyone has an environment variable that points to their local directory for MaskRCNN. For example: MASK_CNN_DIR='/Users/havan/Dropbox/CP/Git/MaskRCNN'
We would then add all necessary paths from code, preferably from a central module/lib:
A subsequent task would be to move all model related code to a central library that we can simply import from. Computing mAP (mean average precision) is one such piece of code, that is currently duplicated across notebooks.
Please let me know what your thoughts are on this. Mentioning @pshivraj since we discussed this offline.
The text was updated successfully, but these errors were encountered:
My thought is that we should clone the mrcnn module and incorporate it into our clomask repo. That way, we can easily customize any training/inference class if needed. The mrcnn module only has 5 scripts so it shouldn't bloat our repo that much. We can put all our research code in a research folder, similar to one of their samples/xxx folder.
When I interned at Clobotics, they copied the giant Caffe repo and developed their own stuff in parallel folders. At the end of the Capstone, I think they would prefer us passing on a custom mrcnn module with detailed requirements/installation instructions, without referencing back and forth to matterport repo.
Since the matterport implementation is not available via a package manager, we want a way to consistently refer to the library from code.
MASK_CNN_DIR='/Users/havan/Dropbox/CP/Git/MaskRCNN'
We would then add all necessary paths from code, preferably from a central module/lib:
A subsequent task would be to move all model related code to a central library that we can simply import from. Computing
mAP
(mean average precision) is one such piece of code, that is currently duplicated across notebooks.Please let me know what your thoughts are on this. Mentioning @pshivraj since we discussed this offline.
The text was updated successfully, but these errors were encountered: