mirror of
https://github.com/blakeblackshear/frigate.git
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clean up detectors section and i18n
This commit is contained in:
Josh Hawkins
@@ -287,155 +287,791 @@
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"label": "Detector hardware",
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"description": "Configuration for object detectors (CPU, GPU, ONNX backends) and any detector-specific model settings.",
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"type": {
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"label": "Type"
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},
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"model": {
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"label": "Detector specific model configuration",
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"description": "Detector-specific model configuration options (path, input size, etc.).",
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"path": {
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"label": "Custom Object detection model path",
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"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
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},
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"labelmap_path": {
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"label": "Label map for custom object detector",
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"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
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},
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"width": {
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"label": "Object detection model input width",
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"description": "Width of the model input tensor in pixels."
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},
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"height": {
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"label": "Object detection model input height",
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"description": "Height of the model input tensor in pixels."
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},
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"labelmap": {
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"label": "Labelmap customization",
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"description": "Overrides or remapping entries to merge into the standard labelmap."
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},
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"attributes_map": {
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"label": "Map of object labels to their attribute labels",
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"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
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},
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"input_tensor": {
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"label": "Model Input Tensor Shape",
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"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
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},
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"input_pixel_format": {
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"label": "Model Input Pixel Color Format",
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"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
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},
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"input_dtype": {
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"label": "Model Input D Type",
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"description": "Data type of the model input tensor (for example 'float32')."
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},
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"model_type": {
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"label": "Object Detection Model Type",
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"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
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}
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},
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"model_path": {
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"label": "Detector specific model path",
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"description": "File path to the detector model binary if required by the chosen detector."
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},
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"num_threads": {
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"label": "Number of detection threads",
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"description": "The number of threads used for CPU-based inference."
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},
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"api_url": {
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"label": "DeepStack API URL",
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"description": "The URL of the DeepStack API."
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},
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"api_timeout": {
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"label": "DeepStack API timeout (in seconds)",
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"description": "Maximum time allowed for a DeepStack API request."
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},
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"api_key": {
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"label": "DeepStack API key (if required)",
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"description": "Optional API key for authenticated DeepStack services."
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},
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"location": {
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"label": "Inference Location",
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"description": "Location of the DeGirim inference engine (e.g. '@cloud', '127.0.0.1')."
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},
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"zoo": {
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"label": "Model Zoo",
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"description": "Path or URL to the DeGirum model zoo."
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},
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"token": {
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"label": "DeGirum Cloud Token",
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"description": "Token for DeGirum Cloud access."
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},
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"device": {
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"label": "GPU Device Index",
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"description": "The GPU device index to use."
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},
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"num_cores": {
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"label": "Number of NPU cores to use.",
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"description": "The number of NPU cores to use (0 for auto)."
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},
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"endpoint": {
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"label": "ZMQ IPC endpoint",
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"description": "The ZMQ endpoint to connect to."
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},
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"request_timeout_ms": {
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"label": "ZMQ request timeout in milliseconds",
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"description": "Timeout for ZMQ requests in milliseconds."
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},
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"linger_ms": {
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"label": "ZMQ socket linger in milliseconds",
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"description": "Socket linger period in milliseconds."
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"label": "Detector Type",
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"description": "Type of detector to use for object detection (for example 'cpu', 'edgetpu', 'openvino')."
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},
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"cpu": {
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"label": "CPU",
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"description": "CPU TFLite detector that runs TensorFlow Lite models on the host CPU without hardware acceleration. Not recommended."
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"description": "CPU TFLite detector that runs TensorFlow Lite models on the host CPU without hardware acceleration. Not recommended.",
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"type": {
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"label": "Type"
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},
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"model": {
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"label": "Detector specific model configuration",
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"description": "Detector-specific model configuration options (path, input size, etc.).",
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"path": {
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"label": "Custom Object detection model path",
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"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
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},
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"labelmap_path": {
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"label": "Label map for custom object detector",
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"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
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},
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"width": {
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"label": "Object detection model input width",
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"description": "Width of the model input tensor in pixels."
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},
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"height": {
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"label": "Object detection model input height",
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"description": "Height of the model input tensor in pixels."
