diff --git a/docs/en/build_and_install/download_prebuilt_libraries.md b/docs/en/build_and_install/download_prebuilt_libraries.md index 9bf7122ce2..58edd1d56e 100755 --- a/docs/en/build_and_install/download_prebuilt_libraries.md +++ b/docs/en/build_and_install/download_prebuilt_libraries.md @@ -3,8 +3,8 @@ FastDeploy provides pre-built libraries for developers to download and install directly. Meanwhile, FastDeploy also offers easy access to compile so that developers can compile FastDeploy according to their own needs. This article is divided into two parts: -- [1.GPU Deployment Environment](##GPU Deployment Environment) -- [2.CPU Deployment Environment](##CPU Deployment Environment) +- [1.GPU Deployment Environment](#gpu-deployment-environment) +- [2.CPU Deployment Environment](#cpu-deployment-environment) ## GPU Deployment Environment diff --git a/examples/vision/facealign/README.md b/examples/vision/facealign/README.md index d145c7c8f9..df0b441112 100644 --- a/examples/vision/facealign/README.md +++ b/examples/vision/facealign/README.md @@ -5,3 +5,5 @@ FastDeploy目前支持如下人脸对齐(关键点检测）模型部署 | 模型 | 说明 | 模型格式 | 版本 | | :--- | :--- | :------- | :--- | | [Hsintao/pfld_106_face_landmarks](./pfld) | PFLD 系列模型 | ONNX | [CommitID:e150195](https://github.com/Hsintao/pfld_106_face_landmarks/commit/e150195) | +| [Single430/FaceLandmark1000](./face_landmark_1000) | FaceLandmark1000 系列模型 | ONNX | [CommitID:1a951b6](https://github.com/Single430/FaceLandmark1000/tree/1a951b6) | +| [jhb86253817/PIPNet](./pipnet) | PIPNet 系列模型 | ONNX | [CommitID:b9eab58](https://github.com/jhb86253817/PIPNet/tree/b9eab58) | diff --git a/examples/vision/facealign/face_landmark_1000/README.md b/examples/vision/facealign/face_landmark_1000/README.md new file mode 100644 index 0000000000..ce45cc285b --- /dev/null +++ b/examples/vision/facealign/face_landmark_1000/README.md @@ -0,0 +1,25 @@ +# FaceLandmark 模型部署 + +## 模型版本说明 + +- [FaceLandmark1000](https://github.com/Single430/FaceLandmark1000/tree/1a951b6) + +## 支持模型列表 + +目前FastDeploy支持如下模型的部署 + +- [FaceLandmark1000 模型](https://github.com/Single430/FaceLandmark1000) + +## 下载预训练模型 + +为了方便开发者的测试，下面提供了FaceLandmark导出的各系列模型，开发者可直接下载使用。 + +| 模型 | 参数大小 | 精度 | 备注 | +|:---------------------------------------------------------------- |:----- |:----- | :------ | +| [FaceLandmark1000](https://bj.bcebos.com/paddlehub/fastdeploy/FaceLandmark1000.onnx) | 2.1M | - | + + +## 详细部署文档 + +- [Python部署](python) +- [C++部署](cpp) diff --git a/examples/vision/facealign/face_landmark_1000/cpp/CMakeLists.txt b/examples/vision/facealign/face_landmark_1000/cpp/CMakeLists.txt new file mode 100644 index 0000000000..c417fcb388 --- /dev/null +++ b/examples/vision/facealign/face_landmark_1000/cpp/CMakeLists.txt @@ -0,0 +1,18 @@ +PROJECT(infer_demo C CXX) +CMAKE_MINIMUM_REQUIRED (VERSION 3.10) + +# 指定下载解压后的fastdeploy库路径 +option(FASTDEPLOY_INSTALL_DIR "Path of downloaded fastdeploy sdk.") +include(${FASTDEPLOY_INSTALL_DIR}/utils/gflags.cmake) +include(${FASTDEPLOY_INSTALL_DIR}/FastDeploy.cmake) + +# 添加FastDeploy依赖头文件 +include_directories(${FASTDEPLOY_INCS}) + +add_executable(infer_demo ${PROJECT_SOURCE_DIR}/infer.cc) +# 添加FastDeploy库依赖 +if(UNIX AND (NOT APPLE) AND (NOT ANDROID)) + target_link_libraries(infer_demo ${FASTDEPLOY_LIBS} gflags pthread) +else() + target_link_libraries(infer_demo ${FASTDEPLOY_LIBS} gflags) +endif() diff --git a/examples/vision/facealign/face_landmark_1000/cpp/README.md b/examples/vision/facealign/face_landmark_1000/cpp/README.md new file mode 100644 index 0000000000..033f54164d --- /dev/null +++ b/examples/vision/facealign/face_landmark_1000/cpp/README.md @@ -0,0 +1,84 @@ +# FaceLandmark1000 C++部署示例 + +本目录下提供`infer.cc`快速完成FaceLandmark1000在CPU/GPU，以及GPU上通过TensorRT加速部署的示例。 + +在部署前，需确认以下两个步骤 + +- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) +- 2. 根据开发环境，下载预编译部署库和samples代码，参考[FastDeploy预编译库](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) + +以Linux上CPU推理为例，在本目录执行如下命令即可完成编译测试，保证 FastDeploy 版本0.7.0以上(x.x.x >= 0.7.0)支持FaceLandmark1000模型 + +```bash +mkdir build +cd build +wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-x.x.x.tgz +tar xvf fastdeploy-linux-x64-x.x.x.tgz +cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x +make -j + +#下载官方转换好的 FaceLandmark1000 模型文件和测试图片 +wget https://bj.bcebos.com/paddlehub/fastdeploy/FaceLandmark1000.onnx +wget https://bj.bcebos.com/paddlehub/fastdeploy/facealign_input.png + +# CPU推理 +./infer_demo --model FaceLandmark1000.onnx --image facealign_input.png --device cpu +# GPU推理 +./infer_demo --model FaceLandmark1000.onnx --image facealign_input.png --device gpu +# GPU上TensorRT推理 +./infer_demo --model FaceLandmark1000.onnx --image facealign_input.png --device gpu --backend trt +``` + +运行完成可视化结果如下图所示 + +
+ +
+ +以上命令只适用于Linux或MacOS, Windows下SDK的使用方式请参考: +- [如何在Windows中使用FastDeploy C++ SDK](../../../../../docs/cn/faq/use_sdk_on_windows.md) + +## FaceLandmark1000 C++接口 + +### FaceLandmark1000 类 + +```c++ +fastdeploy::vision::facealign::FaceLandmark1000( + const string& model_file, + const string& params_file = "", + const RuntimeOption& runtime_option = RuntimeOption(), + const ModelFormat& model_format = ModelFormat::ONNX) +``` + +FaceLandmark1000模型加载和初始化，其中model_file为导出的ONNX模型格式。 + +**参数** + +> * **model_file**(str): 模型文件路径 +> * **params_file**(str): 参数文件路径，当模型格式为ONNX时，此参数传入空字符串即可 +> * **runtime_option**(RuntimeOption): 后端推理配置，默认为None，即采用默认配置 +> * **model_format**(ModelFormat): 模型格式，默认为ONNX格式 + +#### Predict函数 + +> ```c++ +> FaceLandmark1000::Predict(cv::Mat* im, FaceAlignmentResult* result) +> ``` +> +> 模型预测接口，输入图像直接输出landmarks结果。 +> +> **参数** +> +> > * **im**: 输入图像，注意需为HWC，BGR格式 +> > * **result**: landmarks结果, FaceAlignmentResult说明参考[视觉模型预测结果](../../../../../docs/api/vision_results/) + +### 类成员变量 + +用户可按照自己的实际需求，修改下列预处理参数，从而影响最终的推理和部署效果 + +> > * **size**(vector<int>): 通过此参数修改预处理过程中resize的大小，包含两个整型元素，表示[width, height], 默认值为[128, 128] + +- [模型介绍](../../) +- [Python部署](../python) +- [视觉模型预测结果](../../../../../docs/api/vision_results/) +- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md) diff --git a/examples/vision/facealign/face_landmark_1000/cpp/infer.cc b/examples/vision/facealign/face_landmark_1000/cpp/infer.cc new file mode 100644 index 0000000000..702d9609a8 --- /dev/null +++ b/examples/vision/facealign/face_landmark_1000/cpp/infer.cc @@ -0,0 +1,110 @@ +// 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 "fastdeploy/vision.h" +#include "gflags/gflags.h" + +DEFINE_string(model, "", "Directory of the inference model."); +DEFINE_string(image, "", "Path of the image file."); +DEFINE_string(device, "cpu", + "Type of inference device, support 'cpu' or 'gpu'."); +DEFINE_string(backend, "default", + "The inference runtime backend, support: ['default', 'ort', " + "'paddle', 'ov', 'trt', 'paddle_trt']"); +DEFINE_bool(use_fp16, false, "Whether to use FP16 mode, only support 'trt' and 'paddle_trt' backend"); + +void PrintUsage() { + std::cout << "Usage: infer_demo --model model_path --image img_path --device [cpu|gpu] --backend " + "[default|ort|paddle|ov|trt|paddle_trt] " + "--use_fp16 false" + << std::endl; + std::cout << "Default value of device: cpu" << std::endl; + std::cout << "Default value of backend: default" << std::endl; + std::cout << "Default value of use_fp16: false" << std::endl; +} + +bool CreateRuntimeOption(fastdeploy::RuntimeOption* option) { + if (FLAGS_device == "gpu") { + option->UseGpu(); + if (FLAGS_backend == "ort") { + option->UseOrtBackend(); + } else if (FLAGS_backend == "paddle") { + option->UsePaddleBackend(); + } else if (FLAGS_backend == "trt" || + FLAGS_backend == "paddle_trt") { + option->UseTrtBackend(); + option->SetTrtInputShape("input", {1, 3, 128, 128}); + if (FLAGS_backend == "paddle_trt") { + option->EnablePaddleToTrt(); + } + if (FLAGS_use_fp16) { + option->EnableTrtFP16(); + } + } else if (FLAGS_backend == "default") { + return true; + } else { + std::cout << "While inference with GPU, only support default/ort/paddle/trt/paddle_trt now, " << FLAGS_backend << " is not supported." << std::endl; + return false; + } + } else if (FLAGS_device == "cpu") { + if (FLAGS_backend == "ort") { + option->UseOrtBackend(); + } else if (FLAGS_backend == "ov") { + option->UseOpenVINOBackend(); + } else if (FLAGS_backend == "paddle") { + option->UsePaddleBackend(); + } else if (FLAGS_backend == "default") { + return true; + } else { + std::cout << "While inference with CPU, only support default/ort/ov/paddle now, " << FLAGS_backend << " is not supported." << std::endl; + return false; + } + } else { + std::cerr << "Only support device CPU/GPU now, " << FLAGS_device << " is not supported." << std::endl; + return false; + } + + return true; +} + +int main(int argc, char* argv[]) { + google::ParseCommandLineFlags(&argc, &argv, true); + auto option = fastdeploy::RuntimeOption(); + if (!CreateRuntimeOption(&option)) { + PrintUsage(); + return -1; + } + + auto model = fastdeploy::vision::facealign::FaceLandmark1000(FLAGS_model, "", option); + if (!model.Initialized()) { + std::cerr << "Failed to initialize." << std::endl; + return -1; + } + + auto im = cv::imread(FLAGS_image); + auto im_bak = im.clone(); + + fastdeploy::vision::FaceAlignmentResult res; + if (!model.Predict(&im, &res)) { + std::cerr << "Failed to predict." << std::endl; + return -1; + } + std::cout << res.Str() << std::endl; + + auto vis_im = fastdeploy::vision::VisFaceAlignment(im_bak, res); + cv::imwrite("vis_result.jpg", vis_im); + std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl; + + return 0; +} diff --git a/examples/vision/facealign/face_landmark_1000/python/README.md b/examples/vision/facealign/face_landmark_1000/python/README.md new file mode 100644 index 0000000000..380d1cb270 --- /dev/null +++ b/examples/vision/facealign/face_landmark_1000/python/README.md @@ -0,0 +1,71 @@ +# FaceLandmark1000 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/download_prebuilt_libraries.md) +- 2. FastDeploy Python whl包安装，参考[FastDeploy Python安装](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) + +本目录下提供`infer.py`快速完成FaceLandmark1000在CPU/GPU，以及GPU上通过TensorRT加速部署的示例，保证 FastDeploy 版本 >= 0.7.0 支持FaceLandmark1000模型。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/facealign/facelandmark1000/python + +# 下载FaceLandmark1000模型文件和测试图片 +## 原版ONNX模型 +wget https://bj.bcebos.com/paddlehub/fastdeploy/FaceLandmark1000.onnx +wget https://bj.bcebos.com/paddlehub/fastdeploy/facealign_input.png + +# CPU推理 +python infer.py --model FaceLandmark1000.onnx --image facealign_input.png --device cpu +# GPU推理 +python infer.py --model FaceLandmark1000.onnx --image facealign_input.png --device gpu +# TRT推理 +python infer.py --model FaceLandmark1000.onnx --image facealign_input.png --device gpu --backend trt +``` + +运行完成可视化结果如下图所示 + +
+ +
