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[Benchmark] add PaddleDetection to benchmark (#1675)

Browse Source 
* 添加paddleclas模型

* 更新README_CN

* 更新README_CN

* 更新README

* update get_model.sh

* update get_models.sh

* update paddleseg models

* update paddle_seg models

* update paddle_seg models

* modified test resources

* update benchmark_gpu_trt.sh

* add paddle detection

* add paddledetection to benchmark

* modified benchmark cmakelists

* update benchmark scripts

* modified benchmark function calling

---------

Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
This commit is contained in:
linyangshi
2023-04-13 10:29:49 +08:00
committed by GitHub
parent d1da460230
commit 60a44f5af1
19 changed files with 1320 additions and 50 deletions
Download Patch File Download Diff File Expand all files Collapse all files

37
benchmark/cpp/CMakeLists.txt
View File

@@ -22,7 +22,18 @@ add_executable(benchmark_ppmatting ${PROJECT_SOURCE_DIR}/benchmark_ppmatting.cc)
add_executable(benchmark_ppocr_det ${PROJECT_SOURCE_DIR}/benchmark_ppocr_det.cc) add_executable(benchmark_ppocr_det ${PROJECT_SOURCE_DIR}/benchmark_ppocr_det.cc)
add_executable(benchmark_ppocr_cls ${PROJECT_SOURCE_DIR}/benchmark_ppocr_cls.cc) add_executable(benchmark_ppocr_cls ${PROJECT_SOURCE_DIR}/benchmark_ppocr_cls.cc)
add_executable(benchmark_ppocr_rec ${PROJECT_SOURCE_DIR}/benchmark_ppocr_rec.cc) add_executable(benchmark_ppocr_rec ${PROJECT_SOURCE_DIR}/benchmark_ppocr_rec.cc)
add_executable(benchmark_ppyolo ${PROJECT_SOURCE_DIR}/benchmark_ppyolo.cc)
add_executable(benchmark_yolov3 ${PROJECT_SOURCE_DIR}/benchmark_yolov3.cc)
add_executable(benchmark_fasterrcnn ${PROJECT_SOURCE_DIR}/benchmark_fasterrcnn.cc)
add_executable(benchmark_maskrcnn ${PROJECT_SOURCE_DIR}/benchmark_maskrcnn.cc)
add_executable(benchmark_ssd ${PROJECT_SOURCE_DIR}/benchmark_ssd.cc)
add_executable(benchmark_rtmdet ${PROJECT_SOURCE_DIR}/benchmark_rtmdet.cc)
add_executable(benchmark_cascadercnn ${PROJECT_SOURCE_DIR}/benchmark_cascadercnn.cc)
add_executable(benchmark_fcos ${PROJECT_SOURCE_DIR}/benchmark_fcos.cc)
add_executable(benchmark_gfl ${PROJECT_SOURCE_DIR}/benchmark_gfl.cc)
add_executable(benchmark_retinanet ${PROJECT_SOURCE_DIR}/benchmark_retinanet.cc)
add_executable(benchmark_tood ${PROJECT_SOURCE_DIR}/benchmark_tood.cc)
add_executable(benchmark_ttfnet ${PROJECT_SOURCE_DIR}/benchmark_ttfnet.cc)
add_executable(benchmark ${PROJECT_SOURCE_DIR}/benchmark.cc) add_executable(benchmark ${PROJECT_SOURCE_DIR}/benchmark.cc)
if(UNIX AND (NOT APPLE) AND (NOT ANDROID)) if(UNIX AND (NOT APPLE) AND (NOT ANDROID))
@@ -40,6 +51,18 @@ if(UNIX AND (NOT APPLE) AND (NOT ANDROID))
target_link_libraries(benchmark_ppocr_det ${FASTDEPLOY_LIBS} gflags pthread) target_link_libraries(benchmark_ppocr_det ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_ppocr_cls ${FASTDEPLOY_LIBS} gflags pthread) target_link_libraries(benchmark_ppocr_cls ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_ppocr_rec ${FASTDEPLOY_LIBS} gflags pthread) target_link_libraries(benchmark_ppocr_rec ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_ppyolo ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_yolov3 ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_fasterrcnn ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_maskrcnn ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_ssd ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_rtmdet ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_cascadercnn ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_fcos ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_gfl ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_retinanet ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_tood ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark_ttfnet ${FASTDEPLOY_LIBS} gflags pthread)
target_link_libraries(benchmark ${FASTDEPLOY_LIBS} gflags pthread) target_link_libraries(benchmark ${FASTDEPLOY_LIBS} gflags pthread)
else() else()
target_link_libraries(benchmark_yolov5 ${FASTDEPLOY_LIBS} gflags) target_link_libraries(benchmark_yolov5 ${FASTDEPLOY_LIBS} gflags)
@@ -56,6 +79,18 @@ else()
target_link_libraries(benchmark_ppocr_det ${FASTDEPLOY_LIBS} gflags) target_link_libraries(benchmark_ppocr_det ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_ppocr_cls ${FASTDEPLOY_LIBS} gflags) target_link_libraries(benchmark_ppocr_cls ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_ppocr_rec ${FASTDEPLOY_LIBS} gflags) target_link_libraries(benchmark_ppocr_rec ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_ppyolo ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_yolov3 ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_fasterrcnn ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_maskrcnn ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_ssd ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_rtmdet ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_cascadercnn ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_fcos ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_gfl ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_retinanet ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_tood ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark_ttfnet ${FASTDEPLOY_LIBS} gflags)
target_link_libraries(benchmark ${FASTDEPLOY_LIBS} gflags) target_link_libraries(benchmark ${FASTDEPLOY_LIBS} gflags)
endif() endif()
# only for Android ADB test # only for Android ADB test