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},
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"labelmap": {
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"label": "Labelmap customization",
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"description": "Overrides or remapping entries to merge into the standard labelmap."
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},
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"attributes_map": {
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"label": "Map of object labels to their attribute labels",
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"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
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},
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"input_tensor": {
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"label": "Model Input Tensor Shape",
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"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
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},
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"input_pixel_format": {
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"label": "Model Input Pixel Color Format",
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"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
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},
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"input_dtype": {
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"label": "Model Input D Type",
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"description": "Data type of the model input tensor (for example 'float32')."
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},
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"model_type": {
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"label": "Object Detection Model Type",
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"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
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}
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},
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"model_path": {
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"label": "Detector specific model path",
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"description": "File path to the detector model binary if required by the chosen detector."
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},
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"num_threads": {
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"label": "Number of detection threads",
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"description": "The number of threads used for CPU-based inference."
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}
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},
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"deepstack": {
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"label": "DeepStack",
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"description": "DeepStack/CodeProject.AI detector that sends images to a remote DeepStack HTTP API for inference. Not recommended."
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"description": "DeepStack/CodeProject.AI detector that sends images to a remote DeepStack HTTP API for inference. Not recommended.",
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"type": {
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"label": "Type"
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},
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"model": {
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"label": "Detector specific model configuration",
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"description": "Detector-specific model configuration options (path, input size, etc.).",
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"path": {
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"label": "Custom Object detection model path",
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"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
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},
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"labelmap_path": {
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"label": "Label map for custom object detector",
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"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
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},
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"width": {
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"label": "Object detection model input width",
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"description": "Width of the model input tensor in pixels."
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},
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"height": {
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"label": "Object detection model input height",
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"description": "Height of the model input tensor in pixels."
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},
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"labelmap": {
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"label": "Labelmap customization",
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"description": "Overrides or remapping entries to merge into the standard labelmap."
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},
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"attributes_map": {
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"label": "Map of object labels to their attribute labels",
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"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
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},
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"input_tensor": {
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"label": "Model Input Tensor Shape",
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"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
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},
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"input_pixel_format": {
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"label": "Model Input Pixel Color Format",
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"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
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},
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"input_dtype": {
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"label": "Model Input D Type",
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"description": "Data type of the model input tensor (for example 'float32')."
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},
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"model_type": {
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"label": "Object Detection Model Type",
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"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
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}
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},
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"model_path": {
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"label": "Detector specific model path",
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"description": "File path to the detector model binary if required by the chosen detector."
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},
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"api_url": {
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"label": "DeepStack API URL",
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"description": "The URL of the DeepStack API."
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},
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"api_timeout": {
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"label": "DeepStack API timeout (in seconds)",
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"description": "Maximum time allowed for a DeepStack API request."
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},
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"api_key": {
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"label": "DeepStack API key (if required)",
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"description": "Optional API key for authenticated DeepStack services."
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}
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},
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"degirum": {
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"label": "DeGirum",
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"description": "DeGirum detector for running models via DeGirum cloud or local inference services."
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"description": "DeGirum detector for running models via DeGirum cloud or local inference services.",
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"type": {
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"label": "Type"
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},
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"model": {
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"label": "Detector specific model configuration",
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"description": "Detector-specific model configuration options (path, input size, etc.).",
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"path": {
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"label": "Custom Object detection model path",
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"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
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},
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"labelmap_path": {
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"label": "Label map for custom object detector",
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"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
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},
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"width": {
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"label": "Object detection model input width",
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"description": "Width of the model input tensor in pixels."
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},
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"height": {
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"label": "Object detection model input height",
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"description": "Height of the model input tensor in pixels."
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},
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"labelmap": {
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"label": "Labelmap customization",
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"description": "Overrides or remapping entries to merge into the standard labelmap."
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},
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"attributes_map": {
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"label": "Map of object labels to their attribute labels",
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"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
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},
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"input_tensor": {
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"label": "Model Input Tensor Shape",
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"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
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},
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"input_pixel_format": {
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"label": "Model Input Pixel Color Format",
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"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
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},
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"input_dtype": {
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"label": "Model Input D Type",
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"description": "Data type of the model input tensor (for example 'float32')."
