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[Doc]Check and modify broken links in documents (#1207)
* Update README_CN.md 之前的readme cn复制错了，导致存在死链 * Update README_CN.md * Update README_CN.md * Update README.md * Update README.md * Update README.md * Update README_CN.md * Update README_CN.md * Update README.md * Update README_CN.md * Update README.md * Update README_CN.md * Update README.md * Update RNN.md * Update RNN_CN.md * Update WebDemo.md * Update WebDemo_CN.md * Update install_rknn_toolkit2.md * Update export.md * Update use_cpp_sdk_on_android.md * Update README.md * Update README_Pу́сский_язы́к.md * Update README_Pу́сский_язы́к.md * Update README_Pу́сский_язы́к.md * Update README_Pу́сский_язы́к.md * Update README_हिन्दी.md * Update README_日本語.md * Update README_한국인.md * Update README_日本語.md * Update README_CN.md * Update README_CN.md * Update README.md * Update README_CN.md * Update README.md * Update README.md * Update README_CN.md * Update README_CN.md * Update README_CN.md * Update README_CN.md
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@@ -11,7 +11,7 @@
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为了方便开发者的测试，下面提供了FastestDet导出的模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库）
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| 模型 | 大小 | 精度 | 备注 |
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|:---------------------------------------------------------------- |:----- |:----- |:---- |
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| [FastestDet](https://bj.bcebos.com/paddlehub/fastdeploy/FastestDetn.onnx) | 969KB | 25.3% | 此模型文件来源于[FastestDet](https://github.com/dog-qiuqiu/FastestDet.git)，BSD-3-Clause license |
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| [FastestDet](https://bj.bcebos.com/paddlehub/fastdeploy/FastestDet.onnx) | 969KB | 25.3% | 此模型文件来源于[FastestDet](https://github.com/dog-qiuqiu/FastestDet.git)，BSD-3-Clause license |
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## 详细部署文档
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## 版本说明
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- 本版本文档和代码基于[FastestDet](https://github.com/dog-qiuqiu/FastestDet.git) 编写
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- 本版本文档和代码基于[FastestDet](https://github.com/dog-qiuqiu/FastestDet.git) 编写
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@@ -5,7 +5,7 @@
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目前SOPHGO支持如下模型的部署
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- [PP-YOLOE系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/ppyoloe)
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- [PicoDet系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet)
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- [YOLOV8系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/)
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- [YOLOV8系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4)
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## 准备PP-YOLOE YOLOV8或者PicoDet部署模型以及转换模型
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@@ -35,7 +35,7 @@ mkdir thirdpartys
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### Compile and copy SDK to the thirdpartys folder
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Refer to [RK2 generation NPU deployment repository compilation](../../../../../../docs/cn/build_and_install/rknpu2.md). It will generate fastdeploy-0.0.3 directory in the build directory after compilation. Move it to the thirdpartys directory.
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Refer to [RK2 generation NPU deployment repository compilation](../../../../../docs/cn/build_and_install/rknpu2.md). It will generate fastdeploy-0.0.3 directory in the build directory after compilation. Move it to the thirdpartys directory.
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### Copy model files and configuration files to the model folder
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In the process of Paddle dynamic graph model -> Paddle static graph model -> ONNX model, the ONNX file and the corresponding yaml configuration file will be generated. Please save the configuration file in the model folder.
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@@ -66,4 +66,4 @@ cd ./build/install
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- [Model Description](../../)
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- [Python Deployment](../python)
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- [Vision Model Prediction Results](../../../../../../docs/api/vision_results/)
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- [Vision Model Prediction Results](../../../../../docs/api/vision_results/)
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@@ -35,7 +35,7 @@ mkdir thirdpartys
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### 编译并拷贝SDK到thirdpartys文件夹
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请参考[RK2代NPU部署库编译](../../../../../../docs/cn/build_and_install/rknpu2.md)仓库编译SDK，编译完成后，将在build目录下生成
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请参考[RK2代NPU部署库编译](../../../../../docs/cn/build_and_install/rknpu2.md)仓库编译SDK，编译完成后，将在build目录下生成
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fastdeploy-0.0.3目录，请移动它至thirdpartys目录下.
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### 拷贝模型文件，以及配置文件至model文件夹
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@@ -67,4 +67,4 @@ cd ./build/install
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- [模型介绍](../../)
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- [Python部署](../python)
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- [视觉模型预测结果](../../../../../../docs/api/vision_results/)
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- [视觉模型预测结果](../../../../../docs/api/vision_results/)
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@@ -3,7 +3,7 @@ English | [简体中文](README_CN.md)
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Two steps before deployment
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- 1. Software and hardware should meet the requirements. Refer to [FastDeploy Environment Requirements](../../../../../../docs/cn/build_and_install/rknpu2.md)
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- 1. Software and hardware should meet the requirements. Refer to [FastDeploy Environment Requirements](../../../../../docs/cn/build_and_install/rknpu2.md)
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This directory provides examples that `infer.py` fast finishes the deployment of Picodet on RKNPU. The script is as follows
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@@ -31,5 +31,5 @@ The model needs to be in NHWC format on RKNPU. The normalized image will be embe
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- [PaddleDetection Model Description](..)
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- [PaddleDetection C++ Deployment](../cpp)
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- [model prediction Results](../../../../../../docs/api/vision_results/)
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- [model prediction Results](../../../../../docs/api/vision_results/)
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- [Convert PaddleDetection RKNN Model Files](../README.md)
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@@ -3,7 +3,7 @@
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在部署前，需确认以下两个步骤
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- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../../docs/cn/build_and_install/rknpu2.md)
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- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../docs/cn/build_and_install/rknpu2.md)
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本目录下提供`infer.py`快速完成Picodet在RKNPU上部署的示例。执行如下脚本即可完成
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@@ -31,5 +31,5 @@ RKNPU上对模型的输入要求是使用NHWC格式，且图片归一化操作
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- [PaddleDetection 模型介绍](..)
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- [PaddleDetection C++部署](../cpp)
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- [模型预测结果说明](../../../../../../docs/api/vision_results/)
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- [模型预测结果说明](../../../../../docs/api/vision_results/)
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- [转换PaddleDetection RKNN模型文档](../README.md)
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