38
benchmark/cpp/benchmark_arm.sh
View File

@@ -68,6 +68,44 @@ sleep_seconds() {
./benchmark_picodet --model picodet_l_640_coco_lcnet --image 000000014439.jpg --config_path $CONFIG_PATH && sleep_seconds ./benchmark_picodet --model picodet_l_640_coco_lcnet --image 000000014439.jpg --config_path $CONFIG_PATH && sleep_seconds
./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH && sleep_seconds 60 ./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH && sleep_seconds 60
./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH && sleep_seconds 60 ./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH && sleep_seconds 60
./benchmark_ppyolov5 --model yolov5_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov6 --model yolov6_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov7 --model yolov7_l_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov8 --model yolov8_s_500e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolox --model yolox_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyoloe --model ppyoloe_plus_crn_m_80e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_picodet --model picodet_l_640_coco_lcnet_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolo --model ppyolo_r50vd_dcn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_yolov3 --model yolov3_darknet53_270e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolo --model ppyolov2_r101vd_dcn_365e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_picodet --model picodet_l_320_coco_lcnet --image 000000014439.jpg $CONFIG_PATH
./benchmark_fasterrcnn --model faster_rcnn_r50_vd_fpn_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_maskrcnn --model mask_rcnn_r50_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_rtmdet --model rtmdet_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_rtmdet --model rtmdet_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_cascadercnn --model cascade_rcnn_r50_fpn_1x_coco --image 000000014439.jpg $CONFIG_PATH
./benchmark_cascadercnn --model cascade_rcnn_r50_vd_fpn_ssld_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_fcos --model fcos_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_gfl --model gfl_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_retinanet --model retinanet_r101_fpn_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_retinanet --model retinanet_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_tood --model tood_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ttfnet --model ttfnet_darknet53_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov5 --model yolov5_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov6 --model yolov6_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov6 --model yolov6_s_400e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov7 --model yolov7_x_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_fasterrcnn --model faster_rcnn_enhance_3x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_crn_l_80e_sliced_visdrone_640_025 --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssd_mobilenet_v1_300_120e_voc --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssd_vgg16_300_240e_voc --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssdlite_mobilenet_v1_300_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_x_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_l_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_m_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_n_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
# PaddleSeg # PaddleSeg
./benchmark_ppseg --model Portrait_PP_HumanSegV2_Lite_256x144_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH && sleep_seconds ./benchmark_ppseg --model Portrait_PP_HumanSegV2_Lite_256x144_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH && sleep_seconds

89
benchmark/cpp/benchmark_cascadercnn.cc Executable file
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@@ -0,0 +1,89 @@
// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + "model.pdmodel";
auto params_file = FLAGS_model + sep + "model.pdiparams";
auto config_file = FLAGS_model + sep + "infer_cfg.yml";
if (config_info["backend"] == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (config_info["backend"] == "paddle_trt" ||
config_info["backend"] == "trt") {
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
{1, 3, 640, 640});
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2},
{1, 2});
}
auto model_cascade_rcnn = vision::detection::CascadeRCNN(model_file, params_file,
config_file, option,model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_cascade_rcnn.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "cascade_rcnn_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_cascade_rcnn.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_cascade_rcnn, model_cascade_rcnn.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

89
benchmark/cpp/benchmark_fasterrcnn.cc Executable file
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@@ -0,0 +1,89 @@
// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + model_name;
auto params_file = FLAGS_model + sep + params_name;
auto config_file = FLAGS_model + sep + config_name;
if (config_info["backend"] == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (config_info["backend"] == "paddle_trt" ||
config_info["backend"] == "trt") {
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
{1, 3, 640, 640});
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2},
{1, 2});
}
auto model_fasterrcnn = vision::detection::FasterRCNN(
model_file, params_file, config_file, option, model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_fasterrcnn.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "fasterrcnn_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_fasterrcnn.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_fasterrcnn, model_fasterrcnn.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

89
benchmark/cpp/benchmark_fcos.cc Executable file
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@@ -0,0 +1,89 @@
// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + model_name;
auto params_file = FLAGS_model + sep + params_name;
auto config_file = FLAGS_model + sep + config_name;
if (config_info["backend"] == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (config_info["backend"] == "paddle_trt" ||
config_info["backend"] == "trt") {
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
{1, 3, 640, 640});
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2},
{1, 2});
}
auto model_fcos = vision::detection::FCOS(
model_file, params_file, config_file, option, model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_fcos.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "fcos_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_fcos.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_fcos, model_fcos.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

