Custom apparel detection,
built from scratch.
We train purpose-built YOLO models on proprietary apparel annotation datasets to deliver best-in-class garment recognition.
Custom YOLO Models
Off-the-shelf object detection falls short for apparel. We fine-tune YOLO architectures on tens of thousands of annotated garment images — covering categories, brands, conditions, and styles that generic models miss entirely.
- Fine-grained garment classification
- Brand and condition detection
- Optimized for mobile inference
Apparel Annotation Pipeline
Our proprietary annotation pipeline combines human labelers with model-assisted pre-labeling. Every image is tagged with bounding boxes, garment type, color, pattern, brand, and condition — building the richest apparel dataset in the space.
- Human-in-the-loop quality control
- Multi-attribute labeling per item
- Continuous model improvement cycle
On-Device, Real-Time
Our models are quantized and optimized for edge deployment — running directly on iOS (Core ML) and Android (ML Kit) with no cloud round-trips. This means instant detection even without a network connection, keeping your data private and your workflow fast.