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Overview ¶
Package mlvision uses an underlying model from the ML model service as a vision model, and wraps the ML model with the vision service methods.
Index ¶
Constants ¶
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const ( // UInt8 is one of the possible input/output types for tensors. UInt8 = "uint8" // Float32 is one of the possible input/output types for tensors. Float32 = "float32" // DefaultOutTensorName is the prefix key given to output tensors in the map // if there is no metadata. (output0, output1, etc.) DefaultOutTensorName = "output" )
Variables ¶
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Functions ¶
This section is empty.
Types ¶
type MLModelConfig ¶
type MLModelConfig struct {
ModelName string `json:"mlmodel_name"`
RemapInputNames map[string]string `json:"remap_input_names"`
RemapOutputNames map[string]string `json:"remap_output_names"`
BoxOrder []int `json:"xmin_ymin_xmax_ymax_order"`
// optional parameter used to normalize the input image if the ML Model expects it
MeanValue []float32 `json:"input_image_mean_value"`
// optional parameter used to normalize the input image if the ML Model expects it
StdDev []float32 `json:"input_image_std_dev"`
// optional parameter used to change the input image to BGR format if the ML Model expects it
IsBGR bool `json:"input_image_bgr"`
DefaultConfidence float64 `json:"default_minimum_confidence"`
LabelConfidenceMap map[string]float64 `json:"label_confidences"`
}
MLModelConfig specifies the parameters needed to turn an ML model into a vision Model.
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