Nvidia Jetson ffmpeg + TensorRT support (#6458)

* Non-Jetson changes

Required for later commits:
- Allow base image to be overridden (and don't assume its WORKDIR)
- Ensure python3.9
- Map hwaccel decode presets as strings instead of lists
Not required:
- Fix existing documentation
- Simplify hwaccel scale logic

* Prepare for multi-arch tensorrt build

* Add tensorrt images for Jetson boards

* Add Jetson ffmpeg hwaccel

* Update docs

* Add CODEOWNERS

* CI

* Change default model from yolov7-tiny-416 to yolov7-320

In my experience the tiny models perform markedly worse without being
much faster

* fixup! Update docs

docker-compose.yml

@@ -21,6 +21,8 @@ services:
                       - driver: nvidia
                         count: 1
                         capabilities: [gpu]
+    environment:
+      YOLO_MODELS: yolov7-320
     devices:
       - /dev/bus/usb:/dev/bus/usb
       # - /dev/dri:/dev/dri # for intel hwaccel, needs to be updated for your hardware
@@ -30,8 +32,6 @@ services:
       - /etc/localtime:/etc/localtime:ro
       - ./config:/config
       - ./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