task_categories:text-to-image annotations_creators:human generated by using detail_desc and color language_creators:other multilinguality:monolingual size_categories:n=1K source_datasets:www.kaggle.com/competitions/h-and-m-personalized-fashion-recommendations language:en license:apache-2.0 region:us
---
license: apache-2.0
annotations_creators:
- human generated by using detail_desc and color
language:
- en
language_creators:
- other
multilinguality:
- monolingual
pretty_name: 'H&M Clothes captions'
size_categories:
- n=1K
source_datasets:
- www.kaggle.com/competitions/h-and-m-personalized-fashion-recommendations
tags: []
task_categories:
- text-to-image
task_ids: []
---

# Dataset Card for H&M Clothes captions

_Dataset used to train/finetune [Clothes text to image model]

Captions are generated by using the 'detail_desc' and 'colour_group_name' or 'perceived_colour_master_name' from kaggle/competitions/h-and-m-personalized-fashion-recommendations. Original images were also obtained from the url (https://www.kaggle.com/competitions/h-and-m-personalized-fashion-recommendations/data?select=images)

For each row the dataset contains `image` and `text` keys. `image` is a varying size PIL jpeg, and `text` is the accompanying text caption. Only a train split is provided.
---
