feat(traffic_light_classifier): add parameters to launch file for using different tensorrt models (autowarefoundation#2794)

* feat(traffic_light_classifier): add params to launch file

Signed-off-by: Zeynep Akbalık <zeynep@leodrive.ai>

---------

Signed-off-by: Zeynep Akbalık <zeynep@leodrive.ai>
Co-authored-by: Zeynep Akbalık <zeynep@leodrive.ai>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: 3 people

perception/traffic_light_classifier/README.md

@@ -54,15 +54,19 @@ These colors and shapes are assigned to the message as follows:
 
 #### cnn_classifier
 
-| Name              | Type | Description                                       |
-| ----------------- | ---- | ------------------------------------------------- |
-| `model_file_path` | str  | path to the model file                            |
-| `label_file_path` | str  | path to the label file                            |
-| `precision`       | str  | TensorRT precision, `fp16` or `int8`              |
-| `input_c`         | str  | the channel size of an input image                |
-| `input_h`         | str  | the height of an input image                      |
-| `input_w`         | str  | the width of an input image                       |
-| `build_only`      | bool | shutdown node after TensorRT engine file is built |
+| Name              | Type   | Description                                       |
+| ----------------- | ------ | ------------------------------------------------- |
+| `model_file_path` | str    | path to the model file                            |
+| `label_file_path` | str    | path to the label file                            |
+| `precision`       | str    | TensorRT precision, `fp16` or `int8`              |
+| `input_c`         | str    | the channel size of an input image                |
+| `input_h`         | str    | the height of an input image                      |
+| `input_w`         | str    | the width of an input image                       |
+| `input_name`      | str    | the name of neural network's input layer          |
+| `output_name`     | str    | the name of neural network's output name          |
+| `mean`            | double | mean values for image normalization               |
+| `std`             | double | std values for image normalization                |
+| `build_only`      | bool   | shutdown node after TensorRT engine file is built |
 
 #### hsv_classifier
 

perception/traffic_light_classifier/include/traffic_light_classifier/cnn_classifier.hpp

@@ -101,8 +101,8 @@ class CNNClassifier : public ClassifierInterface
   std::shared_ptr<Tn::TrtCommon> trt_;
   image_transport::Publisher image_pub_;
   std::vector<std::string> labels_;
-  std::vector<float> mean_{0.242, 0.193, 0.201};
-  std::vector<float> std_{1.0, 1.0, 1.0};
+  std::vector<double> mean_;
+  std::vector<double> std_;
   int input_c_;
   int input_h_;
   int input_w_;

perception/traffic_light_classifier/launch/traffic_light_classifier.launch.xml

@@ -19,7 +19,12 @@
     <param name="classifier_type" value="$(var classifier_type)"/>
     <param name="model_file_path" value="$(find-pkg-share traffic_light_classifier)/data/traffic_light_classifier_mobilenetv2.onnx"/>
     <param name="label_file_path" value="$(find-pkg-share traffic_light_classifier)/data/lamp_labels.txt"/>
+    <param name="mean" value="[0.242, 0.193, 0.201]"/>
+    <param name="std" value="[1.0, 1.0, 1.0]"/>
     <param name="precision" value="fp16"/>
+    <param name="input_name" value="input_0"/>
+    <param name="output_name" value="output_0"/>
+    <param name="apply_softmax" value="true"/>
     <param name="input_c" value="3"/>
     <param name="input_h" value="224"/>
     <param name="input_w" value="224"/>

perception/traffic_light_classifier/src/cnn_classifier.cpp

@@ -39,8 +39,10 @@ CNNClassifier::CNNClassifier(rclcpp::Node * node_ptr) : node_ptr_(node_ptr)
   input_c_ = node_ptr_->declare_parameter("input_c", 3);
   input_h_ = node_ptr_->declare_parameter("input_h", 224);
   input_w_ = node_ptr_->declare_parameter("input_w", 224);
-  auto input_name = node_ptr_->declare_parameter("input_name", "input_0");
-  auto output_name = node_ptr_->declare_parameter("output_name", "output_0");
+  mean_ = node_ptr_->declare_parameter("mean", std::vector<double>({0.242, 0.193, 0.201}));
+  std_ = node_ptr_->declare_parameter("std", std::vector<double>({1.0, 1.0, 1.0}));
+  std::string input_name = node_ptr_->declare_parameter("input_name", std::string("input_0"));
+  std::string output_name = node_ptr_->declare_parameter("output_name", std::string("output_0"));
   apply_softmax_ = node_ptr_->declare_parameter("apply_softmax", true);
 
   readLabelfile(label_file_path, labels_);