diff --git a/frigate/detectors/plugins/tensorrt.py b/frigate/detectors/plugins/tensorrt.py
index bcab5f027..98c4fe9b5 100644
--- a/frigate/detectors/plugins/tensorrt.py
+++ b/frigate/detectors/plugins/tensorrt.py
@@ -5,8 +5,6 @@ import numpy as np
 import tensorrt as trt
 from cuda import cuda, cudart
 
-# import pycuda.driver as cuda
-# import pycuda.autoinit  # This is needed for initializing CUDA driver
 from frigate.detectors.detection_api import DetectionApi
 from frigate.detectors.detector_config import BaseDetectorConfig
 from typing import Literal
@@ -17,6 +15,28 @@ logger = logging.getLogger(__name__)
 DETECTOR_KEY = "tensorrt"
 
 
+class TrtLogger(trt.ILogger):
+    def __init__(self):
+        trt.ILogger.__init__(self)
+
+    def log(self, severity, msg):
+        logger.log(self.getSeverity(severity), msg)
+
+    def getSeverity(self, sev: trt.ILogger.Severity) -> int:
+        if sev == trt.ILogger.VERBOSE:
+            return logging.DEBUG
+        elif sev == trt.ILogger.INFO:
+            return logging.INFO
+        elif sev == trt.ILogger.WARNING:
+            return logging.WARNING
+        elif sev == trt.ILogger.ERROR:
+            return logging.ERROR
+        elif sev == trt.ILogger.INTERNAL_ERROR:
+            return logging.CRITICAL
+        else:
+            return logging.DEBUG
+
+
 class TensorRTDetectorConfig(BaseDetectorConfig):
     type: Literal[DETECTOR_KEY]
     device: str = Field(default=None, title="Device Type")
@@ -113,11 +133,13 @@ class TensorRtDetector(DetectionApi):
             bindings.append(int(device_mem))
             # Append to the appropriate list.
             if self.engine.binding_is_input(binding):
+                logger.info(f"Input has Shape {binding_dims}")
                 inputs.append(HostDeviceMem(host_mem, device_mem, nbytes, size))
             else:
                 # each grid has 3 anchors, each anchor generates a detection
                 # output of 7 float32 values
                 assert size % 7 == 0, f"output size was {size}"
+                logger.info(f"Output has Shape {binding_dims}")
                 outputs.append(HostDeviceMem(host_mem, device_mem, nbytes, size))
                 output_idx += 1
         assert len(inputs) == 1, f"inputs len was {len(inputs)}"
@@ -159,7 +181,7 @@ class TensorRtDetector(DetectionApi):
         # self.fps = EventsPerSecond()
         self.conf_th = 0.4  ##TODO: model config parameter
         self.nms_threshold = 0.4
-        self.trt_logger = trt.Logger(trt.Logger.INFO)
+        self.trt_logger = TrtLogger()
         self.engine = self._load_engine(detector_config.model.path)
         self.input_shape = self._get_input_shape()