View Source Evision.DNN.TextDetectionModelEAST (Evision v0.1.14)
Link to this section Summary
Types
Type that represents an Evision.DNN.TextDetectionModelEAST
struct.
Functions
Get the detection confidence threshold
Get the detection confidence threshold
Set the detection confidence threshold
Set the detection NMS filter threshold
Variant 1:
Create text detection model from network represented in one of the supported formats. An order of @p model and @p config arguments does not matter.
Create text detection model from network represented in one of the supported formats. An order of @p model and @p config arguments does not matter.
Link to this section Types
@type t() :: %Evision.DNN.TextDetectionModelEAST{ref: reference()}
Type that represents an Evision.DNN.TextDetectionModelEAST
struct.
ref.
reference()
The underlying erlang resource variable.
Link to this section Functions
Get the detection confidence threshold
Return
- retval:
float
Python prototype (for reference):
getConfidenceThreshold() -> retval
Get the detection confidence threshold
Return
- retval:
float
Python prototype (for reference):
getNMSThreshold() -> retval
Set the detection confidence threshold
Positional Arguments
confThreshold:
float
.A threshold used to filter boxes by confidences
Return
Python prototype (for reference):
setConfidenceThreshold(confThreshold) -> retval
Set the detection NMS filter threshold
Positional Arguments
nmsThreshold:
float
.A threshold used in non maximum suppression
Return
Python prototype (for reference):
setNMSThreshold(nmsThreshold) -> retval
@spec textDetectionModelEAST(binary()) :: t() | {:error, String.t()}
@spec textDetectionModelEAST(Evision.DNN.Net.t()) :: t() | {:error, String.t()}
Variant 1:
Create text detection 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.
Return
Python prototype (for reference):
TextDetectionModel_EAST(model[, config]) -> <dnn_TextDetectionModel_EAST object>
Variant 2:
Create text detection algorithm from deep learning network
Positional Arguments
network:
Evision.DNN.Net
.Net object
Return
Python prototype (for reference):
TextDetectionModel_EAST(network) -> <dnn_TextDetectionModel_EAST object>
Create text detection 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.
Return
Python prototype (for reference):
TextDetectionModel_EAST(model[, config]) -> <dnn_TextDetectionModel_EAST object>