[Docs] Pick paddleclas fastdeploy docs from PaddleClas (#1654)

* Adjust folders structures in paddleclas * remove useless files * Update sophgo * improve readme
2026-04-23 00:17:25 +08:00 · 2023-03-23 13:06:09 +08:00
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+
+# PaddleClas 模型在RKNPU2上部署方案-FastDeploy
+
+## 1. 说明  
+PaddleClas支持通过FastDeploy在RKNPU2上部署相关模型.
+
+## 2. 转换模型
+下面以 ResNet50_vd为例子，教大家如何转换分类模型到RKNN模型.
+目前FastDeploy只在PaddleClas测试过ResNet50_vd模型, 欢迎用户尝试其他的PaddleClas模型进行部署.
+
+### 2.1 导出ONNX模型
+```bash
+# 安装 paddle2onnx
+pip install paddle2onnx
+
+# 下载ResNet50_vd模型文件和测试图片
+wget https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz
+tar -xvf ResNet50_vd_infer.tgz
+
+# 静态图转ONNX模型，注意，这里的save_file请和压缩包名对齐
+paddle2onnx --model_dir ResNet50_vd_infer  \
+            --model_filename inference.pdmodel \
+            --params_filename inference.pdiparams  \
+            --save_file ResNet50_vd_infer/ResNet50_vd_infer.onnx  \
+            --enable_dev_version True  \
+            --opset_version 10  \
+            --enable_onnx_checker True
+
+# 固定shape，注意这里的inputs得对应netron.app展示的 inputs 的 name，有可能是image 或者 x
+python -m paddle2onnx.optimize --input_model ResNet50_vd_infer/ResNet50_vd_infer.onnx \
+                               --output_model ResNet50_vd_infer/ResNet50_vd_infer.onnx \
+                               --input_shape_dict "{'inputs':[1,3,224,224]}"
+```  
+
+### 2.2 编写模型导出配置文件
+以转化RK3588的RKNN模型为例子，我们需要编辑./rknpu2_tools/config/ResNet50_vd_infer_rknn.yaml，来转换ONNX模型到RKNN模型。
+
+如果你需要在NPU上执行normalize操作，请根据你的模型配置normalize参数，例如:
+```yaml
+model_path: ./ResNet50_vd_infer/ResNet50_vd_infer.onnx
+output_folder: ./ResNet50_vd_infer
+mean:
+  -
+    - 123.675
+    - 116.28
+    - 103.53
+std:
+  -
+    - 58.395
+    - 57.12
+    - 57.375
+outputs_nodes:
+do_quantization: False
+dataset: "./ResNet50_vd_infer/dataset.txt"
+```
+
+**在CPU上做normalize**可以参考以下yaml：
+```yaml
+model_path: ./ResNet50_vd_infer/ResNet50_vd_infer.onnx
+output_folder: ./ResNet50_vd_infer
+mean:
+  -
+    - 0
+    - 0
+    - 0
+std:
+  -
+    - 1
+    - 1
+    - 1
+outputs_nodes:
+do_quantization: False
+dataset: "./ResNet50_vd_infer/dataset.txt"
+```
+这里我们选择在NPU上执行normalize操作.
+
+
+### 2.3 ONNX模型转RKNN模型
+```shell
+python ./rknpu2_tools/export.py \
+        --config_path ./rknpu2_tools/config/ResNet50_vd_infer_rknn.yaml \
+        --target_platform rk3588
+```
+
+## 3. 其他链接
+- [Cpp部署](./cpp)
+- [Python部署](./python)
+- [视觉模型预测结果](../../../../../docs/api/vision_results/)