opencv::dnn

Trait NetTraitConst

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pub trait NetTraitConst {

Show 32 methods    // Required method
    fn as_raw_Net(&self) -> *const c_void;

    // Provided methods
    fn empty(&self) -> Result<bool> { ... }
    fn get_layer_id(&self, layer: &str) -> Result<i32> { ... }
    fn get_layer_names(&self) -> Result<Vector<String>> { ... }
    fn get_layer(&self, layer_id: i32) -> Result<Ptr<Layer>> { ... }
    fn get_layer_1(&self, layer_name: &str) -> Result<Ptr<Layer>> { ... }
    fn get_layer_2(
        &self,
        layer_id: &impl DictValueTraitConst,
    ) -> Result<Ptr<Layer>> { ... }
    fn get_layer_inputs(&self, layer_id: i32) -> Result<Vector<Ptr<Layer>>> { ... }
    fn get_input_details(
        &self,
        scales: &mut Vector<f32>,
        zeropoints: &mut Vector<i32>,
    ) -> Result<()> { ... }
    fn get_output_details(
        &self,
        scales: &mut Vector<f32>,
        zeropoints: &mut Vector<i32>,
    ) -> Result<()> { ... }
    fn get_param(&self, layer: i32, num_param: i32) -> Result<Mat> { ... }
    fn get_param_def(&self, layer: i32) -> Result<Mat> { ... }
    fn get_param_1(&self, layer_name: &str, num_param: i32) -> Result<Mat> { ... }
    fn get_param_def_1(&self, layer_name: &str) -> Result<Mat> { ... }
    fn get_unconnected_out_layers(&self) -> Result<Vector<i32>> { ... }
    fn get_unconnected_out_layers_names(&self) -> Result<Vector<String>> { ... }
    fn get_layers_shapes(
        &self,
        net_input_shapes: &Vector<MatShape>,
        layers_ids: &mut Vector<i32>,
        in_layers_shapes: &mut Vector<Vector<MatShape>>,
        out_layers_shapes: &mut Vector<Vector<MatShape>>,
    ) -> Result<()> { ... }
    fn get_layers_shapes_1(
        &self,
        net_input_shape: &MatShape,
        layers_ids: &mut Vector<i32>,
        in_layers_shapes: &mut Vector<Vector<MatShape>>,
        out_layers_shapes: &mut Vector<Vector<MatShape>>,
    ) -> Result<()> { ... }
    fn get_layer_shapes(
        &self,
        net_input_shape: &MatShape,
        layer_id: i32,
        in_layer_shapes: &mut Vector<MatShape>,
        out_layer_shapes: &mut Vector<MatShape>,
    ) -> Result<()> { ... }
    fn get_layer_shapes_1(
        &self,
        net_input_shapes: &Vector<MatShape>,
        layer_id: i32,
        in_layer_shapes: &mut Vector<MatShape>,
        out_layer_shapes: &mut Vector<MatShape>,
    ) -> Result<()> { ... }
    fn get_flops(&self, net_input_shapes: &Vector<MatShape>) -> Result<i64> { ... }
    fn get_flops_1(&self, net_input_shape: &MatShape) -> Result<i64> { ... }
    fn get_flops_2(
        &self,
        layer_id: i32,
        net_input_shapes: &Vector<MatShape>,
    ) -> Result<i64> { ... }
    fn get_flops_3(
        &self,
        layer_id: i32,
        net_input_shape: &MatShape,
    ) -> Result<i64> { ... }
    fn get_layer_types(&self, layers_types: &mut Vector<String>) -> Result<()> { ... }
    fn get_layers_count(&self, layer_type: &str) -> Result<i32> { ... }
    fn get_memory_consumption(
        &self,
        net_input_shapes: &Vector<MatShape>,
        weights: &mut size_t,
        blobs: &mut size_t,
    ) -> Result<()> { ... }
    fn get_memory_consumption_1(
        &self,
        net_input_shape: &MatShape,
        weights: &mut size_t,
        blobs: &mut size_t,
    ) -> Result<()> { ... }
    fn get_memory_consumption_for_layer(
        &self,
        layer_id: i32,
        net_input_shapes: &Vector<MatShape>,
        weights: &mut size_t,
        blobs: &mut size_t,
    ) -> Result<()> { ... }
    fn get_memory_consumption_2(
        &self,
        layer_id: i32,
        net_input_shape: &MatShape,
        weights: &mut size_t,
        blobs: &mut size_t,
    ) -> Result<()> { ... }
    fn get_memory_consumption_for_layers(
        &self,
        net_input_shapes: &Vector<MatShape>,
        layer_ids: &mut Vector<i32>,
        weights: &mut Vector<size_t>,
        blobs: &mut Vector<size_t>,
    ) -> Result<()> { ... }
    fn get_memory_consumption_3(
        &self,
        net_input_shape: &MatShape,
        layer_ids: &mut Vector<i32>,
        weights: &mut Vector<size_t>,
        blobs: &mut Vector<size_t>,
    ) -> Result<()> { ... }

}
Expand description

Constant methods for crate::dnn::Net

Required Methods§

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fn as_raw_Net(&self) -> *const c_void

Provided Methods§

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fn empty(&self) -> Result<bool>

Returns true if there are no layers in the network.

