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Parameters
2.0M
FLOPs
4.0G
Input Size
640px
License
MIT
Architecture
Type
one-stage
Backbone
GELAN
Neck
PGI
Head
Decoupled
Benchmark Results
Performance on COCO val2017 across different hardware configurations
| Hardware | Runtime | mAP@50-95 | FPS | Latency | VRAM |
|---|---|---|---|---|---|
| NVIDIA A100 | PyTorch FP32 | 30.2% | 23.2 | 43.0ms | — |
| Raspberry Pi 5 | PyTorch FP32 | 37.0% | 2.7 | 372.0ms | — |
Speed Breakdown(Raspberry Pi 5)
End-to-end latency breakdown showing preprocessing, inference, and postprocessing times
2.9ms
361.2ms
4.7ms
Preprocess
Inference
Postprocess (NMS)
Usage with LibreYOLO
from libreyolo import LIBREYOLO
# Load model (auto-downloads from HuggingFace if not found locally)
model = LIBREYOLO("libreyolo9t.pt")
# 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,)efficientlightweight