View Source Evision.DNN.ClassificationModel (Evision v0.1.9)
Link to this section Summary
Functions
Raising version of classify/2
.
Raising version of dnn_ClassificationModel/1
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Raising version of dnn_ClassificationModel/2
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Variant 1:
Create model from deep learning network.
Create classification model from network represented in one of the supported formats. An order of @p model and @p config arguments does not matter.
Raising version of getEnableSoftmaxPostProcessing/1
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Get enable/disable softmax post processing option.
Raising version of setEnableSoftmaxPostProcessing/2
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Set enable/disable softmax post processing option.
Link to this section Functions
Raising version of classify/2
.
Positional Arguments
- frame:
Evision.Mat
Return
- classId:
int
- conf:
float
Has overloading in C++
Python prototype (for reference):
classify(frame) -> classId, conf
Raising version of dnn_ClassificationModel/1
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Raising version of dnn_ClassificationModel/2
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Variant 1:
Create model from deep learning network.
Positional Arguments
network:
Net
.Net object.
Python prototype (for reference):
ClassificationModel(network) -> <dnn_ClassificationModel object>
Variant 2:
Create classification model from network represented in one of the supported formats. An order of @p model and @p config arguments does not matter.
Positional Arguments
model:
String
.Binary file contains trained weights.
Keyword Arguments
config:
String
.Text file contains network configuration.
Python prototype (for reference):
ClassificationModel(model[, config]) -> <dnn_ClassificationModel object>
Create classification model from network represented in one of the supported formats. An order of @p model and @p config arguments does not matter.
Positional Arguments
model:
String
.Binary file contains trained weights.
Keyword Arguments
config:
String
.Text file contains network configuration.
Python prototype (for reference):
ClassificationModel(model[, config]) -> <dnn_ClassificationModel object>
Raising version of getEnableSoftmaxPostProcessing/1
.
Get enable/disable softmax post processing option.
This option defaults to false, softmax post processing is not applied within the classify() function.
Python prototype (for reference):
getEnableSoftmaxPostProcessing() -> retval
Raising version of setEnableSoftmaxPostProcessing/2
.
Set enable/disable softmax post processing option.
Positional Arguments
enable:
bool
.Set enable softmax post processing within the classify() function.
If this option is true, softmax is applied after forward inference within the classify() function to convert the confidences range to [0.0-1.0]. This function allows you to toggle this behavior. Please turn true when not contain softmax layer in model.
Python prototype (for reference):
setEnableSoftmaxPostProcessing(enable) -> retval