Benchmarks & Datasets
Collection
Evaluation benchmarks and training datasets for garment classification • 2 items • Updated
eval-hard-3500
A curated 3,500-sample hard evaluation benchmark for garment classification VLMs.
Format
JSONL with fields:
image: path to garment imagesource: annotation sourceresponse: ground-truth JSON with 9 fields (type, color, pattern, neckline, sleeve_length, closure, brand, size, defect_type)
Usage
Used to evaluate multi-field structured JSON extraction from garment images. Models are scored on SBERT cosine similarity, NLI entailment, Levenshtein ratio, token F1, and weighted field scores.
Metrics
See eval_all_results.json for model comparison results on this benchmark.
- Downloads last month
- 14