[Add Model]Add RKPicodet

docs/cn/faq/rknpu2/export.md

@@ -22,8 +22,8 @@ model_path: ./portrait_pp_humansegv2_lite_256x144_pretrained.onnx
 output_folder: ./
 target_platform: RK3588
 normalize:
-  mean: [0.5,0.5,0.5]
-  std: [0.5,0.5,0.5]
+  mean: [[0.5,0.5,0.5]]
+  std: [[0.5,0.5,0.5]]
 outputs: None
 ```
 
@@ -45,4 +45,4 @@ python tools/export.py  --config_path=./config.yaml
 
 ## 模型导出要注意的事项
 
-* 请不要导出带softmax和argmax的模型，这两个算子存在bug，请在外部进行运算
+* 请不要导出带softmax和argmax的模型，这两个算子存在bug，请在外部进行运算

examples/vision/detection/rknpu2detection/paddledetection/README.md

@@ -0,0 +1,38 @@
+# PaddleDetection RKNPU2部署示例
+
+## 支持模型列表
+
+目前FastDeploy支持如下模型的部署
+- [PicoDet系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet)
+
+## 准备PaddleSeg部署模型以及转换模型
+RKNPU部署模型前需要将Paddle模型转换成RKNN模型，具体步骤如下:
+* Paddle动态图模型转换为ONNX模型，请参考[PaddleDetection导出模型](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/deploy/EXPORT_MODEL.md)
+  ,注意在转换时请设置**export.nms=True**.
+* ONNX模型转换RKNN模型的过程，请参考[转换文档](../../../../../docs/cn/faq/rknpu2/export.md)进行转换。
+
+
+## 模型转换example
+下面以Picodet-npu为例子,教大家如何转换PPSeg模型到RKNN模型。
+```bash
+## 下载Paddle静态图模型并解压
+wget https://bj.bcebos.com/fastdeploy/models/rknn2/picodet_s_416_coco_npu.zip
+unzip -qo picodet_s_416_coco_npu.zip
+
+# 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 picodet_s_416_coco_npu \
+            --model_filename model.pdmodel \
+            --params_filename model.pdiparams \
+            --save_file picodet_s_416_coco_npu/picodet_s_416_coco_npu.onnx \
+            --enable_dev_version True
+
+python -m paddle2onnx.optimize --input_model picodet_s_416_coco_npu/picodet_s_416_coco_npu.onnx \
+                                --output_model picodet_s_416_coco_npu/picodet_s_416_coco_npu.onnx \
+                                --input_shape_dict "{'image':[1,3,416,416]}"
+# ONNX模型转RKNN模型
+# 转换模型,模型将生成在picodet_s_320_coco_lcnet_non_postprocess目录下
+python tools/rknpu2/export.py --config_path tools/rknpu2/config/RK3588/picodet_s_416_coco_npu.yaml
+```
+
+- [Python部署](./python)
+- [视觉模型预测结果](../../../../../docs/api/vision_results/)

examples/vision/detection/rknpu2detection/paddledetection/cpp/CMakeLists.txt

@@ -0,0 +1,37 @@
+CMAKE_MINIMUM_REQUIRED(VERSION 3.10)
+project(rknpu2_test)
+
+set(CMAKE_CXX_STANDARD 14)
+
+# 指定下载解压后的fastdeploy库路径
+set(FASTDEPLOY_INSTALL_DIR "thirdpartys/fastdeploy-0.0.3")
+
+include(${FASTDEPLOY_INSTALL_DIR}/FastDeployConfig.cmake)
+include_directories(${FastDeploy_INCLUDE_DIRS})
+
+add_executable(infer_picodet infer_picodet.cc)
+target_link_libraries(infer_picodet ${FastDeploy_LIBS})
+
+
+
+set(CMAKE_INSTALL_PREFIX ${CMAKE_SOURCE_DIR}/build/install)
+
+install(TARGETS infer_picodet DESTINATION ./)
+
+install(DIRECTORY model DESTINATION ./)
+install(DIRECTORY images DESTINATION ./)
+
+file(GLOB FASTDEPLOY_LIBS ${FASTDEPLOY_INSTALL_DIR}/lib/*)
+message("${FASTDEPLOY_LIBS}")
+install(PROGRAMS ${FASTDEPLOY_LIBS} DESTINATION lib)
+
+file(GLOB ONNXRUNTIME_LIBS ${FASTDEPLOY_INSTALL_DIR}/third_libs/install/onnxruntime/lib/*)
+install(PROGRAMS ${ONNXRUNTIME_LIBS} DESTINATION lib)
+
+install(DIRECTORY ${FASTDEPLOY_INSTALL_DIR}/third_libs/install/opencv/lib DESTINATION ./)
+
+file(GLOB PADDLETOONNX_LIBS ${FASTDEPLOY_INSTALL_DIR}/third_libs/install/paddle2onnx/lib/*)
+install(PROGRAMS ${PADDLETOONNX_LIBS} DESTINATION lib)
+
+file(GLOB RKNPU2_LIBS ${FASTDEPLOY_INSTALL_DIR}/third_libs/install/rknpu2_runtime/RK3588/lib/*)
+install(PROGRAMS ${RKNPU2_LIBS} DESTINATION lib)

examples/vision/detection/rknpu2detection/paddledetection/cpp/README.md

@@ -0,0 +1,71 @@
+# PaddleDetection C++部署示例
+
+本目录下提供`infer_xxxxx.cc`快速完成PPDetection模型在Rockchip板子上上通过二代NPU加速部署的示例。
+
+在部署前，需确认以下两个步骤:
+
+1. 软硬件环境满足要求
+2. 根据开发环境，下载预编译部署库或者从头编译FastDeploy仓库
+
+以上步骤请参考[RK2代NPU部署库编译](../../../../../../docs/cn/build_and_install/rknpu2.md)实现
+
+## 生成基本目录文件
+
+该例程由以下几个部分组成
+```text
+.
