[Doc] Add tutorial of supporting new models (#418)

* first commit for yolov7 * pybind for yolov7 * CPP README.md * CPP README.md * modified yolov7.cc * README.md * python file modify * delete license in fastdeploy/ * repush the conflict part * README.md modified * README.md modified * file path modified * file path modified * file path modified * file path modified * file path modified * README modified * README modified * move some helpers to private * add examples for yolov7 * api.md modified * api.md modified * api.md modified * YOLOv7 * yolov7 release link * yolov7 release link * yolov7 release link * copyright * change some helpers to private * change variables to const and fix documents. * gitignore * Transfer some funtions to private member of class * Transfer some funtions to private member of class * Merge from develop (#9) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root <[email protected]> * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason <[email protected]> Co-authored-by: root <[email protected]> Co-authored-by: DefTruth <[email protected]> Co-authored-by: huangjianhui <[email protected]> * first commit for yolor * for merge * Develop (#11) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root <[email protected]> * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason <[email protected]> Co-authored-by: root <[email protected]> Co-authored-by: DefTruth <[email protected]> Co-authored-by: huangjianhui <[email protected]> * Yolor (#16) * Develop (#11) (#12) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root <[email protected]> * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason <[email protected]> Co-authored-by: root <[email protected]> Co-authored-by: DefTruth <[email protected]> Co-authored-by: huangjianhui <[email protected]> Co-authored-by: Jason <[email protected]> Co-authored-by: root <[email protected]> Co-authored-by: DefTruth <[email protected]> Co-authored-by: huangjianhui <[email protected]> * Develop (#13) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root <[email protected]> * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason <[email protected]> Co-authored-by: root <[email protected]> Co-authored-by: DefTruth <[email protected]> Co-authored-by: huangjianhui <[email protected]> * documents * documents * documents * documents * documents * documents * documents * documents * documents * documents * documents * documents * Develop (#14) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root <[email protected]> * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: root <[email protected]> Co-authored-by: DefTruth <[email protected]> Co-authored-by: huangjianhui <[email protected]> Co-authored-by: Jason <[email protected]> Co-authored-by: root <[email protected]> Co-authored-by: DefTruth <[email protected]> Co-authored-by: huangjianhui <[email protected]> Co-authored-by: Jason <[email protected]> * add is_dynamic for YOLO series (#22) * modify ppmatting backend and docs * modify ppmatting docs * fix the PPMatting size problem * fix LimitShort's log * retrigger ci * modify PPMatting docs * modify the way for dealing with LimitShort * change develop_a_new_model.md dir Co-authored-by: Jason <[email protected]> Co-authored-by: root <[email protected]> Co-authored-by: DefTruth <[email protected]> Co-authored-by: huangjianhui <[email protected]> Co-authored-by: Jason <[email protected]>
PaddlePaddle · Oct 24, 2022 · 828a81d · 828a81d
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diff --git a/docs/cn/faq/develop_a_new_model.md b/docs/cn/faq/develop_a_new_model.md
@@ -1,3 +1,265 @@
 # FastDeploy集成新模型流程
 
-进行中...