89
benchmark/cpp/benchmark_gfl.cc Executable file
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@@ -0,0 +1,89 @@
// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + model_name;
auto params_file = FLAGS_model + sep + params_name;
auto config_file = FLAGS_model + sep + config_name;
if (config_info["backend"] == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (config_info["backend"] == "paddle_trt" ||
config_info["backend"] == "trt") {
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
{1, 3, 640, 640});
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2},
{1, 2});
}
auto model_gfl = vision::detection::GFL(
model_file, params_file, config_file, option, model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_gfl.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "gfl_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_gfl.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_gfl, model_gfl.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

55
benchmark/cpp/benchmark_gpu.sh
View File

@@ -46,25 +46,58 @@ fi
./benchmark_ppocr_rec --model ch_PP-OCRv2_rec_infer --image rec_img.jpg --rec_label_file ppocr_keys_v1.txt --config_path $CONFIG_PATH ./benchmark_ppocr_rec --model ch_PP-OCRv2_rec_infer --image rec_img.jpg --rec_label_file ppocr_keys_v1.txt --config_path $CONFIG_PATH
# PaddleDetection # PaddleDetection
./benchmark_ppyolov5 --model yolov5_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov6 --model yolov6_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov7 --model yolov7_l_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov8 --model yolov8_s_500e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolox --model yolox_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyoloe --model ppyoloe_plus_crn_m_80e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_picodet --model picodet_l_640_coco_lcnet_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolo --model ppyolo_r50vd_dcn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_yolov3 --model yolov3_darknet53_270e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolo --model ppyolov2_r101vd_dcn_365e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_picodet --model picodet_l_320_coco_lcnet --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_fasterrcnn --model faster_rcnn_r50_vd_fpn_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_maskrcnn --model mask_rcnn_r50_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_rtmdet --model rtmdet_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_rtmdet --model rtmdet_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_cascadercnn --model cascade_rcnn_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_cascadercnn --model cascade_rcnn_r50_vd_fpn_ssld_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_fcos --model fcos_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_gfl --model gfl_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_retinanet --model retinanet_r101_fpn_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_retinanet --model retinanet_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_tood --model tood_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ttfnet --model ttfnet_darknet53_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov5 --model yolov5_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov5 --model yolov5_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov5 --model yolov5_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov6 --model yolov6_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov6 --model yolov6_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_s_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov6 --model yolov6_s_400e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolox --model yolox_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_plus_crn_m_80e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_picodet --model picodet_l_640_coco_lcnet --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov7 --model yolov7_x_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_fasterrcnn --model faster_rcnn_enhance_3x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_crn_l_80e_sliced_visdrone_640_025 --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssd_mobilenet_v1_300_120e_voc --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssd_vgg16_300_240e_voc --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssdlite_mobilenet_v1_300_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_x_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_l_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_m_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_s_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_n_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
# PaddleSeg # PaddleSeg
./benchmark_ppseg --model Portrait_PP_HumanSegV2_Lite_256x144_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH ./benchmark_ppseg --model Portrait_PP_HumanSegV2_Lite_256x144_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH
./benchmark_ppseg --model PP_HumanSegV2_Lite_192x192_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH ./benchmark_ppseg --model PP_HumanSegV2_Lite_192x192_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH
./benchmark_ppseg --model PP_HumanSegV1_Lite_infer --image portrait_heng.jpg --config_path $CONFIG_PATH ./benchmark_ppseg --model PP_HumanSegV1_Lite_infer --image portrait_heng.jpg --config_path $CONFIG_PATH
./benchmark_ppseg --model PP_LiteSeg_B_STDC2_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH ./benchmark_ppseg --model PP_HumanSegV2_Mobile_192x192_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH
./benchmark_ppseg --model FCN_HRNet_W18_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH
./benchmark_ppseg --model SegFormer_B0-cityscapes-with-argmax --image cityscapes_demo.png --config_path $CONFIG_PATH
./benchmark_ppseg --model Deeplabv3_ResNet101_OS8_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH ./benchmark_ppseg --model Deeplabv3_ResNet101_OS8_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH
./benchmark_ppseg --model Unet_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH ./benchmark_ppseg --model PP_LiteSeg_B_STDC2_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH
./benchmark_ppseg --model PP_HumanSegV1_Server_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH ./benchmark_ppseg --model SegFormer_B0-cityscapes-with-argmax --image cityscapes_demo.png --config_path $CONFIG_PATH
./benchmark_ppmatting --model PP-Matting-512 --image matting_input.jpg --config_path $CONFIG_PATH ./benchmark_ppmatting --model PP-Matting-512 --image matting_input.jpg --config_path $CONFIG_PATH
./benchmark_ppmatting --model PPHumanMatting --image matting_input.jpg --config_path $CONFIG_PATH ./benchmark_ppmatting --model PPHumanMatting --image matting_input.jpg --config_path $CONFIG_PATH
./benchmark_ppmatting --model PPModnet_MobileNetV2 --image matting_input.jpg --config_path $CONFIG_PATH ./benchmark_ppmatting --model PPModnet_MobileNetV2 --image matting_input.jpg --config_path $CONFIG_PATH
./benchmark_ppseg --model Unet_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH
./benchmark_ppseg --model PP_HumanSegV1_Server_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH
./benchmark_ppseg --model FCN_HRNet_W18_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH

