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fix(tensorrt_yolo): multi gpu on component container #2297

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merged 4 commits into from
Nov 29, 2022
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fix(tensorrt_yolo): multi gpu on component container #2297

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ed88f11
fix(tensorrt_yolo): multi gpu on component container
kaancolak Nov 15, 2022
f249684
fix(tensorrt_yolo): add return
kaancolak Nov 16, 2022
ced5819
fix(tensorrt_yolo): update readme
kaancolak Nov 21, 2022
302a053
ci(pre-commit): autofix
pre-commit-ci[bot] Nov 21, 2022
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2 changes: 2 additions & 0 deletions perception/tensorrt_yolo/include/tensorrt_yolo/nodelet.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -58,6 +58,8 @@ class TensorrtYoloNodelet : public rclcpp::Node

yolo::Config yolo_config_;

int gpu_device_id_;

std::vector<std::string> labels_;
std::unique_ptr<float[]> out_scores_;
std::unique_ptr<float[]> out_boxes_;
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8 changes: 6 additions & 2 deletions perception/tensorrt_yolo/src/nodelet.cpp
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Expand Up @@ -51,7 +51,7 @@ TensorrtYoloNodelet::TensorrtYoloNodelet(const rclcpp::NodeOptions & options)
std::string calib_image_directory = declare_parameter("calib_image_directory", "");
std::string calib_cache_file = declare_parameter("calib_cache_file", "");
std::string mode = declare_parameter("mode", "FP32");
int gpu_device_id = declare_parameter("gpu_id", 0);
gpu_device_id_ = declare_parameter("gpu_id", 0);
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yolo_config_.num_anchors = declare_parameter("num_anchors", 3);
auto anchors = declare_parameter(
"anchors", std::vector<double>{
Expand All @@ -67,7 +67,7 @@ TensorrtYoloNodelet::TensorrtYoloNodelet(const rclcpp::NodeOptions & options)
yolo_config_.use_darknet_layer = declare_parameter("use_darknet_layer", true);
yolo_config_.ignore_thresh = declare_parameter("ignore_thresh", 0.5);

if (!yolo::set_cuda_device(gpu_device_id)) {
if (!yolo::set_cuda_device(gpu_device_id_)) {
RCLCPP_ERROR(this->get_logger(), "Given GPU not exist or suitable");
}

Expand Down Expand Up @@ -134,6 +134,10 @@ void TensorrtYoloNodelet::callback(const sensor_msgs::msg::Image::ConstSharedPtr

tier4_perception_msgs::msg::DetectedObjectsWithFeature out_objects;

if (!yolo::set_cuda_device(gpu_device_id_)) {
RCLCPP_ERROR(this->get_logger(), "Given GPU not exist or suitable");
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}

cv_bridge::CvImagePtr in_image_ptr;
try {
in_image_ptr = cv_bridge::toCvCopy(in_image_msg, sensor_msgs::image_encodings::BGR8);
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