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},
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"model_type": {
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"label": "Object Detection Model Type",
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"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
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}
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},
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"model_path": {
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"label": "Detector specific model path",
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"description": "File path to the detector model binary if required by the chosen detector."
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},
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"location": {
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"label": "Inference Location",
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"description": "Location of the DeGirim inference engine (e.g. '@cloud', '127.0.0.1')."
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},
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"zoo": {
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"label": "Model Zoo",
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"description": "Path or URL to the DeGirum model zoo."
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},
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"token": {
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"label": "DeGirum Cloud Token",
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"description": "Token for DeGirum Cloud access."
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}
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},
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"edgetpu": {
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"label": "EdgeTPU",
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"description": "EdgeTPU detector that runs TensorFlow Lite models compiled for Coral EdgeTPU using the EdgeTPU delegate."
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"description": "EdgeTPU detector that runs TensorFlow Lite models compiled for Coral EdgeTPU using the EdgeTPU delegate.",
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"type": {
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"label": "Type"
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},
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"model": {
|
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"label": "Detector specific model configuration",
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"description": "Detector-specific model configuration options (path, input size, etc.).",
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"path": {
|
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"label": "Custom Object detection model path",
|
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"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
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},
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"labelmap_path": {
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"label": "Label map for custom object detector",
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"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
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},
|
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"width": {
|
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"label": "Object detection model input width",
|
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"description": "Width of the model input tensor in pixels."
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},
|
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"height": {
|
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"label": "Object detection model input height",
|
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"description": "Height of the model input tensor in pixels."
|
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},
|
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"labelmap": {
|
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"label": "Labelmap customization",
|
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"description": "Overrides or remapping entries to merge into the standard labelmap."
|
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},
|
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"attributes_map": {
|
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"label": "Map of object labels to their attribute labels",
|
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"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
|
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},
|
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"input_tensor": {
|
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"label": "Model Input Tensor Shape",
|
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"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
|
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},
|
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"input_pixel_format": {
|
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"label": "Model Input Pixel Color Format",
|
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"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
|
||||
},
|
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"input_dtype": {
|
||||
"label": "Model Input D Type",
|
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"description": "Data type of the model input tensor (for example 'float32')."
|
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},
|
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"model_type": {
|
||||
"label": "Object Detection Model Type",
|
||||
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
|
||||
}
|
||||
},
|
||||
"model_path": {
|
||||
"label": "Detector specific model path",
|
||||
"description": "File path to the detector model binary if required by the chosen detector."
|
||||
},
|
||||
"device": {
|
||||
"label": "Device Type",
|
||||
"description": "The device to use for EdgeTPU inference (e.g. 'usb', 'pci')."
|
||||
}
|
||||
},
|
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"hailo8l": {
|
||||
"label": "Hailo-8/Hailo-8L",
|
||||
"description": "Hailo-8/Hailo-8L detector using HEF models and the HailoRT SDK for inference on Hailo hardware."
|
||||
"description": "Hailo-8/Hailo-8L detector using HEF models and the HailoRT SDK for inference on Hailo hardware.",
|
||||
"type": {
|
||||
"label": "Type"
|
||||
},
|
||||
"model": {
|
||||
"label": "Detector specific model configuration",
|
||||
"description": "Detector-specific model configuration options (path, input size, etc.).",
|
||||
"path": {
|
||||
"label": "Custom Object detection model path",
|
||||
"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
|
||||
},
|
||||
"labelmap_path": {
|
||||
"label": "Label map for custom object detector",
|
||||
"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
|
||||
},
|
||||
"width": {
|
||||
"label": "Object detection model input width",
|
||||
"description": "Width of the model input tensor in pixels."
|
||||
},
|
||||
"height": {
|
||||
"label": "Object detection model input height",
|
||||
"description": "Height of the model input tensor in pixels."
|
||||
},
|
||||
"labelmap": {
|
||||
"label": "Labelmap customization",
|
||||
"description": "Overrides or remapping entries to merge into the standard labelmap."
