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* 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * Update issues.md * Update fastdeploy_init.sh * 更新交叉编译 * 更新insightface系列模型的rknpu2支持 * 更新insightface系列模型的rknpu2支持 * 更新说明文档 * 更新insightface * 尝试解决pybind问题 Co-authored-by: Jason <928090362@qq.com> Co-authored-by: Jason <jiangjiajun@baidu.com>
35 lines
2.9 KiB
Markdown
35 lines
2.9 KiB
Markdown
[English](../../../en/faq/rknpu2/rknpu2.md) | 中文
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# RKNPU2概述
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## 安装环境
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RKNPU2模型导出只支持在x86Linux平台上进行导出，安装流程请参考[RKNPU2模型导出环境配置文档](./environment.md)
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## ONNX模型转换为RKNN模型
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ONNX模型不能直接调用RK芯片中的NPU进行运算，需要把ONNX模型转换为RKNN模型，具体流程请查看[RKNPU2转换文档](./export.md)
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## RKNPU2已经支持的模型列表
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以下环境测试的速度均为端到端，测试环境如下:
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* 设备型号: RK3588
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* ARM CPU使用ONNX框架进行测试
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* NPU均使用单核进行测试
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| 任务场景 | 模型 | 模型版本(表示已经测试的版本) | ARM CPU/RKNN速度(ms) |
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|----------------------|------------------------------------------------------------------------------------------|--------------------------|--------------------|
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| Detection | [Picodet](../../../../examples/vision/detection/paddledetection/rknpu2/README.md) | Picodet-s | 162/112 |
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| Detection | [RKYOLOV5](../../../../examples/vision/detection/rkyolo/README.md) | YOLOV5-S-Relu(int8) | -/57 |
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| Detection | [RKYOLOX](../../../../examples/vision/detection/rkyolo/README.md) | - | -/- |
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| Detection | [RKYOLOV7](../../../../examples/vision/detection/rkyolo/README.md) | - | -/- |
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| Segmentation | [Unet](../../../../examples/vision/segmentation/paddleseg/rknpu2/README.md) | Unet-cityscapes | -/- |
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| Segmentation | [PP-HumanSegV2Lite](../../../../examples/vision/segmentation/paddleseg/rknpu2/README.md) | portrait(int8) | 133/43 |
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| Segmentation | [PP-HumanSegV2Lite](../../../../examples/vision/segmentation/paddleseg/rknpu2/README.md) | human(int8) | 133/43 |
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| Face Detection | [SCRFD](../../../../examples/vision/facedet/scrfd/rknpu2/README.md) | SCRFD-2.5G-kps-640(int8) | 108/42 |
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| Face FaceRecognition | [InsightFace](../../../../examples/vision/faceid/insightface/rknpu2/README_CN.md) | ms1mv3_arcface_r18(int8) | 81/12 |
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| Classification | [ResNet](../../../../examples/vision/classification/paddleclas/rknpu2/README.md) | ResNet50_vd | -/33 |
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## 预编译库下载
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为了方便大家进行开发，这里提供1.0.2版本的FastDeploy给大家使用
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- [FastDeploy RK356X c++ SDK](https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-aarch64-rk356X-1.0.2.tgz)
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- [FastDeploy RK3588 c++ SDK](https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-aarch64-rk3588-1.0.2.tgz)
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