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Parameters
31.0M
FLOPs
92.0G
Input Size
640px
License
Apache-2.0
Architecture
Type
transformer
Backbone
ResNet-34
Neck
HybridEncoder
Head
DETR
Benchmark Results
Performance on COCO val2017 across different hardware configurations
| Hardware | mAP@50-95 | FPS | Latency | VRAM |
|---|---|---|---|---|
| NVIDIA A100 (TensorRT FP16) | 48.8% | 98.4 | 10.2ms | 1344 MB |
| NVIDIA T4 (TensorRT FP16) | 49.0% | 38.8 | 25.8ms | 1279 MB |
| CPU (ONNX Runtime) | 48.8% | 4.6 | 216.0ms | 1366 MB |
Speed Breakdown (A100 TensorRT)
End-to-end latency breakdown showing preprocessing, inference, and postprocessing times
1.3ms
6.3ms
2.5ms
Preprocess
Inference
Postprocess (NMS)
Usage with LibreYOLO
from libreyolo import YOLO
# Load model
model = YOLO.from_pretrained("https://huggingface.co/Libre-YOLO/rtdetr-r34")
# Run inference
results = model.predict("image.jpg")
# Process results
for box in results.boxes:
print(f"Class: {box.cls}, Confidence: {box.conf:.2f}")transformerno-nms
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