openvino.inference_engine.PreProcessInfo¶
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class
openvino.inference_engine.
PreProcessInfo
¶ This class stores pre-process information for the input
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__init__
()¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__
()Initialize self.
get_number_of_channels
(self)Returns a number of channels to preprocess
init
(self, size_t number_of_channels)Initializes with given number of channels
set_mean_image
(self, Blob mean_image)Sets mean image values if operation is applicable.
set_mean_image_for_channel
(self, …)Sets mean image values if operation is applicable.
Attributes
Color format to be used in on-demand color conversions applied to input before inference
Mean Variant to be applied for input before inference if needed.
Resize Algorithm to be applied for input before inference if needed. .. note::.
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color_format
¶ Color format to be used in on-demand color conversions applied to input before inference
Usage example:
net = ie_core.read_network(model=path_to_xml_file, weights=path_to_bin_file) net.input_info['data'].preprocess_info.color_format = ColorFormat.BGR
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get_number_of_channels
(self)¶ Returns a number of channels to preprocess
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init
(self, size_t number_of_channels)¶ Initializes with given number of channels
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mean_variant
¶ Mean Variant to be applied for input before inference if needed.
Usage example:
net = ie_core.read_network(model=path_to_xml_file, weights=path_to_bin_file) net.input_info['data'].preprocess_info.mean_variant = MeanVariant.MEAN_IMAGE
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resize_algorithm
¶ Resize Algorithm to be applied for input before inference if needed. .. note:
It's need to set your input via the set_blob method.
Usage example:
net = ie_core.read_network(model=path_to_xml_file, weights=path_to_bin_file) net.input_info['data'].preprocess_info.resize_algorithm = ResizeAlgorithm.RESIZE_BILINEAR exec_net = ie_core.load_network(net, 'CPU') tensor_desc = ie.TensorDesc("FP32", [1, 3, image.shape[2], image.shape[3]], "NCHW") img_blob = ie.Blob(tensor_desc, image) request = exec_net.requests[0] request.set_blob('data', img_blob) request.infer()
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set_mean_image
(self, Blob mean_image)¶ Sets mean image values if operation is applicable. Also sets the mean type to MEAN_IMAGE for all channels
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set_mean_image_for_channel
(self, Blob mean_image, size_t channel)¶ Sets mean image values if operation is applicable. Also sets the mean type to MEAN_IMAGE for a particular channel
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