+在FastDeploy里面新增一个模型，包括增加C++/Python的部署支持。 本文以torchvision v0.12.0中的ResNet50模型为例，介绍使用FastDeploy做外部[模型集成](#modelsupport)，具体包括如下3步。
+
+| 步骤 | 说明                                | 创建或修改的文件                            |
+|:------:|:-------------------------------------:|:---------------------------------------------:|
+| [1](#step2)    |  在fastdeploy/vision相应任务模块增加模型实现       | resnet.h、resnet.cc、vision.h                     |
+| [2](#step4)     | 通过pybind完成Python接口绑定 | resnet_pybind.cc、classification_pybind.cc |
+| [3](#step5)     | 实现Python相应调用接口    | resnet.py、\_\_init\_\_.py                        |
+
+在完成上述3步之后，一个外部模型就集成好了。
+<br />
+如果您想为FastDeploy贡献代码，还需要为新增模型添加测试代码、说明文档和代码注释，可在[测试](#test)中查看。
+## 模型集成     <span id="modelsupport"></span>
+
+### 模型准备  <span id="step1"></span>
+
+
+在集成外部模型之前，先要将训练好的模型（.pt，.pdparams 等）转换成FastDeploy支持部署的模型格式（.onnx，.pdmodel）。多数开源仓库会提供模型转换脚本，可以直接利用脚本做模型的转换。由于torchvision没有提供转换脚本，因此手动编写转换脚本，本文中将 `torchvison.models.resnet50` 转换为 `resnet50.onnx`， 参考代码如下：
+
+```python
+import torch
+import torchvision.models as models
+model = models.resnet50(pretrained=True)
+batch_size = 1  #批处理大小
+input_shape = (3, 224, 224)   #输入数据,改成自己的输入shape
+model.eval()
+x = torch.randn(batch_size, *input_shape)	# 生成张量
+export_onnx_file = "resnet50.onnx"			# 目的ONNX文件名
+torch.onnx.export(model,
+                    x,
+                    export_onnx_file,
+                    opset_version=12,
+                    input_names=["input"],	# 输入名
+                    output_names=["output"],	# 输出名
+                    dynamic_axes={"input":{0:"batch_size"},  # 批处理变量
+                                    "output":{0:"batch_size"}})
+```
+执行上述脚本将会得到 `resnet50.onnx` 文件。
+
+### C++部分  <span id="step2"></span>
+* 创建`resnet.h`文件
+  * 创建位置
+    * FastDeploy/fastdeploy/vision/classification/contrib/resnet.h (FastDeploy/C++代码存放位置/视觉模型/任务名称/外部模型/模型名.h)
+  * 创建内容
+    * 首先在resnet.h中创建 ResNet类并继承FastDeployModel父类，之后声明`Predict`、`Initialize`、`Preprocess`、`Postprocess`和`构造函数`，以及必要的变量，具体的代码细节请参考[resnet.h](https://github.com/PaddlePaddle/FastDeploy/pull/347/files#diff-69128489e918f305c208476ba793d8167e77de2aa7cadf5dcbac30da448bd28e)。
+
+```C++
+class FASTDEPLOY_DECL ResNet : public FastDeployModel {
+ public:
+  ResNet(...);
+  virtual bool Predict(...);
+ private:
+  bool Initialize();
+  bool Preprocess(...);
+  bool Postprocess(...);
+};
+```
+
+* 创建`resnet.cc`文件
+  * 创建位置
+    * FastDeploy/fastdeploy/vision/classification/contrib/resnet.cc (FastDeploy/C++代码存放位置/视觉模型/任务名称/外部模型/模型名.cc)
+  * 创建内容
+    * 在`resnet.cc`中实现`resnet.h`中声明函数的具体逻辑，其中`PreProcess` 和 `PostProcess`需要参考源官方库的前后处理逻辑复现，ResNet每个函数具体逻辑如下，具体的代码请参考[resnet.cc](https://github.com/PaddlePaddle/FastDeploy/pull/347/files#diff-d229d702de28345253a53f2a5839fd2c638f3d32fffa6a7d04d23db9da13a871)。
+
+```C++
+ResNet::ResNet(...) {
+  // 构造函数逻辑
+  // 1. 指定 Backend 2. 设置RuntimeOption 3. 调用Initialize()函数
+}
+bool ResNet::Initialize() {
+  // 初始化逻辑
+  // 1. 全局变量赋值 2. 调用InitRuntime()函数
+  return true;
+}
+bool ResNet::Preprocess(Mat* mat, FDTensor* output) {
+// 前处理逻辑
+// 1. Resize 2. BGR2RGB 3. Normalize 4. HWC2CHW 5. 处理结果存入 FDTensor类中  
+  return true;
+}
+bool ResNet::Postprocess(FDTensor& infer_result, ClassifyResult* result, int topk) {
+  //后处理逻辑
+  // 1. Softmax 2. Choose topk labels 3. 结果存入 ClassifyResult类
+  return true;
+}
+bool ResNet::Predict(cv::Mat* im, ClassifyResult* result, int topk) {
+  Preprocess(...)
+  Infer(...)