|
||||
},
|
||||
"attributes_map": {
|
||||
"label": "Map of object labels to their attribute labels",
|
||||
"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
|
||||
},
|
||||
"input_tensor": {
|
||||
"label": "Model Input Tensor Shape",
|
||||
"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
|
||||
},
|
||||
"input_pixel_format": {
|
||||
"label": "Model Input Pixel Color Format",
|
||||
"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
|
||||
},
|
||||
"input_dtype": {
|
||||
"label": "Model Input D Type",
|
||||
"description": "Data type of the model input tensor (for example 'float32')."
|
||||
},
|
||||
"model_type": {
|
||||
"label": "Object Detection Model Type",
|
||||
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
|
||||
}
|
||||
},
|
||||
"model_path": {
|
||||
"label": "Detector specific model path",
|
||||
"description": "File path to the detector model binary if required by the chosen detector."
|
||||
},
|
||||
"device": {
|
||||
"label": "Device Type",
|
||||
"description": "The device to use for Hailo inference (e.g. 'PCIe', 'M.2')."
|
||||
}
|
||||
},
|
||||
"memryx": {
|
||||
"label": "MemryX",
|
||||
"description": "MemryX MX3 detector that runs compiled DFP models on MemryX accelerators."
|
||||
"description": "MemryX MX3 detector that runs compiled DFP models on MemryX accelerators.",
|
||||
"type": {
|
||||
"label": "Type"
|
||||
},
|
||||
"model": {
|
||||
"label": "Detector specific model configuration",
|
||||
"description": "Detector-specific model configuration options (path, input size, etc.).",
|
||||
"path": {
|
||||
"label": "Custom Object detection model path",
|
||||
"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
|
||||
},
|
||||
"labelmap_path": {
|
||||
"label": "Label map for custom object detector",
|
||||
"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
|
||||
},
|
||||
"width": {
|
||||
"label": "Object detection model input width",
|
||||
"description": "Width of the model input tensor in pixels."
|
||||
},
|
||||
"height": {
|
||||
"label": "Object detection model input height",
|
||||
"description": "Height of the model input tensor in pixels."
|
||||
},
|
||||
"labelmap": {
|
||||
"label": "Labelmap customization",
|
||||
"description": "Overrides or remapping entries to merge into the standard labelmap."
|
||||
},
|
||||
"attributes_map": {
|
||||
"label": "Map of object labels to their attribute labels",
|
||||
"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
|
||||
},
|
||||
"input_tensor": {
|
||||
"label": "Model Input Tensor Shape",
|
||||
"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
|
||||
},
|
||||
"input_pixel_format": {
|
||||
"label": "Model Input Pixel Color Format",
|
||||
"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
|
||||
},
|
||||
"input_dtype": {
|
||||
"label": "Model Input D Type",
|
||||
"description": "Data type of the model input tensor (for example 'float32')."
|
||||
},
|
||||
"model_type": {
|
||||
"label": "Object Detection Model Type",
|
||||
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
|
||||
}
|
||||
},
|
||||
"model_path": {
|
||||
"label": "Detector specific model path",
|
||||
"description": "File path to the detector model binary if required by the chosen detector."
|
||||
},
|
||||
"device": {
|
||||
"label": "Device Path",
|
||||
"description": "The device to use for MemryX inference (e.g. 'PCIe')."
|
||||
}
|
||||
},
|
||||
"onnx": {
|
||||
"label": "ONNX",
|
||||
"description": "ONNX detector for running ONNX models; will use available acceleration backends (CUDA/ROCm/OpenVINO) when available."
|
||||
"description": "ONNX detector for running ONNX models; will use available acceleration backends (CUDA/ROCm/OpenVINO) when available.",
|
||||
"type": {
|
||||
"label": "Type"
|
||||
},
|
||||
"model": {
|
||||
"label": "Detector specific model configuration",
|
||||
"description": "Detector-specific model configuration options (path, input size, etc.).",
|
||||
"path": {
|
||||
"label": "Custom Object detection model path",
|
||||
"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
|
||||
},
|
||||
"labelmap_path": {
|
||||
"label": "Label map for custom object detector",
|
||||
"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
|
||||
},
|
||||
"width": {
|
||||
"label": "Object detection model input width",
|
||||
"description": "Width of the model input tensor in pixels."
