Garment Accuracy Evaluator
Training ML models to automatically evaluate how accurately garments appear in on-model photos. Curate labeled datasets, experiment with architectures (fine-tuning vs. training from scratch), and benchmark model performance to find the best evaluator for production deployment.
Dataset Overview
Current staging dataset statistics
Soft Labeling
Create training data by scoring garment accuracy in on-model photos. Compare on-model images with product references and rate accuracy 0-10 to train the evaluator model.
Data Cleanup
Scan and fix data quality issues. Validate real on-model scores, check for inconsistencies, and maintain dataset integrity across all splits.
Dataset Explorer
Coming Soon
Browse labeled examples, analyze score distributions, and validate dataset quality. Ensure balanced splits for robust evaluator training.
Model Benchmarks
Coming Soon
Compare evaluator architectures, test fine-tuned vs. from-scratch models, and identify the best approach for production accuracy scoring.
Training Experiments
Coming Soon
Track experiments across different architectures and training strategies. Visualize loss curves, validation metrics, and convergence behavior.