+  Postprocess(...)
+  return true;
+}
+```
+<span id="step3"></span>
+* 在`vision.h`文件中加入新增模型文件
+  * 修改位置
+    * FastDeploy/fastdeploy/vision.h
+  * 修改内容
+
+```C++
+#ifdef ENABLE_VISION
+#include "fastdeploy/vision/classification/contrib/resnet.h"
+#endif
+```
+
+
+### Pybind部分  <span id="step4"></span>
+
+* 创建Pybind文件  
+  * 创建位置
+    * FastDeploy/fastdeploy/vision/classification/contrib/resnet_pybind.cc (FastDeploy/C++代码存放位置/视觉模型/任务名称/外部模型/模型名_pybind.cc)
+  * 创建内容
+    * 利用Pybind将C++中的函数变量绑定到Python中，具体代码请参考[resnet_pybind.cc](https://github.com/PaddlePaddle/FastDeploy/pull/347/files#diff-270af0d65720310e2cfbd5373c391b2110d65c0f4efa547f7b7eeffcb958bdec)。
+```C++
+void BindResNet(pybind11::module& m) {
+  pybind11::class_<vision::classification::ResNet, FastDeployModel>(
+      m, "ResNet")
+      .def(pybind11::init<std::string, std::string, RuntimeOption, ModelFormat>())
+      .def("predict", ...)
+      .def_readwrite("size", &vision::classification::ResNet::size)
+      .def_readwrite("mean_vals", &vision::classification::ResNet::mean_vals)
+      .def_readwrite("std_vals", &vision::classification::ResNet::std_vals);
+}
+```
+
+* 调用Pybind函数
+  * 修改位置
+    * FastDeploy/fastdeploy/vision/classification/classification_pybind.cc (FastDeploy/C++代码存放位置/视觉模型/任务名称/任务名称}_pybind.cc)
+  * 修改内容
+```C++
+void BindResNet(pybind11::module& m);
+void BindClassification(pybind11::module& m) {
+  auto classification_module =
+      m.def_submodule("classification", "Image classification models.");
+  BindResNet(classification_module);
+}
+```
+
+
+### Python部分  <span id="step5"></span>
+
+
+* 创建`resnet.py`文件
+  * 创建位置
+    * FastDeploy/python/fastdeploy/vision/classification/contrib/resnet.py (FastDeploy/Python代码存放位置/fastdeploy/视觉模型/任务名称/外部模型/模型名.py)
+  * 创建内容
+    * 创建ResNet类继承自FastDeployModel，实现 `\_\_init\_\_`、Pybind绑定的函数（如`predict()`）、以及`对Pybind绑定的全局变量进行赋值和获取的函数`，具体代码请参考[resnet.py](https://github.com/PaddlePaddle/FastDeploy/pull/347/files#diff-a4dc5ec2d450e91f1c03819bf314c238b37ac678df56d7dea3aab7feac10a157)。
+
+```python
+class ResNet(FastDeployModel):
+    def __init__(self, ...):
+        self._model = C.vision.classification.ResNet(...)
+    def predict(self, input_image, topk=1):
+        return self._model.predict(input_image, topk)
+    @property
+    def size(self):
+        return self._model.size
+    @size.setter
+    def size(self, wh):
+        ...
