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synced 2024-11-22 08:57:20 -06:00
Add OpenVino Detector (#3768)
* Initial work for adding OpenVino detector. Not functional * Load model and submit for inference. Sucessfully load model and initialize OpenVino engine with either CPU or GPU as device. Does not parse results for objects. * Detection working with ssdlite_mobilenetv2 FP16 model * Add OpenVIno support and model to docker image * Add documentation for OpenVino detector configuration * Adds support for ARM32/ARM64 and the Myriad X hardware - Use custom-built openvino wheel for all platforms - Add libusb build without udev for NCS2 support * Add documentation around Intel CPU requirements and NCS2 setup * Print all available output tensors * Update documentation for config parameters
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54
Dockerfile
54
Dockerfile
@ -5,6 +5,8 @@ ARG DEBIAN_FRONTEND=noninteractive
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FROM debian:11 AS base
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FROM --platform=linux/amd64 debian:11 AS base_amd64
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FROM debian:11-slim AS slim-base
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FROM blakeblackshear/frigate-nginx:1.0.2 AS nginx
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@ -24,6 +26,51 @@ WORKDIR /rootfs/usr/local/go2rtc/bin
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RUN wget -qO go2rtc "https://github.com/AlexxIT/go2rtc/releases/download/v0.1-rc.3/go2rtc_linux_${TARGETARCH}" \
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&& chmod +x go2rtc
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# Download and Convert OpenVino model
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FROM base_amd64 AS ov-converter
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ARG DEBIAN_FRONTEND
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# Install OpenVino Runtime and Dev library
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COPY requirements-ov.txt /requirements-ov.txt
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RUN apt-get -qq update \
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&& apt-get -qq install -y wget python3 python3-distutils \
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&& wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
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&& python3 get-pip.py "pip" \
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&& pip install -r /requirements-ov.txt
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# Get OpenVino Model
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RUN mkdir /models \
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&& cd /models && omz_downloader --name ssdlite_mobilenet_v2 \
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&& cd /models && omz_converter --name ssdlite_mobilenet_v2 --precision FP16
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# libUSB - No Udev
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FROM wget as libusb-build
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ARG TARGETARCH
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ARG DEBIAN_FRONTEND
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# Build libUSB without udev. Needed for Openvino NCS2 support
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WORKDIR /opt
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RUN apt-get update && apt-get install -y unzip build-essential automake libtool
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RUN wget -q https://github.com/libusb/libusb/archive/v1.0.25.zip -O v1.0.25.zip && \
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unzip v1.0.25.zip && cd libusb-1.0.25 && \
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./bootstrap.sh && \
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./configure --disable-udev --enable-shared && \
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make -j $(nproc --all)
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RUN apt-get update && \
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apt-get install -y --no-install-recommends libusb-1.0-0-dev && \
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rm -rf /var/lib/apt/lists/*
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WORKDIR /opt/libusb-1.0.25/libusb
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RUN /bin/mkdir -p '/usr/local/lib' && \
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/bin/bash ../libtool --mode=install /usr/bin/install -c libusb-1.0.la '/usr/local/lib' && \
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/bin/mkdir -p '/usr/local/include/libusb-1.0' && \
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/usr/bin/install -c -m 644 libusb.h '/usr/local/include/libusb-1.0' && \
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/bin/mkdir -p '/usr/local/lib/pkgconfig' && \
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cd /opt/libusb-1.0.25/ && \
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/usr/bin/install -c -m 644 libusb-1.0.pc '/usr/local/lib/pkgconfig' && \
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ldconfig
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FROM wget AS models
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@ -31,6 +78,10 @@ FROM wget AS models
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RUN wget -qO edgetpu_model.tflite https://github.com/google-coral/test_data/raw/release-frogfish/ssdlite_mobiledet_coco_qat_postprocess_edgetpu.tflite
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RUN wget -qO cpu_model.tflite https://github.com/google-coral/test_data/raw/release-frogfish/ssdlite_mobiledet_coco_qat_postprocess.tflite
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COPY labelmap.txt .
