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facebookresearch / simmc

With the aim of building next generation virtual assistants that can handle multimodal inputs and perform multimodal actions, we introduce two new datasets (both in the virtual shopping domain), the annotation schema, the core technical tasks, and the baseline models. The code for the baselines and the datasets will be opensourced.
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Question about Fashion attributes #31

Closed billkunghappy closed 4 years ago

billkunghappy commented 4 years ago

Hi I have some questions about the attribute value of fashion dataset. I was using the "fashion_devtest_dials_api_calls.json" made by the preprocessing scripts of the mm_action_prediciton When I look into it, I found some weird attribute values.

In the attribute vocabulary and action_evaluation.py, I've found that there exist 6 available attributes and 8 ignored attributes. However, in the "fashion_devtest_dials_api_calls.json" file, I have found 27 kinds of attribute values. available attributes: ["availableSizes", "brand", "color", "customerRating", "info", "other", "price"] ignored attributes: ["minPrice", "maxPrice","furniture_id", "material", "decorStyle", "intendedRoom","raw_matches","focus"] Founded attributes: ['soldBy', 'pattern', 'clothingStyle', 'waistStyle', 'price', 'forOccasion', 'skirtLength', 'clothingCategory', 'customerRating', 'necklineStyle', 'color', 'embellishment', 'size', 'jacketStyle', 'material', 'info', 'ageRange', 'sleeveLength', 'hemLength', 'sweaterStyle', 'dressStyle', 'amountInStock', 'availableSizes', 'sleeveStyle', 'skirtStyle', 'hemStyle', 'brand'] What are those founded attributes which are neither available attributes nor ignored attributes? Should we just ignore them and delete them when training? And will these attributes be ignored by the action_evaluation.py script?

satwikkottur commented 4 years ago

Hello @billkunghappy,

Could you take a look at this PR (https://github.com/facebookresearch/simmc/pull/22) and see if that discussion helps? Feel free to re-open the issue if this does not clarify.