+```
+<span id="step6"></span>
+* 导入ResNet类
+  * 修改位置
+    * FastDeploy/python/fastdeploy/vision/classification/\_\_init\_\_.py (FastDeploy/Python代码存放位置/fastdeploy/视觉模型/任务名称/\_\_init\_\_.py)
+  * 修改内容
+
+```Python
+from .contrib.resnet import ResNet
+```
+
+## 测试  <span id="test"></span>
+### 编译
+  * C++
+    * 位置：FastDeploy/
+
+```
+mkdir build & cd build
+cmake .. -DENABLE_ORT_BACKEND=ON -DENABLE_VISION=ON -DCMAKE_INSTALL_PREFIX=${PWD/fastdeploy-0.0.3
+-DENABLE_PADDLE_BACKEND=ON -DENABLE_TRT_BACKEND=ON -DWITH_GPU=ON -DTRT_DIRECTORY=/PATH/TO/TensorRT/
+make -j8
+make install
+```
+
+ 编译会得到 build/fastdeploy-0.0.3/。
+
+  * Python
+    * 位置：FastDeploy/python/
+
+```
+export TRT_DIRECTORY=/PATH/TO/TensorRT/    # 如果用TensorRT 需要填写TensorRT所在位置，并开启 ENABLE_TRT_BACKEND
+export ENABLE_TRT_BACKEND=ON
+export WITH_GPU=ON
+export ENABLE_PADDLE_BACKEND=ON
+export ENABLE_OPENVINO_BACKEND=ON
+export ENABLE_VISION=ON
+export ENABLE_ORT_BACKEND=ON
+python setup.py build
+python setup.py bdist_wheel
+cd dist
+pip install fastdeploy_gpu_python-版本号-cpxx-cpxxm-系统架构.whl
+```
+
+### 编写测试代码
+  * 创建位置: FastDeploy/examples/vision/classification/resnet/ (FastDeploy/示例目录/视觉模型/任务名称/模型名/)
+  * 创建目录结构
+
+```
+.
+├── cpp
+│   ├── CMakeLists.txt
+│   ├── infer.cc    // C++ 版本测试代码
+│   └── README.md   // C++版本使用文档
+├── python
+│   ├── infer.py    // Python 版本测试代码
+│   └── README.md   // Python版本使用文档
+└── README.md   // ResNet 模型集成说明文档
+```
+
+* C++
+  * 编写CmakeLists文件、C++ 代码以及 README.md 内容请参考[cpp/](https://github.com/PaddlePaddle/FastDeploy/pull/347/files#diff-afcbe607b796509581f89e38b84190717f1eeda2df0419a2ac9034197ead5f96)。
+  * 编译 infer.cc
+    * 位置：FastDeploy/examples/vision/classification/resnet/cpp/
+
+```
+mkdir build & cd build
+cmake .. -DFASTDEPLOY_INSTALL_DIR=/PATH/TO/FastDeploy/build/fastdeploy-0.0.3/
+make
+```
+
+* Python
+  * Python 代码以及 README.md 内容请参考[python/](https://github.com/PaddlePaddle/FastDeploy/pull/347/files#diff-5a0d6be8c603a8b81454ac14c17fb93555288d9adf92bbe40454449309700135)。
+
+### 为代码添加注释
+为了方便用户理解代码，我们需要为新增代码添加注释，添加注释方法可参考如下示例。
+- C++ 代码
+您需要在resnet.h文件中为函数和变量增加注释，有如下三种注释方式，具体可参考[resnet.h](https://github.com/PaddlePaddle/FastDeploy/pull/347/files#diff-69128489e918f305c208476ba793d8167e77de2aa7cadf5dcbac30da448bd28e)。
+
+```C++
+/** \brief Predict for the input "im", the result will be saved in "result".
+*
+* \param[in] im Input image for inference.
+* \param[in] result Saving the inference result.
+* \param[in] topk The length of return values, e.g., if topk==2, the result will include the 2 most possible class label for input image.
+*/
+virtual bool Predict(cv::Mat* im, ClassifyResult* result, int topk = 1);
+/// Tuple of (width, height)
+std::vector<int> size;
+/*! @brief Initialize for ResNet model, assign values to the global variables and call InitRuntime()
+*/
+bool Initialize();
+```
+- Python 代码
+你需要为resnet.py文件中的函数和变量增加适当的注释，示例如下，具体可参考[resnet.py](https://github.com/PaddlePaddle/FastDeploy/pull/347/files#diff-a4dc5ec2d450e91f1c03819bf314c238b37ac678df56d7dea3aab7feac10a157)。
+
+```python  
+  def predict(self, input_image, topk=1):
+    """Classify an input image
+    :param input_image: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+    :param topk: (int)The topk result by the classify confidence score, default 1
+    :return: ClassifyResult
+    """
+    return self._model.predict(input_image, topk)
+```
+
+对于集成模型过程中的其他文件，您也可以对实现的细节添加适当的注释说明。