Nvidia TensorRT detector (#4718)

* Initial WIP dockerfile and scripts to add tensorrt support

* Add tensorRT detector

* WIP attempt to install TensorRT 8.5

* Updates to detector for cuda python library

* TensorRT Cuda library rework WIP

Does not run

* Fixes from rebase to detector factory

* Fix parsing output memory pointer

* Handle TensorRT logs with the python logger

* Use non-async interface and convert input data to float32. Detection runs without error.

* Make TensorRT a separate build from the base Frigate image.

* Add script and documentation for generating TRT Models

* Add support for TensorRT devcontainer

* Add labelmap to trt model script and docs.  Cleanup of old scripts.

* Update detect to normalize input tensor using model input type

* Add config for selecting GPU. Fix Async inference. Update documentation.

* Update some CUDA libraries to clean up version warning

* Add CI stage to build TensorRT tag

* Add note in docs for image tag and model support

docker-compose.yml

@@ -11,7 +11,15 @@ services:
     shm_size: "256mb"
     build:
       context: .
+      # Use target devcontainer-trt for TensorRT dev
       target: devcontainer
+    deploy:
+          resources:
+              reservations:
+                  devices:
+                      - driver: nvidia
+                        count: 1
+                        capabilities: [gpu]
     devices:
       - /dev/bus/usb:/dev/bus/usb
       # - /dev/dri:/dev/dri # for intel hwaccel, needs to be updated for your hardware
@@ -21,6 +29,8 @@ services:
       - /etc/localtime:/etc/localtime:ro
       - ./config/config.yml:/config/config.yml:ro
       - ./debug:/media/frigate
+      # Create the trt-models folder using the documented method of generating TRT models
+      # - ./debug/trt-models:/trt-models
       - /dev/bus/usb:/dev/bus/usb
   mqtt:
     container_name: mqtt