View Source Evision.DNN.DetectionModel (Evision v0.1.8)

Link to this section Summary

Functions

Raising version of detect/2.

Raising version of detect/3.

Given the @p input frame, create input blob, run net and return result detections.

Given the @p input frame, create input blob, run net and return result detections.

Variant 1:

Create model from deep learning network.

Create detection model from network represented in one of the supported formats. An order of @p model and @p config arguments does not matter.

Getter for nmsAcrossClasses. This variable defaults to false, such that when non max suppression is used during the detect() function, it will do so only per-class

nmsAcrossClasses defaults to false, such that when non max suppression is used during the detect() function, it will do so per-class. This function allows you to toggle this behaviour.

Link to this section Functions

Raising version of detect/2.

Link to this function

detect!(self, frame, opts)

View Source

Raising version of detect/3.

Given the @p input frame, create input blob, run net and return result detections.

Positional Arguments
Keyword Arguments
  • confThreshold: float.

    A threshold used to filter boxes by confidences.

  • nmsThreshold: float.

    A threshold used in non maximum suppression.

Return
  • classIds: [int].

    Class indexes in result detection.

  • confidences: [float].

    A set of corresponding confidences.

  • boxes: [Rect].

    A set of bounding boxes.

Python prototype (for reference):

detect(frame[, confThreshold[, nmsThreshold]]) -> classIds, confidences, boxes
Link to this function

detect(self, frame, opts)

View Source

Given the @p input frame, create input blob, run net and return result detections.

Positional Arguments
Keyword Arguments
  • confThreshold: float.

    A threshold used to filter boxes by confidences.

  • nmsThreshold: float.

    A threshold used in non maximum suppression.

Return
  • classIds: [int].

    Class indexes in result detection.

  • confidences: [float].

    A set of corresponding confidences.

  • boxes: [Rect].

    A set of bounding boxes.

Python prototype (for reference):

detect(frame[, confThreshold[, nmsThreshold]]) -> classIds, confidences, boxes
Link to this function

dnn_DetectionModel!(network)

View Source

Raising version of dnn_DetectionModel/1.

Link to this function

dnn_DetectionModel!(model, opts)

View Source

Raising version of dnn_DetectionModel/2.

Link to this function

dnn_DetectionModel(network)

View Source

Variant 1:

Create model from deep learning network.

Positional Arguments
  • network: Net.

    Net object.

Python prototype (for reference):

DetectionModel(network) -> <dnn_DetectionModel object>

Variant 2:

Create 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.

Python prototype (for reference):

DetectionModel(model[, config]) -> <dnn_DetectionModel object>
Link to this function

dnn_DetectionModel(model, opts)

View Source

Create 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.

Python prototype (for reference):

DetectionModel(model[, config]) -> <dnn_DetectionModel object>
Link to this function

getNmsAcrossClasses!(self)

View Source

Raising version of getNmsAcrossClasses/1.

Link to this function

getNmsAcrossClasses(self)

View Source

Getter for nmsAcrossClasses. This variable defaults to false, such that when non max suppression is used during the detect() function, it will do so only per-class

Python prototype (for reference):

getNmsAcrossClasses() -> retval
Link to this function

setNmsAcrossClasses!(self, value)

View Source

Raising version of setNmsAcrossClasses/2.

Link to this function

setNmsAcrossClasses(self, value)

View Source

nmsAcrossClasses defaults to false, such that when non max suppression is used during the detect() function, it will do so per-class. This function allows you to toggle this behaviour.

Positional Arguments
  • value: bool.

    The new value for nmsAcrossClasses

Python prototype (for reference):

setNmsAcrossClasses(value) -> retval