+ +## FaceLandmark1000 Python接口 + +```python +fd.vision.facealign.FaceLandmark1000(model_file, params_file=None, runtime_option=None, model_format=ModelFormat.ONNX) +``` + +FaceLandmark1000模型加载和初始化，其中model_file为导出的ONNX模型格式 + +**参数** + +> * **model_file**(str): 模型文件路径 +> * **params_file**(str): 参数文件路径，当模型格式为ONNX格式时，此参数无需设定 +> * **runtime_option**(RuntimeOption): 后端推理配置，默认为None，即采用默认配置 +> * **model_format**(ModelFormat): 模型格式，默认为ONNX + +### predict函数 + +> ```python +> FaceLandmark1000.predict(input_image) +> ``` +> +> 模型预测结口，输入图像直接输出landmarks坐标结果。 +> +> **参数** +> +> > * **input_image**(np.ndarray): 输入数据，注意需为HWC，BGR格式 + +> **返回** +> +> > 返回`fastdeploy.vision.FaceAlignmentResult`结构体，结构体说明参考文档[视觉模型预测结果](../../../../../docs/api/vision_results/) + + +## 其它文档 + +- [FaceLandmark1000 模型介绍](..) +- [FaceLandmark1000 C++部署](../cpp) +- [模型预测结果说明](../../../../../docs/api/vision_results/) +- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md) diff --git a/examples/vision/facealign/face_landmark_1000/python/infer.py b/examples/vision/facealign/face_landmark_1000/python/infer.py new file mode 100644 index 0000000000..d6f52760c2 --- /dev/null +++ b/examples/vision/facealign/face_landmark_1000/python/infer.py @@ -0,0 +1,90 @@ +import fastdeploy as fd +import cv2 +import os + + +def parse_arguments(): + import argparse + import ast + parser = argparse.ArgumentParser() + parser.add_argument( + "--model", required=True, help="Path of FaceLandmark1000 model.") + parser.add_argument("--image", type=str, help="Path of test image file.") + parser.add_argument( + "--device", + type=str, + default='cpu', + help="Type of inference device, support 'cpu' or 'gpu'.") + parser.add_argument( + "--backend", + type=str, + default="ort", + help="inference backend, ort, ov, trt, paddle, paddle_trt.") + parser.add_argument( + "--enable_trt_fp16", + type=ast.literal_eval, + default=False, + help="whether enable fp16 in trt/paddle_trt backend") + return parser.parse_args() + + +def build_option(args): + option = fd.RuntimeOption() + device = args.device + backend = args.backend + enable_trt_fp16 = args.enable_trt_fp16 + if device == "gpu": + option.use_gpu() + if backend == "ort": + option.use_ort_backend() + elif backend == "paddle": + option.use_paddle_backend() + elif backend in ["trt", "paddle_trt"]: + option.use_trt_backend() + option.set_trt_input_shape("input", [1, 3, 112, 112]) + if backend == "paddle_trt": + option.enable_paddle_to_trt() + if enable_trt_fp16: + option.enable_trt_fp16() + elif backend == "default": + return option + else: + raise Exception( + "While inference with GPU, only support default/ort/paddle/trt/paddle_trt now, {} is not supported.". + format(backend)) + elif device == "cpu": + if backend == "ort": + option.use_ort_backend() + elif backend == "ov": + option.use_openvino_backend() + elif backend == "paddle": + option.use_paddle_backend() + elif backend == "default": + return option + else: + raise Exception( + "While inference with CPU, only support default/ort/ov/paddle now, {} is not supported.". + format(backend)) + else: + raise Exception( + "Only support device CPU/GPU now, {} is not supported.".format( + device)) + + return option + + +args = parse_arguments() + +# 配置runtime，加载模型 +runtime_option = build_option(args) +model = fd.vision.facealign.FaceLandmark1000( + args.model, runtime_option=runtime_option) + +# for image +im = cv2.imread(args.image) +result = model.predict(im.copy()) +print(result) +# 可视化结果 +vis_im = fd.vision.vis_face_alignment(im, result) +cv2.imwrite("visualized_result.jpg", vis_im) +print("Visualized result save in ./visualized_result.jpg") diff --git a/examples/vision/facealign/pipnet/README.md b/examples/vision/facealign/pipnet/README.md new file mode 100644 index 0000000000..504aac2241 --- /dev/null +++ b/examples/vision/facealign/pipnet/README.md @@ -0,0 +1,33 @@ +# PIPNet 模型部署 + +## 模型版本说明 + +- [PIPNet](https://github.com/jhb86253817/PIPNet/tree/b9eab58) + +## 支持模型列表 + +目前FastDeploy支持如下模型的部署 + +- [PIPNet 模型](https://github.com/jhb86253817/PIPNet) + +## 下载预训练模型 + +为了方便开发者的测试，下面提供了PIPNet导出的各系列模型，开发者可直接下载使用。 + +| 模型 | 参数大小 | 精度 | 备注 | +|:---------------------------------------------------------------- |:----- |:----- | :------ | +| [PIPNet19_ResNet18_AFLW](https://bj.bcebos.com/paddlehub/fastdeploy/pipnet_resnet18_10x19x32x256_aflw.onnx) | 45.6M | - | +| [PIPNet29_ResNet18_COFW](https://bj.bcebos.com/paddlehub/fastdeploy/pipnet_resnet18_10x29x32x256_cofw.onnx) | 46.1M | - | +| [PIPNet68_ResNet18_300W](https://bj.bcebos.com/paddlehub/fastdeploy/pipnet_resnet18_10x68x32x256_300w.onnx) | 47.9M | - | +| [PIPNet98_ResNet18_WFLW](https://bj.bcebos.com/paddlehub/fastdeploy/pipnet_resnet18_10x98x32x256_wflw.onnx) | 49.3M | - | +| [PIPNet19_ResNet101_AFLW](https://bj.bcebos.com/paddlehub/fastdeploy/pipnet_resnet101_10x19x32x256_aflw.onnx) | 173.4M | - | +| [PIPNet29_ResNet101_COFW](https://bj.bcebos.com/paddlehub/fastdeploy/pipnet_resnet101_10x29x32x256_cofw.onnx) | 175.3M | - | +| [PIPNet68_ResNet101_300W](https://bj.bcebos.com/paddlehub/fastdeploy/pipnet_resnet101_10x68x32x256_300w.onnx) | 182.6M | - | +| [PIPNet98_ResNet101_WFLW](https://bj.bcebos.com/paddlehub/fastdeploy/pipnet_resnet101_10x98x32x256_wflw.onnx) | 188.3M | - | + + + +## 详细部署文档 + +- [Python部署](python) +- [C++部署](cpp) diff --git a/examples/vision/facealign/pipnet/cpp/CMakeLists.txt b/examples/vision/facealign/pipnet/cpp/CMakeLists.txt new file mode 100644 index 0000000000..c417fcb388 --- /dev/null +++ b/examples/vision/facealign/pipnet/cpp/CMakeLists.txt @@ -0,0 +1,18 @@ +PROJECT(infer_demo C CXX) +CMAKE_MINIMUM_REQUIRED (VERSION 3.10) + +# 指定下载解压后的fastdeploy库路径 +option(FASTDEPLOY_INSTALL_DIR "Path of downloaded fastdeploy sdk.") +include(${FASTDEPLOY_INSTALL_DIR}/utils/gflags.cmake) +include(${FASTDEPLOY_INSTALL_DIR}/FastDeploy.cmake) + +# 添加FastDeploy依赖头文件 +include_directories(${FASTDEPLOY_INCS}) + +add_executable(infer_demo ${PROJECT_SOURCE_DIR}/infer.cc) +# 添加FastDeploy库依赖 +if(UNIX AND (NOT APPLE) AND (NOT ANDROID)) + target_link_libraries(infer_demo ${FASTDEPLOY_LIBS} gflags pthread) +else() + target_link_libraries(infer_demo ${FASTDEPLOY_LIBS} gflags) +endif() diff --git a/examples/vision/facealign/pipnet/cpp/README.md b/examples/vision/facealign/pipnet/cpp/README.md new file mode 100644 index 0000000000..3f11bf62b4 --- /dev/null +++ b/examples/vision/facealign/pipnet/cpp/README.md @@ -0,0 +1,84 @@ +# PIPNet C++部署示例 + +本目录下提供`infer.cc`快速完成PIPNet在CPU/GPU，以及GPU上通过TensorRT加速部署的示例。 + +在部署前，需确认以下两个步骤 + +- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) +- 2. 根据开发环境，下载预编译部署库和samples代码，参考[FastDeploy预编译库](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) + +以Linux上CPU推理为例，在本目录执行如下命令即可完成编译测试，保证 FastDeploy 版本0.7.0以上(x.x.x >= 0.7.0)支持PIPNet模型 + +```bash +mkdir build +cd build +wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-x.x.x.tgz +tar xvf fastdeploy-linux-x64-x.x.x.tgz +cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x +make -j + +#下载官方转换好的 PIPNet 模型文件和测试图片 +wget https://bj.bcebos.com/paddlehub/fastdeploy/pipnet_resnet18_10x19x32x256_aflw.onnx +wget https://bj.bcebos.com/paddlehub/fastdeploy/facealign_input.png + +# CPU推理 +./infer_demo --model pipnet_resnet18_10x19x32x256_aflw.onnx --image facealign_input.png --device cpu +# GPU推理 +./infer_demo --model pipnet_resnet18_10x19x32x256_aflw.onnx --image facealign_input.png --device gpu +# GPU上TensorRT推理 +./infer_demo --model pipnet_resnet18_10x19x32x256_aflw.onnx --image facealign_input.png --device gpu --backend trt +``` + +运行完成可视化结果如下图所示 + +
+ +
+ +以上命令只适用于Linux或MacOS, Windows下SDK的使用方式请参考: +- [如何在Windows中使用FastDeploy C++ SDK](../../../../../docs/cn/faq/use_sdk_on_windows.md) + +## PIPNet C++接口 + +### PIPNet 类 + +```c++ +fastdeploy::vision::facealign::PIPNet( + const string& model_file, + const string& params_file = "", + const RuntimeOption& runtime_option = RuntimeOption(), + const ModelFormat& model_format = ModelFormat::ONNX) +``` + +PIPNet模型加载和初始化，其中model_file为导出的ONNX模型格式。 + +**参数** + +> * **model_file**(str): 模型文件路径 +> * **params_file**(str): 参数文件路径，当模型格式为ONNX时，此参数传入空字符串即可 +> * **runtime_option**(RuntimeOption): 后端推理配置，默认为None，即采用默认配置 +> * **model_format**(ModelFormat): 模型格式，默认为ONNX格式 + +#### Predict函数 + +> ```c++ +> PIPNet::Predict(cv::Mat* im, FaceAlignmentResult* result) +> ``` +> +> 模型预测接口，输入图像直接输出landmarks结果。 +> +> **参数** +> +> > * **im**: 输入图像，注意需为HWC，BGR格式 +> > * **result**: landmarks结果, FaceAlignmentResult说明参考[视觉模型预测结果](../../../../../docs/api/vision_results/) + +### 类成员变量 + +用户可按照自己的实际需求，修改下列预处理参数，从而影响最终的推理和部署效果 + +> > * **size**(vector<int>): 通过此参数修改预处理过程中resize的大小，包含两个整型元素，表示[width, height], 默认值为[256, 256] + +- [模型介绍](../../) +- [Python部署](../python) +- [视觉模型预测结果](../../../../../docs/api/vision_results/) +- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md) diff --git a/examples/vision/facealign/pipnet/cpp/infer.cc b/examples/vision/facealign/pipnet/cpp/infer.cc new file mode 100644 index 0000000000..cba9667d92 --- /dev/null +++ b/examples/vision/facealign/pipnet/cpp/infer.cc @@ -0,0 +1,111 @@ +// 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 "fastdeploy/vision.h" +#include "gflags/gflags.h" + +DEFINE_string(model, "", "Directory of the inference model."); +DEFINE_string(image, "", "Path of the image file."); +DEFINE_string(device, "cpu", + "Type of inference device, support 'cpu' or 'gpu'."); +DEFINE_string(backend, "default", + "The inference runtime backend, support: ['default', 'ort', " + "'paddle', 'ov', 'trt', 'paddle_trt']"); +DEFINE_bool(use_fp16, false, "Whether to use FP16 mode, only support 'trt' and 'paddle_trt' backend"); +DEFINE_int32(num_landmarks, 19, "number of landmarks for PIPNet, the num_lms should be a number in {19, 29, 68, 98}"); + +void PrintUsage() { + std::cout << "Usage: infer_demo --model model_path --image img_path --device [cpu|gpu] --backend " + "[default|ort|paddle|ov|trt|paddle_trt] " + "--use_fp16 false" + << std::endl; + std::cout << "Default value of device: cpu" << std::endl; + std::cout << "Default value of backend: default" << std::endl; + std::cout << "Default value of use_fp16: false" << std::endl; +} + +bool CreateRuntimeOption(fastdeploy::RuntimeOption* option) { + if (FLAGS_device == "gpu") { + option->UseGpu(); + if (FLAGS_backend == "ort") { + option->UseOrtBackend(); + } else if (FLAGS_backend == "paddle") { + option->UsePaddleBackend(); + } else if (FLAGS_backend == "trt" || + FLAGS_backend == "paddle_trt") { + option->UseTrtBackend(); + option->SetTrtInputShape("input", {1, 3, 128, 128}); + if (FLAGS_backend == "paddle_trt") { + option->EnablePaddleToTrt(); + } + if (FLAGS_use_fp16) { + option->EnableTrtFP16(); + } + } else if (FLAGS_backend == "default") { + return true; + } else { + std::cout << "While inference with GPU, only support default/ort/paddle/trt/paddle_trt now, " << FLAGS_backend << " is not supported." << std::endl; + return false; + } + } else if (FLAGS_device == "cpu") { + if (FLAGS_backend == "ort") { + option->UseOrtBackend(); + } else if (FLAGS_backend == "ov") { + option->UseOpenVINOBackend(); + } else if (FLAGS_backend == "paddle") { + option->UsePaddleBackend(); + } else if (FLAGS_backend == "default") { + return true; + } else { + std::cout << "While inference with CPU, only support default/ort/ov/paddle now, " << FLAGS_backend << " is not supported." << std::endl; + return false; + } + } else { + std::cerr << "Only support device CPU/GPU now, " << FLAGS_device << " is not supported." << std::endl; + return false; + } + + return true; +} + +int main(int argc, char* argv[]) { + google::ParseCommandLineFlags(&argc, &argv, true); + auto option = fastdeploy::RuntimeOption(); + if (!CreateRuntimeOption(&option)) { + PrintUsage(); + return -1; + } + + auto model = fastdeploy::vision::facealign::PIPNet(FLAGS_model, "", option); + if (!model.Initialized()) { + std::cerr << "Failed to initialize." << std::endl; + return -1; + } + model.SetNumLandmarks(FLAGS_num_landmarks); + auto im = cv::imread(FLAGS_image); + auto im_bak = im.clone(); + + fastdeploy::vision::FaceAlignmentResult res; + if (!model.Predict(&im, &res)) { + std::cerr << "Failed to predict." << std::endl; + return -1; + } + std::cout << res.Str() << std::endl; + + auto vis_im = fastdeploy::vision::VisFaceAlignment(im_bak, res); + cv::imwrite("vis_result.jpg", vis_im); + std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl; + + return 0; +} diff --git a/examples/vision/facealign/pipnet/python/README.md b/examples/vision/facealign/pipnet/python/README.md new file mode 100644 index 0000000000..ae46849c38 --- /dev/null +++ b/examples/vision/facealign/pipnet/python/README.md @@ -0,0 +1,71 @@ +# PIPNet 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/download_prebuilt_libraries.md) +- 2. FastDeploy Python whl包安装，参考[FastDeploy Python安装](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md) + +本目录下提供`infer.py`快速完成PIPNet在CPU/GPU，以及GPU上通过TensorRT加速部署的示例，保证 FastDeploy 版本 >= 0.7.0 支持PIPNet模型。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/facealign/pipnet/python + +# 下载PIPNet模型文件和测试图片以及视频 +## 原版ONNX模型 +wget https://bj.bcebos.com/paddlehub/fastdeploy/pipnet_resnet18_10x19x32x256_aflw.onnx +wget https://bj.bcebos.com/paddlehub/fastdeploy/facealign_input.png + +# CPU推理 +python infer.py --model pipnet_resnet18_10x19x32x256_aflw.onnx --image facealign_input.png --device cpu +# GPU推理 +python infer.py --model pipnet_resnet18_10x19x32x256_aflw.onnx --image facealign_input.png --device gpu +# TRT推理 +python infer.py --model pipnet_resnet18_10x19x32x256_aflw.onnx --image facealign_input.png --device gpu --backend trt +``` + +运行完成可视化结果如下图所示 + +
