From 0692dcc4057413fe15da9c664d1faac263eae0b5 Mon Sep 17 00:00:00 2001 From: ziqi-jin <67993288+ziqi-jin@users.noreply.github.com> Date: Fri, 7 Oct 2022 21:44:16 +0800 Subject: [PATCH] Add PP-ModNet and PP-HumanMatting Support (#240) * first commit for yolov7 * pybind for yolov7 * CPP README.md * CPP README.md * modified yolov7.cc * README.md * python file modify * delete license in fastdeploy/ * repush the conflict part * README.md modified * README.md modified * file path modified * file path modified * file path modified * file path modified * file path modified * README modified * README modified * move some helpers to private * add examples for yolov7 * api.md modified * api.md modified * api.md modified * YOLOv7 * yolov7 release link * yolov7 release link * yolov7 release link * copyright * change some helpers to private * change variables to const and fix documents. * gitignore * Transfer some funtions to private member of class * Transfer some funtions to private member of class * Merge from develop (#9) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason Co-authored-by: root Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> * first commit for yolor * for merge * Develop (#11) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason Co-authored-by: root Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> * Yolor (#16) * Develop (#11) (#12) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason Co-authored-by: root Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> Co-authored-by: Jason Co-authored-by: root Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> * Develop (#13) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: Jason Co-authored-by: root Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> * documents * documents * documents * documents * documents * documents * documents * documents * documents * documents * documents * documents * Develop (#14) * Fix compile problem in different python version (#26) * fix some usage problem in linux * Fix compile problem Co-authored-by: root * Add PaddleDetetion/PPYOLOE model support (#22) * add ppdet/ppyoloe * Add demo code and documents * add convert processor to vision (#27) * update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * fixed examples/CMakeLists.txt to avoid conflicts * add convert processor to vision * format examples/CMakeLists summary * Fix bug while the inference result is empty with YOLOv5 (#29) * Add multi-label function for yolov5 * Update README.md Update doc * Update fastdeploy_runtime.cc fix variable option.trt_max_shape wrong name * Update runtime_option.md Update resnet model dynamic shape setting name from images to x * Fix bug when inference result boxes are empty * Delete detection.py Co-authored-by: root Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> Co-authored-by: Jason Co-authored-by: root Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> Co-authored-by: Jason <928090362@qq.com> * add is_dynamic for YOLO series (#22) * modify ppmatting backend and docs * modify ppmatting docs * fix the PPMatting size problem * fix LimitShort's log * retrigger ci * modify PPMatting docs * modify the way for dealing with LimitShort * add pphumanmatting and modnet series * docs of PPMatting series * add explanation of newly added processors and fix processors * Modify LimitShort function and ppmatting.cc * modify ResizeByShort and ppmatting.cc * change resize_to_int_mult to limit_by_stride and delete resize_by_input_shape * retrigger ci * retrigger ci * fix problem produced by ResizeByShort * Update eigen.cmake * Delete eigen.cmake * refine code * add test file for ppmatting series * add squeeze for fd_tensor and modify ppmatting.cc Co-authored-by: Jason Co-authored-by: root Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com> Co-authored-by: huangjianhui <852142024@qq.com> Co-authored-by: Jason <928090362@qq.com> --- examples/vision/matting/README.md | 2 + examples/vision/matting/ppmatting/README.md | 12 +- .../vision/matting/ppmatting/cpp/infer.cc | 2 +- fastdeploy/core/fd_tensor.cc | 7 + fastdeploy/core/fd_tensor.h | 4 + fastdeploy/vision/common/processors/crop.cc | 65 +++++++ fastdeploy/vision/common/processors/crop.h | 47 +++++ ...size_to_int_mult.cc => limit_by_stride.cc} | 18 +- ...resize_to_int_mult.h => limit_by_stride.h} | 15 +- .../vision/common/processors/limit_long.cc | 70 ++++++++ .../vision/common/processors/limit_long.h | 51 ++++++ .../vision/common/processors/limit_short.cc | 12 +- .../vision/common/processors/limit_short.h | 8 +- .../vision/common/processors/pad_to_size.cc | 6 + .../vision/common/processors/pad_to_size.h | 2 +- .../common/processors/resize_by_short.cc | 39 +++-- .../common/processors/resize_by_short.h | 13 +- .../vision/common/processors/transform.h | 4 +- fastdeploy/vision/detection/ppdet/ppyoloe.cc | 7 +- .../vision/matting/ppmatting/ppmatting.cc | 162 ++++++++---------- tests/eval_example/test_ppmatting.py | 109 ++++++++++++ 21 files changed, 523 insertions(+), 132 deletions(-) create mode 100644 fastdeploy/vision/common/processors/crop.cc create mode 100644 fastdeploy/vision/common/processors/crop.h rename