From 32d1c94b8675a892a5279073f22aa686c18cfd48 Mon Sep 17 00:00:00 2001 From: knoffelcut Date: Wed, 3 Jun 2026 21:02:59 +0200 Subject: [PATCH] NanoDet-Plus documentation --- docs/docs/configuration/object_detectors.md | 88 ++++++++++++++++++++- 1 file changed, 87 insertions(+), 1 deletion(-) diff --git a/docs/docs/configuration/object_detectors.md b/docs/docs/configuration/object_detectors.md index 1d58973e2b..2b74aaa9a5 100644 --- a/docs/docs/configuration/object_detectors.md +++ b/docs/docs/configuration/object_detectors.md @@ -494,7 +494,8 @@ detectors: | [YOLO-NAS](#yolo-nas) | ✅ | ✅ | | | [MobileNet v2](#ssdlite-mobilenet-v2) | ✅ | ✅ | Fast and lightweight model, less accurate than larger models | | [YOLOX](#yolox) | ✅ | ? | | -| [D-FINE / DEIMv2](#d-fine--deimv2) | ❌ | ❌ | | +| [D-FINE](#d-fine) | ❌ | ❌ | | +| [NanoDet-Plus](#nanodet-plus) | ? | ? | | #### SSDLite MobileNet v2 @@ -791,6 +792,44 @@ Note that the labelmap uses a subset of the complete COCO label set that has onl +#### NanoDet-Plus +[NanoDet-Plus](https://github.com/RangiLyu/nanodet) is a lightweight object detection model that achieves +good accuracy on CPUs given its small footprint. + +Script to export an ONNX model for use in Frigate is provided in [the models section](#downloading-nanodet-plus-models). + +:::warning + +NanoDet-Plus has not been tested in GPU nor NPU modes. + +::: + +
+ NanoDet-Plus Setup & Config + +After placing the exported onnx model in your config/model_cache folder, you can use the following configuration: + +```yaml +detectors: + ov: + type: openvino + device: CPU + +model: + model_type: nanodet_plus + width: 320 + height: 320 + input_tensor: nchw + input_dtype: float + input_pixel_format: bgr + path: /config/model_cache/nanodet_plus.onnx + labelmap_path: /labelmap/coco-80.txt +``` + +Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects. + +
+ ## Apple Silicon detector The NPU in Apple Silicon can't be accessed from within a container, so the [Apple Silicon detector client](https://github.com/frigate-nvr/apple-silicon-detector) must first be setup. It is recommended to use the Frigate docker image with `-standard-arm64` suffix, for example `ghcr.io/blakeblackshear/frigate:stable-standard-arm64`. @@ -1029,6 +1068,7 @@ detectors: | [YOLO-NAS](#yolo-nas-1) | ⚠️ | ⚠️ | Not supported by CUDA Graphs | | [YOLOX](#yolox-1) | ✅ | ✅ | Supports CUDA Graphs for optimal Nvidia performance | | [D-FINE / DEIMv2](#d-fine--deimv2-1) | ⚠️ | ❌ | Not supported by CUDA Graphs | +| [NanoDet-Plus](#nanodet-plus-1) | ✅ | ? | Supports CUDA Graphs for optimal Nvidia performance | There is no default model provided, the following formats are supported: @@ -1311,6 +1351,42 @@ model: Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects. +#### NanoDet-Plus +[NanoDet-Plus](https://github.com/RangiLyu/nanodet) is a lightweight object detection model that achieves +good accuracy on CPUs given its small footprint. + +Script to export an ONNX model for use in Frigate is provided in [the models section](#downloading-nanodet-plus-models). +:::warning + +NanoDet-Plus has not been tested on AMD GPUs. + +::: + +
+ NanoDet-Plus Setup & Config + +After placing the exported onnx model in your config/model_cache folder, you can use the following configuration: + +```yaml +detectors: + onnx: + type: onnx + +model: + model_type: nanodet_plus + width: 320 + height: 320 + input_tensor: nchw + input_dtype: float + input_pixel_format: bgr + path: /config/model_cache/nanodet_plus.onnx + labelmap_path: /labelmap/coco-80.txt +``` + +Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects. + +
+ ## CPU Detector (not recommended) The CPU detector type runs a TensorFlow Lite model utilizing the CPU without hardware acceleration. It is recommended to use a hardware accelerated detector type instead for better performance. To configure a CPU based detector, set the `"type"` attribute to `"cpu"`. @@ -2462,6 +2538,16 @@ EOF ``` ### Downloading NanoDet-Plus models +NanoDet-Plus can be downloaded using the command below. Copy and paste the complete command to your terminal to export +the model as `nanodet_plus.onnx` in the current working directory. The command builds the NanoDet-Plus environment, +downloads the specified model and converts it to ONNX. + +The below command is configured to use the smallest model provided by the authors, NanoDet-Plus-m-320. Other models +can be specified by changing the `URL_WEIGHTS` link to the appropriate pretrained weights URL from +[NanoDet-Plus Model Zoo](https://github.com/RangiLyu/nanodet#model-zoo). Remember to change the `IMG_HEIGHT`, +`IMG_WIDTH` and `CFG_PATH` ([configuration files](https://github.com/RangiLyu/nanodet/tree/main/config)) parameters +accordingly. + Compatible with the `labelmap/coco-80.txt` labelmap ```sh