mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-07 01:22:59 +08:00
[Model] Modify SR (#674)
* 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> * 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 python comments for external models * modify resnet c++ comments * modify C++ comments for external models * modify python comments and add result class comments * fix comments compile error * modify result.h comments * modify examples doc and code for SR models * code style * retrigger ci * python file code style * fix examples links * fix examples links * fix examples links 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>
This commit is contained in:
ziqi-jin
@@ -20,8 +20,8 @@ const char sep = '\\';
|
||||
const char sep = '/';
|
||||
#endif
|
||||
|
||||
void CpuInfer(const std::string& model_dir,
|
||||
const std::string& video_file, int frame_num) {
|
||||
void CpuInfer(const std::string& model_dir, const std::string& video_file,
|
||||
int frame_num) {
|
||||
auto model_file = model_dir + sep + "model.pdmodel";
|
||||
auto params_file = model_dir + sep + "model.pdiparams";
|
||||
auto model = fastdeploy::vision::sr::EDVR(model_file, params_file);
|
||||
@@ -32,34 +32,36 @@ void CpuInfer(const std::string& model_dir,
|
||||
}
|
||||
// note: input/output shape is [b, n, c, h, w] (n = frame_nums; b=1(default))
|
||||
// b and n is dependent on export model shape
|
||||
// see https://github.com/PaddlePaddle/PaddleGAN/blob/develop/docs/zh_CN/tutorials/video_super_resolution.md
|
||||
// see
|
||||
// https://github.com/PaddlePaddle/PaddleGAN/blob/develop/docs/zh_CN/tutorials/video_super_resolution.md
|
||||
cv::VideoCapture capture;
|
||||
// change your save video path
|
||||
std::string video_out_name = "output.mp4";
|
||||
capture.open(video_file);
|
||||
if (!capture.isOpened())
|
||||
{
|
||||
std::cout<<"can not open video "<<std::endl;
|
||||
if (!capture.isOpened()) {
|
||||
std::cout << "can not open video " << std::endl;
|
||||
return;
|
||||
}
|
||||
// Get Video info :fps, frame count
|
||||
// it used 4.x version of opencv below
|
||||
// notice your opencv version and method of api.
|
||||
int video_fps = static_cast<int>(capture.get(cv::CAP_PROP_FPS));
|
||||
int video_frame_count = static_cast<int>(capture.get(cv::CAP_PROP_FRAME_COUNT));
|
||||
int video_frame_count =
|
||||
static_cast<int>(capture.get(cv::CAP_PROP_FRAME_COUNT));
|
||||
// Set fixed size for output frame, only for msvsr model
|
||||
int out_width = 1280;
|
||||
int out_height = 720;
|
||||
std::cout << "fps: " << video_fps << "\tframe_count: " << video_frame_count << std::endl;
|
||||
std::cout << "fps: " << video_fps << "\tframe_count: " << video_frame_count
|
||||
<< std::endl;
|
||||
|
||||
// Create VideoWriter for output
|
||||
cv::VideoWriter video_out;
|
||||
std::string video_out_path("./");
|
||||
video_out_path += video_out_name;
|
||||
int fcc = cv::VideoWriter::fourcc('m', 'p', '4', 'v');
|
||||
video_out.open(video_out_path, fcc, video_fps, cv::Size(out_width, out_height), true);
|
||||
if (!video_out.isOpened())
|
||||
{
|
||||
video_out.open(video_out_path, fcc, video_fps,
|
||||
cv::Size(out_width, out_height), true);
|
||||
if (!video_out.isOpened()) {
|
||||
std::cout << "create video writer failed!" << std::endl;
|
||||
return;
|
||||
}
|
||||
@@ -67,42 +69,40 @@ void CpuInfer(const std::string& model_dir,
|
||||
cv::Mat frame;
|
||||
int frame_id = 0;
|
||||
std::vector<cv::Mat> imgs;
|
||||
while (capture.read(frame)){
|
||||
if (!frame.empty())
|
||||
{
|
||||
if(frame_id < frame_num){
|
||||
while (capture.read(frame)) {
|
||||
if (!frame.empty()) {
