| { | |
| "model_type": "crowd-analysis", | |
| "library_name": "openvino", | |
| "pipeline_tag": "object-detection", | |
| "category": "Object Detection (Crowd Density + Movement)", | |
| "base_model": "YOLO26 (Ultralytics)", | |
| "source_framework": "PyTorch (Ultralytics)", | |
| "supported_precisions": [ | |
| "FP32", | |
| "FP16", | |
| "INT8" | |
| ], | |
| "inference_engine": "OpenVINO", | |
| "hardware": [ | |
| "CPU", | |
| "GPU", | |
| "NPU" | |
| ], | |
| "detected_classes": "`person` (COCO class 0)", | |
| "hf_repo_id": "Intel/crowd-analysis", | |
| "description": "Crowd analysis use case using YOLO26 person detection with density levels and gvatrack-based movement flow" | |
| } | |