+ +
+ +## PIPNet Python接口 + +```python +fd.vision.facealign.PIPNet(model_file, params_file=None, runtime_option=None, model_format=ModelFormat.ONNX) +``` + +PIPNet模型加载和初始化，其中model_file为导出的ONNX模型格式 + +**参数** + +> * **model_file**(str): 模型文件路径 +> * **params_file**(str): 参数文件路径，当模型格式为ONNX格式时，此参数无需设定 +> * **runtime_option**(RuntimeOption): 后端推理配置，默认为None，即采用默认配置 +> * **model_format**(ModelFormat): 模型格式，默认为ONNX + +### predict函数 + +> ```python +> PIPNet.predict(input_image) +> ``` +> +> 模型预测结口，输入图像直接输出landmarks坐标结果。 +> +> **参数** +> +> > * **input_image**(np.ndarray): 输入数据，注意需为HWC，BGR格式 + +> **返回** +> +> > 返回`fastdeploy.vision.FaceAlignmentResult`结构体，结构体说明参考文档[视觉模型预测结果](../../../../../docs/api/vision_results/) + + +## 其它文档 + +- [PIPNet 模型介绍](..) +- [PIPNet C++部署](../cpp) +- [模型预测结果说明](../../../../../docs/api/vision_results/) +- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md) diff --git a/examples/vision/facealign/pipnet/python/infer.py b/examples/vision/facealign/pipnet/python/infer.py new file mode 100644 index 0000000000..fa34d38444 --- /dev/null +++ b/examples/vision/facealign/pipnet/python/infer.py @@ -0,0 +1,93 @@ +import fastdeploy as fd +import cv2 +import os + + +def parse_arguments(): + import argparse + import ast + parser = argparse.ArgumentParser() + parser.add_argument("--model", required=True, help="Path of PIPNet model.") + parser.add_argument("--image", type=str, help="Path of test image file.") + parser.add_argument( + "--device", + type=str, + default='cpu', + help="Type of inference device, support 'cpu' or 'gpu'.") + parser.add_argument( + "--backend", + type=str, + default="ort", + help="inference backend, ort, ov, trt, paddle, paddle_trt.") + parser.add_argument( + "--enable_trt_fp16", + type=ast.literal_eval, + default=False, + help="whether enable fp16 in trt/paddle_trt backend") + parser.add_argument( + "--num_landmarks", + type=int, + default=19, + help="whether enable fp16 in trt/paddle_trt backend") + return parser.parse_args() + + +def build_option(args): + option = fd.RuntimeOption() + device = args.device + backend = args.backend + enable_trt_fp16 = args.enable_trt_fp16 + if device == "gpu": + option.use_gpu() + if backend == "ort": + option.use_ort_backend() + elif backend == "paddle": + option.use_paddle_backend() + elif backend in ["trt", "paddle_trt"]: + option.use_trt_backend() + option.set_trt_input_shape("input", [1, 3, 112, 112]) + if backend == "paddle_trt": + option.enable_paddle_to_trt() + if enable_trt_fp16: + option.enable_trt_fp16() + elif backend == "default": + return option + else: + raise Exception( + "While inference with GPU, only support default/ort/paddle/trt/paddle_trt now, {} is not supported.". + format(backend)) + elif device == "cpu": + if backend == "ort": + option.use_ort_backend() + elif backend == "ov": + option.use_openvino_backend() + elif backend == "paddle": + option.use_paddle_backend() + elif backend == "default": + return option + else: + raise Exception( + "While inference with CPU, only support default/ort/ov/paddle now, {} is not supported.". + format(backend)) + else: + raise Exception( + "Only support device CPU/GPU now, {} is not supported.".format( + device)) + + return option + + +args = parse_arguments() + +# 配置runtime，加载模型 +runtime_option = build_option(args) +model = fd.vision.facealign.PIPNet(args.model, runtime_option=runtime_option) +model.num_landmarks = args.num_landmarks +# for image +im = cv2.imread(args.image) +result = model.predict(im.copy()) +print(result) +# 可视化结果 +vis_im = fd.vision.vis_face_alignment(im, result) +cv2.imwrite("visualized_result.jpg", vis_im) +print("Visualized result save in ./visualized_result.jpg") diff --git a/fastdeploy/vision.h b/fastdeploy/vision.h index 2f8c706613..c9719cc9ea 100755 --- a/fastdeploy/vision.h +++ b/fastdeploy/vision.h @@ -34,6 +34,8 @@ #include "fastdeploy/vision/facedet/contrib/ultraface.h" #include "fastdeploy/vision/facedet/contrib/yolov5face.h" #include "fastdeploy/vision/facealign/contrib/pfld.h" +#include "fastdeploy/vision/facealign/contrib/face_landmark_1000.h" +#include "fastdeploy/vision/facealign/contrib/pipnet.h" #include "fastdeploy/vision/faceid/contrib/adaface.h" #include "fastdeploy/vision/faceid/contrib/arcface.h" #include "fastdeploy/vision/faceid/contrib/cosface.h" diff --git a/fastdeploy/vision/common/processors/color_space_convert.cc b/fastdeploy/vision/common/processors/color_space_convert.cc index 4ccfb65100..c486c53794 100644 --- a/fastdeploy/vision/common/processors/color_space_convert.cc +++ b/fastdeploy/vision/common/processors/color_space_convert.cc @@ -16,7 +16,7 @@ namespace fastdeploy { namespace vision { -bool BGR2RGB::ImplByOpenCV(Mat* mat) { +bool BGR2RGB::ImplByOpenCV(FDMat* mat) { cv::Mat* im = mat->GetOpenCVMat(); cv::Mat new_im; cv::cvtColor(*im, new_im, cv::COLOR_BGR2RGB); @@ -25,7 +25,7 @@ bool BGR2RGB::ImplByOpenCV(Mat* mat) { } #ifdef ENABLE_FLYCV -bool BGR2RGB::ImplByFlyCV(Mat* mat) { +bool BGR2RGB::ImplByFlyCV(FDMat* mat) { fcv::Mat* im = mat->GetFlyCVMat(); if (im->channels() != 3) { FDERROR << "[BGR2RGB] The channel of input image must be 3, but not it's " @@ -39,7 +39,7 @@ bool BGR2RGB::ImplByFlyCV(Mat* mat) { } #endif -bool RGB2BGR::ImplByOpenCV(Mat* mat) { +bool RGB2BGR::ImplByOpenCV(FDMat* mat) { cv::Mat* im = mat->GetOpenCVMat(); cv::Mat new_im; cv::cvtColor(*im, new_im, cv::COLOR_RGB2BGR); @@ -48,7 +48,7 @@ bool RGB2BGR::ImplByOpenCV(Mat* mat) { } #ifdef ENABLE_FLYCV -bool RGB2BGR::ImplByFlyCV(Mat* mat) { +bool RGB2BGR::ImplByFlyCV(FDMat* mat) { fcv::Mat* im = mat->GetFlyCVMat(); if (im->channels() != 3) { FDERROR << "[RGB2BGR] The channel of input image must be 3, but not it's " @@ -62,15 +62,72 @@ bool RGB2BGR::ImplByFlyCV(Mat* mat) { } #endif -bool BGR2RGB::Run(Mat* mat, ProcLib lib) { +bool BGR2GRAY::ImplByOpenCV(FDMat* mat) { + cv::Mat* im = mat->GetOpenCVMat(); + cv::Mat new_im; + cv::cvtColor(*im, new_im, cv::COLOR_BGR2GRAY); + mat->SetMat(new_im); + mat->SetChannels(1); + return true; +} + +#ifdef ENABLE_FLYCV +bool BGR2GRAY::ImplByFalconCV(FDMat* mat) { + fcv::Mat* im = mat->GetFalconCVMat(); + if (im->channels() != 3) { + FDERROR << "[BGR2GRAY] The channel of input image must be 3, but not it's " << im->channels() << "." << std::endl; + return false; + } + fcv::Mat new_im; + fcv::cvt_color(*im, new_im, fcv::ColorConvertType::CVT_PA_BGR2GRAY); + mat->SetMat(new_im); + return true; +} +#endif + +bool RGB2GRAY::ImplByOpenCV(FDMat* mat) { + cv::Mat* im = mat->GetOpenCVMat(); + cv::Mat new_im; + cv::cvtColor(*im, new_im, cv::COLOR_RGB2GRAY); + mat->SetMat(new_im); + return true; +} + +#ifdef ENABLE_FLYCV +bool RGB2GRAY::ImplByFalconCV(FDMat* mat) { + fcv::Mat* im = mat->GetFalconCVMat(); + if (im->channels() != 3) { + FDERROR << "[RGB2GRAY] The channel of input image must be 3, but not it's " << im->channels() << "." << std::endl; + return false; + } + fcv::Mat new_im; + fcv::cvt_color(*im, new_im, fcv::ColorConvertType::CVT_PA_RGB2GRAY); + mat->SetMat(new_im); + return true; +} +#endif + + +bool BGR2RGB::Run(FDMat* mat, ProcLib lib) { auto b = BGR2RGB(); return b(mat, lib); } -bool RGB2BGR::Run(Mat* mat, ProcLib lib) { +bool RGB2BGR::Run(FDMat* mat, ProcLib lib) { auto r = RGB2BGR(); return r(mat, lib); } +bool BGR2GRAY::Run(FDMat* mat, ProcLib lib) { + auto b = BGR2GRAY(); + return b(mat, lib); +} + +bool RGB2GRAY::Run(FDMat* mat, ProcLib lib) { + auto r = RGB2GRAY(); + return r(mat, lib); +} + + } // namespace vision } // namespace fastdeploy diff --git a/fastdeploy/vision/common/processors/color_space_convert.h b/fastdeploy/vision/common/processors/color_space_convert.h index e090bc62d5..f9cb10a190 100644 --- a/fastdeploy/vision/common/processors/color_space_convert.h +++ b/fastdeploy/vision/common/processors/color_space_convert.h @@ -21,24 +21,48 @@ namespace vision { class FASTDEPLOY_DECL BGR2RGB : public Processor { public: - bool ImplByOpenCV(Mat* mat); + bool ImplByOpenCV(FDMat* mat); #ifdef ENABLE_FLYCV - bool ImplByFlyCV(Mat* mat); + bool ImplByFlyCV(FDMat* mat); #endif virtual std::string Name() { return "BGR2RGB"; } - static bool Run(Mat* mat, ProcLib lib = ProcLib::DEFAULT); + static bool Run(FDMat* mat, ProcLib lib = ProcLib::DEFAULT); }; class FASTDEPLOY_DECL RGB2BGR : public Processor { public: - bool ImplByOpenCV(Mat* mat); + bool ImplByOpenCV(FDMat* mat); #ifdef ENABLE_FLYCV - bool ImplByFlyCV(Mat* mat); + bool ImplByFlyCV(FDMat* mat); #endif std::string Name() { return "RGB2BGR"; } - static bool Run(Mat* mat, ProcLib lib = ProcLib::DEFAULT); + static bool Run(FDMat* mat, ProcLib lib = ProcLib::DEFAULT); }; + +class FASTDEPLOY_DECL BGR2GRAY : public Processor { + public: + bool ImplByOpenCV(FDMat* mat); +#ifdef ENABLE_FLYCV + bool ImplByFalconCV(FDMat* mat); +#endif + virtual std::string Name() { return "BGR2GRAY"; } + + static bool Run(FDMat* mat, ProcLib lib = ProcLib::OPENCV); +}; + +class FASTDEPLOY_DECL RGB2GRAY : public Processor { + public: + bool ImplByOpenCV(FDMat* mat); +#ifdef ENABLE_FLYCV + bool ImplByFalconCV(FDMat* mat); +#endif + std::string Name() { return "RGB2GRAY"; } + + static bool Run(FDMat* mat, ProcLib lib = ProcLib::OPENCV); +}; + + } // namespace vision } // namespace fastdeploy diff --git a/fastdeploy/vision/common/result.cc b/fastdeploy/vision/common/result.cc index 4d746797f4..ddb5f616a3 100755 --- a/fastdeploy/vision/common/result.cc +++ b/fastdeploy/vision/common/result.cc @@ -259,7 +259,10 @@ std::string FaceAlignmentResult::Str() { std::string out; out = "FaceAlignmentResult: [x, y]\n"; - for (size_t i = 0; i < landmarks.size(); ++i) { + out = out + "There are " +std::to_string(landmarks.size()) + " landmarks, the top 10 are listed as below:\n"; + int landmarks_size = landmarks.size(); + size_t result_length = std::min(10, landmarks_size); + for (size_t i = 0; i < result_length; ++i) { out = out + std::to_string(landmarks[i][0]) + "," + std::to_string(landmarks[i][1]) + "\n"; } diff --git a/fastdeploy/vision/facealign/contrib/face_landmark_1000.cc b/fastdeploy/vision/facealign/contrib/face_landmark_1000.cc new file mode 100644 index 0000000000..f7b689575c --- /dev/null +++ b/fastdeploy/vision/facealign/contrib/face_landmark_1000.cc @@ -0,0 +1,134 @@ +// 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 "fastdeploy/vision/facealign/contrib/face_landmark_1000.h" + +#include "fastdeploy/utils/perf.h" +#include "fastdeploy/vision/utils/utils.h" + +namespace fastdeploy { + +namespace vision { + +namespace facealign { + +FaceLandmark1000::FaceLandmark1000(const std::string& model_file, + const std::string& params_file, + const RuntimeOption& custom_option, + const ModelFormat& model_format) { + if (model_format == ModelFormat::ONNX) { + valid_cpu_backends = {Backend::OPENVINO, Backend::ORT}; + valid_gpu_backends = {Backend::ORT, Backend::TRT}; + } else { + valid_cpu_backends = {Backend::PDINFER, Backend::ORT}; + valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT}; + } + runtime_option = custom_option; + runtime_option.model_format = model_format; + runtime_option.model_file = model_file; + runtime_option.params_file = params_file; + initialized = Initialize(); +} + +bool FaceLandmark1000::Initialize() { + // parameters for preprocess + size_ = {128, 128}; + + if (!InitRuntime()) { + FDERROR << "Failed to initialize fastdeploy backend." << std::endl; + return false; + } + return true; +} + +bool FaceLandmark1000::Preprocess( + Mat* mat, FDTensor* output, + std::map>* im_info) { + // Resize + int resize_w = size_[0]; + int resize_h = size_[1]; + if (resize_h != mat->Height() || resize_w != mat->Width()) { + Resize::Run(mat, resize_w, resize_h); + } + + // BRG2GRAY + BGR2GRAY::Run(mat); + + // Record output shape of preprocessed image + (*im_info)["output_shape"] = {mat->Height(), mat->Width()}; + HWC2CHW::Run(mat); + Cast::Run(mat, "float"); + mat->ShareWithTensor(output); + output->shape.insert(output->shape.begin(), 1); // reshape to n, h, w, c + return true; +} + +bool FaceLandmark1000::Postprocess( + FDTensor& infer_result, FaceAlignmentResult* result, + const std::map>& im_info) { + FDASSERT(infer_result.shape[0] == 1, "Only support batch = 1 now."); + if (infer_result.dtype != FDDataType::FP32) { + FDERROR << "Only support post process with float32 data." << std::endl; + return false; + } + + auto iter_in = im_info.find("input_shape"); + FDASSERT(iter_in != im_info.end(), "Cannot find input_shape from im_info."); + int in_h = iter_in->second[0]; + int in_w = iter_in->second[1]; + + result->Clear(); + float* data = static_cast(infer_result.Data()); + for (size_t i = 0; i < infer_result.shape[1]; i += 2) { + float x = data[i]; + float y = data[i + 1]; + x = std::min(std::max(0.f, x), 1.0f); + y = std::min(std::max(0.f, y), 1.0f); + // decode landmarks (default 106 landmarks) + result->landmarks.emplace_back(std::array{x * in_w, y * in_h}); + } + + return true; +} + +bool FaceLandmark1000::Predict(cv::Mat* im, FaceAlignmentResult* result) { + Mat mat(*im); + std::vector input_tensors(1); + + std::map> im_info; + + // Record the shape of image and the shape of preprocessed image + im_info["input_shape"] = {mat.Height(), mat.Width()}; + im_info["output_shape"] = {mat.Height(), mat.Width()}; + + if (!Preprocess(&mat, &input_tensors[0], &im_info)) { + FDERROR << "Failed to preprocess input image." << std::endl; + return false; + } + input_tensors[0].name = InputInfoOfRuntime(0).name; + std::vector output_tensors; + if (!Infer(input_tensors, &output_tensors)) { + FDERROR << "Failed to inference." << std::endl; + return false; + } + if (!Postprocess(output_tensors[0], result, im_info)) { + FDERROR << "Failed to post process." << std::endl; + return false; + } + return true; +} + +} // namespace facealign +} // namespace vision +} // namespace fastdeploy \ No newline at end of file diff --git a/fastdeploy/vision/facealign/contrib/face_landmark_1000.h b/fastdeploy/vision/facealign/contrib/face_landmark_1000.h new file mode 100644 index 0000000000..909edfe155 --- /dev/null +++ b/fastdeploy/vision/facealign/contrib/face_landmark_1000.h @@ -0,0 +1,75 @@ +// 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/fastdeploy_model.h" +#include "fastdeploy/vision/common/processors/transform.h" +#include "fastdeploy/vision/common/result.h" + +namespace fastdeploy { + +namespace vision { + +namespace facealign { +/*! @brief FaceLandmark1000 model object used when to load a FaceLandmark1000 model exported by FaceLandmark1000. + */ +class FASTDEPLOY_DECL FaceLandmark1000 : public FastDeployModel { + public: + /** \brief Set path of model file and the configuration of runtime. + * + * \param[in] model_file Path of model file, e.g ./face_landmarks_1000.onnx + * \param[in] params_file Path of parameter file, e.g ppyoloe/model.pdiparams, if the model format is ONNX, this parameter will be ignored + * \param[in] custom_option RuntimeOption for inference, the default will use cpu, and choose the backend defined in "valid_cpu_backends" + * \param[in] model_format Model format of the loaded model, default is ONNX format + */ + FaceLandmark1000(const std::string& model_file, + const std::string& params_file = "", + const RuntimeOption& custom_option = RuntimeOption(), + const ModelFormat& model_format = ModelFormat::ONNX); + + std::string ModelName() const { return "FaceLandmark1000"; } + /** \brief Predict the face detection result for an input image + * + * \param[in] im The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format + * \param[in] result The output face detection result will be writen to this structure + * \return true if the prediction successed, otherwise false + */ + virtual bool Predict(cv::Mat* im, FaceAlignmentResult* result); + + /** \brief Get the input size of image + * + * \return Vector of int values, default {128,128} + */ + std::vector GetSize() { return size_; } + /** \brief Set the input size of image + * + * \param[in] size Vector of int values which represents {width, height} of image + */ + void SetSize(const std::vector& size) { size_ = size; } + + private: + bool Initialize(); + + bool Preprocess(Mat* mat, FDTensor* outputs, + std::map>* im_info); + + bool Postprocess(FDTensor& infer_result, FaceAlignmentResult* result, + const std::map>& im_info); + // tuple of (width, height), default (128, 128) + std::vector size_; +}; + +} // namespace facealign +} // namespace vision +} // namespace fastdeploy diff --git a/fastdeploy/vision/facealign/contrib/face_landmark_1000_pybind.cc b/fastdeploy/vision/facealign/contrib/face_landmark_1000_pybind.cc new file mode 100644 index 0000000000..6cb337e535 --- /dev/null +++ b/fastdeploy/vision/facealign/contrib/face_landmark_1000_pybind.cc @@ -0,0 +1,34 @@ +// 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 "fastdeploy/pybind/main.h" + +namespace fastdeploy { +void BindFaceLandmark1000(pybind11::module& m) { + pybind11::class_( + m, "FaceLandmark1000") + .def(pybind11::init()) + .def( + "predict", + [](vision::facealign::FaceLandmark1000& self, pybind11::array& data) { + auto mat = PyArrayToCvMat(data); + vision::FaceAlignmentResult res; + self.Predict(&mat, &res); + return res; + }) + .def_property("size", &vision::facealign::FaceLandmark1000::GetSize, + &vision::facealign::FaceLandmark1000::SetSize); +} +} // namespace fastdeploy \ No newline at end of file diff --git a/fastdeploy/vision/facealign/contrib/pipnet.cc b/fastdeploy/vision/facealign/contrib/pipnet.cc new file mode 100644 index 0000000000..27ec35c0dd --- /dev/null +++ b/fastdeploy/vision/facealign/contrib/pipnet.cc @@ -0,0 +1,687 @@ +// 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 "fastdeploy/vision/facealign/contrib/pipnet.h" + +#include "fastdeploy/vision/utils/utils.h" + +namespace fastdeploy { + +namespace vision { + +namespace facealign { + +void PIPNet::GenerateLandmarks(std::vector& infer_result, + FaceAlignmentResult* result, float img_height, + float img_width) { + FDTensor outputs_cls = infer_result.at(0); + FDTensor outputs_x = infer_result.at(1); + FDTensor outputs_y = infer_result.at(2); + FDTensor outputs_nb_x = infer_result.at(3); + FDTensor outputs_nb_y = infer_result.at(4); + int grid_h = outputs_cls.shape[2]; // 8 + int grid_w = outputs_cls.shape[3]; // 8 + int grid_length = grid_h * grid_w; // 8 * 8 = 64 + int input_h = size_[1]; + int input_w = size_[0]; + // fetch data from pointers + const float* outputs_cls_ptr = static_cast(outputs_cls.Data()); + const float* outputs_x_ptr = static_cast(outputs_x.Data()); + const float* outputs_y_ptr = static_cast(outputs_y.Data()); + const float* outputs_nb_x_ptr = static_cast(outputs_nb_x.Data()); + const float* outputs_nb_y_ptr = static_cast(outputs_nb_y.Data()); + + // find max_ids + std::vector max_ids(num_landmarks_); + for (unsigned int i = 0; i < num_landmarks_; ++i) { + const float* score_ptr = outputs_cls_ptr + i * grid_length; + unsigned int max_id = 0; + float max_score = score_ptr[0]; + for (unsigned int j = 0; j < grid_length; ++j) { + if (score_ptr[j] > max_score) { + max_score = score_ptr[j]; + max_id = j; + } + } + max_ids[i] = max_id; // range 0~64 + } + // find x & y offsets + std::vector output_x_select(num_landmarks_); + std::vector output_y_select(num_landmarks_); + for (unsigned int i = 0; i < num_landmarks_; ++i) { + const float* offset_x_ptr = outputs_x_ptr + i * grid_length; + const float* offset_y_ptr = outputs_y_ptr + i * grid_length; + const unsigned int max_id = max_ids.at(i); + output_x_select[i] = offset_x_ptr[max_id]; + output_y_select[i] = offset_y_ptr[max_id]; + } + + // find nb_x & nb_y offsets + std::map> output_nb_x_select; + std::map> output_nb_y_select; + // initialize offsets map + for (unsigned int i = 0; i < num_landmarks_; ++i) { + std::vector nb_x_offset(num_nb_); + std::vector nb_y_offset(num_nb_); + output_nb_x_select[i] = nb_x_offset; + output_nb_y_select[i] = nb_y_offset; + } + for (unsigned int i = 0; i < num_landmarks_; ++i) { + for (unsigned int j = 0; j < num_nb_; ++j) { + const unsigned int max_id = max_ids.at(i); + const float* offset_nb_x_ptr = + outputs_nb_x_ptr + (i * num_nb_ + j) * grid_length; + const float* offset_nb_y_ptr = + outputs_nb_y_ptr + (i * num_nb_ + j) * grid_length; + output_nb_x_select[i][j] = offset_nb_x_ptr[max_id]; + output_nb_y_select[i][j] = offset_nb_y_ptr[max_id]; + } + } + + // calculate coords + std::vector lms_pred_x(num_landmarks_); // 19 + std::vector lms_pred_y(num_landmarks_); // 19 + std::map> lms_pred_nb_x; // 19,10 + std::map> lms_pred_nb_y; // 19,10 + + // initialize pred maps + for (unsigned int i = 0; i < num_landmarks_; ++i) { + std::vector nb_x_offset(num_nb_); + std::vector nb_y_offset(num_nb_); + lms_pred_nb_x[i] = nb_x_offset; + lms_pred_nb_y[i] = nb_y_offset; + } + for (unsigned int i = 0; i < num_landmarks_; ++i) { + float cx = static_cast(max_ids.at(i) % grid_w); + float cy = static_cast(max_ids.at(i) / grid_w); + // calculate coords & normalize + lms_pred_x[i] = + ((cx + output_x_select[i]) * (float)net_stride_) / (float)input_w; + lms_pred_y[i] = + ((cy + output_y_select[i]) * (float)net_stride_) / (float)input_h; + for (unsigned int j = 0; j < num_nb_; ++j) { + lms_pred_nb_x[i][j] = + ((cx + output_nb_x_select[i][j]) * (float)net_stride_) / + (float)input_w; + lms_pred_nb_y[i][j] = + ((cy + output_nb_y_select[i][j]) * (float)net_stride_) / + (float)input_h; + } + } + + // reverse indexes + std::map> + tmp_nb_x; // 19,max_len_map_[num_landmarks_] + std::map> + tmp_nb_y; // 19,max_len_map_[num_landmarks_] + // initialize reverse maps + for (unsigned int i = 0; i < num_landmarks_; ++i) { + std::vector tmp_x(max_len_map_[num_landmarks_]); + std::vector tmp_y(max_len_map_[num_landmarks_]); + tmp_nb_x[i] = tmp_x; + tmp_nb_y[i] = tmp_y; + } + for (unsigned int i = 0; i < num_landmarks_; ++i) { + for (unsigned int j = 0; j < max_len_map_[num_landmarks_]; ++j) { + unsigned int ri = + reverse_index1_map_[num_landmarks_] + [i * max_len_map_[num_landmarks_] + j]; + unsigned int rj = + reverse_index2_map_[num_landmarks_] + [i * max_len_map_[num_landmarks_] + j]; + tmp_nb_x[i][j] = lms_pred_nb_x[ri][rj]; + tmp_nb_y[i][j] = lms_pred_nb_y[ri][rj]; + } + } + + // merge predictions + result->Clear(); + for (unsigned int i = 0; i < num_landmarks_; ++i) { + float total_x = lms_pred_x[i]; + float total_y = lms_pred_y[i]; + for (unsigned int j = 0; j < max_len_map_[num_landmarks_]; ++j) { + total_x += tmp_nb_x[i][j]; + total_y += tmp_nb_y[i][j]; + } + float x = total_x / ((float)max_len_map_[num_landmarks_] + 1.f); + float y = total_y / ((float)max_len_map_[num_landmarks_] + 1.f); + x = std::min(std::max(0.f, x), 1.0f); + y = std::min(std::max(0.f, y), 1.0f); + result->landmarks.emplace_back( + std::array{x * img_width, y * img_height}); + } +}; + +void PIPNet::SetNumLandmarks(const int& num_landmarks) { + if (std::find(supported_num_landmarks_.begin(), + supported_num_landmarks_.end(), + num_landmarks) == supported_num_landmarks_.end()) { + FDWARNING << "The number of landmarks should be in {19, 29, 68, 98}." + << std::endl; + } + num_landmarks_ = num_landmarks; +} +PIPNet::PIPNet(const std::string& model_file, const std::string& params_file, + const RuntimeOption& custom_option, + const ModelFormat& model_format) { + if (model_format == ModelFormat::ONNX) { + valid_cpu_backends = {Backend::OPENVINO, Backend::ORT}; + valid_gpu_backends = {Backend::ORT, Backend::TRT}; + } else { + valid_cpu_backends = {Backend::PDINFER, Backend::ORT}; + valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT}; + } + runtime_option = custom_option; + runtime_option.model_format = model_format; + runtime_option.model_file = model_file; + runtime_option.params_file = params_file; + initialized = Initialize(); +} + +bool PIPNet::Initialize() { + // parameters for preprocess + size_ = {256, 256}; + mean_vals_ = {0.485f, 0.456f, 0.406f}; + std_vals_ = {0.229f, 0.224f, 0.225f}; + num_nb_ = 10; + net_stride_ = 32; + num_landmarks_ = 19; + supported_num_landmarks_ = {19, 29, 68, 98}; + // parameters for num_landmarks_ == 19 + reverse_index1_map_[19] = { + 1, 2, 6, 7, 8, 1, 2, 6, 7, 8, 1, 2, 6, 7, 8, 1, 2, 6, + 0, 2, 3, 4, 6, 7, 8, 0, 2, 3, 4, 6, 7, 8, 0, 2, 3, 4, + 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 0, 1, 3, 4, 5, 6, + 0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 14, 0, 1, 2, 4, 5, 6, + 1, 2, 3, 5, 9, 10, 11, 1, 2, 3, 5, 9, 10, 11, 1, 2, 3, 5, + 3, 4, 9, 10, 11, 3, 4, 9, 10, 11, 3, 4, 9, 10, 11, 3, 4, 9, + 0, 1, 2, 3, 7, 8, 12, 13, 15, 0, 1, 2, 3, 7, 8, 12, 13, 15, + 0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 15, 16, 18, 0, 1, + 0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, + 0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, + 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 17, 18, 0, 1, + 3, 4, 5, 9, 10, 14, 17, 3, 4, 5, 9, 10, 14, 17, 3, 4, 5, 9, + 0, 1, 6, 7, 8, 13, 14, 15, 16, 17, 18, 0, 1, 6, 7, 8, 13, 14, + 0, 2, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, 0, 2, 5, + 4, 5, 9, 10, 11, 12, 13, 15, 16, 17, 18, 4, 5, 9, 10, 11, 12, 13, + 12, 13, 14, 16, 17, 18, 12, 13, 14, 16, 17, 18, 12, 13, 14, 16, 17, 18, + 12, 13, 14, 15, 17, 18, 12, 13, 14, 15, 17, 18, 12, 13, 14, 15, 17, 18, + 12, 13, 14, 15, 16, 18, 12, 13, 14, 15, 16, 18, 12, 13, 14, 15, 16, 18, + 15, 16, 17, 15, 16, 17, 15, 16, 17, 15, 16, 17, 15, 16, 17, 15, 16, 17}; + reverse_index2_map_[19] = { + 0, 6, 1, 4, 6, 0, 6, 1, 4, 6, 0, 6, 1, 4, 6, 0, 6, 1, 0, 1, 8, 7, 2, 2, 3, + 0, 1, 8, 7, 2, 2, 3, 0, 1, 8, 7, 3, 1, 3, 5, 5, 4, 3, 1, 5, 6, 6, 9, 3, 1, + 3, 5, 5, 4, 5, 5, 3, 1, 3, 7, 5, 5, 1, 3, 4, 9, 5, 5, 3, 1, 3, 7, 7, 8, 1, + 0, 3, 2, 2, 7, 8, 1, 0, 3, 2, 2, 7, 8, 1, 0, 6, 0, 6, 4, 1, 6, 0, 6, 4, 1, + 6, 0, 6, 4, 1, 6, 0, 6, 1, 3, 4, 9, 1, 2, 6, 9, 8, 1, 3, 4, 9, 1, 2, 6, 9, + 8, 2, 2, 2, 7, 8, 9, 0, 0, 9, 9, 9, 5, 7, 7, 8, 8, 2, 2, 4, 4, 0, 5, 6, 6, + 3, 0, 4, 5, 7, 4, 3, 8, 6, 6, 9, 6, 7, 6, 5, 0, 4, 4, 8, 6, 4, 0, 3, 8, 4, + 4, 9, 7, 6, 7, 9, 8, 7, 2, 2, 2, 9, 9, 9, 0, 0, 8, 5, 9, 7, 9, 9, 8, 4, 3, + 1, 2, 1, 6, 8, 4, 3, 1, 2, 1, 6, 8, 4, 3, 1, 2, 6, 9, 5, 7, 8, 0, 2, 1, 3, + 4, 4, 6, 9, 5, 7, 8, 0, 2, 8, 9, 8, 6, 8, 7, 7, 8, 8, 0, 0, 2, 2, 2, 5, 8, + 9, 8, 9, 7, 8, 7, 5, 2, 1, 4, 4, 1, 3, 9, 7, 8, 7, 5, 2, 1, 1, 5, 7, 0, 3, + 1, 1, 5, 7, 0, 3, 1, 1, 5, 7, 0, 3, 1, 3, 2, 3, 0, 0, 0, 3, 2, 3, 0, 0, 0, + 3, 2, 3, 0, 0, 0, 7, 6, 1, 3, 1, 2, 7, 6, 1, 3, 1, 2, 7, 6, 1, 3, 1, 2, 5, + 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5}; + max_len_map_[19] = 18; + // parameters for num_landmarks_ == 29 + reverse_index1_map_[29] = { + 2, 4, 5, 8, 12, 13, 16, 2, 4, 5, 8, 12, 13, 16, 2, 4, 5, 8, + 12, 3, 6, 7, 9, 14, 15, 17, 3, 6, 7, 9, 14, 15, 17, 3, 6, 7, + 9, 14, 0, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 16, 0, 3, 4, + 5, 6, 7, 0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12, 14, 15, 17, 0, + 1, 2, 4, 5, 0, 2, 5, 8, 10, 12, 13, 16, 0, 2, 5, 8, 10, 12, + 13, 16, 0, 2, 5, 0, 2, 4, 8, 10, 12, 13, 16, 0, 2, 4, 8, 10, + 12, 13, 16, 0, 2, 4, 1, 3, 7, 9, 11, 14, 15, 17, 1, 3, 7, 9, + 11, 14, 15, 17, 1, 3, 7, 1, 3, 6, 9, 11, 14, 15, 17, 1, 3, 6, + 9, 11, 14, 15, 17, 1, 3, 6, 0, 2, 4, 5, 10, 12, 13, 16, 0, 2, + 4, 5, 10, 12, 13, 16, 0, 2, 4, 1, 3, 6, 7, 11, 14, 15, 17, 1, + 3, 6, 7, 11, 14, 15, 17, 1, 3, 6, 0, 2, 3, 4, 5, 8, 12, 13, + 16, 18, 20, 0, 2, 3, 4, 5, 8, 12, 13, 1, 2, 3, 6, 7, 9, 14, + 15, 17, 19, 20, 21, 1, 2, 3, 6, 7, 9, 14, 0, 2, 4, 5, 8, 10, + 13, 16, 0, 2, 4, 5, 8, 10, 13, 16, 0, 2, 4, 0, 2, 4, 5, 8, + 10, 12, 16, 18, 22, 0, 2, 4, 5, 8, 10, 12, 16, 18, 1, 3, 6, 7, + 9, 11, 15, 17, 1, 3, 6, 7, 9, 11, 15, 17, 1, 3, 6, 1, 3, 6, + 7, 9, 11, 14, 17, 19, 23, 1, 3, 6, 7, 9, 11, 14, 17, 19, 0, 2, + 4, 5, 8, 10, 12, 13, 18, 0, 2, 4, 5, 8, 10, 12, 13, 18, 0, 1, + 3, 6, 7, 9, 11, 14, 15, 19, 1, 3, 6, 7, 9, 11, 14, 15, 19, 1, + 0, 4, 5, 8, 10, 12, 13, 16, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, + 0, 1, 6, 7, 9, 11, 14, 15, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27, + 28, 1, 1, 8, 9, 10, 11, 13, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, + 26, 27, 28, 18, 19, 20, 22, 23, 24, 25, 26, 27, 28, 18, 19, 20, 22, 23, + 24, 25, 26, 27, 18, 20, 21, 24, 25, 26, 27, 28, 18, 20, 21, 24, 25, 26, + 27, 28, 18, 20, 21, 19, 21, 24, 25, 26, 27, 28, 19, 21, 24, 25, 26, 27, + 28, 19, 21, 24, 25, 26, 18, 19, 20, 21, 22, 23, 25, 26, 27, 28, 18, 19, + 20, 21, 22, 23, 25, 26, 27, 18, 19, 20, 21, 22, 23, 24, 26, 27, 28, 18, + 19, 20, 21, 22, 23, 24, 26, 27, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28, + 18, 19, 20, 21, 22, 23, 24, 25, 27, 20, 21, 22, 23, 24, 25, 26, 28, 20, + 21, 22, 23, 24, 25, 26, 28, 20, 21, 22, 22, 23, 24, 25, 26, 27, 22, 23, + 24, 25, 26, 27, 22, 23, 24, 25, 26, 27, 22}; + reverse_index2_map_[29] = { + 9, 3, 5, 3, 7, 7, 7, 9, 3, 5, 3, 7, 7, 7, 9, 3, 5, 3, 7, 9, 3, 5, 3, 7, + 7, 7, 9, 3, 5, 3, 7, 7, 7, 9, 3, 5, 3, 7, 7, 6, 6, 6, 8, 9, 7, 0, 9, 6, + 5, 9, 6, 7, 6, 6, 6, 8, 9, 9, 7, 6, 8, 9, 6, 6, 7, 8, 0, 9, 6, 6, 6, 9, + 7, 6, 8, 9, 2, 5, 0, 5, 5, 3, 6, 5, 2, 5, 0, 5, 5, 3, 6, 5, 2, 5, 0, 1, + 3, 0, 4, 4, 2, 4, 2, 1, 3, 0, 4, 4, 2, 4, 2, 1, 3, 0, 2, 4, 0, 5, 5, 3, + 5, 5, 2, 4, 0, 5, 5, 3, 5, 5, 2, 4, 0, 1, 3, 0, 4, 4, 2, 4, 2, 1, 3, 0, + 4, 4, 2, 4, 2, 1, 3, 0, 0, 7, 4, 3, 6, 5, 3, 4, 0, 7, 4, 3, 6, 5, 3, 4, + 0, 7, 4, 0, 7, 4, 3, 6, 5, 2, 4, 0, 7, 4, 3, 6, 5, 2, 4, 0, 7, 4, 6, 0, + 8, 7, 7, 6, 4, 2, 3, 5, 6, 6, 0, 8, 7, 7, 6, 4, 2, 6, 8, 0, 7, 7, 6, 4, + 3, 3, 5, 7, 9, 6, 8, 0, 7, 7, 6, 4, 3, 1, 1, 1, 2, 3, 1, 0, 3, 1, 1, 1, + 2, 3, 1, 0, 3, 1, 1, 5, 4, 5, 4, 0, 2, 1, 1, 6, 9, 5, 4, 5, 4, 0, 2, 1, + 1, 6, 3, 1, 1, 1, 2, 3, 1, 0, 3, 1, 1, 1, 2, 3, 1, 0, 3, 1, 1, 5, 5, 5, + 4, 0, 2, 1, 1, 7, 9, 5, 5, 5, 4, 0, 2, 1, 1, 7, 4, 2, 2, 2, 1, 1, 0, 0, + 9, 4, 2, 2, 2, 1, 1, 0, 0, 9, 4, 4, 2, 2, 2, 1, 1, 0, 0, 9, 4, 2, 2, 2, + 1, 1, 0, 0, 9, 4, 8, 9, 8, 8, 7, 8, 8, 8, 8, 1, 3, 0, 8, 5, 8, 9, 9, 9, + 8, 8, 9, 8, 8, 7, 8, 8, 8, 8, 2, 4, 8, 0, 6, 7, 8, 8, 7, 8, 9, 9, 9, 9, + 8, 9, 9, 9, 9, 0, 0, 0, 6, 6, 4, 4, 6, 7, 8, 1, 1, 0, 5, 5, 2, 3, 3, 4, + 6, 1, 1, 0, 5, 5, 2, 3, 3, 4, 2, 8, 7, 7, 5, 4, 6, 5, 2, 8, 7, 7, 5, 4, + 6, 5, 2, 8, 7, 2, 8, 8, 6, 5, 5, 4, 2, 8, 8, 6, 5, 5, 4, 2, 8, 8, 6, 5, + 3, 3, 3, 1, 2, 3, 0, 2, 2, 3, 3, 3, 3, 1, 2, 3, 0, 2, 2, 4, 4, 4, 2, 1, + 1, 0, 0, 1, 2, 4, 4, 4, 2, 1, 1, 0, 0, 1, 7, 6, 5, 5, 3, 2, 1, 1, 0, 1, + 7, 6, 5, 5, 3, 2, 1, 1, 0, 9, 6, 4, 4, 3, 2, 1, 0, 9, 6, 4, 4, 3, 2, 1, + 0, 9, 6, 4, 7, 7, 9, 9, 7, 3, 7, 7, 9, 9, 7, 3, 7, 7, 9, 9, 7, 3, 7}; + max_len_map_[29] = 19; + // parameters for num_landmarks_ == 68 + reverse_index1_map_[68] = { + 1, 2, 17, 18, 36, 1, 2, 17, 18, 36, 1, 2, 17, 18, 36, 1, 2, 17, + 18, 36, 1, 2, 0, 2, 3, 17, 0, 2, 3, 17, 0, 2, 3, 17, 0, 2, + 3, 17, 0, 2, 3, 17, 0, 2, 0, 1, 3, 4, 0, 1, 3, 4, 0, 1, + 3, 4, 0, 1, 3, 4, 0, 1, 3, 4, 0, 1, 1, 2, 4, 5, 1, 2, + 4, 5, 1, 2, 4, 5, 1, 2, 4, 5, 1, 2, 4, 5, 1, 2, 2, 3, + 5, 6, 2, 3, 5, 6, 2, 3, 5, 6, 2, 3, 5, 6, 2, 3, 5, 6, + 2, 3, 3, 4, 6, 7, 3, 4, 6, 7, 3, 4, 6, 7, 3, 4, 6, 7, + 3, 4, 6, 7, 3, 4, 3, 4, 5, 7, 8, 3, 4, 5, 7, 8, 3, 4, + 5, 7, 8, 3, 4, 5, 7, 8, 3, 4, 5, 6, 8, 9, 5, 6, 8, 9, + 5, 6, 8, 9, 5, 6, 8, 9, 5, 6, 8, 9, 5, 6, 6, 7, 9, 10, + 6, 7, 9, 10, 6, 7, 9, 10, 6, 7, 9, 10, 6, 7, 9, 10, 6, 7, + 7, 8, 10, 11, 7, 8, 10, 11, 7, 8, 10, 11, 7, 8, 10, 11, 7, 8, + 10, 11, 7, 8, 8, 9, 11, 12, 13, 8, 9, 11, 12, 13, 8, 9, 11, 12, + 13, 8, 9, 11, 12, 13, 8, 9, 9, 10, 12, 13, 9, 10, 12, 13, 9, 10, + 12, 13, 9, 10, 12, 13, 9, 10, 12, 13, 9, 10, 10, 11, 13, 14, 10, 11, + 13, 14, 10, 11, 13, 14, 10, 11, 13, 14, 10, 11, 13, 14, 10, 11, 11, 12, + 14, 15, 11, 12, 14, 15, 11, 12, 14, 15, 11, 12, 14, 15, 11, 12, 14, 15, + 11, 12, 12, 13, 15, 16, 12, 13, 15, 16, 12, 13, 15, 16, 12, 13, 15, 16, + 12, 13, 15, 16, 12, 13, 13, 14, 16, 26, 13, 14, 16, 26, 13, 14, 16, 26, + 13, 14, 16, 26, 13, 14, 16, 26, 13, 14, 14, 15, 25, 26, 45, 14, 15, 25, + 26, 45, 14, 15, 25, 26, 45, 14, 15, 25, 26, 45, 14, 15, 0, 1, 2, 18, + 19, 36, 37, 41, 0, 1, 2, 18, 19, 36, 37, 41, 0, 1, 2, 18, 19, 36, + 0, 1, 17, 19, 20, 36, 37, 38, 41, 0, 1, 17, 19, 20, 36, 37, 38, 41, + 0, 1, 17, 19, 0, 17, 18, 20, 21, 36, 37, 38, 40, 41, 0, 17, 18, 20, + 21, 36, 37, 38, 40, 41, 0, 17, 17, 18, 19, 21, 36, 37, 38, 39, 40, 41, + 17, 18, 19, 21, 36, 37, 38, 39, 40, 41, 17, 18, 18, 19, 20, 22, 27, 28, + 37, 38, 39, 40, 41, 18, 19, 20, 22, 27, 28, 37, 38, 39, 40, 41, 21, 23, + 24, 25, 27, 28, 42, 43, 44, 46, 47, 21, 23, 24, 25, 27, 28, 42, 43, 44, + 46, 47, 22, 24, 25, 26, 42, 43, 44, 45, 46, 47, 22, 24, 25, 26, 42, 43, + 44, 45, 46, 47, 22, 24, 16, 22, 23, 25, 26, 43, 44, 45, 46, 47, 16, 22, + 23, 25, 26, 43, 44, 45, 46, 47, 16, 22, 15, 16, 23, 24, 26, 43, 44, 45, + 46, 15, 16, 23, 24, 26, 43, 44, 45, 46, 15, 16, 23, 24, 14, 15, 16, 24, + 25, 44, 45, 46, 14, 15, 16, 24, 25, 44, 45, 46, 14, 15, 16, 24, 25, 44, + 20, 21, 22, 23, 28, 29, 38, 39, 40, 42, 43, 47, 20, 21, 22, 23, 28, 29, + 38, 39, 40, 42, 21, 22, 27, 29, 30, 39, 40, 42, 47, 21, 22, 27, 29, 30, + 39, 40, 42, 47, 21, 22, 27, 29, 27, 28, 30, 31, 35, 39, 42, 27, 28, 30, + 31, 35, 39, 42, 27, 28, 30, 31, 35, 39, 42, 27, 28, 29, 31, 32, 33, 34, + 35, 28, 29, 31, 32, 33, 34, 35, 28, 29, 31, 32, 33, 34, 35, 28, 2, 3, + 29, 30, 32, 33, 48, 49, 2, 3, 29, 30, 32, 33, 48, 49, 2, 3, 29, 30, + 32, 33, 29, 30, 31, 33, 34, 35, 49, 50, 29, 30, 31, 33, 34, 35, 49, 50, + 29, 30, 31, 33, 34, 35, 29, 30, 31, 32, 34, 35, 50, 51, 52, 29, 30, 31, + 32, 34, 35, 50, 51, 52, 29, 30, 31, 32, 29, 30, 31, 32, 33, 35, 52, 53, + 29, 30, 31, 32, 33, 35, 52, 53, 29, 30, 31, 32, 33, 35, 13, 14, 29, 30, + 32, 33, 34, 53, 54, 13, 14, 29, 30, 32, 33, 34, 53, 54, 13, 14, 29, 30, + 0, 1, 2, 17, 18, 19, 20, 37, 38, 39, 40, 41, 0, 1, 2, 17, 18, 19, + 20, 37, 38, 39, 0, 1, 17, 18, 19, 20, 21, 36, 38, 39, 40, 41, 0, 1, + 17, 18, 19, 20, 21, 36, 38, 39, 0, 1, 17, 18, 19, 20, 21, 27, 28, 36, + 37, 39, 40, 41, 0, 1, 17, 18, 19, 20, 21, 27, 19, 20, 21, 27, 28, 29, + 36, 37, 38, 40, 41, 19, 20, 21, 27, 28, 29, 36, 37, 38, 40, 41, 0, 1, + 17, 18, 19, 20, 21, 27, 28, 36, 37, 38, 39, 41, 0, 1, 17, 18, 19, 20, + 21, 27, 0, 1, 2, 17, 18, 19, 20, 21, 36, 37, 38, 39, 40, 0, 1, 2, + 17, 18, 19, 20, 21, 36, 22, 23, 24, 27, 28, 29, 43, 44, 45, 46, 47, 22, + 23, 24, 27, 28, 29, 43, 44, 45, 46, 47, 15, 16, 22, 23, 24, 25, 26, 27, + 42, 44, 45, 46, 47, 15, 16, 22, 23, 24, 25, 26, 27, 42, 15, 16, 22, 23, + 24, 25, 26, 42, 43, 45, 46, 47, 15, 16, 22, 23, 24, 25, 26, 42, 43, 45, + 14, 15, 16, 23, 24, 25, 26, 42, 43, 44, 46, 47, 14, 15, 16, 23, 24, 25, + 26, 42, 43, 44, 14, 15, 16, 22, 23, 24, 25, 26, 42, 43, 44, 45, 47, 14, + 15, 16, 22, 23, 24, 25, 26, 42, 15, 16, 22, 23, 24, 25, 26, 27, 28, 42, + 43, 44, 45, 46, 15, 16, 22, 23, 24, 25, 26, 27, 2, 3, 4, 5, 6, 49, + 59, 60, 2, 3, 4, 5, 6, 49, 59, 60, 2, 3, 4, 5, 6, 49, 3, 4, + 5, 31, 32, 48, 50, 51, 59, 60, 61, 67, 3, 4, 5, 31, 32, 48, 50, 51, + 59, 60, 30, 31, 32, 33, 34, 48, 49, 51, 52, 58, 59, 60, 61, 62, 66, 67, + 30, 31, 32, 33, 34, 48, 30, 31, 32, 33, 34, 35, 48, 49, 50, 52, 53, 54, + 56, 58, 60, 61, 62, 63, 64, 65, 66, 67, 30, 32, 33, 34, 35, 50, 51, 53, + 54, 55, 56, 62, 63, 64, 65, 30, 32, 33, 34, 35, 50, 51, 11, 12, 13, 34, + 35, 52, 54, 55, 63, 64, 65, 11, 12, 13, 34, 35, 52, 54, 55, 63, 64, 65, + 10, 11, 12, 13, 14, 53, 55, 64, 10, 11, 12, 13, 14, 53, 55, 64, 10, 11, + 12, 13, 14, 53, 8, 9, 10, 11, 12, 13, 53, 54, 56, 57, 63, 64, 65, 8, + 9, 10, 11, 12, 13, 53, 54, 56, 7, 8, 9, 10, 11, 12, 54, 55, 57, 58, + 63, 64, 65, 66, 7, 8, 9, 10, 11, 12, 54, 55, 6, 7, 8, 9, 10, 55, + 56, 58, 59, 62, 65, 66, 67, 6, 7, 8, 9, 10, 55, 56, 58, 59, 4, 5, + 6, 