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fix model manager with various batchsize

This commit is contained in:
jario 2024-01-19 21:12:13 +08:00
parent 334c2055d9
commit 212c9f18fa
15 changed files with 72 additions and 19 deletions
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12
algorithm/common_det/cuda/common_det_cuda_impl.cpp
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@ -363,10 +363,16 @@ bool CommonObjectDetectorCUDAImpl::cudaSetup(CommonObjectDetectorBase* base_, bo
bool with_segmentation = base_->withSegmentation();
double thrs_conf = base_->getThrsConf();
double thrs_nms = base_->getThrsNms();
std::string model = base_->getModel();
int bs = base_->getBatchSize();
char bs_c[8];
itoa(bs, bs_c, 10);
std::string bs_s(bs_c);
std::string engine_fn = get_home() + SV_MODEL_DIR + dataset + ".engine";
std::vector<std::string> files;
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.engine", "Nv-" + dataset + "-yolov5s_c");
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.engine", "Nv-" + dataset + "-yolov5" + model + "_b" + bs_s + "_c");
if (files.size() > 0)
{
std::sort(files.rbegin(), files.rend(), _comp_str_lesser);
@ -376,7 +382,7 @@ bool CommonObjectDetectorCUDAImpl::cudaSetup(CommonObjectDetectorBase* base_, bo
if (input_w == 1280)
{
files.clear();
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.engine", "Nv-" + dataset + "-yolov5s6_");
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.engine", "Nv-" + dataset + "-yolov5" + model + "6_b" + bs_s + "_c");
if (files.size() > 0)
{
std::sort(files.rbegin(), files.rend(), _comp_str_lesser);
@ -392,7 +398,7 @@ bool CommonObjectDetectorCUDAImpl::cudaSetup(CommonObjectDetectorBase* base_, bo
base_->setInputH(640);
base_->setInputW(640);
files.clear();
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.engine", "Nv-" + dataset + "-yolov5s_seg_");
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.engine", "Nv-" + dataset + "-yolov5" + model + "_seg_b" + bs_s + "_c");
if (files.size() > 0)
{
std::sort(files.rbegin(), files.rend(), _comp_str_lesser);

7
algorithm/common_det/intel/common_det_intel_impl.cpp
View File

@ -125,10 +125,11 @@ namespace sv
inpHeight = base_->getInputH();
inpWidth = base_->getInputW();
with_segmentation = base_->withSegmentation();
std::string model = base_->getModel();
std::string openvino_fn = get_home() + SV_MODEL_DIR + dataset + ".onnx";
std::vector<std::string> files;
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.onnx", "Int-" + dataset + "-yolov5s_c");
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.onnx", "Int-" + dataset + "-yolov5" + model + "_c");
if (files.size() > 0)
{
std::sort(files.rbegin(), files.rend(), _comp_str_lesser);
@ -138,7 +139,7 @@ namespace sv
if (inpWidth == 1280)
{
files.clear();
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.onnx", "Int-" + dataset + "-yolov5s6_");
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.onnx", "Int-" + dataset + "-yolov5" + model + "6_c");
if (files.size() > 0)
{
std::sort(files.rbegin(), files.rend(), _comp_str_lesser);
@ -154,7 +155,7 @@ namespace sv
base_->setInputH(640);
base_->setInputW(640);
files.clear();
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.onnx", "Int-" + dataset + "-yolov5s_seg_");
_list_dir(get_home() + SV_MODEL_DIR, files, "-online.onnx", "Int-" + dataset + "-yolov5" + model + "_seg_c");
if (files.size() > 0)
{
std::sort(files.rbegin(), files.rend(), _comp_str_lesser);