+├── CMakeLists.txt
+├── build  # 编译文件夹
+├── image  # 存放图片的文件夹
+├── infer_cpu_npu.cc
+├── infer_cpu_npu.h
+├── main.cc
+├── model  # 存放模型文件的文件夹
+└── thirdpartys  # 存放sdk的文件夹
+```
+
+首先需要先生成目录结构
+```bash
+mkdir build
+mkdir images
+mkdir model
+mkdir thirdpartys
+```
+
+## 编译
+
+### 编译并拷贝SDK到thirdpartys文件夹
+
+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
+fastdeploy-0.0.3目录，请移动它至thirdpartys目录下.
+
+### 拷贝模型文件，以及配置文件至model文件夹
+在Paddle动态图模型 -> Paddle静态图模型 -> ONNX模型的过程中，将生成ONNX文件以及对应的yaml配置文件，请将配置文件存放到model文件夹内。
+转换为RKNN后的模型文件也需要拷贝至model。
+
+### 准备测试图片至image文件夹
+```bash
+wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
+cp 000000014439.jpg ./images
+```
+
+### 编译example
+
+```bash
+cd build
+cmake ..
+make -j8
+make install
+```
+
+## 运行例程
+
+```bash
+cd ./build/install
+./rknpu_test
+```
+
+
+- [模型介绍](../../)
+- [Python部署](../python)
+- [视觉模型预测结果](../../../../../../docs/api/vision_results/)

examples/vision/detection/rknpu2detection/paddledetection/cpp/infer_picodet.cc

@@ -0,0 +1,86 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+#include <iostream>
+#include <string>
+#include "fastdeploy/vision.h"
+
+void InferPicodet(const std::string& device = "cpu");
+
+int main() {
+  InferPicodet("npu");
+  return 0;
+}
+
+fastdeploy::RuntimeOption GetOption(const std::string& device) {
+  auto option = fastdeploy::RuntimeOption();
+  if (device == "npu") {
+    option.UseRKNPU2();
+  } else {
+    option.UseCpu();
+  }
+  return option;
+}
+
+fastdeploy::ModelFormat GetFormat(const std::string& device) {
+  auto format = fastdeploy::ModelFormat::ONNX;
+  if (device == "npu") {
+    format = fastdeploy::ModelFormat::RKNN;
+  } else {
+    format = fastdeploy::ModelFormat::ONNX;
+  }
+  return format;
+}
+
+std::string GetModelPath(std::string& model_path, const std::string& device) {
+  if (device == "npu") {
+    model_path += "rknn";
+  } else {
+    model_path += "onnx";
+  }
+  return model_path;
+}
+
+void InferPicodet(const std::string &device) {
+  std::string model_file = "./model/picodet_s_416_coco_npu/picodet_s_416_coco_npu_rk3588.";
+  std::string params_file;
+  std::string config_file = "./model/picodet_s_416_coco_npu/infer_cfg.yml";
+
+  fastdeploy::RuntimeOption option = GetOption(device);
+  fastdeploy::ModelFormat format = GetFormat(device);
+  model_file = GetModelPath(model_file, device);
+  auto model = fastdeploy::vision::detection::RKPicoDet(
+      model_file, params_file, config_file,option,format);
+
+  if (!model.Initialized()) {
+    std::cerr << "Failed to initialize." << std::endl;
+    return;
+  }
+  auto image_file = "./images/000000014439.jpg";
+  auto im = cv::imread(image_file);
+
+  fastdeploy::vision::DetectionResult res;
+  clock_t start = clock();
+  if (!model.Predict(&im, &res)) {
+    std::cerr << "Failed to predict." << std::endl;
+    return;
+  }
+  clock_t end = clock();
+  auto dur = static_cast<double>(end - start);
+  printf("picodet_npu use time:%f\n", (dur / CLOCKS_PER_SEC));
+
+  std::cout << res.Str() << std::endl;
+  auto vis_im = fastdeploy::vision::VisDetection(im, res,0.5);
+  cv::imwrite("picodet_npu_result.jpg", vis_im);
+  std::cout << "Visualized result saved in ./picodet_npu_result.jpg" << std::endl;
+}

examples/vision/detection/rknpu2detection/paddledetection/python/README.md

@@ -0,0 +1,35 @@
+# PaddleDetection Python部署示例
+
+在部署前，需确认以下两个步骤
+
+- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../../docs/cn/build_and_install/rknpu2.md)
+