7, 8, 9, 48, 56, 57, 59, 60, 61, 62, 66, 67, 4, 5, 6, 7, 8, + 9, 48, 3, 4, 5, 6, 7, 8, 48, 49, 57, 58, 60, 61, 67, 3, 4, 5, + 6, 7, 8, 48, 49, 57, 2, 3, 4, 5, 6, 31, 48, 49, 59, 2, 3, 4, + 5, 6, 31, 48, 49, 59, 2, 3, 4, 5, 31, 32, 33, 48, 49, 50, 51, 52, + 57, 58, 59, 60, 62, 63, 66, 67, 31, 32, 33, 48, 49, 50, 33, 34, 48, 49, + 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 64, 65, 66, 67, 33, + 34, 35, 50, 51, 52, 53, 54, 55, 56, 57, 61, 62, 64, 65, 66, 34, 35, 50, + 51, 52, 53, 54, 10, 11, 12, 13, 14, 35, 53, 54, 55, 10, 11, 12, 13, 14, + 35, 53, 54, 55, 10, 11, 12, 13, 9, 10, 11, 12, 51, 52, 53, 54, 55, 56, + 57, 58, 61, 62, 63, 64, 66, 67, 9, 10, 11, 12, 7, 8, 9, 50, 51, 52, + 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 67, 7, 8, 9, 50, 4, 5, + 6, 7, 48, 49, 50, 51, 56, 57, 58, 59, 60, 61, 62, 63, 65, 66, 4, 5, + 6, 7}; + reverse_index2_map_[68] = { + 0, 3, 1, 7, 8, 0, 3, 1, 7, 8, 0, 3, 1, 7, 8, 0, 3, 1, 7, 8, 0, 3, 1, 1, 4, + 9, 1, 1, 4, 9, 1, 1, 4, 9, 1, 1, 4, 9, 1, 1, 4, 9, 1, 1, 6, 1, 1, 5, 6, 1, + 1, 5, 6, 1, 1, 5, 6, 1, 1, 5, 6, 1, 1, 5, 6, 1, 5, 0, 0, 6, 5, 0, 0, 6, 5, + 0, 0, 6, 5, 0, 0, 6, 5, 0, 0, 6, 5, 0, 2, 0, 1, 7, 2, 0, 1, 7, 2, 0, 1, 7, + 2, 0, 1, 7, 2, 0, 1, 7, 2, 0, 2, 1, 1, 6, 2, 1, 1, 6, 2, 1, 1, 6, 2, 1, 1, + 6, 2, 1, 1, 6, 2, 1, 9, 4, 0, 1, 4, 9, 4, 0, 1, 4, 9, 4, 0, 1, 4, 9, 4, 0, + 1, 4, 9, 4, 5, 0, 1, 3, 5, 0, 1, 3, 5, 0, 1, 3, 5, 0, 1, 3, 5, 0, 1, 3, 5, + 0, 4, 0, 0, 4, 4, 0, 0, 4, 4, 0, 0, 4, 4, 0, 0, 4, 4, 0, 0, 4, 4, 0, 3, 0, + 0, 5, 3, 0, 0, 5, 3, 0, 0, 5, 3, 0, 0, 5, 3, 0, 0, 5, 3, 0, 3, 1, 0, 4, 9, + 3, 1, 0, 4, 9, 3, 1, 0, 4, 9, 3, 1, 0, 4, 9, 3, 1, 6, 1, 0, 2, 6, 1, 0, 2, + 6, 1, 0, 2, 6, 1, 0, 2, 6, 1, 0, 2, 6, 1, 7, 1, 0, 2, 7, 1, 0, 2, 7, 1, 0, + 2, 7, 1, 0, 2, 7, 1, 0, 2, 7, 1, 6, 1, 1, 4, 6, 1, 1, 4, 6, 1, 1, 4, 6, 1, + 1, 4, 6, 1, 1, 4, 6, 1, 5, 1, 0, 6, 5, 1, 0, 6, 5, 1, 0, 6, 5, 1, 0, 6, 5, + 1, 0, 6, 5, 1, 3, 0, 0, 9, 3, 0, 0, 9, 3, 0, 0, 9, 3, 0, 0, 9, 3, 0, 0, 9, + 3, 0, 3, 1, 7, 2, 8, 3, 1, 7, 2, 8, 3, 1, 7, 2, 8, 3, 1, 7, 2, 8, 3, 1, 0, + 3, 9, 0, 4, 4, 8, 6, 0, 3, 9, 0, 4, 4, 8, 6, 0, 3, 9, 0, 4, 4, 3, 8, 0, 0, + 6, 5, 7, 9, 7, 3, 8, 0, 0, 6, 5, 7, 9, 7, 3, 8, 0, 0, 7, 4, 1, 1, 6, 6, 5, + 7, 9, 5, 7, 4, 1, 1, 6, 6, 5, 7, 9, 5, 7, 4, 8, 4, 1, 0, 9, 6, 4, 7, 6, 8, + 8, 4, 1, 0, 9, 6, 4, 7, 6, 8, 8, 4, 9, 6, 0, 4, 2, 7, 9, 6, 5, 5, 9, 9, 6, + 0, 4, 2, 7, 9, 6, 5, 5, 9, 4, 1, 6, 9, 3, 8, 5, 6, 9, 9, 6, 4, 1, 6, 9, 3, + 8, 5, 6, 9, 9, 6, 0, 1, 4, 8, 7, 5, 7, 9, 8, 5, 0, 1, 4, 8, 7, 5, 7, 9, 8, + 5, 0, 1, 7, 6, 0, 1, 4, 7, 5, 6, 6, 9, 7, 6, 0, 1, 4, 7, 5, 6, 6, 9, 7, 6, + 8, 3, 5, 0, 0, 9, 6, 5, 7, 8, 3, 5, 0, 0, 9, 6, 5, 7, 8, 3, 5, 0, 8, 3, 1, + 4, 0, 8, 4, 5, 8, 3, 1, 4, 0, 8, 4, 5, 8, 3, 1, 4, 0, 8, 9, 1, 1, 9, 1, 2, + 8, 4, 7, 2, 8, 7, 9, 1, 1, 9, 1, 2, 8, 4, 7, 2, 8, 8, 0, 0, 6, 6, 8, 6, 8, + 8, 8, 0, 0, 6, 6, 8, 6, 8, 8, 8, 0, 0, 5, 0, 0, 9, 9, 9, 9, 5, 0, 0, 9, 9, + 9, 9, 5, 0, 0, 9, 9, 9, 9, 5, 4, 1, 2, 2, 2, 2, 2, 4, 1, 2, 2, 2, 2, 2, 4, + 1, 2, 2, 2, 2, 2, 4, 8, 8, 6, 5, 0, 7, 7, 9, 8, 8, 6, 5, 0, 7, 7, 9, 8, 8, + 6, 5, 0, 7, 4, 3, 0, 0, 4, 5, 8, 7, 4, 3, 0, 0, 4, 5, 8, 7, 4, 3, 0, 0, 4, + 5, 7, 2, 1, 1, 1, 1, 5, 8, 5, 7, 2, 1, 1, 1, 1, 5, 8, 5, 7, 2, 1, 1, 3, 1, + 5, 4, 1, 0, 6, 9, 3, 1, 5, 4, 1, 0, 6, 9, 3, 1, 5, 4, 1, 0, 8, 9, 5, 4, 9, + 6, 0, 8, 7, 8, 9, 5, 4, 9, 6, 0, 8, 7, 8, 9, 5, 4, 2, 2, 4, 2, 3, 5, 8, 1, + 5, 8, 4, 1, 2, 2, 4, 2, 3, 5, 8, 1, 5, 8, 5, 6, 3, 2, 2, 3, 7, 1, 1, 3, 3, + 0, 5, 6, 3, 2, 2, 3, 7, 1, 1, 3, 9, 9, 6, 6, 3, 2, 2, 7, 9, 3, 2, 1, 0, 3, + 9, 9, 6, 6, 3, 2, 2, 7, 9, 4, 3, 4, 3, 9, 7, 4, 2, 1, 4, 9, 4, 3, 4, 3, 9, + 7, 4, 2, 1, 4, 8, 7, 7, 8, 8, 5, 5, 8, 5, 2, 3, 0, 0, 2, 8, 7, 7, 8, 8, 5, + 5, 8, 4, 4, 5, 5, 5, 7, 7, 9, 0, 0, 3, 2, 2, 4, 4, 5, 5, 5, 7, 7, 9, 0, 3, + 4, 9, 1, 2, 8, 2, 4, 7, 4, 2, 3, 4, 9, 1, 2, 8, 2, 4, 7, 4, 2, 9, 9, 2, 2, + 3, 6, 6, 6, 1, 2, 3, 3, 0, 9, 9, 2, 2, 3, 6, 6, 6, 1, 6, 5, 7, 3, 2, 2, 3, + 4, 1, 1, 1, 3, 6, 5, 7, 3, 2, 2, 3, 4, 1, 1, 4, 2, 2, 8, 5, 3, 1, 8, 4, 1, + 0, 4, 4, 2, 2, 8, 5, 3, 1, 8, 4, 1, 5, 5, 4, 9, 7, 7, 5, 5, 3, 3, 0, 0, 1, + 5, 5, 4, 9, 7, 7, 5, 5, 3, 7, 8, 5, 6, 8, 8, 7, 9, 6, 0, 0, 3, 2, 2, 7, 8, + 5, 6, 8, 8, 7, 9, 6, 3, 2, 2, 5, 3, 3, 0, 6, 3, 2, 2, 5, 3, 3, 0, 6, 3, 2, + 2, 5, 3, 6, 7, 8, 4, 6, 1, 3, 9, 4, 1, 5, 8, 6, 7, 8, 4, 6, 1, 3, 9, 4, 1, + 7, 3, 3, 4, 8, 5, 1, 1, 7, 9, 8, 5, 1, 6, 9, 5, 7, 3, 3, 4, 8, 5, 9, 6, 5, + 3, 5, 6, 9, 6, 1, 1, 6, 9, 8, 8, 8, 3, 0, 3, 8, 6, 6, 6, 8, 8, 5, 3, 3, 8, + 2, 1, 5, 8, 9, 7, 1, 5, 4, 8, 8, 5, 3, 3, 8, 2, 8, 7, 6, 6, 4, 3, 1, 3, 5, + 1, 8, 8, 7, 6, 6, 4, 3, 1, 3, 5, 1, 8, 5, 2, 2, 4, 6, 2, 4, 0, 5, 2, 2, 4, + 6, 2, 4, 0, 5, 2, 2, 4, 6, 2, 7, 5, 2, 3, 6, 7, 5, 2, 2, 9, 8, 2, 5, 7, 5, + 2, 3, 6, 7, 5, 2, 2, 7, 5, 2, 3, 7, 8, 6, 0, 1, 5, 7, 6, 3, 8, 7, 5, 2, 3, + 7, 8, 6, 0, 8, 4, 2, 4, 8, 7, 0, 0, 7, 8, 7, 4, 7, 8, 4, 2, 4, 8, 7, 0, 0, + 7, 9, 7, 3, 2, 6, 7, 6, 5, 0, 0, 6, 7, 9, 7, 3, 9, 7, 3, 2, 6, 7, 6, 7, 6, + 3, 2, 5, 8, 2, 5, 8, 2, 2, 8, 4, 7, 6, 3, 2, 5, 8, 2, 5, 8, 7, 5, 3, 4, 6, + 8, 0, 0, 1, 7, 5, 3, 4, 6, 8, 0, 0, 1, 7, 5, 3, 4, 7, 7, 9, 3, 2, 0, 3, 9, + 6, 4, 5, 3, 2, 6, 3, 0, 7, 7, 9, 3, 2, 0, 8, 9, 8, 7, 2, 0, 2, 7, 8, 9, 6, + 5, 6, 9, 7, 2, 2, 7, 2, 0, 2, 8, 7, 7, 9, 4, 0, 3, 3, 5, 4, 7, 6, 3, 3, 0, + 5, 7, 7, 9, 4, 0, 3, 3, 6, 4, 3, 5, 7, 8, 0, 0, 1, 6, 4, 3, 5, 7, 8, 0, 0, + 1, 6, 4, 3, 5, 8, 9, 9, 9, 7, 4, 4, 4, 2, 1, 4, 7, 9, 5, 0, 4, 2, 9, 8, 9, + 9, 9, 9, 9, 9, 6, 5, 8, 6, 3, 2, 3, 6, 9, 4, 1, 4, 9, 1, 1, 9, 9, 9, 6, 8, + 9, 9, 8, 4, 4, 4, 6, 7, 3, 1, 2, 4, 0, 4, 9, 9, 1, 8, 9, 9, 8}; + max_len_map_[68] = 22; + // parameters for num_landmarks_ == 98 + reverse_index1_map_[98] = { + 1, 2, 3, 4, 5, 33, 1, 2, 3, 4, 5, 33, 1, 2, 3, 4, 5, 0, + 2, 3, 4, 5, 6, 33, 0, 2, 3, 4, 5, 6, 33, 0, 2, 3, 0, 1, + 3, 4, 5, 6, 0, 1, 3, 4, 5, 6, 0, 1, 3, 4, 5, 0, 1, 2, + 4, 5, 6, 7, 0, 1, 2, 4, 5, 6, 7, 0, 1, 2, 0, 1, 2, 3, + 5, 6, 7, 8, 0, 1, 2, 3, 5, 6, 7, 8, 0, 1, 2, 3, 4, 6, + 7, 8, 9, 1, 2, 3, 4, 6, 7, 8, 9, 1, 2, 3, 4, 5, 7, 8, + 9, 10, 2, 3, 4, 5, 7, 8, 9, 10, 2, 3, 4, 5, 6, 8, 9, 10, + 3, 4, 5, 6, 8, 9, 10, 3, 4, 5, 4, 5, 6, 7, 9, 10, 11, 4, + 5, 6, 7, 9, 10, 11, 4, 5, 6, 4, 5, 6, 7, 8, 10, 11, 12, 4, + 5, 6, 7, 8, 10, 11, 12, 4, 5, 6, 7, 8, 9, 11, 12, 13, 76, 5, + 6, 7, 8, 9, 11, 12, 13, 7, 8, 9, 10, 12, 13, 14, 76, 88, 7, 8, + 9, 10, 12, 13, 14, 76, 8, 9, 10, 11, 13, 14, 15, 8, 9, 10, 11, 13, + 14, 15, 8, 9, 10, 10, 11, 12, 14, 15, 16, 10, 11, 12, 14, 15, 16, 10, + 11, 12, 14, 15, 11, 12, 13, 15, 16, 17, 11, 12, 13, 15, 16, 17, 11, 12, + 13, 15, 16, 12, 13, 14, 16, 17, 18, 12, 13, 14, 16, 17, 18, 12, 13, 14, + 16, 17, 13, 14, 15, 17, 18, 19, 13, 14, 15, 17, 18, 19, 13, 14, 15, 17, + 18, 14, 15, 16, 18, 19, 20, 14, 15, 16, 18, 19, 20, 14, 15, 16, 18, 19, + 15, 16, 17, 19, 20, 21, 15, 16, 17, 19, 20, 21, 15, 16, 17, 19, 20, 16, + 17, 18, 20, 21, 22, 16, 17, 18, 20, 21, 22, 16, 17, 18, 20, 21, 17, 18, + 19, 21, 22, 23, 24, 17, 18, 19, 21, 22, 23, 24, 17, 18, 19, 18, 19, 20, + 22, 23, 24, 25, 82, 18, 19, 20, 22, 23, 24, 25, 82, 18, 19, 20, 21, 23, + 24, 25, 26, 27, 19, 20, 21, 23, 24, 25, 26, 27, 19, 20, 21, 22, 24, 25, + 26, 27, 28, 20, 21, 22, 24, 25, 26, 27, 28, 20, 21, 22, 23, 25, 26, 27, + 28, 21, 22, 23, 25, 26, 27, 28, 21, 22, 23, 21, 22, 23, 24, 26, 27, 28, + 29, 21, 22, 23, 24, 26, 27, 28, 29, 21, 22, 23, 24, 25, 27, 28, 29, 30, + 22, 23, 24, 25, 27, 28, 29, 30, 22, 23, 24, 25, 26, 28, 29, 30, 31, 23, + 24, 25, 26, 28, 29, 30, 31, 23, 24, 25, 26, 27, 29, 30, 31, 32, 24, 25, + 26, 27, 29, 30, 31, 32, 24, 25, 26, 27, 28, 30, 31, 32, 25, 26, 27, 28, + 30, 31, 32, 25, 26, 27, 26, 27, 28, 29, 31, 32, 26, 27, 28, 29, 31, 32, + 26, 27, 28, 29, 31, 26, 27, 28, 29, 30, 32, 46, 26, 27, 28, 29, 30, 32, + 46, 26, 27, 28, 27, 28, 29, 30, 31, 46, 27, 28, 29, 30, 31, 46, 27, 28, + 29, 30, 31, 0, 1, 2, 3, 34, 41, 60, 0, 1, 2, 3, 34, 41, 60, 0, + 1, 2, 0, 33, 35, 40, 41, 60, 0, 33, 35, 40, 41, 60, 0, 33, 35, 40, + 41, 33, 34, 36, 37, 39, 40, 41, 60, 61, 62, 33, 34, 36, 37, 39, 40, 41, + 34, 35, 37, 38, 39, 40, 63, 64, 34, 35, 37, 38, 39, 40, 63, 64, 34, 36, + 38, 39, 51, 64, 36, 38, 39, 51, 64, 36, 38, 39, 51, 64, 36, 38, 36, 37, + 39, 51, 52, 63, 64, 65, 36, 37, 39, 51, 52, 63, 64, 65, 36, 35, 36, 37, + 38, 40, 62, 63, 64, 65, 66, 67, 96, 35, 36, 37, 38, 40, 33, 34, 35, 36, + 37, 38, 39, 41, 60, 61, 62, 63, 65, 66, 67, 96, 33, 0, 1, 2, 33, 34, + 35, 40, 60, 61, 67, 0, 1, 2, 33, 34, 35, 40, 43, 49, 50, 51, 68, 43, + 49, 50, 51, 68, 43, 49, 50, 51, 68, 43, 49, 42, 44, 45, 48, 49, 50, 68, + 69, 42, 44, 45, 48, 49, 50, 68, 69, 42, 42, 43, 45, 46, 47, 48, 49, 70, + 42, 43, 45, 46, 47, 48, 49, 70, 42, 32, 44, 46, 47, 48, 71, 72, 73, 32, + 44, 46, 47, 48, 71, 72, 73, 32, 29, 30, 31, 32, 45, 47, 72, 29, 30, 31, + 32, 45, 47, 72, 29, 30, 31, 30, 31, 32, 44, 45, 46, 48, 71, 72, 73, 30, + 31, 32, 44, 45, 46, 48, 42, 43, 44, 45, 46, 47, 49, 50, 69, 70, 71, 72, + 73, 74, 75, 97, 42, 42, 43, 44, 48, 50, 68, 69, 70, 74, 75, 97, 42, 43, + 44, 48, 50, 68, 42, 43, 49, 51, 52, 68, 69, 75, 42, 43, 49, 51, 52, 68, + 69, 75, 42, 37, 38, 42, 50, 52, 53, 64, 68, 37, 38, 42, 50, 52, 53, 64, + 68, 37, 51, 53, 54, 51, 53, 54, 51, 53, 54, 51, 53, 54, 51, 53, 54, 51, + 53, 51, 52, 54, 55, 56, 57, 59, 51, 52, 54, 55, 56, 57, 59, 51, 52, 54, + 52, 53, 55, 56, 57, 58, 59, 52, 53, 55, 56, 57, 58, 59, 52, 53, 55, 53, + 54, 56, 57, 76, 77, 78, 88, 53, 54, 56, 57, 76, 77, 78, 88, 53, 53, 54, + 55, 57, 58, 77, 78, 79, 88, 53, 54, 55, 57, 58, 77, 78, 79, 53, 54, 55, + 56, 58, 59, 78, 79, 80, 90, 53, 54, 55, 56, 58, 59, 78, 53, 54, 56, 57, + 59, 79, 80, 81, 82, 92, 53, 54, 56, 57, 59, 79, 80, 53, 54, 57, 58, 80, + 81, 82, 92, 53, 54, 57, 58, 80, 81, 82, 92, 53, 0, 1, 2, 3, 4, 33, + 34, 41, 61, 62, 66, 67, 96, 0, 1, 2, 3, 0, 1, 33, 34, 35, 40, 41, + 60, 62, 63, 65, 66, 67, 96, 0, 1, 33, 33, 34, 35, 36, 37, 38, 39, 40, + 41, 60, 61, 63, 64, 65, 66, 67, 96, 35, 36, 37, 38, 39, 40, 51, 52, 61, + 62, 64, 65, 66, 67, 96, 35, 36, 36, 37, 38, 39, 51, 52, 53, 63, 65, 66, + 96, 36, 37, 38, 39, 51, 52, 36, 37, 38, 39, 52, 61, 62, 63, 64, 66, 67, + 96, 36, 37, 38, 39, 52, 41, 60, 61, 62, 63, 64, 65, 67, 96, 41, 60, 61, + 62, 63, 64, 65, 67, 0, 1, 2, 3, 33, 34, 35, 40, 41, 60, 61, 62, 65, + 66, 96, 0, 1, 42, 43, 49, 50, 51, 52, 53, 69, 74, 75, 97, 42, 43, 49, + 50, 51, 52, 42, 43, 44, 48, 49, 50, 51, 68, 70, 71, 73, 74, 75, 97, 42, + 43, 44, 42, 43, 44, 45, 46, 47, 48, 49, 50, 68, 69, 71, 72, 73, 74, 75, + 97, 31, 32, 44, 45, 46, 47, 48, 69, 70, 72, 73, 74, 75, 97, 31, 32, 44, + 28, 29, 30, 31, 32, 45, 46, 47, 70, 71, 73, 74, 97, 28, 29, 30, 31, 29, + 30, 31, 32, 44, 45, 46, 47, 48, 70, 71, 72, 74, 75, 97, 29, 30, 47, 68, + 69, 70, 71, 72, 73, 75, 97, 47, 68, 69, 70, 71, 72, 73, 75, 42, 43, 49, + 50, 52, 68, 69, 70, 71, 72, 73, 74, 97, 42, 43, 49, 50, 6, 7, 8, 9, + 10, 11, 12, 55, 77, 87, 88, 89, 95, 6, 7, 8, 9, 55, 56, 76, 78, 86, + 87, 88, 89, 95, 55, 56, 76, 78, 86, 87, 88, 89, 54, 55, 56, 57, 58, 76, + 77, 79, 80, 85, 86, 87, 88, 89, 90, 94, 95, 54, 55, 56, 57, 58, 59, 77, + 78, 80, 81, 84, 85, 86, 89, 90, 91, 94, 54, 57, 58, 59, 78, 79, 81, 82, + 83, 84, 85, 90, 91, 92, 93, 94, 54, 58, 59, 80, 82, 83, 84, 91, 92, 93, + 58, 59, 80, 82, 83, 84, 91, 92, 20, 21, 22, 23, 24, 25, 26, 59, 81, 83, + 91, 92, 93, 20, 21, 22, 23, 17, 18, 19, 20, 21, 22, 23, 81, 82, 84, 91, + 92, 93, 17, 18, 19, 20, 16, 17, 18, 19, 20, 81, 82, 83, 85, 91, 92, 93, + 94, 16, 17, 18, 19, 14, 15, 16, 17, 18, 83, 84, 86, 87, 90, 93, 94, 95, + 14, 15, 16, 17, 11, 12, 13, 14, 15, 16, 76, 77, 85, 87, 88, 89, 94, 95, + 11, 12, 13, 9, 10, 11, 12, 13, 14, 76, 77, 86, 88, 89, 95, 9, 10, 11, + 12, 13, 7, 8, 9, 10, 11, 12, 13, 55, 76, 77, 86, 87, 89, 95, 7, 8, + 9, 55, 56, 76, 77, 78, 79, 86, 87, 88, 90, 95, 55, 56, 76, 77, 78, 79, + 56, 57, 58, 78, 79, 80, 83, 84, 85, 86, 87, 89, 91, 92, 93, 94, 95, 58, + 59, 79, 80, 81, 82, 83, 84, 85, 90, 92, 93, 94, 58, 59, 79, 80, 19, 20, + 21, 22, 23, 24, 25, 59, 81, 82, 83, 84, 91, 93, 19, 20, 21, 18, 19, 79, + 80, 81, 82, 83, 84, 85, 90, 91, 92, 94, 18, 19, 79, 80, 15, 16, 17, 78, + 79, 