|
||||
},
|
||||
"height": {
|
||||
"label": "Object detection model input height",
|
||||
"description": "Height of the model input tensor in pixels."
|
||||
},
|
||||
"labelmap": {
|
||||
"label": "Labelmap customization",
|
||||
"description": "Overrides or remapping entries to merge into the standard labelmap."
|
||||
},
|
||||
"attributes_map": {
|
||||
"label": "Map of object labels to their attribute labels",
|
||||
"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
|
||||
},
|
||||
"input_tensor": {
|
||||
"label": "Model Input Tensor Shape",
|
||||
"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
|
||||
},
|
||||
"input_pixel_format": {
|
||||
"label": "Model Input Pixel Color Format",
|
||||
"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
|
||||
},
|
||||
"input_dtype": {
|
||||
"label": "Model Input D Type",
|
||||
"description": "Data type of the model input tensor (for example 'float32')."
|
||||
},
|
||||
"model_type": {
|
||||
"label": "Object Detection Model Type",
|
||||
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
|
||||
}
|
||||
},
|
||||
"model_path": {
|
||||
"label": "Detector specific model path",
|
||||
"description": "File path to the detector model binary if required by the chosen detector."
|
||||
},
|
||||
"device": {
|
||||
"label": "Device Type",
|
||||
"description": "The device to use for ONNX inference (e.g. 'AUTO', 'CPU', 'GPU')."
|
||||
}
|
||||
},
|
||||
"openvino": {
|
||||
"label": "OpenVINO",
|
||||
"description": "OpenVINO detector for AMD and Intel CPUs, Intel GPUs and Intel VPU hardware."
|
||||
"description": "OpenVINO detector for AMD and Intel CPUs, Intel GPUs and Intel VPU hardware.",
|
||||
"type": {
|
||||
"label": "Type"
|
||||
},
|
||||
"model": {
|
||||
"label": "Detector specific model configuration",
|
||||
"description": "Detector-specific model configuration options (path, input size, etc.).",
|
||||
"path": {
|
||||
"label": "Custom Object detection model path",
|
||||
"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
|
||||
},
|
||||
"labelmap_path": {
|
||||
"label": "Label map for custom object detector",
|
||||
"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
|
||||
},
|
||||
"width": {
|
||||
"label": "Object detection model input width",
|
||||
"description": "Width of the model input tensor in pixels."
|
||||
},
|
||||
"height": {
|
||||
"label": "Object detection model input height",
|
||||
"description": "Height of the model input tensor in pixels."
|
||||
},
|
||||
"labelmap": {
|
||||
"label": "Labelmap customization",
|
||||
"description": "Overrides or remapping entries to merge into the standard labelmap."
|
||||
},
|
||||
"attributes_map": {
|
||||
"label": "Map of object labels to their attribute labels",
|
||||
"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
|
||||
},
|
||||
"input_tensor": {
|
||||
"label": "Model Input Tensor Shape",
|
||||
"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
|
||||
},
|
||||
"input_pixel_format": {
|
||||
"label": "Model Input Pixel Color Format",
|
||||
"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
|
||||
},
|
||||
"input_dtype": {
|
||||
"label": "Model Input D Type",
|
||||
"description": "Data type of the model input tensor (for example 'float32')."
|
||||
},
|
||||
"model_type": {
|
||||
"label": "Object Detection Model Type",
|
||||
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
|
||||
}
|
||||
},
|
||||
"model_path": {
|
||||
"label": "Detector specific model path",
|
||||
"description": "File path to the detector model binary if required by the chosen detector."
|
||||
},
|
||||
"device": {
|
||||
"label": "Device Type",
|
||||
"description": "The device to use for OpenVINO inference (e.g. 'CPU', 'GPU', 'NPU')."
|
||||
}
|
||||
},
|
||||
"rknn": {
|
||||
"label": "RKNN",
|
||||
"description": "RKNN detector for Rockchip NPUs; runs compiled RKNN models on Rockchip hardware."