47
benchmark/cpp/benchmark_gpu_trt.sh
View File

@@ -45,35 +45,44 @@ fi
./benchmark_ppocr_det --model ch_PP-OCRv2_det_infer --image 12.jpg --config_path $CONFIG_PATH --trt_shape 1,3,960,608:1,3,960,608:1,3,960,608 ./benchmark_ppocr_det --model ch_PP-OCRv2_det_infer --image 12.jpg --config_path $CONFIG_PATH --trt_shape 1,3,960,608:1,3,960,608:1,3,960,608
./benchmark_ppocr_rec --model ch_PP-OCRv2_rec_infer --image rec_img.jpg --rec_label_file ppocr_keys_v1.txt --config_path $CONFIG_PATH --trt_shape 1,3,32,10:1,3,32,320:1,3,32,2304 ./benchmark_ppocr_rec --model ch_PP-OCRv2_rec_infer --image rec_img.jpg --rec_label_file ppocr_keys_v1.txt --config_path $CONFIG_PATH --trt_shape 1,3,32,10:1,3,32,320:1,3,32,2304
# PaddleDetection # PaddleDetection
./benchmark_ppyolov5 --model yolov5_s_300e_coco_trt_nms --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov5 --model yolov5_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov6 --model yolov6_s_300e_coco_trt_nms --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov6 --model yolov6_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov8 --model yolov8_s_500e_coco_trt_nms --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov7 --model yolov7_l_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolox --model yolox_s_300e_coco_trt_nms --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov8 --model yolov8_s_500e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyoloe --model ppyoloe_plus_crn_m_80e_coco_trt_nms --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolox --model yolox_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_picodet --model picodet_l_640_coco_lcnet_trt_nms --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov7 --model yolov7_l_300e_coco_trt_nms --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyoloe --model ppyoloe_plus_crn_m_80e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco_trt_nms --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_picodet --model picodet_l_640_coco_lcnet_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_yolov3 --model yolov3_darknet53_270e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_picodet --model picodet_l_320_coco_lcnet --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_rtmdet --model rtmdet_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_rtmdet --model rtmdet_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov5 --model yolov5_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov5 --model yolov5_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov5 --model yolov5_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov6 --model yolov6_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov6 --model yolov6_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_s_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov6 --model yolov6_s_400e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolox --model yolox_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_plus_crn_m_80e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_picodet --model picodet_l_640_coco_lcnet --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov7 --model yolov7_x_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_crn_l_80e_sliced_visdrone_640_025 --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_x_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_l_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_m_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_s_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_n_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
# PaddleSeg # PaddleSeg
./benchmark_ppseg --model Portrait_PP_HumanSegV2_Lite_256x144_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --trt_shape 1,3,144,256:1,3,144,256:1,3,144,256 ./benchmark_ppseg --model Portrait_PP_HumanSegV2_Lite_256x144_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --trt_shape 1,3,144,256:1,3,144,256:1,3,144,256
./benchmark_ppseg --model PP_HumanSegV2_Lite_192x192_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --trt_shape 1,3,192,192:1,3,192,192:1,3,192,192 ./benchmark_ppseg --model PP_HumanSegV2_Lite_192x192_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --trt_shape 1,3,192,192:1,3,192,192:1,3,192,192
./benchmark_ppseg --model PP_HumanSegV1_Lite_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --trt_shape 1,3,192,192:1,3,192,192:1,3,192,192 ./benchmark_ppseg --model PP_HumanSegV1_Lite_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --trt_shape 1,3,192,192:1,3,192,192:1,3,192,192
./benchmark_ppseg --model PP_HumanSegV2_Mobile_192x192_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --trt_shape 1,3,192,192:1,3,192,192:1,3,192,192 ./benchmark_ppseg --model PP_HumanSegV2_Mobile_192x192_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --trt_shape 1,3,192,192:1,3,192,192:1,3,192,192
./benchmark_ppseg --model PP_LiteSeg_B_STDC2_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512
./benchmark_ppseg --model FCN_HRNet_W18_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512
./benchmark_ppseg --model SegFormer_B0-cityscapes-with-argmax --image cityscapes_demo.png --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512
./benchmark_ppseg --model Deeplabv3_ResNet101_OS8_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512 ./benchmark_ppseg --model Deeplabv3_ResNet101_OS8_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512
./benchmark_ppseg --model Unet_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512 ./benchmark_ppseg --model PP_LiteSeg_B_STDC2_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512
./benchmark_ppseg --model PP_HumanSegV1_Server_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512 ./benchmark_ppseg --model SegFormer_B0-cityscapes-with-argmax --image cityscapes_demo.png --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512
./benchmark_ppmatting --model PP-Matting-512 --image matting_input.jpg --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512 ./benchmark_ppmatting --model PP-Matting-512 --image matting_input.jpg --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512
./benchmark_ppmatting --model PPHumanMatting --image matting_input.jpg --config_path $CONFIG_PATH --trt_shape 1,3,2048,2048:1,3,2048,2048:1,3,2048,2048 ./benchmark_ppmatting --model PPHumanMatting --image matting_input.jpg --config_path $CONFIG_PATH --trt_shape 1,3,2048,2048:1,3,2048,2048:1,3,2048,2048
./benchmark_ppmatting --model PPModnet_MobileNetV2 --image matting_input.jpg --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512 ./benchmark_ppmatting --model PPModnet_MobileNetV2 --image matting_input.jpg --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512
./benchmark_ppseg --model Unet_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512
./benchmark_ppseg --model PP_HumanSegV1_Server_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512
./benchmark_ppseg --model FCN_HRNet_W18_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH --trt_shape 1,3,512,512:1,3,512,512:1,3,512,512