|
||||
if (frame_id < frame_num) {
|
||||
imgs.push_back(frame);
|
||||
frame_id ++;
|
||||
frame_id++;
|
||||
continue;
|
||||
}
|
||||
imgs.erase(imgs.begin());
|
||||
imgs.push_back(frame);
|
||||
}
|
||||
frame_id ++;
|
||||
frame_id++;
|
||||
std::vector<cv::Mat> results;
|
||||
model.Predict(imgs, results);
|
||||
for (auto &item : results)
|
||||
{
|
||||
for (auto& item : results) {
|
||||
// cv::imshow("13",item);
|
||||
// cv::waitKey(30);
|
||||
video_out.write(item);
|
||||
std::cout << "Processing frame: "<< frame_id << std::endl;
|
||||
std::cout << "Processing frame: " << frame_id << std::endl;
|
||||
}
|
||||
}
|
||||
std::cout << "inference finished, output video saved at " << video_out_path << std::endl;
|
||||
std::cout << "inference finished, output video saved at " << video_out_path
|
||||
<< std::endl;
|
||||
capture.release();
|
||||
video_out.release();
|
||||
}
|
||||
|
||||
void GpuInfer(const std::string& model_dir,
|
||||
const std::string& video_file, int frame_num) {
|
||||
void GpuInfer(const std::string& model_dir, const std::string& video_file,
|
||||
int frame_num) {
|
||||
auto model_file = model_dir + sep + "model.pdmodel";
|
||||
auto params_file = model_dir + sep + "model.pdiparams";
|
||||
|
||||
auto option = fastdeploy::RuntimeOption();
|
||||
option.UseGpu();
|
||||
auto model = fastdeploy::vision::sr::EDVR(
|
||||
model_file, params_file, option);
|
||||
auto model = fastdeploy::vision::sr::EDVR(model_file, params_file, option);
|
||||
|
||||
if (!model.Initialized()) {
|
||||
std::cerr << "Failed to initialize." << std::endl;
|
||||
@@ -110,32 +110,34 @@ void GpuInfer(const std::string& model_dir,
|
||||
}
|
||||
// note: input/output shape is [b, n, c, h, w] (n = frame_nums; b=1(default))
|
||||
// b and n is dependent on export model shape
|
||||
// see https://github.com/PaddlePaddle/PaddleGAN/blob/develop/docs/zh_CN/tutorials/video_super_resolution.md
|
||||
// see
|
||||
// https://github.com/PaddlePaddle/PaddleGAN/blob/develop/docs/zh_CN/tutorials/video_super_resolution.md
|
||||
cv::VideoCapture capture;
|
||||
// change your save video path
|
||||
std::string video_out_name = "output.mp4";
|
||||
capture.open(video_file);
|
||||
if (!capture.isOpened())
|
||||
{
|
||||
std::cout<<"can not open video "<<std::endl;
|
||||
if (!capture.isOpened()) {
|
||||
std::cout << "can not open video " << std::endl;
|
||||
return;
|
||||
}
|
||||
// Get Video info :fps, frame count
|
||||
int video_fps = static_cast<int>(capture.get(cv::CAP_PROP_FPS));
|
||||
int video_frame_count = static_cast<int>(capture.get(cv::CAP_PROP_FRAME_COUNT));
|
||||
int video_frame_count =
|
||||
static_cast<int>(capture.get(cv::CAP_PROP_FRAME_COUNT));
|
||||
// Set fixed size for output frame, only for msvsr model
|
||||
int out_width = 1280;
|
||||
int out_height = 720;
|
||||
std::cout << "fps: " << video_fps << "\tframe_count: " << video_frame_count << std::endl;
|
||||
std::cout << "fps: " << video_fps << "\tframe_count: " << video_frame_count
|
||||
<< std::endl;
|
||||
|
||||
// Create VideoWriter for output
|
||||
cv::VideoWriter video_out;
|
||||
std::string video_out_path("./");
|
||||
video_out_path += video_out_name;
|
||||
int fcc = cv::VideoWriter::fourcc('m', 'p', '4', 'v');
|
||||
video_out.open(video_out_path, fcc, video_fps, cv::Size(out_width, out_height), true);
|
||||
if (!video_out.isOpened())
|
||||
{
|
||||
video_out.open(video_out_path, fcc, video_fps,
|
||||
cv::Size(out_width, out_height), true);
|
||||
if (!video_out.isOpened()) {
|
||||
std::cout << "create video writer failed!" << std::endl;
|
||||
return;
|
||||
}
|
||||
