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

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

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

docker/tensorrt/Dockerfile.base

@@ -23,4 +23,4 @@ ENV S6_CMD_WAIT_FOR_SERVICES_MAXTIME=0
 COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
 COPY --from=trt-deps /usr/local/src/tensorrt_demos /usr/local/src/tensorrt_demos
 COPY docker/tensorrt/detector/rootfs/ /
-ENV YOLO_MODELS="yolov7-tiny-416"
+ENV YOLO_MODELS="yolov7-320"

docs/docs/configuration/object_detectors.md

@@ -196,9 +196,9 @@ The model used for TensorRT must be preprocessed on the same hardware platform t
 
 The Frigate image will generate model files during startup if the specified model is not found.  Processed models are stored in the `/config/model_cache` folder.  Typically the `/config` path is mapped to a directory on the host already and the `model_cache` does not need to be mapped separately unless the user wants to store it in a different location on the host.
 
-By default, the `yolov7-tiny-416` model will be generated, but this can be overridden by specifying the `YOLO_MODELS` environment variable in Docker. One or more models may be listed in a comma-separated format, and each one will be generated. To select no model generation, set the variable to an empty string, `YOLO_MODELS=""`. Models will only be generated if the corresponding `{model}.trt` file is not present in the `model_cache` folder, so you can force a model to be regenerated by deleting it from your Frigate data folder.
+By default, the `yolov7-320` model will be generated, but this can be overridden by specifying the `YOLO_MODELS` environment variable in Docker. One or more models may be listed in a comma-separated format, and each one will be generated. To select no model generation, set the variable to an empty string, `YOLO_MODELS=""`. Models will only be generated if the corresponding `{model}.trt` file is not present in the `model_cache` folder, so you can force a model to be regenerated by deleting it from your Frigate data folder.
 
-If you have a Jetson device with DLAs (Xavier or Orin), you can generate a model that will run on the DLA by appending `-dla` to your model name, e.g. specify `YOLO_MODELS=yolov7-tiny-416-dla`. The model will run on DLA0 (Frigate does not currently support DLA1). DLA-incompatible layers will fall back to running on the GPU.
+If you have a Jetson device with DLAs (Xavier or Orin), you can generate a model that will run on the DLA by appending `-dla` to your model name, e.g. specify `YOLO_MODELS=yolov7-320-dla`. The model will run on DLA0 (Frigate does not currently support DLA1). DLA-incompatible layers will fall back to running on the GPU.
 
 If your GPU does not support FP16 operations, you can pass the environment variable `USE_FP16=False` to disable it.
 
@@ -254,11 +254,11 @@ detectors:
     device: 0 #This is the default, select the first GPU
 
 model:
-  path: /config/model_cache/tensorrt/yolov7-tiny-416.trt
+  path: /config/model_cache/tensorrt/yolov7-320.trt
   input_tensor: nchw
   input_pixel_format: rgb
-  width: 416
+  width: 320
-  height: 416
+  height: 320
 ```
 
 ## Deepstack / CodeProject.AI Server Detector