80, 83, 84, 85, 86, 87, 89, 90, 91, 93, 95, 15, 13, 14, 15, 76, 77, + 78, 85, 86, 87, 88, 89, 90, 94, 13, 14, 15, 76, 34, 35, 36, 38, 39, 40, + 41, 60, 61, 62, 63, 64, 65, 66, 67, 34, 35, 43, 44, 45, 47, 48, 49, 50, + 68, 69, 70, 71, 72, 73, 74, 75, 43, 44}; + reverse_index2_map_[98] = { + 0, 2, 4, 6, 8, 4, 0, 2, 4, 6, 8, 4, 0, 2, 4, 6, 8, 0, 0, 2, 4, 6, 8, 8, 0, + 0, 2, 4, 6, 8, 8, 0, 0, 2, 1, 1, 0, 2, 4, 6, 1, 1, 0, 2, 4, 6, 1, 1, 0, 2, + 4, 3, 2, 1, 0, 2, 4, 6, 3, 2, 1, 0, 2, 4, 6, 3, 2, 1, 6, 3, 3, 1, 0, 2, 4, + 7, 6, 3, 3, 1, 0, 2, 4, 7, 6, 6, 4, 3, 1, 0, 2, 4, 8, 6, 4, 3, 1, 0, 2, 4, + 8, 6, 7, 5, 3, 1, 0, 2, 4, 9, 7, 5, 3, 1, 0, 2, 4, 9, 7, 6, 5, 3, 1, 0, 2, + 4, 6, 5, 3, 1, 0, 2, 4, 6, 5, 3, 7, 5, 3, 1, 0, 2, 4, 7, 5, 3, 1, 0, 2, 4, + 7, 5, 3, 9, 7, 5, 3, 1, 0, 2, 5, 9, 7, 5, 3, 1, 0, 2, 5, 9, 9, 7, 5, 3, 1, + 0, 2, 5, 8, 9, 7, 5, 3, 1, 0, 2, 5, 7, 5, 3, 1, 0, 2, 5, 9, 9, 7, 5, 3, 1, + 0, 2, 5, 9, 9, 5, 3, 1, 0, 2, 4, 9, 5, 3, 1, 0, 2, 4, 9, 5, 3, 6, 3, 1, 0, + 2, 6, 6, 3, 1, 0, 2, 6, 6, 3, 1, 0, 2, 7, 3, 1, 0, 3, 7, 7, 3, 1, 0, 3, 7, + 7, 3, 1, 0, 3, 6, 3, 1, 1, 3, 6, 6, 3, 1, 1, 3, 6, 6, 3, 1, 1, 3, 7, 3, 1, + 1, 3, 7, 7, 3, 1, 1, 3, 7, 7, 3, 1, 1, 3, 6, 3, 0, 1, 3, 6, 6, 3, 0, 1, 3, + 6, 6, 3, 0, 1, 3, 7, 2, 0, 1, 3, 5, 7, 2, 0, 1, 3, 5, 7, 2, 0, 1, 3, 5, 2, + 0, 1, 3, 5, 5, 2, 0, 1, 3, 5, 5, 2, 0, 1, 3, 4, 2, 0, 1, 3, 5, 8, 4, 2, 0, + 1, 3, 5, 8, 4, 2, 0, 5, 2, 0, 1, 3, 5, 7, 9, 5, 2, 0, 1, 3, 5, 7, 9, 5, 4, + 2, 0, 1, 3, 5, 7, 9, 4, 2, 0, 1, 3, 5, 7, 9, 4, 4, 2, 0, 1, 3, 5, 7, 9, 4, + 2, 0, 1, 3, 5, 7, 9, 4, 4, 2, 0, 1, 3, 5, 7, 4, 2, 0, 1, 3, 5, 7, 4, 2, 0, + 9, 4, 2, 0, 1, 3, 5, 6, 9, 4, 2, 0, 1, 3, 5, 6, 9, 9, 4, 2, 0, 1, 3, 5, 6, + 9, 4, 2, 0, 1, 3, 5, 6, 9, 8, 4, 2, 0, 1, 3, 4, 6, 8, 4, 2, 0, 1, 3, 4, 6, + 8, 6, 4, 2, 0, 1, 3, 3, 5, 6, 4, 2, 0, 1, 3, 3, 5, 6, 6, 4, 2, 0, 1, 2, 3, + 6, 4, 2, 0, 1, 2, 3, 6, 4, 2, 6, 4, 2, 0, 1, 1, 6, 4, 2, 0, 1, 1, 6, 4, 2, + 0, 1, 8, 6, 4, 2, 0, 0, 9, 8, 6, 4, 2, 0, 0, 9, 8, 6, 4, 8, 6, 4, 2, 0, 6, + 8, 6, 4, 2, 0, 6, 8, 6, 4, 2, 0, 2, 4, 5, 8, 3, 1, 6, 2, 4, 5, 8, 3, 1, 6, + 2, 4, 5, 7, 1, 1, 5, 0, 8, 7, 1, 1, 5, 0, 8, 7, 1, 1, 5, 0, 7, 1, 2, 8, 6, + 0, 5, 9, 8, 8, 7, 1, 2, 8, 6, 0, 5, 8, 2, 1, 4, 0, 6, 7, 9, 8, 2, 1, 4, 0, + 6, 7, 9, 8, 1, 0, 5, 5, 7, 1, 0, 5, 5, 7, 1, 0, 5, 5, 7, 1, 0, 4, 0, 2, 2, + 6, 6, 2, 8, 4, 0, 2, 2, 6, 6, 2, 8, 4, 4, 0, 2, 1, 4, 7, 4, 4, 5, 9, 9, 7, + 4, 0, 2, 1, 4, 5, 2, 0, 3, 9, 9, 4, 2, 7, 5, 4, 8, 9, 8, 6, 6, 5, 5, 7, 9, + 0, 0, 3, 3, 2, 6, 7, 5, 7, 9, 0, 0, 3, 3, 2, 5, 0, 6, 7, 2, 5, 0, 6, 7, 2, + 5, 0, 6, 7, 2, 5, 1, 1, 8, 5, 0, 4, 9, 7, 1, 1, 8, 5, 0, 4, 9, 7, 1, 8, 1, + 1, 7, 4, 0, 6, 9, 8, 1, 1, 7, 4, 0, 6, 9, 8, 7, 2, 1, 0, 6, 9, 8, 9, 7, 2, + 1, 0, 6, 9, 8, 9, 7, 8, 5, 4, 2, 2, 1, 6, 8, 5, 4, 2, 2, 1, 6, 8, 5, 4, 9, + 7, 6, 3, 0, 0, 3, 6, 2, 7, 9, 7, 6, 3, 0, 0, 3, 7, 3, 0, 3, 5, 2, 2, 9, 8, + 4, 5, 7, 6, 7, 9, 6, 7, 2, 0, 4, 2, 1, 3, 2, 7, 9, 5, 8, 2, 0, 4, 2, 1, 3, + 0, 4, 3, 1, 5, 2, 6, 8, 0, 4, 3, 1, 5, 2, 6, 8, 0, 5, 6, 5, 5, 1, 5, 8, 8, + 5, 6, 5, 5, 1, 5, 8, 8, 5, 0, 1, 9, 0, 1, 9, 0, 1, 9, 0, 1, 9, 0, 1, 9, 0, + 1, 7, 0, 1, 9, 9, 9, 9, 7, 0, 1, 9, 9, 9, 9, 7, 0, 1, 4, 0, 5, 2, 0, 2, 4, + 4, 0, 5, 2, 0, 2, 4, 4, 0, 5, 6, 5, 0, 8, 6, 6, 9, 6, 6, 5, 0, 8, 6, 6, 9, + 6, 6, 3, 2, 0, 2, 7, 7, 5, 7, 8, 3, 2, 0, 2, 7, 7, 5, 7, 2, 0, 2, 1, 1, 2, + 4, 3, 5, 7, 2, 0, 2, 1, 1, 2, 4, 4, 3, 7, 1, 0, 5, 4, 8, 8, 8, 4, 3, 7, 1, + 0, 5, 4, 7, 4, 7, 0, 9, 6, 6, 6, 7, 4, 7, 0, 9, 6, 6, 6, 7, 4, 5, 6, 7, 8, + 2, 5, 4, 1, 9, 6, 1, 9, 4, 5, 6, 7, 8, 9, 3, 4, 6, 2, 3, 1, 2, 9, 7, 4, 0, + 5, 8, 9, 3, 9, 6, 5, 6, 7, 7, 3, 1, 7, 4, 2, 3, 6, 4, 1, 4, 0, 8, 5, 3, 3, + 1, 8, 8, 9, 7, 3, 1, 0, 5, 8, 3, 8, 5, 8, 4, 2, 8, 4, 3, 9, 1, 1, 7, 8, 8, + 4, 2, 8, 4, 3, 9, 6, 5, 9, 7, 9, 6, 0, 0, 3, 5, 2, 9, 6, 5, 9, 7, 9, 3, 4, + 1, 5, 5, 3, 2, 1, 9, 3, 4, 1, 5, 5, 3, 2, 9, 8, 8, 9, 6, 7, 9, 9, 6, 0, 0, + 5, 6, 2, 4, 9, 8, 4, 8, 8, 2, 3, 2, 8, 1, 8, 1, 9, 4, 8, 8, 2, 3, 2, 3, 5, + 8, 8, 1, 3, 9, 0, 3, 7, 8, 5, 0, 5, 3, 5, 8, 9, 6, 5, 6, 8, 6, 1, 4, 7, 6, + 4, 2, 5, 4, 2, 4, 0, 9, 8, 6, 4, 3, 3, 4, 9, 1, 1, 0, 4, 7, 2, 9, 8, 6, 8, + 7, 7, 5, 4, 5, 2, 5, 8, 1, 1, 6, 7, 8, 7, 7, 5, 9, 8, 8, 9, 9, 7, 4, 7, 9, + 5, 0, 0, 1, 6, 3, 9, 8, 9, 5, 5, 2, 4, 3, 2, 3, 1, 9, 5, 5, 2, 4, 3, 2, 3, + 6, 9, 9, 6, 8, 1, 0, 6, 8, 9, 5, 3, 4, 6, 9, 9, 6, 9, 8, 6, 6, 5, 6, 7, 8, + 4, 2, 0, 8, 7, 9, 8, 6, 6, 1, 5, 2, 7, 5, 3, 2, 0, 3, 1, 5, 2, 7, 5, 3, 2, + 0, 7, 4, 3, 4, 9, 7, 5, 1, 3, 7, 7, 6, 7, 2, 2, 3, 4, 6, 7, 4, 3, 4, 6, 9, + 0, 0, 9, 9, 6, 9, 7, 0, 7, 2, 8, 5, 3, 3, 3, 2, 5, 7, 6, 7, 8, 3, 2, 7, 4, + 4, 8, 5, 1, 6, 2, 3, 5, 0, 2, 3, 5, 1, 6, 2, 3, 5, 0, 2, 7, 6, 6, 6, 7, 8, + 9, 8, 4, 2, 8, 0, 8, 7, 6, 6, 6, 8, 7, 6, 5, 7, 8, 9, 3, 1, 1, 3, 1, 2, 8, + 7, 6, 5, 7, 5, 4, 5, 9, 7, 5, 5, 1, 4, 5, 1, 5, 7, 5, 4, 5, 8, 5, 4, 6, 8, + 8, 2, 2, 8, 4, 9, 0, 9, 8, 5, 4, 6, 9, 8, 4, 4, 6, 8, 5, 8, 2, 5, 5, 4, 6, + 1, 9, 8, 4, 9, 8, 5, 4, 6, 7, 1, 3, 1, 1, 3, 2, 9, 8, 5, 4, 6, 9, 8, 7, 7, + 8, 9, 9, 6, 0, 2, 8, 1, 5, 5, 9, 8, 7, 3, 6, 3, 0, 2, 8, 3, 4, 3, 6, 0, 3, + 6, 3, 0, 2, 8, 8, 6, 8, 1, 0, 1, 9, 6, 3, 6, 9, 6, 6, 9, 7, 1, 8, 6, 5, 6, + 2, 0, 3, 4, 3, 9, 5, 3, 0, 9, 6, 5, 6, 2, 9, 8, 8, 7, 7, 9, 9, 7, 2, 0, 1, + 8, 5, 5, 9, 8, 8, 9, 8, 9, 8, 1, 4, 0, 0, 4, 8, 1, 4, 7, 9, 8, 9, 8, 8, 9, + 9, 6, 4, 7, 7, 4, 0, 4, 7, 9, 1, 9, 6, 6, 8, 8, 9, 9, 4, 1, 8, 5, 0, 0, 4, + 1, 9, 8, 8, 9, 9, 4, 9, 7, 7, 8, 7, 7, 8, 5, 3, 0, 2, 3, 2, 0, 3, 9, 7, 7, + 7, 9, 8, 7, 7, 8, 4, 3, 0, 3, 4, 3, 0, 2, 7, 7}; + max_len_map_[98] = 17; + if (!InitRuntime()) { + FDERROR << "Failed to initialize fastdeploy backend." << std::endl; + return false; + } + return true; +} + +bool PIPNet::Preprocess(Mat* mat, FDTensor* output, + std::map>* im_info) { + // Resize + int resize_w = size_[0]; + int resize_h = size_[1]; + if (resize_h != mat->Height() || resize_w != mat->Width()) { + Resize::Run(mat, resize_w, resize_h); + } + // RGR2RGB + BGR2RGB::Run(mat); + + // Normalize + Normalize::Run(mat, mean_vals_, std_vals_); + + // Record output shape of preprocessed image + (*im_info)["output_shape"] = {mat->Height(), mat->Width()}; + + HWC2CHW::Run(mat); + Cast::Run(mat, "float"); + mat->ShareWithTensor(output); + output->shape.insert(output->shape.begin(), 1); // reshape to n, h, w, c + return true; +} + +bool PIPNet::Postprocess( + std::vector& infer_result, FaceAlignmentResult* result, + const std::map>& im_info) { + FDASSERT(infer_result.at(0).shape[0] == 1, "Only support batch = 1 now."); + if (infer_result.at(0).dtype != FDDataType::FP32) { + FDERROR << "Only support post process with float32 data." << std::endl; + return false; + } + + auto iter_in = im_info.find("input_shape"); + FDASSERT(iter_in != im_info.end(), "Cannot find input_shape from im_info."); + int in_h = iter_in->second[0]; + int in_w = iter_in->second[1]; + GenerateLandmarks(infer_result, result, in_h, in_w); + + return true; +} + +bool PIPNet::Predict(cv::Mat* im, FaceAlignmentResult* result) { + Mat mat(*im); + std::vector input_tensors(1); + + std::map> im_info; + + // Record the shape of image and the shape of preprocessed image + im_info["input_shape"] = {mat.Height(), mat.Width()}; + im_info["output_shape"] = {mat.Height(), mat.Width()}; + + if (!Preprocess(&mat, &input_tensors[0], &im_info)) { + FDERROR << "Failed to preprocess input image." << std::endl; + return false; + } + input_tensors[0].name = InputInfoOfRuntime(0).name; + std::vector output_tensors; + if (!Infer(input_tensors, &output_tensors)) { + FDERROR << "Failed to inference." << std::endl; + return false; + } + + if (!Postprocess(output_tensors, result, im_info)) { + FDERROR << "Failed to post process." << std::endl; + return false; + } + return true; +} + +} // namespace facealign +} // namespace vision +} // namespace fastdeploy \ No newline at end of file diff --git a/fastdeploy/vision/facealign/contrib/pipnet.h b/fastdeploy/vision/facealign/contrib/pipnet.h new file mode 100644 index 0000000000..b0ea801f4d --- /dev/null +++ b/fastdeploy/vision/facealign/contrib/pipnet.h @@ -0,0 +1,127 @@ +// 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/fastdeploy_model.h" +#include "fastdeploy/vision/common/processors/transform.h" +#include "fastdeploy/vision/common/result.h" + +namespace fastdeploy { + +namespace vision { + +namespace facealign { +/*! @brief PIPNet model object used when to load a PIPNet model exported by PIPNet. + */ +class FASTDEPLOY_DECL PIPNet : public FastDeployModel { + public: + /** \brief Set path of model file and the configuration of runtime. + * + * \param[in] model_file Path of model file, e.g ./pipnet.onnx + * \param[in] params_file Path of parameter file, e.g ppyoloe/model.pdiparams, if the model format is ONNX, this parameter will be ignored + * \param[in] custom_option RuntimeOption for inference, the default will use cpu, and choose the backend defined in "valid_cpu_backends" + * \param[in] model_format Model format of the loaded model, default is ONNX format + */ + PIPNet(const std::string& model_file, const std::string& params_file = "", + const RuntimeOption& custom_option = RuntimeOption(), + const ModelFormat& model_format = ModelFormat::ONNX); + + std::string ModelName() const { return "PIPNet"; } + /** \brief Predict the face detection result for an input image + * + * \param[in] im The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format + * \param[in] result The output face detection result will be writen to this structure + * \return true if the prediction successed, otherwise false + */ + virtual bool Predict(cv::Mat* im, FaceAlignmentResult* result); + + /** \brief Get the number of landmakrs + * + * \return Integer type, default num_landmarks = 19 + */ + int GetNumLandmarks() {return num_landmarks_; } + /** \brief Get the mean values for normalization + * + * \return Vector of float values, default mean_vals = {0.485f, 0.456f, 0.406f} + */ + std::vector GetMeanVals() { return mean_vals_; } + /** \brief Get the std values for normalization + * + * \return Vector of float values, default std_vals = {0.229f, 0.224f, 0.225f} + */ + std::vector GetStdVals() { return std_vals_; } + /** \brief Get the input size of image + * + * \return Vector of int values, default {256, 256} + */ + std::vector GetSize() { return size_; } + /** \brief Set the number of landmarks + * + * \param[in] num_landmarks Integer value which represents number of landmarks + */ + void SetNumLandmarks(const int& num_landmarks); + /** \brief Set the mean values for normalization + * + * \param[in] mean_vals Vector of float values whose length is equal to 3 + */ + void SetMeanVals(const std::vector& mean_vals) { + mean_vals_ = mean_vals; + } + /** \brief Set the std values for normalization + * + * \param[in] std_vals Vector of float values whose length is equal to 3 + */ + void SetStdVals(const std::vector& std_vals) { std_vals_ = std_vals; } + /** \brief Set the input size of image + * + * \param[in] size Vector of int values which represents {width, height} of image + */ + void SetSize(const std::vector& size) { size_ = size; } + + private: + bool Initialize(); + + bool Preprocess(Mat* mat, FDTensor* outputs, + std::map>* im_info); + + bool Postprocess(std::vector& infer_result, + FaceAlignmentResult* result, + const std::map>& im_info); + void GenerateLandmarks(std::vector& infer_result, + FaceAlignmentResult* result, + float img_height, float img_width); + std::map num_lms_map_; + std::map max_len_map_; + std::map> reverse_index1_map_; + std::map> reverse_index2_map_; + int num_nb_; + int net_stride_; + // Now PIPNet support num_landmarks in {19, 29, 68, 98} + std::vector supported_num_landmarks_; + // tuple of (width, height), default (256, 256) + std::vector size_; + + // Mean parameters for normalize, size should be the the same as channels, + // default mean_vals = {0.485f, 0.456f, 0.406f} + std::vector mean_vals_; + // Std parameters for normalize, size should be the the same as channels, + // default std_vals = {0.229f, 0.224f, 0.225f} + std::vector std_vals_; + // number