Datasets:

owj0421
/

polyvore-outfits

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README.md CHANGED Viewed

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----
-license: other
-license_name: .
-license_link: LICENSE
----

+---
+language:
+- en
+license: other
+task_categories:
+- image-classification
+- zero-shot-retrieval
+tags:
+- fashion
+- recommendation-system
+- polyvore
+pretty_name: Polyvore Outfits
+size_categories:
+- 10K<n<100K
+---
+# Polyvore Outfits (Refactored Version)
+This repository provides a **refactored version** of the Polyvore Outfits dataset, originally introduced in the paper **"Learning Type-Aware Embeddings for Fashion Compatibility"** by Mariya I. Vasileva et al.
+## 📌 Overview
+The goal of this refactoring is to improve **usability** and **developer experience**. While the core data remains identical to the original, the file structure and JSON schemas have been standardized to make it easier to load and use in modern deep learning pipelines.
+### Key Improvements:
+- **Standardized Item Referencing**: All items are referenced using the `<set_id>_<index>` format.
+- **Task-Specific Separation**: Data is clearly organized into `compatibility`, `fill_in_the_blank`, and `outfit_sets`.
+- **Clean JSON Schema**: Consistent naming conventions across all files.
+## 📂 Directory Structure
+The dataset is organized into `disjoint` and `nondisjoint` splits, covering three main tasks:
+```text
+polyvore-outfits/
+├── disjoint_compatibility/
+├── disjoint_fill_in_the_blank/
+├── disjoint_outfit_sets/
+├── nondisjoint_compatibility/
+│   ├── train.json, valid.json, test.json
+├── nondisjoint_fill_in_the_blank/
+│   ├── train.json, valid.json, test.json
+└── nondisjoint_outfit_sets/
+    ├── train.json, valid.json, test.json
+```
+## 📊 Data Formats
+### 1. Outfit Sets
+Contains metadata for each outfit set.
+```json
+{
+  "set_id": "217320763",
+  "items": [
+    { "item_id": "193458045", "index": 1 }
+  ]
+}
+```
+### 2. Compatibility
+Binary classification data to determine if a set of items matches.
+* `label: 1`: Compatible
+* `label: 0`: Incompatible
+```json
+{
+  "items": ["217320763_1", "217320763_2"],
+  "label": 1
+}
+```
+### 3. Fill-in-the-Blank (FITB)
+Multiple-choice data to predict the most suitable item for a missing slot.
+```json
+{
+  "items": ["217320763_1", "217320763_2"],
+  "blank_index": 2,
+  "candidates": ["217320763_3", "xxxx_x"],
+  "label": 0
+}
+```
+## 📜 Citation & Original Work
+This is a refactored version of the work by Vasileva et al. If you use this dataset, please cite the original paper:
+```bibtex
+@misc{vasileva2018learningtypeawareembeddingsfashion,
+      title={Learning Type-Aware Embeddings for Fashion Compatibility},
+      author={Mariya I. Vasileva and Bryan A. Plummer and Krishna Dusad and Shreya Rajpal and Ranjitha Kumar and David Forsyth},
+      year={2018},
+      eprint={1803.09196},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={[https://arxiv.org/abs/1803.09196](https://arxiv.org/abs/1803.09196)},
+}
+```
+## ⚖️ License
+This refactored version follows the same licensing terms as the original Polyvore Outfits dataset. Please refer to the original source for specific usage restrictions.

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