Parameters3.6M
GFLOPs6.9
Input Size640px
Best mAP43.0%
LicenseApache-2.0
Architecture
Type
transformer
Backbone
DINOv3-distilled ViT
Neck
HybridEncoder
Head
DEIM
Benchmark Results
Performance on COCO val2017 across different hardware configurations
| Hardware | Runtime | mAP@50-95 | FPS | Latency | VRAM |
|---|---|---|---|---|---|
| NVIDIA RTX 5070 Ti | PyTorch FP32 | 43.0% | 38.8 | 25.8ms | 69 MB |
Speed Breakdown(NVIDIA RTX 5070 Ti)
6.2ms
18.5ms
1.0ms
Preprocess
Inference
Postprocess (NMS)
Usage with LibreYOLO
from libreyolo import LIBREYOLO
# Load model (auto-downloads from HuggingFace if not found locally)
model = LIBREYOLO("libredeimv2n.pth")
# Run inference
result = model("image.jpg", conf=0.25, iou=0.45)
# Process results
print(f"Found {len(result)} objects")
print(result.boxes.xyxy) # bounding boxes (N, 4)
print(result.boxes.conf) # confidence scores (N,)
print(result.boxes.cls) # class IDs (N,)detrnms-freePaper: 43% mAP