|
||||
"description": "RKNN detector for Rockchip NPUs; runs compiled RKNN models on Rockchip hardware.",
|
||||
"type": {
|
||||
"label": "Type"
|
||||
},
|
||||
"model": {
|
||||
"label": "Detector specific model configuration",
|
||||
"description": "Detector-specific model configuration options (path, input size, etc.).",
|
||||
"path": {
|
||||
"label": "Custom Object detection model path",
|
||||
"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
|
||||
},
|
||||
"labelmap_path": {
|
||||
"label": "Label map for custom object detector",
|
||||
"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
|
||||
},
|
||||
"width": {
|
||||
"label": "Object detection model input width",
|
||||
"description": "Width of the model input tensor in pixels."
|
||||
},
|
||||
"height": {
|
||||
"label": "Object detection model input height",
|
||||
"description": "Height of the model input tensor in pixels."
|
||||
},
|
||||
"labelmap": {
|
||||
"label": "Labelmap customization",
|
||||
"description": "Overrides or remapping entries to merge into the standard labelmap."
|
||||
},
|
||||
"attributes_map": {
|
||||
"label": "Map of object labels to their attribute labels",
|
||||
"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
|
||||
},
|
||||
"input_tensor": {
|
||||
"label": "Model Input Tensor Shape",
|
||||
"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
|
||||
},
|
||||
"input_pixel_format": {
|
||||
"label": "Model Input Pixel Color Format",
|
||||
"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
|
||||
},
|
||||
"input_dtype": {
|
||||
"label": "Model Input D Type",
|
||||
"description": "Data type of the model input tensor (for example 'float32')."
|
||||
},
|
||||
"model_type": {
|
||||
"label": "Object Detection Model Type",
|
||||
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
|
||||
}
|
||||
},
|
||||
"model_path": {
|
||||
"label": "Detector specific model path",
|
||||
"description": "File path to the detector model binary if required by the chosen detector."
|
||||
},
|
||||
"num_cores": {
|
||||
"label": "Number of NPU cores to use.",
|
||||
"description": "The number of NPU cores to use (0 for auto)."
|
||||
}
|
||||
},
|
||||
"synaptics": {
|
||||
"label": "Synaptics",
|
||||
"description": "Synaptics NPU detector for models in .synap format using the Synap SDK on Synaptics hardware."
|
||||
"description": "Synaptics NPU detector for models in .synap format using the Synap SDK on Synaptics hardware.",
|
||||
"type": {
|
||||
"label": "Type"
|
||||
},
|
||||
"model": {
|
||||
"label": "Detector specific model configuration",
|
||||
"description": "Detector-specific model configuration options (path, input size, etc.).",
|
||||
"path": {
|
||||
"label": "Custom Object detection model path",
|
||||
"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
|
||||
},
|
||||
"labelmap_path": {
|
||||
"label": "Label map for custom object detector",
|
||||
"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
|
||||
},
|
||||
"width": {
|
||||
"label": "Object detection model input width",
|
||||
"description": "Width of the model input tensor in pixels."
|
||||
},
|
||||
"height": {
|
||||
"label": "Object detection model input height",
|
||||
"description": "Height of the model input tensor in pixels."
|
||||
},
|
||||
"labelmap": {
|
||||
"label": "Labelmap customization",
|
||||
"description": "Overrides or remapping entries to merge into the standard labelmap."
|
||||
},
|
||||
"attributes_map": {
|
||||
"label": "Map of object labels to their attribute labels",
|
||||
"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
|
||||
},
|
||||
"input_tensor": {
|
||||
"label": "Model Input Tensor Shape",
|
||||
"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
|
||||
},
|
||||
"input_pixel_format": {
|
||||
"label": "Model Input Pixel Color Format",
|
||||
"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
|
||||
},
|
||||
"input_dtype": {
|
||||
"label": "Model Input D Type",
|
||||
"description": "Data type of the model input tensor (for example 'float32')."
|
||||
},
|
||||
"model_type": {
|
||||
"label": "Object Detection Model Type",
|
||||
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
|
||||
}
|
||||
},
|
||||
"model_path": {
|
||||
"label": "Detector specific model path",
|
||||
"description": "File path to the detector model binary if required by the chosen detector."