fastdeploy/vision/common/processors/{resize_to_int_mult.cc => limit_by_stride.cc} (75%) rename fastdeploy/vision/common/processors/{resize_to_int_mult.h => limit_by_stride.h} (76%) create mode 100644 fastdeploy/vision/common/processors/limit_long.cc create mode 100644 fastdeploy/vision/common/processors/limit_long.h create mode 100644 tests/eval_example/test_ppmatting.py diff --git a/examples/vision/matting/README.md b/examples/vision/matting/README.md index fafc3b6e1..afe434f52 100644 --- a/examples/vision/matting/README.md +++ b/examples/vision/matting/README.md @@ -6,3 +6,5 @@ FastDeploy目前支持如下抠图模型部署 | :--- | :--- | :------- | :--- | | [ZHKKKe/MODNet](./modnet) | MODNet 系列模型 | ONNX | [CommitID:28165a4](https://github.com/ZHKKKe/MODNet/commit/28165a4) | | [PaddleSeg/PPMatting](./ppmatting) | PPMatting 系列模型 | Paddle | [Release/2.6](https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/Matting) | +| [PaddleSeg/PPHumanMatting](./ppmatting) | PPHumanMatting 系列模型 | Paddle | [Release/2.6](https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/Matting) | +| [PaddleSeg/ModNet](./ppmatting) | ModNet 系列模型 | Paddle | [Release/2.6](https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/Matting) | diff --git a/examples/vision/matting/ppmatting/README.md b/examples/vision/matting/ppmatting/README.md index d71432284..067fde308 100644 --- a/examples/vision/matting/ppmatting/README.md +++ b/examples/vision/matting/ppmatting/README.md @@ -9,11 +9,13 @@ 目前FastDeploy支持如下模型的部署 - [PPMatting系列模型](https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/Matting) +- [PPHumanMatting系列模型](https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/Matting) +- [ModNet系列模型](https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/Matting) ## 导出部署模型 -在部署前，需要先将PPMatting导出成部署模型，导出步骤参考文档[导出模型](https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/Matting) +在部署前，需要先将PPMatting导出成部署模型，导出步骤参考文档[导出模型](https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/Matting)(Tips:导出PPMatting系列模型和PPHumanMatting系列模型需要设置导出脚本的`--input_shape`参数) ## 下载预训练模型 @@ -25,8 +27,12 @@ | 模型 | 参数大小 | 精度 | 备注 | |:---------------------------------------------------------------- |:----- |:----- | :------ | -| [PPMatting-512](https://bj.bcebos.com/paddlehub/fastdeploy/PP-Matting-512.tgz) | 87MB | - | -| [PPMatting-1024](https://bj.bcebos.com/paddlehub/fastdeploy/PP-Matting-1024.tgz) | 87MB | - | +| [PPMatting-512](https://bj.bcebos.com/paddlehub/fastdeploy/PP-Matting-512.tgz) | 106MB | - | +| [PPMatting-1024](https://bj.bcebos.com/paddlehub/fastdeploy/PP-Matting-1024.tgz) | 106MB | - | +| [PPHumanMatting](https://bj.bcebos.com/paddlehub/fastdeploy/PPHumanMatting.tgz) | 247MB | - | +| [Modnet_ResNet50_vd](https://bj.bcebos.com/paddlehub/fastdeploy/PPModnet_ResNet50_vd.tgz) | 355MB | - | +| [Modnet_MobileNetV2](https://bj.bcebos.com/paddlehub/fastdeploy/PPModnet_MobileNetV2.tgz) | 28MB | - | +| [Modnet_HRNet_w18](https://bj.bcebos.com/paddlehub/fastdeploy/PPModnet_HRNet_w18.tgz) | 51MB | - | diff --git a/examples/vision/matting/ppmatting/cpp/infer.cc b/examples/vision/matting/ppmatting/cpp/infer.cc index f47b484e5..d7cad27d4 100644 --- a/examples/vision/matting/ppmatting/cpp/infer.cc +++ b/examples/vision/matting/ppmatting/cpp/infer.cc @@ -81,7 +81,7 @@ void GpuInfer(const std::string& model_dir, const std::string& image_file, cv::imwrite("visualized_result.jpg", vis_im_with_bg); cv::imwrite("visualized_result_fg.jpg", vis_im); std::cout << "Visualized result save in ./visualized_result_replaced_bg.jpg " - "and ./visualized_result_fg.jpgg" + "and ./visualized_result_fg.jpg" << std::endl; } diff --git a/fastdeploy/core/fd_tensor.cc b/fastdeploy/core/fd_tensor.cc index 00a7ae2b7..2670b355e 100644 --- a/fastdeploy/core/fd_tensor.cc +++ b/fastdeploy/core/fd_tensor.cc @@ -85,6 +85,13 @@ void FDTensor::ExpandDim(int64_t axis) { shape.insert(shape.begin() + axis, 1); } +void FDTensor::Squeeze(int64_t axis) { + size_t ndim = shape.size(); + FDASSERT(axis >= 0 && axis < ndim, + "The allowed 'axis' must be in range of (0, %lu)!", ndim); + shape.erase(shape.begin() + axis); +} + void FDTensor::Allocate(const std::vector& new_shape, const FDDataType& data_type, const std::string& tensor_name, diff --git a/fastdeploy/core/fd_tensor.h b/fastdeploy/core/fd_tensor.h index 08e500d08..7e8bb7851 100644 --- a/fastdeploy/core/fd_tensor.h +++ b/fastdeploy/core/fd_tensor.h @@ -71,6 +71,10 @@ struct FASTDEPLOY_DECL FDTensor { // at the `axis` position in the expanded Tensor shape. void ExpandDim(int64_t axis = 0); + // Squeeze the shape of a Tensor. Erase the axis that will appear + // at the `axis` position in the squeezed Tensor shape. + void Squeeze(int64_t axis = 0); + // Initialize Tensor // Include setting attribute for tensor // and allocate cpu memory buffer diff --git a/fastdeploy/vision/common/processors/crop.cc b/fastdeploy/vision/common/processors/crop.cc new file mode 100644 index 000000000..19c451616 --- /dev/null +++ b/fastdeploy/vision/common/processors/crop.cc @@ -0,0 +1,65 @@ +// 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/common/processors/crop.h" + +namespace fastdeploy { +namespace vision { + +bool