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* Modify documents of YOLOv7 (PaddlePaddle#44)

* 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 <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>

* 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 <jiangjiajun@baidu.com>
Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>
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 <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>

* 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 <jiangjiajun@baidu.com>
Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>
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 <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>

* 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 <jiangjiajun@baidu.com>
Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>
Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
Co-authored-by: huangjianhui <852142024@qq.com>

Co-authored-by: Jason <jiangjiajun@baidu.com>
Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>
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 <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>

* 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 <jiangjiajun@baidu.com>
Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>
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 <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>

* 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 <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>
Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
Co-authored-by: huangjianhui <852142024@qq.com>

Co-authored-by: Jason <jiangjiajun@baidu.com>
Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>
Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
Co-authored-by: huangjianhui <852142024@qq.com>
Co-authored-by: Jason <928090362@qq.com>

* about onnx file with  nms operation in yolov7

* retrigger ci

* retrigger ci

Co-authored-by: Jason <jiangjiajun@baidu.com>
Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>
Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
Co-authored-by: huangjianhui <852142024@qq.com>
Co-authored-by: Jason <928090362@qq.com>

* Fix evaluation import problem (PaddlePaddle#46)

* Detection evaluation function

* Add license

* Fix python import problem

* Modify requirement.txt

* Add requirements.txt

Co-authored-by: Jason <jiangjiajun@baidu.com>

* Fix bug in ppyoloe (PaddlePaddle#47)

* Fix output format for PPYOLOE (PaddlePaddle#50)

* Fix bug in ppyoloe

* fix ppyoloe output format

* Add RetinaFace Model support (PaddlePaddle#48)

* 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

* Add RetinaFace Model support

* fixed retinaface/api.md typos

Co-authored-by: Jason <jiangjiajun@baidu.com>
Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>
Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
Co-authored-by: huangjianhui <852142024@qq.com>
Co-authored-by: Jason <928090362@qq.com>
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1 change: 1 addition & 0 deletions csrcs/fastdeploy/vision.h
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#include "fastdeploy/core/config.h"
#ifdef ENABLE_VISION
#include "fastdeploy/vision/biubug6/retinaface.h"
#include "fastdeploy/vision/deepcam/yolov5face.h"
#include "fastdeploy/vision/linzaer/ultraface.h"
#include "fastdeploy/vision/megvii/yolox.h"
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40 changes: 40 additions & 0 deletions csrcs/fastdeploy/vision/biubug6/biubug6_pybind.cc
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// 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 BindBiubug6(pybind11::module& m) {
auto biubug6_module = m.def_submodule(
"biubug6", "https://github.com/biubug6/Pytorch_Retinaface");
pybind11::class_<vision::biubug6::RetinaFace, FastDeployModel>(biubug6_module,
"RetinaFace")
.def(pybind11::init<std::string, std::string, RuntimeOption, Frontend>())
.def("predict",
[](vision::biubug6::RetinaFace& self, pybind11::array& data,
float conf_threshold, float nms_iou_threshold) {
auto mat = PyArrayToCvMat(data);
vision::FaceDetectionResult res;
self.Predict(&mat, &res, conf_threshold, nms_iou_threshold);
return res;
})
.def_readwrite("size", &vision::biubug6::RetinaFace::size)
.def_readwrite("variance", &vision::biubug6::RetinaFace::variance)
.def_readwrite("downsample_strides",
&vision::biubug6::RetinaFace::downsample_strides)
.def_readwrite("min_sizes", &vision::biubug6::RetinaFace::min_sizes)
.def_readwrite("landmarks_per_face",
&vision::biubug6::RetinaFace::landmarks_per_face);
}
} // namespace fastdeploy
310 changes: 310 additions & 0 deletions csrcs/fastdeploy/vision/biubug6/retinaface.cc
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// 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/biubug6/retinaface.h"
#include "fastdeploy/utils/perf.h"
#include "fastdeploy/vision/utils/utils.h"

namespace fastdeploy {

namespace vision {

namespace biubug6 {

struct RetinaAnchor {
float cx;
float cy;
float s_kx;
float s_ky;
};

void GenerateRetinaAnchors(const std::vector<int>& size,
const std::vector<int>& downsample_strides,
const std::vector<std::vector<int>>& min_sizes,
std::vector<RetinaAnchor>* anchors) {
// size: tuple of input (width, height)
// downsample_strides: downsample strides (steps), e.g (8,16,32)
// min_sizes: width and height for each anchor,
// e.g {{16, 32}, {64, 128}, {256, 512}}
int h = size[1];
int w = size[0];
std::vector<std::vector<int>> feature_maps;
for (auto s : downsample_strides) {
feature_maps.push_back(
{static_cast<int>(
std::ceil(static_cast<float>(h) / static_cast<float>(s))),
static_cast<int>(
std::ceil(static_cast<float>(w) / static_cast<float>(s)))});
}

