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

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In my experience the tiny models perform markedly worse without being
much faster
This commit is contained in:
Andrew Reiter 2023-07-25 02:59:17 -04:00
parent 9996617b4d
commit 08542daeba
3 changed files with 8 additions and 6 deletions
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2
docker-compose.yml
View File

@ -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

2
docker/tensorrt/Dockerfile.base
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@ -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"

10
docs/docs/configuration/object_detectors.md
View File

@ -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
height: 416
width: 320
height: 320
```
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