Package: maskrcnn-modanet
A Mask R-CNN Keras implementation with Modanet annotations on the Paperdoll datasetMask R-CNN with ModaNetMy bachelor's thesis project.To sum it all up, I created a program that enables you to quickly train any model usingfizyr's keras-maskrcnn(I spent around a month to make it work).
And in particular to train it usingModaNet.
ModaNet, I discovered, had its flaws, particularly on the footwear and boots. They had the bounding boxes overlap with each other.
You can check them out by runningmaskrcnn-modanet viewimage --all-set --originalWith and without the "original" parameter, in parallel in two different terminal tabs/windows.So I fixed them (although help is much appreciated to refine it).Then I ran some tests to check the results and footwear and boots recognition were dramatically improved.I then formulated a simple application to analyze how many shoes, or skirts, or one of the other 13 labels, are in the user's instagram account, only analyzing images in which there is only one person in the frame. More details again on therelease notes for v1.0.Below is the home screen of the program.Usage: maskrcnn-modanet [OPTIONS] COMMAND [ARGS]...

  Main CLI.

Options:
  --help  Show this message and exit.

Commands:
  datasets        Manage your datasets run 1 -> maskrcnn-modanet datasets...
  evaluate        Evaluate any trained model, average precision and recall.
  instagram       Simple implementation to track instagram metrics per...
  processimage    View and save processed image and annotations from input...
  savedvars       Show and edit saved variables
  train           Train using the dataset downloaded usage: maskrcnn-
                  modanet...
  viewannotation  View and (not yet needed) save dataset images, plain (not...
  viewimage       View and (not yet needed) save dataset images, plain (not...I'll be very happy to merge your pull requests that add new implementations, or link to them in a section here!Regarding the Instagram analyzer, I started from theInstaloaderclasses and overrode some methods to get the urls of the posts instead of downloading them.It then runs through the COCO model to determine the images that have only one person that is bigger than 10% of the image, and on those images I run the ModaNet model to show some statistics about what type of apparel the user is wearing and even display the instances of them, if you request it.Say you want to quickly find what skirt (or footwear) your instagram star always wears. With this tool you can! And you can also see how often the instagram user shows himself alone in their images, and what he/she usually shares of him (always pictures with shoes? always only the top part?)Link to the Thesis PresentationShort VersionGetting StartedThis project is written in Python 3, so it works in all major OSes. Although only Linux and MacOS are fully supported.
Keep in mind to use pip or pip3 depending on your settings.Clone this repoRunpip install maskrcnn-modanetOr go to the repo you just cloned on the terminal and runpip install -e .If you see any errors, just install the dependencies manually, just like this:pip3 install --upgrade cythonNow that you've installed it, runmaskrcnn-modanet datasets download the/folder/you/want/to/put/data/inIt will take a while, about 40GB to download!
EDIT: it is now reduced to just 2-3 GB. See therelease notes for v1.0for details on this and on the instagram application.Then you can explore its features and commands by runningmaskrcnn-modanetPrerequisitesInstall Python and KerasInstallGit LFS (Large File Storage)to get all the files!Built WithSublime Text- The text editor usedPython 3- Language utilizedGitHub Desktop- To manage developementSublime Merge- To manage developementContributingThe following is a copy of PurpleBoothPlease readCONTRIBUTING.mdfor details on our code of conduct, and the process for submitting pull requests to us.VersioningFor the versions available, see thereleases on this repository.AuthorsPier Carlo Cadoppi-Initial workSee also the list ofcontributorswho participated in this project.LicenseThis project is licensed under the MIT License - see theLICENSE.mdfile for detailsAcknowledgmentsHat tip to anyone whose code was usedBillie Thompson-README Template-PurpleBoothInspirationetc lol