89
benchmark/cpp/benchmark_maskrcnn.cc Executable file
View File

@@ -0,0 +1,89 @@
// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + model_name;
auto params_file = FLAGS_model + sep + params_name;
auto config_file = FLAGS_model + sep + config_name;
if (config_info["backend"] == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (config_info["backend"] == "paddle_trt" ||
config_info["backend"] == "trt") {
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
{1, 3, 640, 640});
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2},
{1, 2});
}
auto model_maskrcnn = vision::detection::MaskRCNN(
model_file, params_file, config_file, option, model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_maskrcnn.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "maskrcnn_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_maskrcnn.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_maskrcnn, model_maskrcnn.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

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benchmark/cpp/benchmark_ppyolo.cc Executable file
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// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + model_name;
auto params_file = FLAGS_model + sep + params_name;
auto config_file = FLAGS_model + sep + config_name;
if (config_info["backend"] == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (config_info["backend"] == "paddle_trt" ||
config_info["backend"] == "trt") {
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
{1, 3, 640, 640});
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2},
{1, 2});
}
auto model_ppyolo = vision::detection::PPYOLO(
model_file, params_file, config_file, option, model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_ppyolo.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "ppyolo_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_ppyolo.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_ppyolo, model_ppyolo.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

89
benchmark/cpp/benchmark_retinanet.cc Executable file
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// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + model_name;
auto params_file = FLAGS_model + sep + params_name;
auto config_file = FLAGS_model + sep + config_name;
if (config_info["backend"] == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (config_info["backend"] == "paddle_trt" ||
config_info["backend"] == "trt") {
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
{1, 3, 640, 640});
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2},
{1, 2});
}
auto model_retinanet = vision::detection::RetinaNet(
model_file, params_file, config_file, option, model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_retinanet.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "retinanet_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_retinanet.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_retinanet, model_retinanet.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

89
benchmark/cpp/benchmark_rtmdet.cc Executable file
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// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + model_name;
auto params_file = FLAGS_model + sep + params_name;
auto config_file = FLAGS_model + sep + config_name;
if (config_info["backend"] == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (config_info["backend"] == "paddle_trt" ||
config_info["backend"] == "trt") {
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
{1, 3, 640, 640});
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2},
{1, 2});
}
auto model_rtmdet = vision::detection::RTMDet(
model_file, params_file, config_file, option, model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_rtmdet.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "rtmdet_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_rtmdet.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_rtmdet, model_rtmdet.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

89
benchmark/cpp/benchmark_ssd.cc Executable file
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// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + model_name;
auto params_file = FLAGS_model + sep + params_name;
auto config_file = FLAGS_model + sep + config_name;
if (config_info["backend"] == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (config_info["backend"] == "paddle_trt" ||
config_info["backend"] == "trt") {
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
{1, 3, 640, 640});
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2},
{1, 2});
}
auto model_ssd = vision::detection::SSD(
model_file, params_file, config_file, option, model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_ssd.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "ssd_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_ssd.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_ssd, model_ssd.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

89
benchmark/cpp/benchmark_tood.cc Executable file
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@@ -0,0 +1,89 @@
// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + model_name;
auto params_file = FLAGS_model + sep + params_name;
auto config_file = FLAGS_model + sep + config_name;
if (config_info["backend"] == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (config_info["backend"] == "paddle_trt" ||
config_info["backend"] == "trt") {
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
{1, 3, 640, 640});
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2},
{1, 2});
}
auto model_tood = vision::detection::TOOD(
model_file, params_file, config_file, option, model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_tood.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "tood_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_tood.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_tood, model_tood.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

89
benchmark/cpp/benchmark_ttfnet.cc Executable file
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@@ -0,0 +1,89 @@
// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + model_name;
auto params_file = FLAGS_model + sep + params_name;
auto config_file = FLAGS_model + sep + config_name;
if (config_info["backend"] == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (config_info["backend"] == "paddle_trt" ||
config_info["backend"] == "trt") {
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
{1, 3, 640, 640});
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2},
{1, 2});
}
auto model_ttfnet = vision::detection::TTFNet(
model_file, params_file, config_file, option, model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_ttfnet.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "ttfnet_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_ttfnet.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_ttfnet, model_ttfnet.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

