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/util/services.py

@@ -309,6 +309,21 @@ def get_nvidia_gpu_stats() -> dict[int, dict]:
         return results
 
 
+def get_jetson_stats() -> dict[int, dict]:
+    results = {}
+
+    try:
+        results["mem"] = "-"  # no discrete gpu memory
+
+        with open("/sys/devices/gpu.0/load", "r") as f:
+            gpuload = float(f.readline()) / 10
+            results["gpu"] = f"{gpuload}%"
+    except Exception:
+        return None
+
+    return results
+
+
 def ffprobe_stream(path: str) -> sp.CompletedProcess:
     """Run ffprobe on stream."""
     clean_path = escape_special_characters(path)