16
algorithm/sv_algorithm_base.cpp
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@ -916,6 +916,14 @@ void CommonObjectDetectorBase::setInputW(int w_)
{
this->_input_w = w_;
}
std::string CommonObjectDetectorBase::getModel()
{
return this->_model;
}
int CommonObjectDetectorBase::getBatchSize()
{
return this->_batch_size;
}
void CommonObjectDetectorBase::warmUp()
{
@ -1082,6 +1090,8 @@ void CommonObjectDetectorBase::_load()
this->_thrs_nms = 0.6;
this->_thrs_conf = 0.4;
this->_use_width_or_height = 0;
this->_batch_size = 1;
this->_model = "s";
for (auto i : detector_params_value) {
@ -1089,6 +1099,12 @@ void CommonObjectDetectorBase::_load()
this->_dataset = i->value.toString();
std::cout << "dataset: " << this->_dataset << std::endl;
}
else if ("batchSize" == std::string(i->key)) {
this->_batch_size = i->value.toNumber();
}
else if ("model" == std::string(i->key)) {
this->_model = i->value.toString();
}
else if ("inputSize" == std::string(i->key)) {
// std::cout << "inputSize (old, new): " << this->_input_w << ", " << i->value.toNumber() << std::endl;
this->_input_w = i->value.toNumber();

4
include/sv_algorithm_base.h
View File

@ -140,6 +140,8 @@ public:
double getThrsConf();
int useWidthOrHeight();
bool withSegmentation();
std::string getModel();
int getBatchSize();
protected:
virtual bool setupImpl();
virtual void detectImpl(
@ -166,6 +168,8 @@ protected:
double _thrs_conf;
int _use_width_or_height;
bool _with_segmentation;
std::string _model;
int _batch_size;
};

4
params/a-params/sv_algorithm_params.json
View File

@ -1,11 +1,13 @@
{
"CommonObjectDetector": {
"dataset": "COCO",
"model": "s",
"batchSize": 1,
"inputSize": 640,
"withSegmentation": true,
"nmsThrs": 0.6,
"scoreThrs": 0.4,
"useWidthOrHeight": 1,
"withSegmentation": true,
"datasetPersonVehicle": {
"person": [0.5, 1.8],
"car": [4.1, 1.5],

4
params/a-params/sv_algorithm_params_1280_wo_mask.json
View File

@ -1,11 +1,13 @@
{
"CommonObjectDetector": {
"dataset": "COCO",
"model": "s",
"batchSize": 1,
"inputSize": 1280,
"withSegmentation": false,
"nmsThrs": 0.6,
"scoreThrs": 0.4,
"useWidthOrHeight": 1,
"withSegmentation": false,
"datasetPersonVehicle": {
"person": [0.5, 1.8],
"car": [4.1, 1.5],

4
params/a-params/sv_algorithm_params_640_w_mask.json
View File

@ -1,11 +1,13 @@
{
"CommonObjectDetector": {
"dataset": "COCO",
"model": "s",
"batchSize": 1,
"inputSize": 640,
"withSegmentation": true,
"nmsThrs": 0.6,
"scoreThrs": 0.4,
"useWidthOrHeight": 1,
"withSegmentation": true,
"datasetPersonVehicle": {
"person": [0.5, 1.8],
"car": [4.1, 1.5],

4
params/a-params/sv_algorithm_params_640_wo_mask.json
View File

@ -1,11 +1,13 @@
{
"CommonObjectDetector": {
"dataset": "COCO",
"model": "s",
"batchSize": 1,
"inputSize": 640,
"withSegmentation": false,
"nmsThrs": 0.6,
"scoreThrs": 0.4,
"useWidthOrHeight": 1,
"withSegmentation": false,
"datasetPersonVehicle": {
"person": [0.5, 1.8],
"car": [4.1, 1.5],

4
params/a-params/sv_algorithm_params_coco_1280.json
View File

@ -1,11 +1,13 @@
{
"CommonObjectDetector": {
"dataset": "COCO",
"model": "s",
"batchSize": 1,
"inputSize": 1280,
"withSegmentation": false,
"nmsThrs": 0.6,
"scoreThrs": 0.4,
"useWidthOrHeight": 1,
"withSegmentation": false,
"datasetPersonVehicle": {
"person": [0.5, 1.8],
"car": [4.1, 1.5],