47
benchmark/cpp/benchmark_x86.sh
View File

@@ -46,21 +46,53 @@ fi
./benchmark_ppocr_rec --model ch_PP-OCRv2_rec_infer --image rec_img.jpg --rec_label_file ppocr_keys_v1.txt --config_path $CONFIG_PATH ./benchmark_ppocr_rec --model ch_PP-OCRv2_rec_infer --image rec_img.jpg --rec_label_file ppocr_keys_v1.txt --config_path $CONFIG_PATH
# PaddleDetection # PaddleDetection
./benchmark_ppyolov5 --model yolov5_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov6 --model yolov6_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov7 --model yolov7_l_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov8 --model yolov8_s_500e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolox --model yolox_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyoloe --model ppyoloe_plus_crn_m_80e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_picodet --model picodet_l_640_coco_lcnet_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolo --model ppyolo_r50vd_dcn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_yolov3 --model yolov3_darknet53_270e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolo --model ppyolov2_r101vd_dcn_365e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_picodet --model picodet_l_320_coco_lcnet --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_fasterrcnn --model faster_rcnn_r50_vd_fpn_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_maskrcnn --model mask_rcnn_r50_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_rtmdet --model rtmdet_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_rtmdet --model rtmdet_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_cascadercnn --model cascade_rcnn_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_cascadercnn --model cascade_rcnn_r50_vd_fpn_ssld_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_fcos --model fcos_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_gfl --model gfl_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_retinanet --model retinanet_r101_fpn_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_retinanet --model retinanet_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_tood --model tood_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ttfnet --model ttfnet_darknet53_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov5 --model yolov5_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov5 --model yolov5_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov5 --model yolov5_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov6 --model yolov6_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov6 --model yolov6_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_s_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov6 --model yolov6_s_400e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolox --model yolox_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_plus_crn_m_80e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_picodet --model picodet_l_640_coco_lcnet --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov7 --model yolov7_x_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_fasterrcnn --model faster_rcnn_enhance_3x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_crn_l_80e_sliced_visdrone_640_025 --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssd_mobilenet_v1_300_120e_voc --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssd_vgg16_300_240e_voc --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssdlite_mobilenet_v1_300_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_x_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_l_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_m_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_s_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_n_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
# PaddleSeg # PaddleSeg
./benchmark_ppseg --model Portrait_PP_HumanSegV2_Lite_256x144_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH ./benchmark_ppseg --model Portrait_PP_HumanSegV2_Lite_256x144_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH
./benchmark_ppseg --model PP_HumanSegV2_Lite_192x192_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH ./benchmark_ppseg --model PP_HumanSegV2_Lite_192x192_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH
./benchmark_ppseg --model PP_HumanSegV1_Lite_infer --image portrait_heng.jpg --config_path $CONFIG_PATH ./benchmark_ppseg --model PP_HumanSegV1_Lite_infer --image portrait_heng.jpg --config_path $CONFIG_PATH
./benchmark_ppseg --model PP_HumanSegV2_Mobile_192x192_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH
./benchmark_ppseg --model PP_LiteSeg_B_STDC2_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH ./benchmark_ppseg --model PP_LiteSeg_B_STDC2_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH
./benchmark_ppseg --model FCN_HRNet_W18_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH
./benchmark_ppseg --model SegFormer_B0-cityscapes-with-argmax --image cityscapes_demo.png --config_path $CONFIG_PATH ./benchmark_ppseg --model SegFormer_B0-cityscapes-with-argmax --image cityscapes_demo.png --config_path $CONFIG_PATH
./benchmark_ppseg --model Deeplabv3_ResNet101_OS8_cityscapes_with_argmax_infer --image cityscapes_demo.png --warmup 10 --repeat 50 --config_path $CONFIG_PATH ./benchmark_ppseg --model Deeplabv3_ResNet101_OS8_cityscapes_with_argmax_infer --image cityscapes_demo.png --warmup 10 --repeat 50 --config_path $CONFIG_PATH
./benchmark_ppseg --model Unet_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH ./benchmark_ppseg --model Unet_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH
@@ -68,3 +100,4 @@ fi
./benchmark_ppmatting --model PP-Matting-512 --image matting_input.jpg --warmup 10 --repeat 50 --config_path $CONFIG_PATH ./benchmark_ppmatting --model PP-Matting-512 --image matting_input.jpg --warmup 10 --repeat 50 --config_path $CONFIG_PATH
./benchmark_ppmatting --model PPHumanMatting --image matting_input.jpg --warmup 10 --repeat 50 --config_path $CONFIG_PATH ./benchmark_ppmatting --model PPHumanMatting --image matting_input.jpg --warmup 10 --repeat 50 --config_path $CONFIG_PATH
./benchmark_ppmatting --model PPModnet_MobileNetV2 --image matting_input.jpg --config_path $CONFIG_PATH ./benchmark_ppmatting --model PPModnet_MobileNetV2 --image matting_input.jpg --config_path $CONFIG_PATH
./benchmark_ppseg --model FCN_HRNet_W18_cityscapes_with_argmax_infer --image cityscapes_demo.png --config_path $CONFIG_PATH