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# Copy OpenVino model
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COPY --from=ov-converter /models/public/ssdlite_mobilenet_v2/FP16 openvino-model
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RUN wget -q https://github.com/openvinotoolkit/open_model_zoo/raw/master/data/dataset_classes/coco_91cl_bkgr.txt -O openvino-model/coco_91cl_bkgr.txt
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FROM wget AS s6-overlay
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@ -85,6 +136,7 @@ RUN pip3 wheel --wheel-dir=/wheels -r requirements-wheels.txt
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FROM scratch AS deps-rootfs
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COPY --from=nginx /usr/local/nginx/ /usr/local/nginx/
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COPY --from=go2rtc /rootfs/ /
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COPY --from=libusb-build /usr/local/lib /usr/local/lib
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COPY --from=s6-overlay /rootfs/ /
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COPY --from=models /rootfs/ /
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COPY docker/rootfs/ /
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@ -112,6 +164,8 @@ RUN --mount=type=bind,from=wheels,source=/wheels,target=/deps/wheels \
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COPY --from=deps-rootfs / /
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RUN ldconfig
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EXPOSE 5000
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EXPOSE 1935
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EXPOSE 8554
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@ -52,7 +52,9 @@ if [[ "${TARGETARCH}" == "amd64" ]]; then
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# Use debian testing repo only for hwaccel packages
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echo 'deb http://deb.debian.org/debian testing main non-free' >/etc/apt/sources.list.d/debian-testing.list
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apt-get -qq update
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# intel-opencl-icd specifically for GPU support in OpenVino
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apt-get -qq install --no-install-recommends --no-install-suggests -y \
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intel-opencl-icd \
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mesa-va-drivers libva-drm2 intel-media-va-driver-non-free i965-va-driver libmfx1 radeontop intel-gpu-tools
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rm -f /etc/apt/sources.list.d/debian-testing.list
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fi
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@ -77,3 +77,64 @@ 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`, `MYRIAD`, 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 is supported on 6th Gen Intel platforms (Skylake) and newer. A supported Intel platform is required to use the GPU device with OpenVINO. The `MYRIAD` device may be run on any platform, including Arm devices. For detailed system requirements, see [OpenVINO System Requirements](https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/system-requirements.html)
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#### Intel NCS2 VPU and Myriad X Setup
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Intel produces a neural net inference accelleration chip called Myriad X. This chip was sold in their Neural Compute Stick 2 (NCS2) which has been discontinued. If intending to use the MYRIAD device for accelleration, additional setup is required to pass through the USB device. The host needs a udev rule installed to handle the NCS2 device.
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```bash
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sudo usermod -a -G users "$(whoami)"
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cat <<EOF > 97-myriad-usbboot.rules
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SUBSYSTEM=="usb", ATTRS{idProduct}=="2485", ATTRS{idVendor}=="03e7", GROUP="users", MODE="0666", ENV{ID_MM_DEVICE_IGNORE}="1"
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SUBSYSTEM=="usb", ATTRS{idProduct}=="f63b", ATTRS{idVendor}=="03e7", GROUP="users", MODE="0666", ENV{ID_MM_DEVICE_IGNORE}="1"
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EOF
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sudo cp 97-myriad-usbboot.rules /etc/udev/rules.d/
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sudo udevadm control --reload-rules
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sudo udevadm trigger
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```
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Additionally, the Frigate docker container needs to run with the following configuration:
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```bash
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--device-cgroup-rule='c 189:\* rmw' -v /dev/bus/usb:/dev/bus/usb
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```
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or in your compose file:
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```yml
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device_cgroup_rules:
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- 'c 189:* rmw'
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volumes:
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- /dev/bus/usb:/dev/bus/usb
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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: nhwc
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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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# 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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@ -104,7 +104,7 @@ model:
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input_pixel_format: rgb
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# Optional: Object detection model input tensor format
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# Valid values are nhwc or nchw (default: shown below)
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input_tensor: "nhwc"
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input_tensor: nhwc
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# Optional: Label name modifications. These are merged into the standard labelmap.
