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Add documentation for OpenVino detector configuration
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@ -77,3 +77,33 @@ detectors:
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```
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When using CPU detectors, you can add a CPU detector per camera. Adding more detectors than the number of cameras should not improve performance.
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## OpenVino
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The OpenVino detector allows Frigate to run an OpenVino IR model on Intel CPU, GPU and VPU hardware.
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### OpenVino Devices
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The OpenVino detector supports the Intel-supplied device plugins and can specify one or more devices in the configuration. See OpenVino's device naming conventions in the [Device Documentation](https://docs.openvino.ai/latest/openvino_docs_OV_UG_Working_with_devices.html) for more detail. Other supported devices could be `AUTO`, `CPU`, `GPU`, etc.
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```yaml
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detectors:
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ov_detector:
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type: openvino
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device: GPU
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```
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### OpenVino Models
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The included model for an OpenVino detector comes from Intel's Open Model Zoo [SSDLite MobileNet V2](https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/ssdlite_mobilenet_v2) and is converted to an FP16 precision IR model. Use the model configuration shown below when using the OpenVino detector.
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```yaml
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model:
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path: /openvino-model/ssdlite_mobilenet_v2.xml
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width: 300
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height: 300
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input_tensor: [B, H, W, C]
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input_pixel_format: "bgr"
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labelmap_path: /openvino-model/coco_91cl_bkgr.txt
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```
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@ -76,9 +76,9 @@ detectors:
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# Required: name of the detector
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coral:
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# Required: type of the detector
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# Valid values are 'edgetpu' (requires device property below) and 'cpu'.
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# Valid values are 'edgetpu' (requires device property below) `openvino` (see Detectors documentation), and 'cpu'.
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type: edgetpu
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# Optional: device name as defined here: https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api
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# Optional: Edgetpu or OpenVino device name
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device: usb
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# Optional: num_threads value passed to the tflite.Interpreter (default: shown below)
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# This value is only used for CPU types
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