|
||||
}
|
||||
},
|
||||
"teflon_tfl": {
|
||||
"label": "Teflon",
|
||||
"description": "Teflon delegate detector for TFLite using Mesa Teflon delegate library to accelerate inference on supported GPUs."
|
||||
"description": "Teflon delegate detector for TFLite using Mesa Teflon delegate library to accelerate inference on supported GPUs.",
|
||||
"type": {
|
||||
"label": "Type"
|
||||
},
|
||||
"model": {
|
||||
"label": "Detector specific model configuration",
|
||||
"description": "Detector-specific model configuration options (path, input size, etc.).",
|
||||
"path": {
|
||||
"label": "Custom Object detection model path",
|
||||
"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
|
||||
},
|
||||
"labelmap_path": {
|
||||
"label": "Label map for custom object detector",
|
||||
"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
|
||||
},
|
||||
"width": {
|
||||
"label": "Object detection model input width",
|
||||
"description": "Width of the model input tensor in pixels."
|
||||
},
|
||||
"height": {
|
||||
"label": "Object detection model input height",
|
||||
"description": "Height of the model input tensor in pixels."
|
||||
},
|
||||
"labelmap": {
|
||||
"label": "Labelmap customization",
|
||||
"description": "Overrides or remapping entries to merge into the standard labelmap."
|
||||
},
|
||||
"attributes_map": {
|
||||
"label": "Map of object labels to their attribute labels",
|
||||
"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
|
||||
},
|
||||
"input_tensor": {
|
||||
"label": "Model Input Tensor Shape",
|
||||
"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
|
||||
},
|
||||
"input_pixel_format": {
|
||||
"label": "Model Input Pixel Color Format",
|
||||
"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
|
||||
},
|
||||
"input_dtype": {
|
||||
"label": "Model Input D Type",
|
||||
"description": "Data type of the model input tensor (for example 'float32')."
|
||||
},
|
||||
"model_type": {
|
||||
"label": "Object Detection Model Type",
|
||||
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
|
||||
}
|
||||
},
|
||||
"model_path": {
|
||||
"label": "Detector specific model path",
|
||||
"description": "File path to the detector model binary if required by the chosen detector."
|
||||
}
|
||||
},
|
||||
"tensorrt": {
|
||||
"label": "TensorRT",
|
||||
"description": "TensorRT detector for Nvidia Jetson devices using serialized TensorRT engines for accelerated inference."
|
||||
"description": "TensorRT detector for Nvidia Jetson devices using serialized TensorRT engines for accelerated inference.",
|
||||
"type": {
|
||||
"label": "Type"
|
||||
},
|
||||
"model": {
|
||||
"label": "Detector specific model configuration",
|
||||
"description": "Detector-specific model configuration options (path, input size, etc.).",
|
||||
"path": {
|
||||
"label": "Custom Object detection model path",
|
||||
"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
|
||||
},
|
||||
"labelmap_path": {
|
||||
"label": "Label map for custom object detector",
|
||||
"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
|
||||
},
|
||||
"width": {
|
||||
"label": "Object detection model input width",
|
||||
"description": "Width of the model input tensor in pixels."
|
||||
},
|
||||
"height": {
|
||||
"label": "Object detection model input height",
|
||||
"description": "Height of the model input tensor in pixels."
|
||||
},
|
||||
"labelmap": {
|
||||
"label": "Labelmap customization",
|
||||
"description": "Overrides or remapping entries to merge into the standard labelmap."
|
||||
},
|
||||
"attributes_map": {
|
||||
"label": "Map of object labels to their attribute labels",
|
||||
"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
|
||||
},
|
||||
"input_tensor": {
|
||||
"label": "Model Input Tensor Shape",
|
||||
"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
|
||||
},
|
||||
"input_pixel_format": {
|
||||
"label": "Model Input Pixel Color Format",
|
||||
"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
|
||||
},
|
||||
"input_dtype": {
|
||||
"label": "Model Input D Type",
|
||||
"description": "Data type of the model input tensor (for example 'float32')."