Crop::CpuRun(Mat* mat) { + cv::Mat* im = mat->GetCpuMat(); + int height = static_cast(im->rows); + int width = static_cast(im->cols); + if (height < height_ + offset_h_ || width < width_ + offset_w_) { + FDERROR << "[Crop] Cannot crop [" << height_ << ", " << width_ + << "] from the input image [" << height << ", " << width + << "], with offset [" << offset_h_ << ", " << offset_w_ << "]." + << std::endl; + return false; + } + cv::Rect crop_roi(offset_w_, offset_h_, width_, height_); + *im = (*im)(crop_roi); + mat->SetWidth(width_); + mat->SetHeight(height_); + return true; +} + +#ifdef ENABLE_OPENCV_CUDA +bool Crop::GpuRun(Mat* mat) { + cv::cuda::GpuMat* im = mat->GetGpuMat(); + int height = static_cast(im->rows); + int width = static_cast(im->cols); + if (height < height_ + offset_h_ || width < width_ + offset_w_) { + FDERROR << "[Crop] Cannot crop [" << height_ << ", " << width_ + << "] from the input image [" << height << ", " << width + << "], with offset [" << offset_h_ << ", " << offset_w_ << "]." + << std::endl; + return false; + } + cv::Rect crop_roi(offset_w_, offset_h_, width_, height_); + *im = (*im)(crop_roi); + mat->SetWidth(width_); + mat->SetHeight(height_); + return true; +} +#endif + +bool Crop::Run(Mat* mat, int offset_w, int offset_h, int width, int height, + ProcLib lib) { + auto c = Crop(offset_w, offset_h, width, height); + return c(mat, lib); +} + +} // namespace vision +} // namespace fastdeploy diff --git a/fastdeploy/vision/common/processors/crop.h b/fastdeploy/vision/common/processors/crop.h new file mode 100644 index 000000000..0148faed2 --- /dev/null +++ b/fastdeploy/vision/common/processors/crop.h @@ -0,0 +1,47 @@ +// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#pragma once + +#include "fastdeploy/vision/common/processors/base.h" + +namespace fastdeploy { +namespace vision { + +class Crop : public Processor { + public: + Crop(int offset_w, int offset_h, int width, int height) { + offset_w_ = offset_w; + offset_h_ = offset_h; + width_ = width; + height_ = height; + } + bool CpuRun(Mat* mat); +#ifdef ENABLE_OPENCV_CUDA + bool GpuRun(Mat* mat); +#endif + std::string Name() { return "Crop"; } + + static bool Run(Mat* mat, int offset_w, int offset_h, int width, int height, + ProcLib lib = ProcLib::OPENCV_CPU); + + private: + int offset_w_; + int offset_h_; + int height_; + int width_; +}; + +} // namespace vision +} // namespace fastdeploy diff --git a/fastdeploy/vision/common/processors/resize_to_int_mult.cc b/fastdeploy/vision/common/processors/limit_by_stride.cc similarity index 75% rename from fastdeploy/vision/common/processors/resize_to_int_mult.cc rename to fastdeploy/vision/common/processors/limit_by_stride.cc index 9659b101f..aa573ce88 100644 --- a/fastdeploy/vision/common/processors/resize_to_int_mult.cc +++ b/fastdeploy/vision/common/processors/limit_by_stride.cc @@ -12,17 +12,17 @@ // See the License for the specific language governing permissions and // limitations under the License. -#include "fastdeploy/vision/common/processors/resize_to_int_mult.h" +#include "fastdeploy/vision/common/processors/limit_by_stride.h" namespace fastdeploy { namespace vision { -bool ResizeToIntMult::CpuRun(Mat* mat) { +bool LimitByStride::CpuRun(Mat* mat) { cv::Mat* im = mat->GetCpuMat(); int origin_w = im->cols; int origin_h = im->rows; - int rw = origin_w - origin_w % mult_int_; - int rh = origin_h - origin_h % mult_int_; + int rw = origin_w - origin_w % stride_; + int rh = origin_h - origin_h % stride_; if (rw != origin_w || rh != origin_w) { cv::resize(*im, *im, cv::Size(rw, rh), 0, 0, interp_); mat->SetWidth(im->cols); @@ -32,13 +32,13 @@ bool ResizeToIntMult::CpuRun(Mat* mat) { } #ifdef ENABLE_OPENCV_CUDA -bool ResizeToIntMult::GpuRun(Mat* mat) { +bool LimitByStride::GpuRun(Mat* mat) { cv::cuda::GpuMat* im = mat->GetGpuMat(); int origin_w = im->cols; int origin_h = im->rows; im->convertTo(*im, CV_32FC(im->channels())); - int rw = origin_w - origin_w % mult_int_; - int rh = origin_h - origin_h % mult_int_; + int rw = origin_w - origin_w % stride_; + int rh = origin_h - origin_h % stride_; if (rw != origin_w || rh != origin_w) { cv::cuda::resize(*im, *im, cv::Size(rw, rh), 0, 0, interp_); mat->SetWidth(im->cols); @@ -48,8 +48,8 @@ bool ResizeToIntMult::GpuRun(Mat* mat) { } #endif -bool ResizeToIntMult::Run(Mat* mat, int mult_int, int interp, ProcLib lib) { - auto r = ResizeToIntMult(mult_int, interp); +bool LimitByStride::Run(Mat* mat, int stride, int interp, ProcLib lib) { + auto r = LimitByStride(stride, interp); return r(mat, lib); } } // namespace vision diff --git a/fastdeploy/vision/common/processors/resize_to_int_mult.h b/fastdeploy/vision/common/processors/limit_by_stride.h similarity index 76% rename from fastdeploy/vision/common/processors/resize_to_int_mult.h rename to fastdeploy/vision/common/processors/limit_by_stride.h index 71a2aaa8d..13c6e307e 100644 --- a/fastdeploy/vision/common/processors/resize_to_int_mult.h +++ b/fastdeploy/vision/common/processors/limit_by_stride.h @@ -19,24 +19,27 @@ namespace fastdeploy { namespace vision { -class ResizeToIntMult : public Processor { +class LimitByStride : public Processor { public: - explicit ResizeToIntMult(int mult_int = 32, int interp = 1) { - mult_int_ = mult_int; + explicit LimitByStride(int stride = 32, int interp = 1) { + stride_ = stride; interp_ = interp; } + + // Resize Mat* mat to make the size divisible by stride_. + bool CpuRun(Mat* mat); #ifdef ENABLE_OPENCV_CUDA bool GpuRun(Mat* mat); #endif - std::string Name() { return "ResizeToIntMult"; } + std::string Name() { return "LimitByStride"; } - static bool Run(Mat* mat, int mult_int = 32, int interp = 1, + static bool Run(Mat* mat, int stride = 32, int interp = 1, ProcLib lib = ProcLib::OPENCV_CPU); private: int interp_; - int mult_int_; + int stride_; }; } // namespace vision } // namespace fastdeploy diff --git a/fastdeploy/vision/common/processors/limit_long.cc b/fastdeploy/vision/common/processors/limit_long.cc new file mode 100644 index 000000000..246497c97 --- /dev/null +++ b/fastdeploy/vision/common/processors/limit_long.cc @@ -0,0 +1,70 @@ +// 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/common/processors/limit_long.h" + +namespace fastdeploy { +namespace vision { + +bool LimitLong::CpuRun(Mat* mat) { + cv::Mat* im = mat->GetCpuMat(); + int origin_w = im->cols; + int origin_h = im->rows; + int im_size_max = std::max(origin_w, origin_h); + int target = im_size_max; + if (max_long_ > 0 && im_size_max > max_long_) { + target = max_long_; + } else if (min_long_ > 0 && im_size_max < min_long_) { + target = min_long_; + } + if (target != im_size_max) { + double scale = + static_cast(target) / static_cast(im_size_max); + cv::resize(*im, *im, cv::Size(), scale, scale, interp_); + mat->SetWidth(im->cols); + mat->SetHeight(im->rows); + } + return true; +} + +#ifdef ENABLE_OPENCV_CUDA +bool LimitLong::GpuRun(Mat* mat) { + cv::cuda::GpuMat* im = mat->GetGpuMat(); + int origin_w = im->cols; + int origin_h = im->rows; + im->convertTo(*im, CV_32FC(im->channels())); + int im_size_max = std::max(origin_w, origin_h); + int target = im_size_max; + if (max_long_ > 0 && im_size_max > max_long_) { + target = max_long_; + } else if (min_long_ > 0 && im_size_max < min_long_) { + target = min_long_; + } + if (target != im_size_max) { + double scale = + static_cast(target) / static_cast(im_size_max); + cv::cuda::resize(*im, *im, cv::Size(), scale, scale, interp_); + mat->SetWidth(im->cols); + mat->SetHeight(im->rows); + } + return true; +} +#endif + +bool LimitLong::Run(Mat* mat, int max_long, int min_long, ProcLib lib) { + auto l = LimitLong(max_long, min_long); + return l(mat, lib); +} +} // namespace vision +} // namespace fastdeploy diff --git a/fastdeploy/vision/common/processors/limit_long.h b/fastdeploy/vision/common/processors/limit_long.h new file mode 100644 index 000000000..8c67212a5 --- /dev/null +++ b/fastdeploy/vision/common/processors/limit_long.h @@ -0,0 +1,51 @@ +// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#pragma once + +#include "fastdeploy/vision/common/processors/base.h" + +namespace fastdeploy { +namespace vision { + +class LimitLong : public Processor { + public: + explicit LimitLong(int max_long = -1, int min_long = -1, int interp = 1) { + max_long_ = max_long; + min_long_ = min_long; + interp_ = interp; + } + + // Limit the long edge of image. + // If the long edge is larger than max_long_, resize the long edge + // to max_long_, while scale the short edge proportionally. + // If the long edge is smaller than min_long_, resize the long edge + // to min_long_, while scale the short edge proportionally. + bool CpuRun(Mat* mat); +#ifdef ENABLE_OPENCV_CUDA + bool GpuRun(Mat* mat); +#endif + std::string Name() { return "LimitLong"; } + + static bool Run(Mat* mat, int max_long = -1, int min_long = -1, + ProcLib lib = ProcLib::OPENCV_CPU); + int GetMaxLong() const { return max_long_; } + + private: + int max_long_; + int min_long_; + int interp_; +}; +} // namespace vision +} // namespace fastdeploy diff --git a/fastdeploy/vision/common/processors/limit_short.cc b/fastdeploy/vision/common/processors/limit_short.cc index b08bb0ef5..ce0daa282 100644 --- a/fastdeploy/vision/common/processors/limit_short.cc +++ b/fastdeploy/vision/common/processors/limit_short.cc @@ -28,9 +28,11 @@ bool LimitShort::CpuRun(Mat* mat) { } else if (min_short_ > 0 && im_size_min < min_short_) { target = min_short_; } + double scale = -1.f; if (target != im_size_min) { - double scale = - static_cast(target) / static_cast(im_size_min); + scale = static_cast(target) / static_cast(im_size_min); + } + if (scale > 0) { cv::resize(*im, *im, cv::Size(), scale, scale, interp_); mat->SetWidth(im->cols); mat->SetHeight(im->rows); @@ -51,9 +53,11 @@ bool LimitShort::GpuRun(Mat* mat) { } else if (min_short_ > 0 && im_size_min < min_short_) { target = min_short_; } + double scale = -1.f; if (target != im_size_min) { - double scale = - static_cast(target) / static_cast(im_size_min); + scale = static_cast(target) / static_cast(im_size_min); + } + if (scale > 0) { cv::cuda::resize(*im, *im, cv::Size(), scale, scale, interp_); mat->SetWidth(im->cols); mat->SetHeight(im->rows); diff --git a/fastdeploy/vision/common/processors/limit_short.h b/fastdeploy/vision/common/processors/limit_short.h index 