@@ -143,44 +145,44 @@ void GpuInfer(const std::string& model_dir,
|
||||
cv::Mat frame;
|
||||
int frame_id = 0;
|
||||
std::vector<cv::Mat> imgs;
|
||||
while (capture.read(frame)){
|
||||
if (!frame.empty())
|
||||
{
|
||||
if(frame_id < frame_num){
|
||||
while (capture.read(frame)) {
|
||||
if (!frame.empty()) {
|
||||
if (frame_id < frame_num) {
|
||||
imgs.push_back(frame);
|
||||
frame_id ++;
|
||||
frame_id++;
|
||||
continue;
|
||||
}
|
||||
imgs.erase(imgs.begin());
|
||||
imgs.push_back(frame);
|
||||
}
|
||||
frame_id ++;
|
||||
frame_id++;
|
||||
std::vector<cv::Mat> results;
|
||||
model.Predict(imgs, results);
|
||||
for (auto &item : results)
|
||||
{
|
||||
for (auto& item : results) {
|
||||
// cv::imshow("13",item);
|
||||
// cv::waitKey(30);
|
||||
video_out.write(item);
|
||||
std::cout << "Processing frame: "<< frame_id << std::endl;
|
||||
std::cout << "Processing frame: " << frame_id << std::endl;
|
||||
}
|
||||
}
|
||||
std::cout << "inference finished, output video saved at " << video_out_path << std::endl;
|
||||
std::cout << "inference finished, output video saved at " << video_out_path
|
||||
<< std::endl;
|
||||
capture.release();
|
||||
video_out.release();
|
||||
}
|
||||
|
||||
void TrtInfer(const std::string& model_dir,
|
||||
const std::string& video_file, int frame_num) {
|
||||
void TrtInfer(const std::string& model_dir, const std::string& video_file,
|
||||
int frame_num) {
|
||||
auto model_file = model_dir + sep + "model.pdmodel";
|
||||
auto params_file = model_dir + sep + "model.pdiparams";
|
||||
auto option = fastdeploy::RuntimeOption();
|
||||
option.UseGpu();
|
||||
option.UseTrtBackend();
|
||||
// use paddle-TRT
|
||||
option.UseTrtBackend();
|
||||
option.EnablePaddleTrtCollectShape();
|
||||
option.SetTrtInputShape("x", {1, 5, 3, 180, 320});
|
||||
option.EnablePaddleToTrt();
|
||||
auto model = fastdeploy::vision::sr::EDVR(
|
||||
model_file, params_file, option);
|
||||
auto model = fastdeploy::vision::sr::EDVR(model_file, params_file, option);
|
||||
|
||||
if (!model.Initialized()) {
|
||||
std::cerr << "Failed to initialize." << std::endl;
|
||||
@@ -189,75 +191,77 @@ void TrtInfer(const std::string& model_dir,
|
||||
|
||||
// note: input/output shape is [b, n, c, h, w] (n = frame_nums; b=1(default))
|
||||
// b and n is dependent on export model shape
|
||||
// see https://github.com/PaddlePaddle/PaddleGAN/blob/develop/docs/zh_CN/tutorials/video_super_resolution.md
|
||||
// see
|
||||
// https://github.com/PaddlePaddle/PaddleGAN/blob/develop/docs/zh_CN/tutorials/video_super_resolution.md
|
||||
cv::VideoCapture capture;
|
||||
// change your save video path
|
||||
std::string video_out_name = "output.mp4";
|
||||
capture.open(video_file);
|
||||
if (!capture.isOpened())
|
||||
{
|
||||
std::cout<<"can not open video "<<std::endl;
|
||||
if (!capture.isOpened()) {
|
||||
std::cout << "can not open video " << std::endl;
|
||||
return;
|
||||
}
|
||||
// Get Video info :fps, frame count
|
||||
int video_fps = static_cast<int>(capture.get(cv::CAP_PROP_FPS));
|
||||
int video_frame_count = static_cast<int>(capture.get(cv::CAP_PROP_FRAME_COUNT));
|
||||
int video_frame_count =
|
||||
static_cast<int>(capture.get(cv::CAP_PROP_FRAME_COUNT));
|
||||
// Set fixed size for output frame, only for msvsr model
|
||||
//Note that the resolution between the size and the original input is consistent when the model is exported,
|
||||
// Note that the resolution between the size and the original input is
|
||||
// consistent when the model is exported,
|
||||
// for example: [1,2,3,180,320], after 4x super separation [1,2,3,720,1080].