38
benchmark/cpp/benchmark_xpu.sh
View File

@@ -54,6 +54,44 @@ fi
./benchmark_picodet --model picodet_l_640_coco_lcnet --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_picodet --model picodet_l_640_coco_lcnet --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH ./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov5 --model yolov5_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov6 --model yolov6_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov7 --model yolov7_l_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolov8 --model yolov8_s_500e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolox --model yolox_s_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyoloe --model ppyoloe_crn_l_300e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyoloe --model ppyoloe_plus_crn_m_80e_coco_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_picodet --model picodet_l_640_coco_lcnet_no_nms --image 000000014439.jpg --config_path $CONFIG_PATH --no_nms
./benchmark_ppyolo --model ppyolo_r50vd_dcn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_yolov3 --model yolov3_darknet53_270e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolo --model ppyolov2_r101vd_dcn_365e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_picodet --model picodet_l_320_coco_lcnet --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_fasterrcnn --model faster_rcnn_r50_vd_fpn_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_maskrcnn --model mask_rcnn_r50_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_rtmdet --model rtmdet_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_rtmdet --model rtmdet_s_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_cascadercnn --model cascade_rcnn_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_cascadercnn --model cascade_rcnn_r50_vd_fpn_ssld_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_fcos --model fcos_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_gfl --model gfl_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_retinanet --model retinanet_r101_fpn_2x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_retinanet --model retinanet_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_tood --model tood_r50_fpn_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ttfnet --model ttfnet_darknet53_1x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov5 --model yolov5_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov6 --model yolov6_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov6 --model yolov6_s_400e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov7 --model yolov7_l_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov7 --model yolov7_x_300e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_fasterrcnn --model faster_rcnn_enhance_3x_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyoloe --model ppyoloe_crn_l_80e_sliced_visdrone_640_025 --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssd_mobilenet_v1_300_120e_voc --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssd_vgg16_300_240e_voc --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ssd --model ssdlite_mobilenet_v1_300_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_x_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_l_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_m_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
./benchmark_ppyolov8 --model yolov8_n_500e_coco --image 000000014439.jpg --config_path $CONFIG_PATH
# PaddleSeg # PaddleSeg
./benchmark_ppseg --model Portrait_PP_HumanSegV2_Lite_256x144_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --xpu_l3_cache 0 ./benchmark_ppseg --model Portrait_PP_HumanSegV2_Lite_256x144_with_argmax_infer --image portrait_heng.jpg --config_path $CONFIG_PATH --xpu_l3_cache 0

79
benchmark/cpp/benchmark_yolov3.cc Normal file
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@@ -0,0 +1,79 @@
// Copyright (c) 2023 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 "flags.h"
#include "macros.h"
#include "option.h"
namespace vision = fastdeploy::vision;
namespace benchmark = fastdeploy::benchmark;
DEFINE_bool(no_nms, false, "Whether the model contains nms.");
int main(int argc, char* argv[]) {
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
// Initialization
auto option = fastdeploy::RuntimeOption();
if (!CreateRuntimeOption(&option, argc, argv, true)) {
return -1;
}
auto im = cv::imread(FLAGS_image);
std::unordered_map<std::string, std::string> config_info;
benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path,
&config_info);
std::string model_name, params_name, config_name;
auto model_format = fastdeploy::ModelFormat::PADDLE;
if (!UpdateModelResourceName(&model_name, &params_name, &config_name,
&model_format, config_info)) {
return -1;
}
auto model_file = FLAGS_model + sep + model_name;
auto params_file = FLAGS_model + sep + params_name;
auto config_file = FLAGS_model + sep + config_name;
auto model_yolov3 = vision::detection::YOLOv3(
model_file, params_file, config_file, option, model_format);
vision::DetectionResult res;
if (config_info["precision_compare"] == "true") {
// Run once at least
model_yolov3.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string det_result_path = "yolov3_result.txt";
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
// Load result from <- disk.
vision::DetectionResult res_loaded;
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
// Calculate diff between two results.
auto det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "Boxes diff: mean=" << det_diff.boxes.mean
<< ", max=" << det_diff.boxes.max
<< ", min=" << det_diff.boxes.min << std::endl;
std::cout << "Label_ids diff: mean=" << det_diff.labels.mean
<< ", max=" << det_diff.labels.max
<< ", min=" << det_diff.labels.min << std::endl;
}
// Run profiling
if (FLAGS_no_nms) {
model_yolov3.GetPostprocessor().ApplyNMS();
}
BENCHMARK_MODEL(model_yolov3, model_yolov3.Predict(im, &res))
auto vis_im = vision::VisDetection(im, res);
cv::imwrite("vis_result.jpg", vis_im);
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
#endif
return 0;
}