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labelmap:
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2: vehicle
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@ -54,6 +54,7 @@ class FrigateBaseModel(BaseModel):
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class DetectorTypeEnum(str, Enum):
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edgetpu = "edgetpu"
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openvino = "openvino"
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cpu = "cpu"
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54
frigate/detectors/openvino.py
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54
frigate/detectors/openvino.py
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@ -0,0 +1,54 @@
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import logging
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import numpy as np
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import openvino.runtime as ov
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from frigate.detectors.detection_api import DetectionApi
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logger = logging.getLogger(__name__)
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class OvDetector(DetectionApi):
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def __init__(self, det_device=None, model_config=None, num_threads=1):
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self.ov_core = ov.Core()
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self.ov_model = self.ov_core.read_model(model_config.path)
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self.interpreter = self.ov_core.compile_model(
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model=self.ov_model, device_name=det_device
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)
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logger.info(f"Model Input Shape: {self.interpreter.input(0).shape}")
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self.output_indexes = 0
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while True:
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try:
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tensor_shape = self.interpreter.output(self.output_indexes).shape
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logger.info(f"Model Output-{self.output_indexes} Shape: {tensor_shape}")
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self.output_indexes += 1
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except:
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logger.info(f"Model has {self.output_indexes} Output Tensors")
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break
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def detect_raw(self, tensor_input):
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infer_request = self.interpreter.create_infer_request()
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infer_request.infer([tensor_input])
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results = infer_request.get_output_tensor()
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detections = np.zeros((20, 6), np.float32)
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i = 0
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for object_detected in results.data[0, 0, :]:
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if object_detected[0] != -1:
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logger.debug(object_detected)
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if object_detected[2] < 0.1 or i == 20:
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break
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detections[i] = [
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object_detected[1], # Label ID
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float(object_detected[2]), # Confidence
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object_detected[4], # y_min
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object_detected[3], # x_min
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object_detected[6], # y_max
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object_detected[5], # x_max
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]
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i += 1
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return detections
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@ -12,6 +12,7 @@ from setproctitle import setproctitle
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from frigate.config import DetectorTypeEnum, InputTensorEnum
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from frigate.detectors.edgetpu_tfl import EdgeTpuTfl
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from frigate.detectors.openvino import OvDetector
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from frigate.detectors.cpu_tfl import CpuTfl
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from frigate.util import EventsPerSecond, SharedMemoryFrameManager, listen, load_labels
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@ -57,6 +58,10 @@ class LocalObjectDetector(ObjectDetector):
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self.detect_api = EdgeTpuTfl(
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det_device=det_device, model_config=model_config
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)
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elif det_type == DetectorTypeEnum.openvino:
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self.detect_api = OvDetector(
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det_device=det_device, model_config=model_config
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)
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else:
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logger.warning(
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"CPU detectors are not recommended and should only be used for testing or for trial purposes."
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3
requirements-ov.txt
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3
requirements-ov.txt
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numpy == 1.19.*
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openvino == 2022.*
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openvino-dev[tensorflow2] == 2022.*
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@ -18,3 +18,7 @@ scipy == 1.8.*
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setproctitle == 1.2.*
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ws4py == 0.5.*
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zeroconf == 0.39.4
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# Openvino Library - Custom built with MYRIAD support
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openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.2.0/openvino-2022.2.0-000-cp39-cp39-manylinux_2_31_x86_64.whl; platform_machine == 'x86_64'
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openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.2.0/openvino-2022.2.0-000-cp39-cp39-linux_aarch64.whl; platform_machine == 'aarch64'
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openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.2.0/openvino-2022.2.0-000-cp39-cp39-linux_armv7l.whl; platform_machine == 'armv7l'
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