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Add `MNN` benchmarks to Raspberry Pi doc (#17910)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Lakshantha Dissanayake 1 week ago committed by GitHub
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      docs/en/guides/raspberry-pi.md

47
docs/en/guides/raspberry-pi.md
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@ -142,9 +142,10 @@ YOLO11 benchmarks were run by the Ultralytics team on nine different model forma
We have only included benchmarks for YOLO11n and YOLO11s models because other models sizes are too big to run on the Raspberry Pis and does not offer decent performance.
<div style="text-align: center;">
<img width="800" src="https://github.com/ultralytics/docs/releases/download/0/rpi-yolo11-benchmarks.avif" alt="YOLO11 benchmarks on RPi 5">
</div>
<figure style="text-align: center;">
<img width="800" src="https://github.com/ultralytics/assets/releases/download/v0.0.0/rpi-yolo11-benchmarks.avif" alt="YOLO11 benchmarks on RPi 5">
<figcaption style="font-style: italic; color: gray;">Benchmarked with Ultralytics v8.3.39</figcaption>
</figure>
### Detailed Comparison Table
@ -156,29 +157,33 @@ The below table represents the benchmark results for two different models (YOLO1
| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
|---------------|--------|-------------------|-------------|------------------------|
| PyTorch | ✅ | 5.4 | 0.61 | 524.828 |
| TorchScript | ✅ | 10.5 | 0.6082 | 666.874 |
| ONNX | ✅ | 10.2 | 0.6082 | 181.818 |
| OpenVINO | ✅ | 10.4 | 0.6082 | 530.224 |
| TF SavedModel | ✅ | 25.8 | 0.6082 | 405.964 |
| TF GraphDef | ✅ | 10.3 | 0.6082 | 473.558 |
| TF Lite | ✅ | 10.3 | 0.6082 | 324.158 |
| PaddlePaddle | ✅ | 20.4 | 0.6082 | 644.312 |
| NCNN | ✅ | 10.2 | 0.6106 | 93.938 |
| PyTorch | ✅ | 5.4 | 0.6100 | 405.238 |
| TorchScript | ✅ | 10.5 | 0.6082 | 526.628 |
| ONNX | ✅ | 10.2 | 0.6082 | 168.082 |
| OpenVINO | ✅ | 10.4 | 0.6082 | 81.192 |
| TF SavedModel | ✅ | 25.8 | 0.6082 | 377.968 |
| TF GraphDef | ✅ | 10.3 | 0.6082 | 487.244 |
| TF Lite | ✅ | 10.3 | 0.6082 | 317.398 |
| PaddlePaddle | ✅ | 20.4 | 0.6082 | 561.892 |
| MNN | ✅ | 10.1 | 0.6106 | 112.554 |
| NCNN | ✅ | 10.2 | 0.6106 | 88.026 |
=== "YOLO11s"
| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
|---------------|--------|-------------------|-------------|------------------------|
| PyTorch | ✅ | 18.4 | 0.7526 | 1226.426 |
| TorchScript | ✅ | 36.5 | 0.7416 | 1507.95 |
| ONNX | ✅ | 36.3 | 0.7416 | 415.24 |
| OpenVINO | ✅ | 36.4 | 0.7416 | 1167.102 |
| TF SavedModel | ✅ | 91.1 | 0.7416 | 776.14 |
| TF GraphDef | ✅ | 36.4 | 0.7416 | 1014.396 |
| TF Lite | ✅ | 36.4 | 0.7416 | 845.934 |
| PaddlePaddle | ✅ | 72.5 | 0.7416 | 1567.824 |
| NCNN | ✅ | 36.2 | 0.7419 | 197.358 |
| PyTorch | ✅ | 18.4 | 0.7526 | 1011.60 |
| TorchScript | ✅ | 36.5 | 0.7416 | 1268.502 |
| ONNX | ✅ | 36.3 | 0.7416 | 324.17 |
| OpenVINO | ✅ | 36.4 | 0.7416 | 179.324 |
| TF SavedModel | ✅ | 91.1 | 0.7416 | 714.382 |
| TF GraphDef | ✅ | 36.4 | 0.7416 | 1019.83 |
| TF Lite | ✅ | 36.4 | 0.7416 | 849.86 |
| PaddlePaddle | ✅ | 72.5 | 0.7416 | 1276.34 |
| MNN | ✅ | 36.2 | 0.7409 | 273.032 |
| NCNN | ✅ | 36.2 | 0.7419 | 194.858 |
Benchmarked with Ultralytics `v8.3.39`
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