|
||||
//Therefore, it is very important to derive the model
|
||||
// Therefore, it is very important to derive the model
|
||||
int out_width = 1280;
|
||||
int out_height = 720;
|
||||
std::cout << "fps: " << video_fps << "\tframe_count: " << video_frame_count << std::endl;
|
||||
std::cout << "fps: " << video_fps << "\tframe_count: " << video_frame_count
|
||||
<< std::endl;
|
||||
|
||||
// Create VideoWriter for output
|
||||
cv::VideoWriter video_out;
|
||||
std::string video_out_path("./");
|
||||
video_out_path += video_out_name;
|
||||
int fcc = cv::VideoWriter::fourcc('m', 'p', '4', 'v');
|
||||
video_out.open(video_out_path, fcc, video_fps, cv::Size(out_width, out_height), true);
|
||||
if (!video_out.isOpened())
|
||||
{
|
||||
video_out.open(video_out_path, fcc, video_fps,
|
||||
cv::Size(out_width, out_height), true);
|
||||
if (!video_out.isOpened()) {
|
||||
std::cout << "create video writer failed!" << std::endl;
|
||||
return;
|
||||
}
|
||||
// Capture all frames and do inference
|
||||
cv::Mat frame;
|
||||
int frame_id = 0;
|
||||
std::vector<cv::Mat> imgs;
|
||||
while (capture.read(frame)){
|
||||
if (!frame.empty())
|
||||
{
|
||||
if(frame_id < frame_num){
|
||||
imgs.push_back(frame);
|
||||
frame_id ++;
|
||||
continue;
|
||||
}
|
||||
imgs.erase(imgs.begin());
|
||||
imgs.push_back(frame);
|
||||
}
|
||||
frame_id ++;
|
||||
std::vector<cv::Mat> results;
|
||||
model.Predict(imgs, results);
|
||||
for (auto &item : results)
|
||||
{
|
||||
// cv::imshow("13",item);
|
||||
// cv::waitKey(30);
|
||||
video_out.write(item);
|
||||
std::cout << "Processing frame: "<< frame_id << std::endl;
|
||||
}
|
||||
std::vector<cv::Mat> imgs;
|
||||
while (capture.read(frame)) {
|
||||
if (!frame.empty()) {
|
||||
if (frame_id < frame_num) {
|
||||
imgs.push_back(frame);
|
||||
frame_id++;
|
||||
continue;
|
||||
}
|
||||
imgs.erase(imgs.begin());
|
||||
imgs.push_back(frame);
|
||||
}
|
||||
std::cout << "inference finished, output video saved at " << video_out_path << std::endl;
|
||||
frame_id++;
|
||||
std::vector<cv::Mat> results;
|
||||
model.Predict(imgs, results);
|
||||
for (auto& item : results) {
|
||||
// cv::imshow("13",item);
|
||||
// cv::waitKey(30);
|
||||
video_out.write(item);
|
||||
std::cout << "Processing frame: " << frame_id << std::endl;
|
||||
}
|
||||
}
|
||||
std::cout << "inference finished, output video saved at " << video_out_path
|
||||
<< std::endl;
|
||||
capture.release();
|
||||
video_out.release();
|
||||
}
|
||||
|
||||
int main(int argc, char* argv[]) {
|
||||
if (argc < 4) {
|
||||
std::cout
|
||||
<< "Usage: infer_demo path/to/model_dir path/to/video frame number run_option, "
|
||||
"e.g ./infer_model ./vsr_model_dir ./person.mp4 0 2"
|
||||
<< std::endl;
|
||||
std::cout << "Usage: infer_demo path/to/model_dir path/to/video frame "
|
||||
"number run_option, "
|
||||
"e.g ./infer_model ./vsr_model_dir ./vsr_src.mp4 0 5"
|
||||
<< std::endl;
|
||||
std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
|
||||
"with gpu; 2: run with gpu and use tensorrt backend."
|
||||
<< std::endl;
|
||||
|
||||
Reference in New Issue
Block a user