(*anchors).clear();
const size_t num_feature_map = feature_maps.size();
// reference: layers/functions/prior_box.py#L21
for (size_t k = 0; k < num_feature_map; ++k) {
auto f_map = feature_maps.at(k); // e.g [640//8,640//8]
auto tmp_min_sizes = min_sizes.at(k); // e.g [8,16]
int f_h = f_map.at(0);
int f_w = f_map.at(1);
for (size_t i = 0; i < f_h; ++i) {
for (size_t j = 0; j < f_w; ++j) {
for (auto min_size : tmp_min_sizes) {
float s_kx =
static_cast<float>(min_size) / static_cast<float>(w); // e.g 16/w
float s_ky =
static_cast<float>(min_size) / static_cast<float>(h); // e.g 16/h
// (x + 0.5) * step / w normalized loc mapping to input width
// (y + 0.5) * step / h normalized loc mapping to input height
float s = static_cast<float>(downsample_strides.at(k));
float cx = (static_cast<float>(j) + 0.5f) * s / static_cast<float>(w);
float cy = (static_cast<float>(i) + 0.5f) * s / static_cast<float>(h);
(*anchors).emplace_back(
RetinaAnchor{cx, cy, s_kx, s_ky}); // without clip
}
}
}
}
}

RetinaFace::RetinaFace(const std::string& model_file,
const std::string& params_file,
const RuntimeOption& custom_option,
const Frontend& model_format) {
if (model_format == Frontend::ONNX) {
valid_cpu_backends = {Backend::ORT}; // 指定可用的CPU后端
valid_gpu_backends = {Backend::ORT, Backend::TRT}; // 指定可用的GPU后端
} 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 RetinaFace::Initialize() {
// parameters for preprocess
size = {640, 640};
variance = {0.1f, 0.2f};
downsample_strides = {8, 16, 32};
min_sizes = {{16, 32}, {64, 128}, {256, 512}};
landmarks_per_face = 5;

if (!InitRuntime()) {
FDERROR << "Failed to initialize fastdeploy backend." << std::endl;
return false;
}
// Check if the input shape is dynamic after Runtime already initialized,
is_dynamic_input_ = false;
auto shape = InputInfoOfRuntime(0).shape;
for (int i = 0; i < shape.size(); ++i) {
// if height or width is dynamic
if (i >= 2 && shape[i] <= 0) {
is_dynamic_input_ = true;
break;
}
}
return true;
}

bool RetinaFace::Preprocess(
Mat* mat, FDTensor* output,
std::map<std::string, std::array<float, 2>>* im_info) {
// retinaface's preprocess steps
// 1. Resize
// 2. Convert(opencv style) or Normalize
// 3. HWC->CHW
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);
}

// Compute `result = mat * alpha + beta` directly by channel
// Reference: detect.py#L94
std::vector<float> alpha = {1.f, 1.f, 1.f};
std::vector<float> beta = {-104.f, -117.f, -123.f}; // BGR;
Convert::Run(mat, alpha, beta);

// Record output shape of preprocessed image
(*im_info)["output_shape"] = {static_cast<float>(mat->Height()),
static_cast<float>(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 RetinaFace::Postprocess(
std::vector<FDTensor>& infer_result, FaceDetectionResult* result,
const std::map<std::string, std::array<float, 2>>& im_info,
float conf_threshold, float nms_iou_threshold) {
// retinaface has 3 output tensors, boxes & conf & landmarks
FDASSERT(
(infer_result.size() == 3),
"The default number of output tensor must be 3 according to retinaface.");
FDTensor& boxes_tensor = infer_result.at(0); // (1,n,4)
FDTensor& conf_tensor = infer_result.at(1); // (1,n,2)
FDTensor& landmarks_tensor = infer_result.at(2); // (1,n,10)
FDASSERT((boxes_tensor.shape[0] == 1), "Only support batch =1 now.");
if (boxes_tensor.dtype != FDDataType::FP32) {
FDERROR << "Only support post process with float32 data." << std::endl;
return false;
}

result->Clear();
// must be setup landmarks_per_face before reserve
result->landmarks_per_face = landmarks_per_face;
result->Reserve(boxes_tensor.shape[1]);

float* boxes_ptr = static_cast<float*>(boxes_tensor.Data());
float* conf_ptr = static_cast<float*>(conf_tensor.Data());
float* landmarks_ptr = static_cast<float*>(landmarks_tensor.Data());
const size_t num_bboxes = boxes_tensor.shape[1]; // n
// fetch original image shape
auto iter_ipt = im_info.find("input_shape");
FDASSERT((iter_ipt != im_info.end()),
"Cannot find input_shape from im_info.");
float ipt_h = iter_ipt->second[0];
float ipt_w = iter_ipt->second[1];

// generate anchors with dowmsample strides
std::vector<RetinaAnchor> anchors;
GenerateRetinaAnchors(size, downsample_strides, min_sizes, &anchors);

// decode bounding boxes
for (size_t i = 0; i < num_bboxes; ++i) {
float confidence = conf_ptr[2 * i + 1];
// filter boxes by conf_threshold
if (confidence <= conf_threshold) {
continue;
}
float prior_cx = anchors.at(i).cx;
float prior_cy = anchors.at(i).cy;
float prior_s_kx = anchors.at(i).s_kx;
float prior_s_ky = anchors.at(i).s_ky;

