[Benchmark] Support PaddleClas cpp benchmark (#1324)

* add GPL lisence

* add GPL-3.0 lisence

* add GPL-3.0 lisence

* add GPL-3.0 lisence

* support yolov8

* add pybind for yolov8

* add yolov8 readme

* add cpp benchmark

* add cpu and gpu mem

* public part split

* add runtime mode

* fixed bugs

* add cpu_thread_nums

* deal with comments

* deal with comments

* deal with comments

* rm useless code

* add FASTDEPLOY_DECL

* add FASTDEPLOY_DECL

* fixed for windows

* mv rss to pss

* mv rss to pss

* Update utils.cc

* use thread to collect mem

* Add ResourceUsageMonitor

* rm useless code

* fixed bug

* fixed typo

* update ResourceUsageMonitor

* fixed bug

* fixed bug

* add note for ResourceUsageMonitor

* deal with comments

* add macros

* deal with comments

* deal with comments

* deal with comments

* re-lint

* rm pmap and use mem api

* rm pmap and use mem api

* add mem api

* Add PrintBenchmarkInfo func

* Add PrintBenchmarkInfo func

* Add PrintBenchmarkInfo func

* deal with comments

* fixed enable_paddle_to_trt

* add log for paddle_trt

* support ppcls benchmark

* use new trt option api

* update benchmark info

* simplify benchmark.cc

* simplify benchmark.cc

* deal with comments

---------

Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
This commit is contained in:
WJJ1995
2023-02-15 17:25:49 +08:00
committed by GitHub
parent 6a2cfde8d1
commit da94fc46cf
12 changed files with 86 additions and 35 deletions

View File

@@ -12,20 +12,17 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "macros.h"
#include "flags.h"
#include "macros.h"
#include "option.h"
int main(int argc, char* argv[]) {
google::ParseCommandLineFlags(&argc, &argv, true);
auto im = cv::imread(FLAGS_image);
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option)) {
PrintUsage();
return false;
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
PrintBenchmarkInfo();
auto im = cv::imread(FLAGS_image);
auto model_yolov5 =
fastdeploy::vision::detection::YOLOv5(FLAGS_model, "", option);
fastdeploy::vision::DetectionResult res;
@@ -34,4 +31,4 @@ int main(int argc, char* argv[]) {
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
return 0;
}
}