diff --git a/CMakeLists.txt b/CMakeLists.txt
index 1e1f08b6..b04a8e9d 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -319,7 +319,6 @@ install(PROGRAMS
         localization/basestation_gps_driver.py
         superstructure/superstructure.py
         scripts/debug_course_publisher.py
-		scripts/visualizer.py
 
         # starter project sources
         starter_project/autonomy/src/localization.py
diff --git a/perception/object_detector/object_detector.cpp b/perception/object_detector/object_detector.cpp
index 7f53f883..601b03a1 100644
--- a/perception/object_detector/object_detector.cpp
+++ b/perception/object_detector/object_detector.cpp
@@ -32,7 +32,7 @@ namespace mrover {
 
         using namespace std::placeholders;
 
-        mModel = Model(modelName, {0, 0}, {"bottle", "hammer"}, mTensorRT.getInputTensorSize(), mTensorRT.getOutputTensorSize(), [this](Model const& model, cv::Mat& rgbImage, cv::Mat& blobSizedImage, cv::Mat& blob){preprocessYOLOv8Input(model, rgbImage, blobSizedImage, blob);}, [this](Model const& model, cv::Mat& output, std::vector<Detection>& detections){parseYOLOv8Output(model, output, detections);});
+        mModel = Model(modelName, {0, 0}, {"bottle", "hammer"}, mTensorRT.getInputTensorSize(), mTensorRT.getOutputTensorSize(), [](Model const& model, cv::Mat& rgbImage, cv::Mat& blobSizedImage, cv::Mat& blob){preprocessYOLOv8Input(model, rgbImage, blobSizedImage, blob);}, [this](Model const& model, cv::Mat& output, std::vector<Detection>& detections){parseYOLOv8Output(model, output, detections);});
 
         RCLCPP_INFO_STREAM(get_logger(), std::format("Object detector initialized with model: {} and thresholds: {} and {}", mModel.modelName, mModelScoreThreshold, mModelNMSThreshold));
     }
diff --git a/tensorrt/inference.cu b/tensorrt/inference.cu
index f8c83198..20a73bfc 100644
--- a/tensorrt/inference.cu
+++ b/tensorrt/inference.cu
@@ -1,4 +1,5 @@
 #include "inference.cuh"
+#include <ios>
 
 using namespace nvinfer1;
 
@@ -106,7 +107,7 @@ auto Inference::createCudaEngine() -> ICudaEngine* {
 		// Save Engine to File
 		auto trtModelStream = tempEng->serialize();
 		std::ofstream outputFileStream{mEngineModelPath, std::ios::binary};
-		outputFileStream.write(static_cast<char const*>(trtModelStream->data()), static_cast<int32_t>(trtModelStream->size()));
+		outputFileStream.write(static_cast<char const*>(trtModelStream->data()), static_cast<std::streamsize>(trtModelStream->size()));
 		outputFileStream.close();
 
 		return tempEng;