// fetch offsets (dx,dy,dw,dh)
float dx = boxes_ptr[4 * i + 0];
float dy = boxes_ptr[4 * i + 1];
float dw = boxes_ptr[4 * i + 2];
float dh = boxes_ptr[4 * i + 3];
// reference: Pytorch_Retinaface/utils/box_utils.py
float x = prior_cx + dx * variance[0] * prior_s_kx;
float y = prior_cy + dy * variance[0] * prior_s_ky;
float w = prior_s_kx * std::exp(dw * variance[1]);
float h = prior_s_ky * std::exp(dh * variance[1]); // (0.~1.)
// from (x,y,w,h) to (x1,y1,x2,y2)
float x1 = (x - w / 2.f) * ipt_w;
float y1 = (y - h / 2.f) * ipt_h;
float x2 = (x + w / 2.f) * ipt_w;
float y2 = (y + h / 2.f) * ipt_h;
result->boxes.emplace_back(std::array<float, 4>{x1, y1, x2, y2});
result->scores.push_back(confidence);
// decode landmarks (default 5 landmarks)
if (landmarks_per_face > 0) {
// reference: utils/box_utils.py#L241
for (size_t j = 0; j < landmarks_per_face * 2; j += 2) {
float ldx = landmarks_ptr[i * (landmarks_per_face * 2) + (j + 0)];
float ldy = landmarks_ptr[i * (landmarks_per_face * 2) + (j + 1)];
float lx = (prior_cx + ldx * variance[0] * prior_s_kx) * ipt_w;
float ly = (prior_cy + ldy * variance[0] * prior_s_ky) * ipt_h;
result->landmarks.emplace_back(std::array<float, 2>{lx, ly});
}
}
}

if (result->boxes.size() == 0) {
return true;
}

utils::NMS(result, nms_iou_threshold);

// scale and clip box
for (size_t i = 0; i < result->boxes.size(); ++i) {
result->boxes[i][0] = std::max(result->boxes[i][0], 0.0f);
result->boxes[i][1] = std::max(result->boxes[i][1], 0.0f);
result->boxes[i][2] = std::max(result->boxes[i][2], 0.0f);
result->boxes[i][3] = std::max(result->boxes[i][3], 0.0f);
result->boxes[i][0] = std::min(result->boxes[i][0], ipt_w - 1.0f);
result->boxes[i][1] = std::min(result->boxes[i][1], ipt_h - 1.0f);
result->boxes[i][2] = std::min(result->boxes[i][2], ipt_w - 1.0f);
result->boxes[i][3] = std::min(result->boxes[i][3], ipt_h - 1.0f);
}
// scale and clip landmarks
for (size_t i = 0; i < result->landmarks.size(); ++i) {
result->landmarks[i][0] = std::max(result->landmarks[i][0], 0.0f);
result->landmarks[i][1] = std::max(result->landmarks[i][1], 0.0f);
result->landmarks[i][0] = std::min(result->landmarks[i][0], ipt_w - 1.0f);
result->landmarks[i][1] = std::min(result->landmarks[i][1], ipt_h - 1.0f);
}
return true;
}

bool RetinaFace::Predict(cv::Mat* im, FaceDetectionResult* result,
float conf_threshold, float nms_iou_threshold) {
#ifdef FASTDEPLOY_DEBUG
TIMERECORD_START(0)
#endif

Mat mat(*im);
std::vector<FDTensor> input_tensors(1);

std::map<std::string, std::array<float, 2>> im_info;

// Record the shape of image and the shape of preprocessed image
im_info["input_shape"] = {static_cast<float>(mat.Height()),
static_cast<float>(mat.Width())};
im_info["output_shape"] = {static_cast<float>(mat.Height()),
static_cast<float>(mat.Width())};

if (!Preprocess(&mat, &input_tensors[0], &im_info)) {
FDERROR << "Failed to preprocess input image." << std::endl;
return false;
}

#ifdef FASTDEPLOY_DEBUG
TIMERECORD_END(0, "Preprocess")
TIMERECORD_START(1)
#endif

input_tensors[0].name = InputInfoOfRuntime(0).name;
std::vector<FDTensor> output_tensors;
if (!Infer(input_tensors, &output_tensors)) {
FDERROR << "Failed to inference." << std::endl;
return false;
}
#ifdef FASTDEPLOY_DEBUG
TIMERECORD_END(1, "Inference")
TIMERECORD_START(2)
#endif

if (!Postprocess(output_tensors, result, im_info, conf_threshold,
nms_iou_threshold)) {
FDERROR << "Failed to post process." << std::endl;
return false;
}

#ifdef FASTDEPLOY_DEBUG
TIMERECORD_END(2, "Postprocess")
#endif
return true;
}

} // namespace biubug6
} // namespace vision
} // namespace fastdeploy
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