4
params/a-params/sv_algorithm_params_coco_640.json
View File

@ -1,11 +1,13 @@
{
"CommonObjectDetector": {
"dataset": "COCO",
"model": "s",
"batchSize": 1,
"inputSize": 640,
"withSegmentation": false,
"nmsThrs": 0.6,
"scoreThrs": 0.4,
"useWidthOrHeight": 1,
"withSegmentation": true,
"datasetPersonVehicle": {
"person": [0.5, 1.8],
"car": [4.1, 1.5],

4
params/a-params/sv_algorithm_params_csrt.json
View File

@ -1,11 +1,13 @@
{
"CommonObjectDetector": {
"dataset": "COCO",
"model": "s",
"batchSize": 1,
"inputSize": 640,
"withSegmentation": true,
"nmsThrs": 0.6,
"scoreThrs": 0.4,
"useWidthOrHeight": 1,
"withSegmentation": true,
"datasetPersonVehicle": {
"person": [0.5, 1.8],
"car": [4.1, 1.5],

4
params/a-params/sv_algorithm_params_kcf.json
View File

@ -1,11 +1,13 @@
{
"CommonObjectDetector": {
"dataset": "COCO",
"model": "s",
"batchSize": 1,
"inputSize": 640,
"withSegmentation": true,
"nmsThrs": 0.6,
"scoreThrs": 0.4,
"useWidthOrHeight": 1,
"withSegmentation": true,
"datasetPersonVehicle": {
"person": [0.5, 1.8],
"car": [4.1, 1.5],

4
params/a-params/sv_algorithm_params_nano.json
View File

@ -1,11 +1,13 @@
{
"CommonObjectDetector": {
"dataset": "COCO",
"model": "s",
"batchSize": 1,
"inputSize": 640,
"withSegmentation": true,
"nmsThrs": 0.6,
"scoreThrs": 0.4,
"useWidthOrHeight": 1,
"withSegmentation": true,
"datasetPersonVehicle": {
"person": [0.5, 1.8],
"car": [4.1, 1.5],

4
params/a-params/sv_algorithm_params_siamrpn.json
View File

@ -1,11 +1,13 @@
{
"CommonObjectDetector": {
"dataset": "COCO",
"model": "s",
"batchSize": 1,
"inputSize": 640,
"withSegmentation": true,
"nmsThrs": 0.6,
"scoreThrs": 0.4,
"useWidthOrHeight": 1,
"withSegmentation": true,
"datasetPersonVehicle": {
"person": [0.5, 1.8],
"car": [4.1, 1.5],

12
scripts/model_sync.py
View File

@ -51,10 +51,16 @@ def main():
if os.path.exists(model_file):
print("[1] Model:", line, "EXIST!")
if line.startswith('Nv'):
engine_fn = os.path.splitext(model_file)[0] + '.engine'
online_fn = os.path.splitext(model_file)[0] + '-online.engine'
net = line.split('-')[2]
if len(net.split('_')) == 3:
name, seg, ncls = net.split('_')
engine_fn = os.path.splitext(model_file)[0].replace(net, name + "_" + seg + '_b1_' + ncls) + '.engine'
online_fn = os.path.splitext(model_file)[0].replace(net, name + "_" + seg + '_b1_' + ncls) + '-online.engine'
else:
name, ncls = net.split('_')
engine_fn = os.path.splitext(model_file)[0].replace(net, name + '_b1_' + ncls) + '.engine'
online_fn = os.path.splitext(model_file)[0].replace(net, name + '_b1_' + ncls) + '-online.engine'
if not os.path.exists(engine_fn) and not os.path.exists(online_fn):
net = line.split('-')[2]
if net.startswith("yolov5"):
if len(net.split('_')) == 3:
name, seg, ncls = net.split('_')