administrator/frigate
1
0
Fork 0
mirror of https://github.com/blakeblackshear/frigate.git synced 2026-06-21 03:41:55 +03:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

docs: fix typos and revert incorrect dfine to define rename

Browse Source
This commit is contained in:
TheInfamousToTo 2026-06-01 17:45:31 +00:00
parent 619b234901
commit 4f6bb31276
2 changed files with 15 additions and 15 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

28
docs/docs/configuration/object_detectors.md
View File

@ -732,12 +732,12 @@ Navigate to <NavPath path="Settings > System > Detectors and model" /> and selec
| Field | Value |
| ---------------------------------------- | ---------------------------------- |
| **Object Detection Model Type** | `define` |
| **Object Detection Model Type** | `dfine` |
| **Object detection model input width** | `640` |
| **Object detection model input height** | `640` |
| **Model Input Tensor Shape** | `nchw` |
| **Model Input D Type** | `float` |
| **Custom object detector model path** | `/config/model_cache/define-s.onnx` |
| **Custom object detector model path** | `/config/model_cache/dfine-s.onnx` |
| **Label map for custom object detector** | `/labelmap/coco-80.txt` |
</TabItem>
@ -750,12 +750,12 @@ detectors:
device: CPU
model:
model_type: define
model_type: dfine
width: 640
height: 640
input_tensor: nchw
input_dtype: float
path: /config/model_cache/define-s.onnx
path: /config/model_cache/dfine-s.onnx
labelmap_path: /labelmap/coco-80.txt
```
@ -778,7 +778,7 @@ detectors:
device: CPU
model:
model_type: define
model_type: dfine
width: 640
height: 640
input_tensor: nchw
@ -1256,12 +1256,12 @@ Navigate to <NavPath path="Settings > System > Detectors and model" /> and selec
| Field | Value |
| ---------------------------------------- | ------------------------------------------- |
| **Object Detection Model Type** | `define` |
| **Object Detection Model Type** | `dfine` |
| **Object detection model input width** | `640` |
| **Object detection model input height** | `640` |
| **Model Input Tensor Shape** | `nchw` |
| **Model Input D Type** | `float` |
| **Custom object detector model path** | `/config/model_cache/define_m_obj2coco.onnx` |
| **Custom object detector model path** | `/config/model_cache/dfine_m_obj2coco.onnx` |
| **Label map for custom object detector** | `/labelmap/coco-80.txt` |
</TabItem>
@ -1273,12 +1273,12 @@ detectors:
type: onnx
model:
model_type: define
model_type: dfine
width: 640
height: 640
input_tensor: nchw
input_dtype: float
path: /config/model_cache/define_m_obj2coco.onnx
path: /config/model_cache/dfine_m_obj2coco.onnx
labelmap_path: /labelmap/coco-80.txt
```
@ -1298,7 +1298,7 @@ detectors:
type: onnx
model:
model_type: define
model_type: dfine
width: 640
height: 640
input_tensor: nchw
@ -2324,20 +2324,20 @@ docker build . --build-arg MODEL_SIZE=s --output . -f- <<'EOF'
FROM python:3.11 AS build
RUN apt-get update && apt-get install --no-install-recommends -y libgl1 && rm -rf /var/lib/apt/lists/*
COPY --from=ghcr.io/astral-sh/uv:0.8.0 /uv /bin/
WORKDIR /define
WORKDIR /dfine
RUN git clone https://github.com/Peterande/D-FINE.git .
RUN uv pip install --system -r requirements.txt
RUN uv pip install --system onnx onnxruntime onnxsim onnxscript
# Create output directory and download checkpoint
RUN mkdir -p output
ARG MODEL_SIZE
RUN wget https://github.com/Peterande/storage/releases/download/definev1.0/define_${MODEL_SIZE}_obj2coco.pth -O output/define_${MODEL_SIZE}_obj2coco.pth
RUN wget https://github.com/Peterande/storage/releases/download/dfinev1.0/dfine_${MODEL_SIZE}_obj2coco.pth -O output/dfine_${MODEL_SIZE}_obj2coco.pth
# Modify line 58 of export_onnx.py to change batch size to 1
RUN sed -i '58s/data = torch.rand(.*)/data = torch.rand(1, 3, 640, 640)/' tools/deployment/export_onnx.py
RUN python3 tools/deployment/export_onnx.py -c configs/define/objects365/define_hgnetv2_${MODEL_SIZE}_obj2coco.yml -r output/define_${MODEL_SIZE}_obj2coco.pth
RUN python3 tools/deployment/export_onnx.py -c configs/dfine/objects365/dfine_hgnetv2_${MODEL_SIZE}_obj2coco.yml -r output/dfine_${MODEL_SIZE}_obj2coco.pth
FROM scratch
ARG MODEL_SIZE
COPY --from=build /define/output/define_${MODEL_SIZE}_obj2coco.onnx /define-${MODEL_SIZE}.onnx
COPY --from=build /dfine/output/dfine_${MODEL_SIZE}_obj2coco.onnx /dfine-${MODEL_SIZE}.onnx
EOF
```

2
docs/docs/frigate/installation.md
View File

@ -749,7 +749,7 @@ Failure to remap port 5000 on the host will result in the WebUI and all API endp
:::
Docker containers on macOS can be orchestrated by either [Docker Desktop](https://docs.docker.com/desktop/setup/install/mac-install/) or [OrbStack](https://orbstack.dev) (native swift app). The difference in inference speeds is negligible, however CPU, power consumption and container start times will be lower on OrbStack because it is a native Swift application.
Docker containers on macOS can be orchestrated by either [Docker Desktop](https://docs.docker.com/desktop/setup/install/mac-install/) or [OrbStack](https://orbstack.dev) (native Swift app). The difference in inference speeds is negligible, however CPU, power consumption and container start times will be lower on OrbStack because it is a native Swift application.
To allow Frigate to use the Apple Silicon Neural Engine / Processing Unit (NPU) the host must be running [Apple Silicon Detector](../configuration/object_detectors.md#apple-silicon-detector) on the host (outside Docker)