of landmarks + int num_landmarks_; +}; + +} // namespace facealign +} // namespace vision +} // namespace fastdeploy diff --git a/fastdeploy/vision/facealign/contrib/pipnet_pybind.cc b/fastdeploy/vision/facealign/contrib/pipnet_pybind.cc new file mode 100644 index 0000000000..025259ebc7 --- /dev/null +++ b/fastdeploy/vision/facealign/contrib/pipnet_pybind.cc @@ -0,0 +1,39 @@ +// 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 "fastdeploy/pybind/main.h" + +namespace fastdeploy { +void BindPIPNet(pybind11::module& m) { + pybind11::class_(m, "PIPNet") + .def(pybind11::init()) + .def("predict", + [](vision::facealign::PIPNet& self, pybind11::array& data) { + auto mat = PyArrayToCvMat(data); + vision::FaceAlignmentResult res; + self.Predict(&mat, &res); + return res; + }) + .def_property("size", &vision::facealign::PIPNet::GetSize, + &vision::facealign::PIPNet::SetSize) + .def_property("mean_vals", &vision::facealign::PIPNet::GetMeanVals, + &vision::facealign::PIPNet::SetMeanVals) + .def_property("std_vals", &vision::facealign::PIPNet::GetStdVals, + &vision::facealign::PIPNet::SetStdVals) + .def_property("num_landmarks", + &vision::facealign::PIPNet::GetNumLandmarks, + &vision::facealign::PIPNet::SetNumLandmarks); +} +} // namespace fastdeploy \ No newline at end of file diff --git a/fastdeploy/vision/facealign/facealign_pybind.cc b/fastdeploy/vision/facealign/facealign_pybind.cc index 60ccdf605a..19067d5669 100644 --- a/fastdeploy/vision/facealign/facealign_pybind.cc +++ b/fastdeploy/vision/facealign/facealign_pybind.cc @@ -17,9 +17,14 @@ namespace fastdeploy { void BindPFLD(pybind11::module& m); +void BindFaceLandmark1000(pybind11::module& m); +void BindPIPNet(pybind11::module& m); void BindFaceAlign(pybind11::module& m) { auto facedet_module = m.def_submodule("facealign", "Face alignment models."); BindPFLD(facedet_module); + BindFaceLandmark1000(facedet_module); + BindPIPNet(facedet_module); + } } // namespace fastdeploy diff --git a/python/fastdeploy/vision/facealign/__init__.py b/python/fastdeploy/vision/facealign/__init__.py index be5b8c76cb..c55585ff9a 100644 --- a/python/fastdeploy/vision/facealign/__init__.py +++ b/python/fastdeploy/vision/facealign/__init__.py @@ -14,3 +14,5 @@ from __future__ import absolute_import from .contrib.pfld import PFLD +from .contrib.pipnet import PIPNet +from .contrib.face_landmark_1000 import FaceLandmark1000 diff --git a/python/fastdeploy/vision/facealign/contrib/face_landmark_1000.py b/python/fastdeploy/vision/facealign/contrib/face_landmark_1000.py new file mode 100644 index 0000000000..67f980f409 --- /dev/null +++ b/python/fastdeploy/vision/facealign/contrib/face_landmark_1000.py @@ -0,0 +1,68 @@ +# 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. + +from __future__ import absolute_import +import logging +from .... import FastDeployModel, ModelFormat +from .... import c_lib_wrap as C + + +class FaceLandmark1000(FastDeployModel): + def __init__(self, + model_file, + params_file="", + runtime_option=None, + model_format=ModelFormat.ONNX): + """Load a face alignment model exported by FaceLandmark1000. + + :param model_file: (str)Path of model file, e.g ./FaceLandmark1000.onnx + :param params_file: (str)Path of parameters file, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string + :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU + :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model, default is ONNX + """ + + super(FaceLandmark1000, self).__init__(runtime_option) + + assert model_format == ModelFormat.ONNX, "FaceLandmark1000 only support model format of ModelFormat.ONNX now." + self._model = C.vision.facealign.FaceLandmark1000( + model_file, params_file, self._runtime_option, model_format) + assert self.initialized, "FaceLandmark1000 initialize failed." + + def predict(self, input_image): + """Detect an input image landmarks + + :param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format + :return: FaceAlignmentResult + """ + + return self._model.predict(input_image) + + @property + def size(self): + """ + Returns the preprocess image size, default (128, 128) + """ + return self._model.size + + @size.setter + def size(self, wh): + """ + Set the preprocess image size, default (128, 128) + """ + assert isinstance(wh, (list, tuple)),\ + "The value to set `size` must be type of tuple or list." + assert len(wh) == 2,\ + "The value to set `size` must contatins 2 elements means [width, height], but now it contains {} elements.".format( + len(wh)) + self._model.size = wh diff --git a/python/fastdeploy/vision/facealign/contrib/pipnet.py b/python/fastdeploy/vision/facealign/contrib/pipnet.py new file mode 100644 index 0000000000..6ba3fc7114 --- /dev/null +++ b/python/fastdeploy/vision/facealign/contrib/pipnet.py @@ -0,0 +1,107 @@ +# 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. + +from __future__ import absolute_import +import logging +from .... import FastDeployModel, ModelFormat +from .... import c_lib_wrap as C + + +class PIPNet(FastDeployModel): + def __init__(self, + model_file, + params_file="", + runtime_option=None, + model_format=ModelFormat.ONNX): + """Load a face alignment model exported by PIPNet. + + :param model_file: (str)Path of model file, e.g ./PIPNet.onnx + :param params_file: (str)Path of parameters file, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string + :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU + :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model, default is ONNX + """ + + super(PIPNet, self).__init__(runtime_option) + + assert model_format == ModelFormat.ONNX, "PIPNet only support model format of ModelFormat.ONNX now." + self._model = C.vision.facealign.PIPNet( + model_file, params_file, self._runtime_option, model_format) + assert self.initialized, "PIPNet initialize failed." + + def predict(self, input_image): + """Detect an input image landmarks + + :param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format + :return: FaceAlignmentResult + """ + + return self._model.predict(input_image) + + @property + def size(self): + """ + Returns the preprocess image size, default (256, 256) + """ + return self._model.size + + @property + def mean_vals(self): + """ + Returns the mean value of normlization, default mean_vals = [0.485f, 0.456f, 0.406f]; + """ + return self._model.mean_vals + + @property + def std_vals(self): + """ + Returns the std value of normlization, default std_vals = [0.229f, 0.224f, 0.225f]; + """ + return self._model.std_vals + + @property + def num_landmarks(self): + """ + Returns the number of landmarks + """ + return self._model.num_landmarks + + @size.setter + def size(self, wh): + """ + Set the preprocess image size, default (256, 256) + """ + assert isinstance(wh, (list, tuple)),\ + "The value to set `size` must be type of tuple or list." + assert len(wh) == 2,\ + "The value to set `size` must contatins 2 elements means [width, height], but now it contains {} elements.".format( + len(wh)) + self._model.size = wh + + @mean_vals.setter + def mean_vals(self, value): + assert isinstance( + value, list), "The value to set `mean_vals` must be type of list." + self._model.mean_vals = value + + @std_vals.setter + def std_vals(self, value): + assert isinstance( + value, list), "The value to set `std_vals` must be type of list." + self._model.std_vals = value + + @num_landmarks.setter + def num_landmarks(self, value): + assert isinstance( + value, int), "The value to set `std_vals` must be type of int." + self._model.num_landmarks = value diff --git a/tests/eval_example/test_facelandmark1000.py b/tests/eval_example/test_facelandmark1000.py new file mode 100644 index 0000000000..5fc2f87302 --- /dev/null +++ b/tests/eval_example/test_facelandmark1000.py @@ -0,0 +1,43 @@ +# 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 +import numpy as np + + +def test_facealignment_pipnet(): + model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/FaceLandmark1000.onnx" + input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/facealign_input.png" + output_url = "https://bj.bcebos.com/paddlehub/fastdeploy/tests/facelandmark1000_result_landmarks.npy" + fd.download(model_url, ".") + fd.download(input_url, ".") + fd.download(output_url, ".") + model_path = "FaceLandmark1000.onnx" + # use ORT + runtime_option = fd.RuntimeOption() + runtime_option.use_ort_backend() + model = fd.vision.facealign.FaceLandmark1000( + model_path, runtime_option=runtime_option) + + # compare diff + im = cv2.imread("./facealign_input.png") + result = model.predict(im.copy()) + expect = np.load("./facelandmark1000_result_landmarks.npy") + + diff = np.fabs(np.array(result.landmarks) - expect) + thres = 1e-04 + assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( + diff.max(), thres) diff --git a/tests/eval_example/test_pipnet.py b/tests/eval_example/test_pipnet.py new file mode 100644 index 0000000000..012ae67586 --- /dev/null +++ b/tests/eval_example/test_pipnet.py @@ -0,0 +1,43 @@ +# 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 +import numpy as np + + +def test_facealignment_pipnet(): + model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/pipnet_resnet18_10x19x32x256_aflw.onnx" + input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/facealign_input.png" + output_url = "https://bj.bcebos.com/paddlehub/fastdeploy/tests/pipnet_result_landmarks.npy" + fd.download(model_url, ".") + fd.download(input_url, ".") + fd.download(output_url, ".") + model_path = "pipnet_resnet18_10x19x32x256_aflw.onnx" + # use ORT + runtime_option = fd.RuntimeOption() + runtime_option.use_ort_backend() + model = fd.vision.facealign.PIPNet( + model_path, runtime_option=runtime_option) + + # compare diff + im = cv2.imread("./facealign_input.png") + result = model.predict(im.copy()) + expect = np.load("./pipnet_result_landmarks.npy") + + diff = np.fabs(np.array(result.landmarks) - expect) + thres = 1e-04 + assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( + diff.max(), thres) diff --git a/tests/vision_preprocess/test_vision_colorspace_convert.cc b/tests/vision_preprocess/test_vision_colorspace_convert.cc index f1253d959c..d9cdc82315 100644 --- a/tests/vision_preprocess/test_vision_colorspace_convert.cc +++ b/tests/vision_preprocess/test_vision_colorspace_convert.cc @@ -71,6 +71,56 @@ TEST(fastdeploy, flycv_rgb2bgr) { check_data(reinterpret_cast(opencv.Data()), reinterpret_cast(flycv.Data()), opencv.Numel()); check_type(opencv.dtype, flycv.dtype); } + +TEST(fastdeploy, flycv_rgb2gray) { + CheckShape check_shape; + CheckData check_data; + CheckType check_type; + + cv::Mat mat(64, 64, CV_8UC3); + cv::randu(mat, cv::Scalar::all(0), cv::Scalar::all(255)); + cv::Mat mat1 = mat.clone(); + + vision::Mat mat_opencv(mat); + vision::Mat mat_flycv(mat1); + vision::RGB2GRAY::Run(&mat_opencv, vision::ProcLib::OPENCV); + vision::RGB2GRAY::Run(&mat_flycv, vision::ProcLib::FLYCV); + + FDTensor opencv; + FDTensor flycv; + + mat_opencv.ShareWithTensor(&opencv); + mat_flycv.ShareWithTensor(&flycv); + + check_shape(opencv.shape, flycv.shape); + check_data(reinterpret_cast(opencv.Data()), reinterpret_cast(flycv.Data()), opencv.Numel()); + check_type(opencv.dtype, flycv.dtype); +} + +TEST(fastdeploy, flycv_bgr2gray) { + CheckShape check_shape; + CheckData check_data; + CheckType check_type; + + cv::Mat mat(64, 64, CV_8UC3); + cv::randu(mat, cv::Scalar::all(0), cv::Scalar::all(255)); + cv::Mat mat1 = mat.clone(); + + vision::Mat mat_opencv(mat); + vision::Mat mat_flycv(mat1); + vision::BGR2GRAY::Run(&mat_opencv, vision::ProcLib::OPENCV); + vision::BGR2GRAY::Run(&mat_flycv, vision::ProcLib::FLYCV); + + FDTensor opencv; + FDTensor flycv; + + mat_opencv.ShareWithTensor(&opencv); + mat_flycv.ShareWithTensor(&flycv); + + check_shape(opencv.shape, flycv.shape); + check_data(reinterpret_cast(opencv.Data()), reinterpret_cast(flycv.Data()), opencv.Numel()); + check_type(opencv.dtype, flycv.dtype); +} #endif } // namespace fastdeploy