25eff6d71..5995c8753 100644 --- a/fastdeploy/vision/common/processors/limit_short.h +++ b/fastdeploy/vision/common/processors/limit_short.h @@ -26,6 +26,12 @@ class LimitShort : public Processor { min_short_ = min_short; interp_ = interp; } + + // Limit the short edge of image. + // If the short edge is larger than max_short_, resize the short edge + // to max_short_, while scale the long edge proportionally. + // If the short edge is smaller than min_short_, resize the short edge + // to min_short_, while scale the long edge proportionally. bool CpuRun(Mat* mat); #ifdef ENABLE_OPENCV_CUDA bool GpuRun(Mat* mat); @@ -34,7 +40,7 @@ class LimitShort : public Processor { static bool Run(Mat* mat, int max_short = -1, int min_short = -1, ProcLib lib = ProcLib::OPENCV_CPU); - int GetMaxShort() { return max_short_; } + int GetMaxShort() const { return max_short_; } private: int max_short_; diff --git a/fastdeploy/vision/common/processors/pad_to_size.cc b/fastdeploy/vision/common/processors/pad_to_size.cc index d4cbacd87..77bf271bd 100644 --- a/fastdeploy/vision/common/processors/pad_to_size.cc +++ b/fastdeploy/vision/common/processors/pad_to_size.cc @@ -18,6 +18,9 @@ namespace fastdeploy { namespace vision { bool PadToSize::CpuRun(Mat* mat) { + if (width_ == -1 || height_ == -1) { + return true; + } if (mat->layout != Layout::HWC) { FDERROR << "PadToSize: The input data must be Layout::HWC format!" << std::endl; @@ -74,6 +77,9 @@ bool PadToSize::CpuRun(Mat* mat) { #ifdef ENABLE_OPENCV_CUDA bool PadToSize::GpuRun(Mat* mat) { + if (width_ == -1 || height_ == -1) { + return true; + } if (mat->layout != Layout::HWC) { FDERROR << "PadToSize: The input data must be Layout::HWC format!" << std::endl; diff --git a/fastdeploy/vision/common/processors/pad_to_size.h b/fastdeploy/vision/common/processors/pad_to_size.h index ece0158f7..ff3ac159f 100644 --- a/fastdeploy/vision/common/processors/pad_to_size.h +++ b/fastdeploy/vision/common/processors/pad_to_size.h @@ -21,7 +21,7 @@ namespace vision { class PadToSize : public Processor { public: - // only support pad with left-top padding mode + // only support pad with right-bottom padding mode PadToSize(int width, int height, const std::vector& value) { width_ = width; height_ = height; diff --git a/fastdeploy/vision/common/processors/resize_by_short.cc b/fastdeploy/vision/common/processors/resize_by_short.cc index 8e850425f..72ac33ac9 100644 --- a/fastdeploy/vision/common/processors/resize_by_short.cc +++ b/fastdeploy/vision/common/processors/resize_by_short.cc @@ -22,12 +22,14 @@ bool ResizeByShort::CpuRun(Mat* mat) { int origin_w = im->cols; int origin_h = im->rows; double scale = GenerateScale(origin_w, origin_h); - if (use_scale_) { + if (use_scale_ && fabs(scale - 1.0) >= 1e-06) { cv::resize(*im, *im, cv::Size(), scale, scale, interp_); } else { int width = static_cast(round(scale * im->cols)); int height = static_cast(round(scale * im->rows)); - cv::resize(*im, *im, cv::Size(width, height), 0, 0, interp_); + if (width != origin_w || height != origin_h) { + cv::resize(*im, *im, cv::Size(width, height), 0, 0, interp_); + } } mat->SetWidth(im->cols); mat->SetHeight(im->rows); @@ -41,12 +43,14 @@ bool ResizeByShort::GpuRun(Mat* mat) { int origin_h = im->rows; double scale = GenerateScale(origin_w, origin_h); im->convertTo(*im, CV_32FC(im->channels())); - if (use_scale_) { + if (use_scale_ && fabs(scale - 1.0) >= 1e-06) { cv::cuda::resize(*im, *im, cv::Size(), scale, scale, interp_); } else { int width = static_cast(round(scale * im->cols)); int height = static_cast(round(scale * im->rows)); - cv::cuda::resize(*im, *im, cv::Size(width, height), 0, 0, interp_); + if (width != origin_w || height != origin_h) { + cv::cuda::resize(*im, *im, cv::Size(width, height), 0, 0, interp_); + } } mat->SetWidth(im->cols); mat->SetHeight(im->rows); @@ -59,18 +63,31 @@ double ResizeByShort::GenerateScale(const int origin_w, const int origin_h) { int im_size_min = std::min(origin_w, origin_h); double scale = static_cast(target_size_) / static_cast(im_size_min); - if (max_size_ > 0) { - if (round(scale * im_size_max) > max_size_) { - scale = static_cast(max_size_) / static_cast(im_size_max); + + if (max_hw_.size() > 0) { + FDASSERT(max_hw_.size() == 2, + "Require size of max_hw_ be 2, but now it's %zu.", max_hw_.size()); + FDASSERT( + max_hw_[0] > 0 && max_hw_[1] > 0, + "Require elements in max_hw_ greater than 0, but now it's [%d, %d].", + max_hw_[0], max_hw_[1]); + + double scale_h = + static_cast(max_hw_[0]) / static_cast(origin_h); + double scale_w = + static_cast(max_hw_[1]) / static_cast(origin_w); + double min_scale = std::min(scale_h, scale_w); + if (min_scale < scale) { + scale = min_scale; } } return scale; } bool ResizeByShort::Run(Mat* mat, int target_size, int interp, bool use_scale, - int max_size, ProcLib lib) { - auto r = ResizeByShort(target_size, interp, use_scale, max_size); + const std::vector& max_hw, ProcLib lib) { + auto r = ResizeByShort(target_size, interp, use_scale, max_hw); return r(mat, lib); } -} // namespace vision -} // namespace fastdeploy +} // namespace vision +} // namespace fastdeploy diff --git