| { | |
| "model_type": "object-counting", | |
| "library_name": "openvino", | |
| "pipeline_tag": "object-detection", | |
| "category": "Object Detection + Counting (80-class COCO)", | |
| "base_model": "YOLO26 (Ultralytics, default) or DETR facebook/detr-resnet-50 (alternative)", | |
| "source_framework": "PyTorch (Ultralytics, Hugging Face Transformers)", | |
| "supported_precisions": [ | |
| "FP32", | |
| "FP16", | |
| "INT8" | |
| ], | |
| "inference_engine": "OpenVINO", | |
| "hardware": [ | |
| "CPU", | |
| "GPU", | |
| "NPU" | |
| ], | |
| "detected_classes": "All 80 COCO classes (counted per class)", | |
| "hf_repo_id": "Intel/object-counting", | |
| "description": "Object counting use case using YOLO26 (default) or DETR to detect and report per-class counts across all 80 COCO classes", | |
| "selectable_models": [ | |
| "yolo26n", | |
| "yolo26s", | |
| "yolo26m", | |
| "yolo26l", | |
| "detr-resnet-50" | |
| ], | |
| "default_model": "yolo26n" | |
| } | |