Borda / kaggle_iMet-collection

Classify museum objects with multiple topic related labels

Home Page:https://borda.github.io/kaggle_iMet-collection/

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Kaggle: iMet Collection 2021 x AIC - FGVC8

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The online cataloguing information is generated by subject matter experts and includes a wide range of data. These include, but are not limited to: multiple object classifications, artist, title, period, date, medium, culture, size, provenance, geographic location, and other related museum objects within The Met’s collection. Adding fine-grained attributes to aid in the visual understanding of the museum objects will enable the ability to search for visually related objects.

Sample images

Experimentation

install this tooling

A simple way how to use this basic functions:

! pip install https://github.com/Borda/kaggle_iMet-collection/archive/main.zip

run notebooks in Kaggle

run notebooks in Colab

I would recommend uploading the dataset to you personal gDrive and then in notebooks connect the gDrive which saves you lost of time with re-uploading dataset when ever your Colab is reset... :]

some results

Training progress with ResNet50 with training for 35 epochs and subset labels with ore then 100 samples:

training on 100 samples per class

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Classify museum objects with multiple topic related labels

https://borda.github.io/kaggle_iMet-collection/

License:MIT License


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