| --- |
| license: mit |
| pretty_name: EquiFashion-DB (Mini) |
| language: |
| - en |
| task_categories: |
| - text-to-image |
| - image-to-image |
| size_categories: |
| - 1K<n<10K |
| tags: |
| - fashion |
| - diffusion |
| - multimodal |
| - text2image |
| - pose |
| - sketch |
| - fabric |
| --- |
| |
| # EquiFashion-DB (Mini) |
|
|
| **EquiFashion-DB (Mini)** is a compact subset of EquiFashion-DB with **aligned multimodal signals** for controllable fashion generation: **image, text, pose, sketch, and fabric**. |
|
|
| **Full Dataset Public at:** https://drive.google.com/file/d/13TS1U0IY8oG1gjMvsGCQCXrxLxm2SH-Z/view?usp=drive_link |
| |
| ## Structure (current `EquiFashion_DB/`) |
|
|
| ```text |
| EquiFashion_DB/ |
| ├── train/ # training images |
| ├── test/ # test images |
| ├── train_pose/ # pose assets (json/ + pose/ visualizations) |
| ├── train_sketch/ # extracted Canny sketch maps (PNG) |
| ├── train_fabric/ # extracted fabric texture patches (PNG) |
| ├── train.json # train captions (list of {gt, caption}) |
| ├── test.json # test captions (list of {gt, caption}) |
| └── train_pose.json # train captions + pose path (list of {gt, caption, pose}) |
| ``` |
|
|
| ## Annotation format (as provided) |
|
|
| **Train captions** (`train.json`) |
|
|
| ```json |
| { "gt": "009292_0.jpg", "caption": "Sweater, Commute, Homewear, ..." } |
| ``` |
|
|
| **Train captions + pose path** (`train_pose.json`) |
|
|
| ```json |
| { "gt": "009292_0.jpg", "caption": "Sweater, ...", "pose": "train_pose/pose/009292_0.jpg" } |
| ``` |
|
|
| **Pose keypoints JSON** (`train_pose/json/<gt_stem>.json`) |
|
|
| - Key `candidate`: list of \([x, y, confidence, joint_index]\) |
| |
| ```json |
| { |
| "candidate": [[282.0, 3.0, 0.54, 0.0], [247.0, 58.0, 0.92, 2.0]] |
| } |
| ``` |
| |
| ## Modalities |
| |
| - **Image**: `train/<gt>` and `test/<gt>` |
| - **Text**: `train.json`, `test.json` (captions) |
| - **Pose**: `train_pose/json/*.json` (keypoints) and `train_pose/pose/*.jpg` (visualization) |
| - **Sketch**: `train_sketch/<gt_stem>.png` |
| - **Fabric**: `train_fabric/<gt_stem>.png` (fixed-size texture patch) |
|
|
| ## Data construction pipeline |
|
|
| The mini version follows the EquiFashion-DB construction pipeline: |
|
|
|  |
|
|
| 1. **Public sources → raw pool** |
| Multiple fashion datasets (captioning, recognition, segmentation, editing) are merged into a raw pool with images, captions/attributes, categories and pose/parsing when available. |
| 2. **Cleaning & quality filtering** |
| - Remove broken images, heavy occlusions and extreme truncation. |
| - Discard samples with invalid / missing key joints or inconsistent parsing when pose is available. |
| 3. **Resolution & category normalization** |
| - Crop/resize all images to \(512 \times 512\) around the main garment / person. |
| - Map dataset-specific labels into a unified garment taxonomy (40+ categories). |
| 4. **Multimodal enrichment (this repo)** |
| Using the `equifashion_pipeline/` code: |
| - Generate Canny **sketch maps** inside garment regions (from pose keypoints when available). |
| - Sample high-frequency **fabric patches** from garment regions. |
| - Normalize **pose** JSON into a unified keypoint format. |
| 5. **Packaging** |
| Final JSON manifests (`train.json`, `test.json`, `train_pose.json`) store standardized paths and captions, with all modalities aligned by filename stem. |
|
|
| ## References |
|
|
| [1] Xie et al. — HieraFashDiff: Hierarchical Fashion Design with Mu |
| [2] Baldrati et al. — Multimodal Garment Designer: Human-Centric Latent Diffusion Models for Fashion Image Editing (2023) |
| [3] Zhang et al. — ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design (2022) |
| [4] Jiang et al. — Text2Human: Text-Driven Controllable Human Image Generation (2022) |
| [5] Rostamzadeh et al. — Fashion-Gen: The Generative Fashion Dataset and Challenge (2018) |
| [6] Yang et al. — Fashion Captioning: Towards Generating Accurate Descriptions with Semantic Rewards (2020) |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("NguyenDinhHieu/EquiFashion-DB") |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @dataset{NguyenDinhHieu_EquiFashionDBMini, |
| title = {EquiFashion: Hybrid GAN–Diffusion Balancing Diversity–Fidelity for Fashion Design Generation}, |
| author = {Nguyen Dinh Hieu, Tran Minh Khuong, Phan Duy Hung}, |
| year = {2026}, |
| url = {https://huggingface.co/datasets/NguyenDinhHieu/EquiFashion-DB} |
| } |
| ``` |
|
|