a/fastdeploy/vision/common/processors/resize_by_short.h b/fastdeploy/vision/common/processors/resize_by_short.h index 023748e9e..4fadb905e 100644 --- a/fastdeploy/vision/common/processors/resize_by_short.h +++ b/fastdeploy/vision/common/processors/resize_by_short.h @@ -22,9 +22,9 @@ namespace vision { class ResizeByShort : public Processor { public: ResizeByShort(int target_size, int interp = 1, bool use_scale = true, - int max_size = -1) { + const std::vector& max_hw = std::vector()) { target_size_ = target_size; - max_size_ = max_size; + max_hw_ = max_hw; interp_ = interp; use_scale_ = use_scale; } @@ -35,15 +35,16 @@ class ResizeByShort : public Processor { std::string Name() { return "ResizeByShort"; } static bool Run(Mat* mat, int target_size, int interp = 1, - bool use_scale = true, int max_size = -1, + bool use_scale = true, + const std::vector& max_hw = std::vector(), ProcLib lib = ProcLib::OPENCV_CPU); private: double GenerateScale(const int origin_w, const int origin_h); int target_size_; - int max_size_; + std::vector max_hw_; int interp_; bool use_scale_; }; -} // namespace vision -} // namespace fastdeploy +} // namespace vision +} // namespace fastdeploy diff --git a/fastdeploy/vision/common/processors/transform.h b/fastdeploy/vision/common/processors/transform.h index cf720ceb7..5522c138c 100644 --- a/fastdeploy/vision/common/processors/transform.h +++ b/fastdeploy/vision/common/processors/transform.h @@ -18,7 +18,10 @@ #include "fastdeploy/vision/common/processors/center_crop.h" #include "fastdeploy/vision/common/processors/color_space_convert.h" #include "fastdeploy/vision/common/processors/convert.h" +#include "fastdeploy/vision/common/processors/crop.h" #include "fastdeploy/vision/common/processors/hwc2chw.h" +#include "fastdeploy/vision/common/processors/limit_by_stride.h" +#include "fastdeploy/vision/common/processors/limit_long.h" #include "fastdeploy/vision/common/processors/limit_short.h" #include "fastdeploy/vision/common/processors/normalize.h" #include "fastdeploy/vision/common/processors/pad.h" @@ -26,5 +29,4 @@ #include "fastdeploy/vision/common/processors/resize.h" #include "fastdeploy/vision/common/processors/resize_by_long.h" #include "fastdeploy/vision/common/processors/resize_by_short.h" -#include "fastdeploy/vision/common/processors/resize_to_int_mult.h" #include "fastdeploy/vision/common/processors/stride_pad.h" diff --git a/fastdeploy/vision/detection/ppdet/ppyoloe.cc b/fastdeploy/vision/detection/ppdet/ppyoloe.cc index 0c0207404..ee28dfe38 100644 --- a/fastdeploy/vision/detection/ppdet/ppyoloe.cc +++ b/fastdeploy/vision/detection/ppdet/ppyoloe.cc @@ -122,8 +122,13 @@ bool PPYOLOE::BuildPreprocessPipelineFromConfig() { } else { int min_target_size = std::min(target_size[0], target_size[1]); int max_target_size = std::max(target_size[0], target_size[1]); + std::vector max_size; + if (max_target_size > 0) { + max_size.push_back(max_target_size); + max_size.push_back(max_target_size); + } processors_.push_back(std::make_shared( - min_target_size, interp, true, max_target_size)); + min_target_size, interp, true, max_size)); } } else if (op_name == "Permute") { // Do nothing, do permute as the last operation diff --git a/fastdeploy/vision/matting/ppmatting/ppmatting.cc b/fastdeploy/vision/matting/ppmatting/ppmatting.cc index a3d0a25e4..a11e220b4 100644 --- a/fastdeploy/vision/matting/ppmatting/ppmatting.cc +++ b/fastdeploy/vision/matting/ppmatting/ppmatting.cc @@ -60,33 +60,54 @@ bool PPMatting::BuildPreprocessPipelineFromConfig() { return false; } + FDASSERT((cfg["Deploy"]["input_shape"]), + "The yaml file should include input_shape parameters"); + // input_shape + // b c h w + auto input_shape = cfg["Deploy"]["input_shape"].as>(); + FDASSERT(input_shape.size() == 4, + "The input_shape in yaml file need to be 4-dimensions, but now its " + "dimension is %zu.", + input_shape.size()); + + bool is_fixed_input_shape = false; + if (input_shape[2] > 0 && input_shape[3] > 0) { + is_fixed_input_shape = true; + } + if (input_shape[2] < 0 || input_shape[3] < 0) { + FDWARNING << "Detected dynamic input shape of your model, only Paddle " + "Inference / OpenVINO support this model now." + << std::endl; + } if (cfg["Deploy"]["transforms"]) { auto preprocess_cfg = cfg["Deploy"]["transforms"]; + int long_size = -1; for (const auto& op : preprocess_cfg) { FDASSERT(op.IsMap(), "Require the transform information in yaml be Map type."); if (op["type"].as() == "LimitShort") { - int max_short = -1; - int min_short = -1; - if (op["max_short"]) { - max_short = op["max_short"].as(); + int max_short = op["max_short"] ? op["max_short"].as() : -1; + int min_short = op["min_short"] ? op["min_short"].as() : -1; + if (is_fixed_input_shape) { + // if the input shape is fixed, will resize by scale, and the max + // shape will not exceed input_shape + long_size = max_short; + std::vector max_size = {input_shape[2], input_shape[3]}; + processors_.push_back( + std::make_shared(long_size, 1, true, max_size)); + } else { + processors_.push_back( + std::make_shared(max_short, min_short)); } - if (op["min_short"]) { - min_short = op["min_short"].as(); - } - FDINFO << "Detected LimitShort