Cleaned up TODO's and added filesystem

src/perception/object_detector/inference.cu

@@ -24,12 +24,11 @@ namespace mrover {
     constexpr static char const* INPUT_BINDING_NAME = "images";
     constexpr static char const* OUTPUT_BINDING_NAME = "output0";
 
-    Inference::Inference(std::string const& onnxModelPath, cv::Size modelInputShape = {640, 640}, std::string const& classesTxtFile = "") {
+    Inference::Inference(std::filesystem::path const& onnxModelPath) {
         //Create the engine object from either the file or from onnx file
         mEngine = std::unique_ptr<ICudaEngine, Destroy<ICudaEngine>>{createCudaEngine(onnxModelPath)};
         if (!mEngine) throw std::runtime_error("Failed to create CUDA engine");
 
-        //Log the Engine was created
         mLogger.log(ILogger::Severity::kINFO, "Created CUDA Engine");
 
         //Check some assumptions about the model
@@ -44,8 +43,8 @@ namespace mrover {
         prepTensors();
     }
 
-    ICudaEngine* Inference::createCudaEngine(std::string const& onnxModelPath) {
-        // See link sfor additional context
+    ICudaEngine* Inference::createCudaEngine(std::filesystem::path const& onnxModelPath) {
+        //Define the size of Batches
         constexpr auto explicitBatch = 1U << static_cast<uint32_t>(NetworkDefinitionCreationFlag::kEXPLICIT_BATCH);
 
         //Init logger

src/perception/object_detector/inference.cuh

@@ -29,9 +29,6 @@ namespace mrover {
         //Bindings
         std::array<void*, 2> mBindings{};
 
-        //ONNX Model Path
-        std::string mOnnxModelPath{};
-
         //Size of Model
         cv::Size mModelInputShape;
         cv::Size mModelOutputShape;
@@ -41,7 +38,7 @@ namespace mrover {
 
     private:
         //Creates a ptr to the engine
-        ICudaEngine* createCudaEngine(std::string const& onnxModelPath);
+        ICudaEngine* createCudaEngine(std::filesystem::path const& onnxModelPath);
 
         //Launch the model execution onto the GPU
         void launchInference(cv::Mat const& input, cv::Mat const& output) const;
@@ -54,7 +51,7 @@ namespace mrover {
 
     public:
         //Inference Constructor
-        Inference(std::string const& onnxModelPath, cv::Size modelInputShape, std::string const& classesTxtFile);
+        Inference(std::filesystem::path const& onnxModelPath);
 
         //Forward Pass of the model
         void doDetections(const cv::Mat& img) const;

src/perception/object_detector/inference_wrapper.cu

@@ -18,9 +18,9 @@ using namespace nvinfer1;
 */
 namespace mrover {
 
-    InferenceWrapper::InferenceWrapper(std::string onnxModelPath, cv::Size const modelInputShape = {640, 640}, std::string classesTxtFile = "") : mInference({}) {
+    InferenceWrapper::InferenceWrapper(std::string onnxModelPath) : mInference({}) {
         //Initialize the unique_ptr to the inference class
-        mInference.reset(new Inference(std::move(onnxModelPath), modelInputShape, std::move(classesTxtFile)));
+        mInference.reset(new Inference(std::move(onnxModelPath)));
     }
 
 

src/perception/object_detector/inference_wrapper.hpp

@@ -17,7 +17,7 @@ namespace mrover {
         ~InferenceWrapper() = default;
 
         //Inference Wrapper Constructor
-        InferenceWrapper(std::string onnxModelPath, cv::Size const modelInputShape, std::string classesTxtFile);
+        InferenceWrapper(std::string onnxModelPath);
 
         //Forward Pass on the model
         void doDetections(cv::Mat const& img) const;

src/perception/object_detector/object_detector.cpp

@@ -12,18 +12,13 @@ namespace mrover {
         std::filesystem::path packagePath = ros::package::getPath("mrover");
         std::filesystem::path modelPath = packagePath / "data" / "best.onnx";
 
-        // TODO: resolution should be a parameter
-        // TODO: get size of the model from the model itself
-        // TODO: remove empty string
-        mInferenceWrapper = InferenceWrapper{modelPath, cv::Size{640, 640}, ""};
+        mInferenceWrapper = InferenceWrapper{modelPath};
 
         //Create the publishers and subscribers for the detected image and the debug image
         mImgSub = mNh.subscribe("/camera/left/points", 1, &ObjectDetectorNodelet::imageCallback, this);
         mDebugImgPub = mNh.advertise<sensor_msgs::Image>("/object_detector/debug_img", 1);
         mDetectionData = mNh.advertise<DetectedObject>("/object_detector/detected_object", 1);
 
-        //READ ROS PARAMETERS
-
         //Create the Reference Frames
         mNh.param<std::string>("camera_frame", mCameraFrameId, "zed2i_left_camera_frame");
         mNh.param<std::string>("world_frame", mMapFrameId, "map");

src/perception/object_detector/object_detector.hpp

@@ -20,11 +20,6 @@ namespace mrover {
         //Mat for the image from the point cloud
         cv::Mat mImg;
 
-        //Image information
-        constexpr static int NUM_CHANNELS = 3;
-        constexpr static int IMG_WIDTH = 1280;
-        constexpr static int IMG_HEIGHT = 720;
-
         //List of class names
         std::vector<std::string> classes{"Hammer"};//{"person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut", "cake", "chair", "couch", "potted plant", "bed", "dining table", "toilet", "tv", "laptop", "mouse", "remote", "keyboard", "cell phone", "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors", "teddy bear", "hair drier", "toothbrush"};
 

src/perception/object_detector/pch.hpp

@@ -1,6 +1,6 @@
 #pragma once
 
-#include <algorithm>//TODO: clean up :)
+#include <algorithm>
 #include <array>
 #include <cassert>
 #include <cmath>
@@ -17,17 +17,6 @@
 #include <string>
 #include <type_traits>
 #include <unordered_map>
-#include <cassert>
-#include <cmath>
-#include <cstdint>
-#include <execution>
-#include <limits>
-#include <numeric>
-#include <optional>
-#include <string>
-#include <type_traits>
-#include <unordered_map>
-
 
 #include <boost_cpp23_workaround.hpp>