metadata
dataset_info:
features:
- name: image
dtype: image
- name: prompt
dtype: string
- name: ground_truth
dtype: string
license: other
task_categories:
- image-classification
- visual-question-answering
tags:
- fashion
- clothing
- garment
- apparel
- vlm
- multimodal
- evaluation
- benchmark
size_categories:
- 10K<n<100K
Denali-AI Eval Benchmark 18k (Strict V2)
An evaluation benchmark of ~18,000 garment images with structured attribute annotations for benchmarking Vision-Language Models on apparel classification.
Dataset Description
Each sample contains:
- image: A garment photograph (clothing laid flat, on hangers, or worn)
- prompt: Classification instruction prompt for VLM inference
- ground_truth: JSON string with 9 garment attributes
Attribute Schema
| Field | Description | Examples |
|---|---|---|
| type | Garment type | Shirt, Pants, Dress, Jacket |
| color | Primary color | Blue, Red, Black |
| pattern | Fabric pattern | Solid, Striped, Floral, Plaid |
| neckline | Neckline style | Crew, V-Neck, Collared Neckline |
| sleeve_length | Sleeve length | Short, Long, Sleeveless |
| closure | Closure type | Button, Zipper, Pullover |
| brand | Brand (if visible on tag) | Nike, Gap, N/A |
| size | Size (if visible on tag) | M, XL, N/A |
| defect_type | Visible defects | Hole, Stain, N/A |
Data Sources
Images sourced from multiple collections:
- crowd: Crowdsourced garment photos
- posh: Resale marketplace listings
- zen: Processing facility station captures
- defect-spectrum: Garments with various defect types
- nike-shoes-authenticity: Nike footwear samples
- nike-shoes-classification: Nike footwear classification
- training-eval: Cross-validation subset
Usage
Intended Use
This dataset is intended for evaluating VLM models on garment attribute extraction tasks using the Denali-AI evaluation pipeline and PeakBench. It is disjoint from the Denali-AI/train-35k training set.
Organization
Part of the Denali-AI garment classification project.