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Renesas/YOLOX-Tiny-ONNX
YOLOX-Tiny-ONNX is a object detection model from Renesas. Use it when you need objects located in an image. The card lists the license as apache-2.0.
This repository hosts YOLOX-Tiny, targeting the Renesas R-Car X5H platform for object-detection inference on the NPX6 NPU.
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Updated Sep 28, 2026
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From the Hugging Face model README
This repository hosts YOLOX-Tiny, targeting the Renesas R-Car X5H platform for object-detection inference on the NPX6 NPU.
The FP32 ONNX model is auto-cast to INT8 by the Renesas MWMX toolchain at compile time — no separate quantization step is required.
yolox_tiny_fast_8xb8-300e_coco.onnx (FP32)
│
└─▶ MWMX Runtime ──▶ INT8 auto-cast ──▶ NPX6 NPU
| Artifact | Status | Notes |
|---|---|---|
| FP32 (ONNX) | ⏳ Pending | fp32/yolox_tiny_fast_8xb8-300e_coco.onnx — to be added; will be auto-cast to INT8 by the MWMX toolchain at compile time (see Deployment Flow above); no separate INT8 file will be shipped |
Measured on Renesas R-Car X5H via the MWMX runtime (APM80 ship-performance CI pipeline).
Benchmark configuration: Single NPU · Batch size: 1 · Input: 3 × 416 × 416
| AI Cores | Runtime | Precision | Device | Latency (ms) | Type |
|---|---|---|---|---|---|
| 1 | MWMX Runtime | INT8 (auto) | X5H · 1× NPU · 1 Core · 850 MHz | 3.57 | Measured |
| 3 | MWMX Runtime | INT8 (auto) | X5H · 1× NPU · 3 Core · 850 MHz | 2.21 | Measured |
| 4 | MWMX Runtime | INT8 (auto) | X5H · 1× NPU · 4 Core · 850 MHz | 2.15 | Measured |
| 6 | MWMX Runtime | INT8 (auto) | X5H · 1× NPU · 6 Core · 850 MHz | 2.09 | Measured |
| 12 | MWMX Runtime | INT8 (auto) | X5H · 1× NPU · 12 Core · 850 MHz | 2.59 | Measured |
TBD — not yet measured/published for this repo.
To run inference on Renesas R-Car X5H, you need:
hf download Renesas/YOLOX-Tiny-ONNX --repo-type=model --include "fp32/*"
metawaremx_runtime CI pipeline, "APM80" ship-performance target)