50
benchmark/cpp/get_models.sh
View File

@@ -102,22 +102,48 @@ download_common_file() {
} }
# PaddleDetection # PaddleDetection
download_fd_model_zxvf ppyoloe_crn_l_300e_coco.tgz
download_fd_model_zxvf picodet_l_640_coco_lcnet.tgz download_fd_model_zxvf ppyoloe_crn_l_300e_coco_no_nms.tgz
download_fd_model_zxvf ppyoloe_plus_crn_m_80e_coco.tgz download_fd_model_zxvf picodet_l_640_coco_lcnet_no_nms.tgz
download_fd_model_zxvf ppyoloe_plus_crn_m_80e_coco_no_nms.tgz
download_fd_model_zxvf yolox_s_300e_coco_no_nms.tgz
download_fd_model_zxvf yolov5_s_300e_coco_no_nms.tgz
download_fd_model_zxvf yolov6_s_300e_coco_no_nms.tgz
download_fd_model_zxvf yolov7_l_300e_coco_no_nms.tgz
download_fd_model_zxvf yolov8_s_500e_coco_no_nms.tgz
download_fd_model_zxvf ppyolo_r50vd_dcn_1x_coco.tgz
download_fd_model_zxvf ppyolov2_r101vd_dcn_365e_coco.tgz
download_fd_model_zxvf yolov3_darknet53_270e_coco.tgz
download_fd_model_zxvf yolox_s_300e_coco.tgz download_fd_model_zxvf yolox_s_300e_coco.tgz
download_fd_model_zxvf faster_rcnn_r50_vd_fpn_2x_coco.tgz
download_fd_model_zxvf mask_rcnn_r50_1x_coco.tgz
download_fd_model_zxvf ssd_mobilenet_v1_300_120e_voc.tgz
download_fd_model_zxvf ssd_vgg16_300_240e_voc.tgz
download_fd_model_zxvf ssdlite_mobilenet_v1_300_coco.tgz
download_fd_model_zxvf rtmdet_l_300e_coco.tgz
download_fd_model_zxvf rtmdet_s_300e_coco.tgz
download_fd_model_zxvf yolov5_l_300e_coco.tgz
download_fd_model_zxvf yolov5_s_300e_coco.tgz download_fd_model_zxvf yolov5_s_300e_coco.tgz
download_fd_model_zxvf yolov6_s_300e_coco.tgz download_fd_model_zxvf yolov6_l_300e_coco.tgz
download_fd_model_zxvf yolov6_s_400e_coco.tgz
download_fd_model_zxvf yolov7_l_300e_coco.tgz download_fd_model_zxvf yolov7_l_300e_coco.tgz
download_fd_model_zxvf cascade_rcnn_r50_fpn_1x_coco.tgz
download_fd_model_zxvf cascade_rcnn_r50_vd_fpn_ssld_2x_coco.tgz
download_fd_model_zxvf faster_rcnn_enhance_3x_coco.tgz
download_fd_model_zxvf fcos_r50_fpn_1x_coco.tgz
download_fd_model_zxvf gfl_r50_fpn_1x_coco.tgz
download_fd_model_zxvf ppyoloe_crn_l_80e_sliced_visdrone_640_025.tgz
download_fd_model_zxvf retinanet_r101_fpn_2x_coco.tgz
download_fd_model_zxvf retinanet_r50_fpn_1x_coco.tgz
download_fd_model_zxvf tood_r50_fpn_1x_coco.tgz
download_fd_model_zxvf ttfnet_darknet53_1x_coco.tgz
download_fd_model_zxvf yolov8_x_500e_coco.tgz
download_fd_model_zxvf yolov8_l_500e_coco.tgz
download_fd_model_zxvf yolov8_m_500e_coco.tgz
download_fd_model_zxvf yolov8_s_500e_coco.tgz download_fd_model_zxvf yolov8_s_500e_coco.tgz
download_fd_model_zxvf ppyoloe_crn_l_300e_coco_trt_nms.tgz download_fd_model_zxvf yolov8_n_500e_coco.tgz
download_fd_model_zxvf picodet_l_640_coco_lcnet_trt_nms.tgz download_fd_model_zxvf picodet_l_320_coco_lcnet.tgz
download_fd_model_zxvf ppyoloe_plus_crn_m_80e_coco_trt_nms.tgz download_fd_model_zxvf yolov7_x_300e_coco.tgz
download_fd_model_zxvf yolox_s_300e_coco_trt_nms.tgz
download_fd_model_zxvf yolov5_s_300e_coco_trt_nms.tgz
download_fd_model_zxvf yolov6_s_300e_coco_trt_nms.tgz
download_fd_model_zxvf yolov7_l_300e_coco_trt_nms.tgz
download_fd_model_zxvf yolov8_s_500e_coco_trt_nms.tgz
# PaddleClas # PaddleClas
download_fd_model_zxvf PPLCNet_x1_0_infer.tgz download_fd_model_zxvf PPLCNet_x1_0_infer.tgz