processing step in yaml file, if the " - "model is exported from PaddleSeg, please make sure the " - "input of your model is fixed with a square shape, and " - "greater than or equal to " - << max_short << "." << std::endl; - processors_.push_back( - std::make_shared(max_short, min_short)); } else if (op["type"].as() == "ResizeToIntMult") { - int mult_int = 32; - if (op["mult_int"]) { - mult_int = op["mult_int"].as(); + if (is_fixed_input_shape) { + std::vector max_size = {input_shape[2], input_shape[3]}; + processors_.push_back( + std::make_shared(long_size, 1, true, max_size)); + } else { + int mult_int = op["mult_int"] ? op["mult_int"].as() : 32; + processors_.push_back(std::make_shared(mult_int)); } - processors_.push_back(std::make_shared(mult_int)); } else if (op["type"].as() == "Normalize") { std::vector mean = {0.5, 0.5, 0.5}; std::vector std = {0.5, 0.5, 0.5}; @@ -97,58 +118,40 @@ bool PPMatting::BuildPreprocessPipelineFromConfig() { std = op["std"].as>(); } processors_.push_back(std::make_shared(mean, std)); - } else if (op["type"].as() == "ResizeByLong") { - int target_size = op["long_size"].as(); - processors_.push_back(std::make_shared(target_size)); - } else if (op["type"].as() == "Pad") { - // size: (w, h) - auto size = op["size"].as>(); - std::vector value = {127.5, 127.5, 127.5}; - if (op["fill_value"]) { - auto value = op["fill_value"].as>(); - } - processors_.push_back(std::make_shared("float")); - processors_.push_back( - std::make_shared(size[1], size[0], value)); } else if (op["type"].as() == "ResizeByShort") { - int target_size = op["short_size"].as(); - processors_.push_back(std::make_shared(target_size)); + long_size = op["short_size"].as(); + if (is_fixed_input_shape) { + std::vector max_size = {input_shape[2], input_shape[3]}; + processors_.push_back( + std::make_shared(long_size, 1, true, max_size)); + } else { + processors_.push_back(std::make_shared(long_size)); + } } } + // the default padding value is {127.5,127.5,127.5} so after normalizing, + // ((127.5/255)-0.5)/0.5 = 0.0 + std::vector value = {0.0, 0.0, 0.0}; + processors_.push_back(std::make_shared("float")); + processors_.push_back( + std::make_shared(input_shape[3], input_shape[2], value)); processors_.push_back(std::make_shared()); } + return true; } bool PPMatting::Preprocess(Mat* mat, FDTensor* output, std::map>* im_info) { + (*im_info)["input_shape"] = {mat->Height(), mat->Width()}; for (size_t i = 0; i < processors_.size(); ++i) { - if (processors_[i]->Name().compare("LimitShort") == 0) { - int input_h = static_cast(mat->Height()); - int input_w = static_cast(mat->Width()); - auto processor = dynamic_cast(processors_[i].get()); - int max_short = processor->GetMaxShort(); - if (runtime_option.backend != Backend::PDINFER) { - if (input_w != input_h || input_h < max_short || input_w < max_short) { - Resize::Run(mat, max_short, max_short); - } - } - } if (!(*(processors_[i].get()))(mat)) { FDERROR << "Failed to process image data in " << processors_[i]->Name() << "." << std::endl; return false; } - if (processors_[i]->Name().compare("ResizeByLong") == 0) { - (*im_info)["resize_by_long"] = {static_cast(mat->Height()), - static_cast(mat->Width())}; - } } - - // Record output shape of preprocessed image - (*im_info)["output_shape"] = {static_cast(mat->Height()), - static_cast(mat->Width())}; - + (*im_info)["output_shape"] = {mat->Height(), mat->Width()}; mat->ShareWithTensor(output); output->shape.insert(output->shape.begin(), 1); output->name = InputInfoOfRuntime(0).name; @@ -159,8 +162,7 @@ bool PPMatting::Postprocess( std::vector& infer_result, MattingResult* result, const std::map>& im_info) { FDASSERT((infer_result.size() == 1), - "The default number of output tensor must be 1 according to " - "modnet."); + "The default number of output tensor must be 1 "); FDTensor& alpha_tensor = infer_result.at(0); // (1,h,w,1) FDASSERT((alpha_tensor.shape[0] == 1), "Only support batch =1 now."); if (alpha_tensor.dtype != FDDataType::FP32) { @@ -170,41 +172,31 @@ bool PPMatting::Postprocess( auto iter_ipt = im_info.find("input_shape"); auto iter_out = im_info.find("output_shape"); - auto resize_by_long = im_info.find("resize_by_long"); - FDASSERT(iter_out != im_info.end() && iter_ipt != im_info.end(), - "Cannot find input_shape or output_shape from im_info."); - int out_h = iter_out->second[0]; - int out_w = iter_out->second[1]; - int ipt_h = iter_ipt->second[0]; - int ipt_w = iter_ipt->second[1]; - float* alpha_ptr = static_cast(alpha_tensor.Data()); - cv::Mat alpha_zero_copy_ref(out_h, out_w, CV_32FC1, alpha_ptr); - cv::Mat cropped_alpha; - if (resize_by_long != im_info.end()) { - int resize_h = resize_by_long->second[0]; - int resize_w = resize_by_long->second[1]; - alpha_zero_copy_ref(cv::Rect(0, 0, resize_w, resize_h)) - .copyTo(cropped_alpha); - } else { - cropped_alpha = alpha_zero_copy_ref; - } - Mat alpha_resized(cropped_alpha); // ref-only, zero copy. + double scale_h = static_cast(iter_out->second[0]) / + static_cast(iter_ipt->second[0]); + double scale_w = static_cast(iter_out->second[1]) / + static_cast(iter_ipt->second[1]); + double actual_scale = std::min(scale_h, scale_w); - if ((out_h != ipt_h) || (out_w != ipt_w)) { - // already allocated a new continuous memory after resize. - // cv::resize(alpha_resized, alpha_resized, cv::Size(ipt_w, ipt_h)); - Resize::Run(&alpha_resized, ipt_w, ipt_h, -1, -1); - } + int size_before_pad_h = round(actual_scale * iter_ipt->second[0]); + int size_before_pad_w = round(actual_scale * iter_ipt->second[1]); + std::vector dim{0, 2, 3, 1}; + Transpose(alpha_tensor, &alpha_tensor, dim); + alpha_tensor.Squeeze(0); + Mat mat = CreateFromTensor(alpha_tensor); + + Crop::Run(&mat, 0, 0, size_before_pad_w, size_before_pad_h); + Resize::Run(&mat, iter_ipt->second[1], iter_ipt->second[0]); result->Clear(); // note: must be setup shape before Resize result->contain_foreground = false; - result->shape = {static_cast(ipt_h), static_cast(ipt_w)}; - int numel = ipt_h * ipt_w; + result->shape = {iter_ipt->second[0], iter_ipt->second[1]}; + int numel = iter_ipt->second[0] * iter_ipt->second[1]; int nbytes = numel * sizeof(float); result->Resize(numel); - std::memcpy(result->alpha.data(), alpha_resized.GetCpuMat()->data, nbytes); + std::memcpy(result->alpha.data(), mat.GetCpuMat()->data, nbytes); return true; } @@ -214,12 +206,6 @@ bool PPMatting::Predict(cv::Mat* im, MattingResult* result) { std::map> im_info; - // Record the shape of image and the shape of preprocessed image - im_info["input_shape"] = {static_cast(mat.Height()), - static_cast(mat.Width())}; - im_info["output_shape"] = {static_cast(mat.Height()), - static_cast(mat.Width())}; - if (!Preprocess(&mat, &(processed_data[0]), &im_info)) { FDERROR << "Failed to preprocess input data while using model:" << ModelName() << "." << std::endl; diff --git a/tests/eval_example/test_ppmatting.py b/tests/eval_example/test_ppmatting.py new file mode 100644 index 000000000..190f3017f --- /dev/null +++ b/tests/eval_example/test_ppmatting.py @@ -0,0 +1,109 @@ +# Copyright (c) 2020 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 pickle +import numpy as np + + +def test_matting_ppmatting(): + model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/PP-Matting-512.tgz" + input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/matting_input.jpg" + fd.download_and_decompress(model_url, ".") + fd.download(input_url, ".") + model_path = "./PP-Matting-512" + # 配置runtime，加载模型 + runtime_option = fd.RuntimeOption() + model_file = os.path.join(model_path, "model.pdmodel") + params_file = os.path.join(model_path, "model.pdiparams") + config_file = os.path.join(model_path, "deploy.yaml") + model = fd.vision.matting.PPMatting( + model_file, params_file, config_file, runtime_option=runtime_option) + + # 预测图片抠图结果 + im = cv2.imread("./matting_input.jpg") + result = model.predict(im.copy()) + pkl_url = "" + if pkl_url: + fd.download("ppmatting_result.pkl", ".") + with open("./ppmatting_result.pkl", "rb") as f: + baseline = pickle.load(f) + + diff = np.fabs(np.array(result.alpha) - np.array(baseline)) + thres = 1e-05 + assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( + diff.max(), thres) + + +def test_matting_ppmodnet(): + model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/PPModnet_MobileNetV2.tgz" + input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/matting_input.jpg" + fd.download_and_decompress(model_url, ".") + fd.download(input_url, ".") + model_path = "./PPModnet_MobileNetV2" + # 配置runtime，加载模型 + runtime_option = fd.RuntimeOption() + model_file = os.path.join(model_path, "model.pdmodel") + params_file = os.path.join(model_path, "model.pdiparams") + config_file = os.path.join(model_path, "deploy.yaml") + model = fd.vision.matting.PPMatting( + model_file, params_file, config_file, runtime_option=runtime_option) + + # 预测图片抠图结果 + im = cv2.imread("./matting_input.jpg") + result = model.predict(im.copy()) + + pkl_url = "" + if pkl_url: + fd.download("ppmodnet_result.pkl", ".") + with open("./ppmodnet_result.pkl", "rb") as f: + baseline = pickle.load(f) + + diff = np.fabs(np.array(result.alpha) - np.array(baseline)) + thres = 1e-05 + assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( + diff.max(), thres) + + +def test_matting_pphumanmatting(): + model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/PPHumanMatting.tgz" + input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/matting_input.jpg" + fd.download_and_decompress(model_url, ".") + fd.download(input_url, ".") + model_path = "./PPHumanMatting" + # 配置runtime，加载模型 + runtime_option = fd.RuntimeOption() + model_file = os.path.join(model_path, "model.pdmodel") + params_file = os.path.join(model_path, "model.pdiparams") + config_file = os.path.join(model_path, "deploy.yaml") + model = fd.vision.matting.PPMatting( + model_file, params_file, config_file, runtime_option=runtime_option) + + # 预测图片抠图结果 + im = cv2.imread("./matting_input.jpg") + result = model.predict(im.copy()) + + pkl_url = "" + if pkl_url: + fd.download("pphumanmatting_result.pkl", ".") + + with open("./pphumanmatting_result.pkl", "rb") as f: + baseline = pickle.load(f) + + diff = np.fabs(np.array(result.alpha) - np.array(baseline)) + thres = 1e-05 + assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( + diff.max(), thres)