|
||||
},
|
||||
"model_type": {
|
||||
"label": "Object Detection Model Type",
|
||||
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
|
||||
}
|
||||
},
|
||||
"model_path": {
|
||||
"label": "Detector specific model path",
|
||||
"description": "File path to the detector model binary if required by the chosen detector."
|
||||
},
|
||||
"device": {
|
||||
"label": "GPU Device Index",
|
||||
"description": "The GPU device index to use."
|
||||
}
|
||||
},
|
||||
"zmq": {
|
||||
"label": "ZMQ IPC",
|
||||
"description": "ZMQ IPC detector that offloads inference to an external process via a ZeroMQ IPC endpoint."
|
||||
"description": "ZMQ IPC detector that offloads inference to an external process via a ZeroMQ IPC endpoint.",
|
||||
"type": {
|
||||
"label": "Type"
|
||||
},
|
||||
"model": {
|
||||
"label": "Detector specific model configuration",
|
||||
"description": "Detector-specific model configuration options (path, input size, etc.).",
|
||||
"path": {
|
||||
"label": "Custom Object detection model path",
|
||||
"description": "Path to a custom detection model file (or plus://<model_id> for Frigate+ models)."
|
||||
},
|
||||
"labelmap_path": {
|
||||
"label": "Label map for custom object detector",
|
||||
"description": "Path to a labelmap file that maps numeric classes to string labels for the detector."
|
||||
},
|
||||
"width": {
|
||||
"label": "Object detection model input width",
|
||||
"description": "Width of the model input tensor in pixels."
|
||||
},
|
||||
"height": {
|
||||
"label": "Object detection model input height",
|
||||
"description": "Height of the model input tensor in pixels."
|
||||
},
|
||||
"labelmap": {
|
||||
"label": "Labelmap customization",
|
||||
"description": "Overrides or remapping entries to merge into the standard labelmap."
|
||||
},
|
||||
"attributes_map": {
|
||||
"label": "Map of object labels to their attribute labels",
|
||||
"description": "Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate'])."
|
||||
},
|
||||
"input_tensor": {
|
||||
"label": "Model Input Tensor Shape",
|
||||
"description": "Tensor format expected by the model: 'nhwc' or 'nchw'."
|
||||
},
|
||||
"input_pixel_format": {
|
||||
"label": "Model Input Pixel Color Format",
|
||||
"description": "Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'."
|
||||
},
|
||||
"input_dtype": {
|
||||
"label": "Model Input D Type",
|
||||
"description": "Data type of the model input tensor (for example 'float32')."
|
||||
},
|
||||
"model_type": {
|
||||
"label": "Object Detection Model Type",
|
||||
"description": "Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization."
|
||||
}
|
||||
},
|
||||
"model_path": {
|
||||
"label": "Detector specific model path",
|
||||
"description": "File path to the detector model binary if required by the chosen detector."
|
||||
},
|
||||
"endpoint": {
|
||||
"label": "ZMQ IPC endpoint",
|
||||
"description": "The ZMQ endpoint to connect to."
|
||||
},
|
||||
"request_timeout_ms": {
|
||||
"label": "ZMQ request timeout in milliseconds",
|
||||
"description": "Timeout for ZMQ requests in milliseconds."
|
||||
},
|
||||
"linger_ms": {
|
||||
"label": "ZMQ socket linger in milliseconds",
|
||||
"description": "Socket linger period in milliseconds."
|
||||
}
|
||||
}
|
||||
},
|
||||
"model": {
|
||||
|
||||
@@ -1234,6 +1234,14 @@
|
||||
"detect": {
|
||||
"title": "Detection Settings"
|
||||
},
|
||||
"detectors": {
|
||||
"title": "Detector Settings",
|
||||
"singleType": "Only one {{type}} detector is allowed.",
|
||||
"keyRequired": "Detector name is required.",
|
||||
"keyDuplicate": "Detector name already exists.",
|
||||
"noSchema": "No detector schemas are available.",
|
||||
"none": "No detector instances configured."
|
||||
},
|
||||
"record": {
|
||||
"title": "Recording Settings"
|
||||
},
|
||||
|
||||
Reference in New Issue
Block a user