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

frigate/config.py

@@ -804,9 +804,19 @@ class CameraConfig(FrigateBaseModel):
             ffmpeg_input.global_args or self.ffmpeg.global_args
         )
         hwaccel_args = get_ffmpeg_arg_list(
-            parse_preset_hardware_acceleration_decode(ffmpeg_input.hwaccel_args)
+            parse_preset_hardware_acceleration_decode(
+                ffmpeg_input.hwaccel_args,
+                self.detect.fps,
+                self.detect.width,
+                self.detect.height,
+            )
             or ffmpeg_input.hwaccel_args
-            or parse_preset_hardware_acceleration_decode(self.ffmpeg.hwaccel_args)
+            or parse_preset_hardware_acceleration_decode(
+                self.ffmpeg.hwaccel_args,
+                self.detect.fps,
+                self.detect.width,
+                self.detect.height,
+            )
             or self.ffmpeg.hwaccel_args
         )
         input_args = get_ffmpeg_arg_list(