| --- |
| license: apache-2.0 |
| tags: |
| - object-detection |
| - onnx |
| - rk3588 |
| - rknn |
| --- |
| |
| # 🚀 RKNN Object Detection Models |
|
|
| ONNX + RKNN models for object detection, optimized for Rockchip RK3588 NPU deployment via [rknn_model_zoo](https://github.com/airockchip/rknn_model_zoo). |
|
|
| ## 📦 Models |
|
|
| ### ONNX (Universal Format) |
|
|
| | Model | File | Architecture | Size | Source | |
| |:------|:-----|:-------------|-----:|:-------| |
| | YOLOX-S | `yolox/yolox_s.onnx` | CNN | ~24 MB | [examples/yolox](https://github.com/airockchip/rknn_model_zoo/tree/main/examples/yolox) | |
| | YOLOX-M | `yolox/yolox_m.onnx` | CNN | ~68 MB | [examples/yolox](https://github.com/airockchip/rknn_model_zoo/tree/main/examples/yolox) | |
| | PP-YOLOE-S | `ppyoloe/ppyoloe_s.onnx` | CNN | ~24 MB | [examples/ppyoloe](https://github.com/airockchip/rknn_model_zoo/tree/main/examples/ppyoloe) | |
| | PP-YOLOE-M | `ppyoloe/ppyoloe_m.onnx` | CNN | ~68 MB | [examples/ppyoloe](https://github.com/airockchip/rknn_model_zoo/tree/main/examples/ppyoloe) | |
|
|
| ### RKNN (RK3588 NPU Format, INT8 Quantized) |
|
|
| | Model | File | Quantization | Size | Tool | |
| |:------|:-----|:-------------|-----:|:-----| |
| | YOLOX-S | `yolox/yolox_s.rknn` | INT8 | ~11 MB | rknn-toolkit2 2.3.2 | |
| | YOLOX-M | `yolox/yolox_m.rknn` | INT8 | ~27 MB | rknn-toolkit2 2.3.2 | |
| | PP-YOLOE-S | `ppyoloe/ppyoloe_s.rknn` | INT8 | ~9.3 MB | rknn-toolkit2 2.3.2 | |
| | PP-YOLOE-M | `ppyoloe/ppyoloe_m.rknn` | INT8 | ~25 MB | rknn-toolkit2 2.3.2 | |
|
|
| > RKNN files are converted from ONNX with INT8 quantization. Input/output dtype changed from float32 to int8 for NPU performance. |
|
|
| ### Original Download URLs |
|
|
| | Model | ONNX | |
| |:------|:-----| |
| | YOLOX-S | [yolox_s.onnx](https://ftrg.zbox.filez.com/v2/delivery/data/95f00b0fc900458ba134f8b180b3f7a1/examples/yolox/yolox_s.onnx) | |
| | YOLOX-M | [yolox_m.onnx](https://ftrg.zbox.filez.com/v2/delivery/data/95f00b0fc900458ba134f8b180b3f7a1/examples/yolox/yolox_m.onnx) | |
| | PP-YOLOE-S | [ppyoloe_s.onnx](https://ftrg.zbox.filez.com/v2/delivery/data/95f00b0fc900458ba134f8b180b3f7a1/examples/ppyoloe/ppyoloe_s.onnx) | |
| | PP-YOLOE-M | [ppyoloe_m.onnx](https://ftrg.zbox.filez.com/v2/delivery/data/95f00b0fc900458ba134f8b180b3f7a1/examples/ppyoloe/ppyoloe_m.onnx) | |
|
|
| ## 📥 Download |
|
|
| ```python |
| from huggingface_hub import hf_hub_download |
| |
| # Download ONNX (universal) |
| hf_hub_download(repo_id="eebyp/RKNN", filename="yolox/yolox_s.onnx", local_dir="./model") |
| |
| # Download RKNN (RK3588 NPU, INT8) |
| hf_hub_download(repo_id="eebyp/RKNN", filename="yolox/yolox_s.rknn", local_dir="./model") |
| ``` |
|
|
| ## 🔗 Source |
|
|
| - **Repository**: [airockchip/rknn_model_zoo](https://github.com/airockchip/rknn_model_zoo) |
| - **Platform**: RK3562 / RK3566 / RK3568 / RK3576 / RK3588 |
| - **Conversion**: rknn-toolkit2 2.3.2, target_platform=rk3588, INT8 quantization |
| |
| ## 📄 License |
| |
| Apache 2.0 |
| |
| --- |
| |
| > **Note:** This repository is hosted for **personal research purposes only**. For production use, please refer to the official repository above. |
| |
