aiy.vision.inference¶
An inference engine that communicates with the Vision Bonnet from the Raspberry Pi side.
It can be used to load a model, analyze local image or image from camera shot. It automatically unload the model once the associated object is deleted. See image_classification.py and object_recognition.py as examples on how to use this API.
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class
aiy.vision.inference.
CameraInference
(descriptor, params=None, sparse_configs=None)¶ Bases:
object
Helper class to run camera inference.
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close
()¶
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count
¶
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engine
¶
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rate
¶
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run
(count=None)¶
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class
aiy.vision.inference.
FirmwareVersion
(major, minor)¶ Bases:
tuple
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major
¶ Alias for field number 0
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minor
¶ Alias for field number 1
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class
aiy.vision.inference.
FromSparseTensorConfig
(logical_shape, tensor_name, squeeze_dims)¶ Bases:
tuple
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logical_shape
¶ Alias for field number 0
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squeeze_dims
¶ Alias for field number 2
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tensor_name
¶ Alias for field number 1
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class
aiy.vision.inference.
ImageInference
(descriptor)¶ Bases:
object
Helper class to run image inference.
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close
()¶
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engine
¶
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run
(image, params=None, sparse_configs=None)¶
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class
aiy.vision.inference.
InferenceEngine
¶ Bases:
object
Class to access InferenceEngine on VisionBonnet board.
Inference result has the following format:
message InferenceResult { string model_name; // Name of the model to run inference on. int32 width; // Input image/frame width. int32 height; // Input image/frame height. Rectangle window; // Window inside width x height image/frame. int32 duration_ms; // Inference duration. map<string, FloatTensor> tensors; // Output tensors. message Frame { int32 index; // Frame number. int64 timestamp_us; // Frame timestamp. } Frame frame; // Frame-specific inference data. }
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camera_inference
()¶ Returns the latest inference result from VisionBonnet.
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close
()¶
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get_camera_state
()¶ Returns current camera state.
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get_firmware_info
()¶ Returns firmware version as (major, minor) tuple.
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get_inference_state
()¶ Returns inference state.
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get_system_info
()¶ Returns system information: uptime, memory usage, temperature.
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image_inference
(model_name, image, params=None, sparse_configs=None)¶ Runs inference on image using model identified by model_name.
Parameters: - model_name – string, unique identifier used to refer a model.
- image – PIL.Image,
- params – dict, additional parameters to run inference
Returns: pb2.Response.InferenceResult
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load_model
(descriptor)¶ Loads model on VisionBonnet.
Parameters: descriptor – ModelDescriptor, meta info that defines model name, where to get the model and etc. Returns: Model identifier.
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reset
()¶
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start_camera_inference
(model_name, params=None, sparse_configs=None)¶ Starts inference running on VisionBonnet.
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stop_camera_inference
()¶ Stops inference running on VisionBonnet.
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unload_model
(model_name)¶ Deletes model on VisionBonnet.
Parameters: model_name – string, unique identifier used to refer a model.
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