+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
+
+```bash
+# 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd FastDeploy/examples/vision/segmentation/paddleseg/python
+
+# 下载图片
+wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
+
+# copy model
+cp -r ./picodet_s_416_coco_npu /path/to/FastDeploy/examples/vision/detection/rknpu2detection/paddledetection/python
+
+# 推理
+python3 infer.py --model_file ./picodet_s_416_coco_npu/picodet_s_416_coco_npu_3588.rknn  \
+                  --config_file ./picodet_s_416_coco_npu/infer_cfg.yml \
+                  --image 000000014439.jpg
+```
+
+
+## 注意事项
+RKNPU上对模型的输入要求是使用NHWC格式，且图片归一化操作会在转RKNN模型时，内嵌到模型中，因此我们在使用FastDeploy部署时，
+需要先调用DisableNormalizePermute(C++)或`disable_normalize_permute(Python)，在预处理阶段禁用归一化以及数据格式的转换。
+## 其它文档
+
+- [PaddleSeg 模型介绍](..)
+- [PaddleSeg C++部署](../cpp)
+- [模型预测结果说明](../../../../../../docs/api/vision_results/)
+- [转换PPSeg RKNN模型文档](../README.md)

examples/vision/detection/rknpu2detection/paddledetection/python/infer.py

@@ -0,0 +1,60 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import fastdeploy as fd
+import cv2
+import os
+
+
+def parse_arguments():
+    import argparse
+    import ast
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model_file", required=True, help="Path of PaddleSeg model.")
+    parser.add_argument(
+        "--config_file", required=True, help="Path of PaddleSeg config.")
+    parser.add_argument(
+        "--image", type=str, required=True, help="Path of test image file.")
+    return parser.parse_args()
+
+
+def build_option(args):
+    option = fd.RuntimeOption()
+    option.use_rknpu2()
+    return option
+
+
+args = parse_arguments()
+
+# 配置runtime，加载模型
+runtime_option = build_option(args)
+model_file = args.model_file
+params_file = ""
+config_file = args.config_file
+model = fd.vision.detection.RKPicoDet(
+    model_file,
+    params_file,
+    config_file,
+    runtime_option=runtime_option,
+    model_format=fd.ModelFormat.RKNN)
+
+# 预测图片分割结果
+im = cv2.imread(args.image)
+result = model.predict(im.copy())
+print(result)
+
+# 可视化结果
+vis_im = fd.vision.vis_detection(im, result, score_threshold=0.5)
+cv2.imwrite("visualized_result.jpg", vis_im)
+print("Visualized result save in ./visualized_result.jpg")

fastdeploy/vision.h

@@ -29,6 +29,7 @@
 #include "fastdeploy/vision/detection/contrib/yolov7end2end_trt.h"
 #include "fastdeploy/vision/detection/contrib/yolox.h"
 #include "fastdeploy/vision/detection/ppdet/model.h"
+#include "fastdeploy/vision/detection/rknpu2/model.h"
 #include "fastdeploy/vision/facedet/contrib/retinaface.h"
 #include "fastdeploy/vision/facedet/contrib/scrfd.h"
 #include "fastdeploy/vision/facedet/contrib/ultraface.h"

fastdeploy/vision/detection/detection_pybind.cc

@@ -27,6 +27,8 @@ void BindNanoDetPlus(pybind11::module& m);
 void BindPPDet(pybind11::module& m);
 void BindYOLOv7End2EndTRT(pybind11::module& m);
 void BindYOLOv7End2EndORT(pybind11::module& m);
+void BindRKDet(pybind11::module& m);
+
 
 void BindDetection(pybind11::module& m) {
   auto detection_module =
@@ -42,5 +44,6 @@ void BindDetection(pybind11::module& m) {
   BindNanoDetPlus(detection_module);
   BindYOLOv7End2EndTRT(detection_module);
   BindYOLOv7End2EndORT(detection_module);
+  BindRKDet(detection_module);
 }
 }  // namespace fastdeploy

fastdeploy/vision/detection/rknpu2/model.h

@@ -0,0 +1,16 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+#include "fastdeploy/vision/detection/rknpu2/rkpicodet.h"