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fn get_layer_id(&self, layer: &str) -> Result<i32>

Converts string name of the layer to the integer identifier.

§Returns

id of the layer, or -1 if the layer wasn’t found.

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fn get_layer_names(&self) -> Result<Vector<String>>

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fn get_layer(&self, layer_id: i32) -> Result<Ptr<Layer>>

Returns pointer to layer with specified id or name which the network use.

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fn get_layer_1(&self, layer_name: &str) -> Result<Ptr<Layer>>

👎Deprecated: Use int getLayerId(const String &layer)

Returns pointer to layer with specified id or name which the network use.

§Overloaded parameters

Deprecated: Use int getLayerId(const String &layer)

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fn get_layer_2(&self, layer_id: &impl DictValueTraitConst) -> Result<Ptr<Layer>>

👎Deprecated: to be removed

Returns pointer to layer with specified id or name which the network use.

§Overloaded parameters

Deprecated: to be removed

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fn get_layer_inputs(&self, layer_id: i32) -> Result<Vector<Ptr<Layer>>>

Returns pointers to input layers of specific layer.

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fn get_input_details( &self, scales: &mut Vector<f32>, zeropoints: &mut Vector<i32>, ) -> Result<()>

Returns input scale and zeropoint for a quantized Net.

§Parameters
  • scales: output parameter for returning input scales.
  • zeropoints: output parameter for returning input zeropoints.
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fn get_output_details( &self, scales: &mut Vector<f32>, zeropoints: &mut Vector<i32>, ) -> Result<()>

Returns output scale and zeropoint for a quantized Net.

§Parameters
  • scales: output parameter for returning output scales.
  • zeropoints: output parameter for returning output zeropoints.
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fn get_param(&self, layer: i32, num_param: i32) -> Result<Mat>

Returns parameter blob of the layer.

§Parameters
  • layer: name or id of the layer.
  • numParam: index of the layer parameter in the Layer::blobs array.
§See also

Layer::blobs

§C++ default parameters
  • num_param: 0
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fn get_param_def(&self, layer: i32) -> Result<Mat>

Returns parameter blob of the layer.

§Parameters
  • layer: name or id of the layer.
  • numParam: index of the layer parameter in the Layer::blobs array.
§See also

Layer::blobs

§Note

This alternative version of NetTraitConst::get_param function uses the following default values for its arguments:

  • num_param: 0
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fn get_param_1(&self, layer_name: &str, num_param: i32) -> Result<Mat>

§C++ default parameters
  • num_param: 0
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fn get_param_def_1(&self, layer_name: &str) -> Result<Mat>

§Note

This alternative version of NetTraitConst::get_param function uses the following default values for its arguments:

  • num_param: 0
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fn get_unconnected_out_layers(&self) -> Result<Vector<i32>>

Returns indexes of layers with unconnected outputs.

FIXIT: Rework API to registerOutput() approach, deprecate this call

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fn get_unconnected_out_layers_names(&self) -> Result<Vector<String>>

Returns names of layers with unconnected outputs.

FIXIT: Rework API to registerOutput() approach, deprecate this call

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fn get_layers_shapes( &self, net_input_shapes: &Vector<MatShape>, layers_ids: &mut Vector<i32>, in_layers_shapes: &mut Vector<Vector<MatShape>>, out_layers_shapes: &mut Vector<Vector<MatShape>>, ) -> Result<()>

Returns input and output shapes for all layers in loaded model; preliminary inferencing isn’t necessary.

§Parameters
  • netInputShapes: shapes for all input blobs in net input layer.
  • layersIds: output parameter for layer IDs.
  • inLayersShapes: output parameter for input layers shapes; order is the same as in layersIds
  • outLayersShapes: output parameter for output layers shapes; order is the same as in layersIds
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fn get_layers_shapes_1( &self, net_input_shape: &MatShape, layers_ids: &mut Vector<i32>, in_layers_shapes: &mut Vector<Vector<MatShape>>, out_layers_shapes: &mut Vector<Vector<MatShape>>, ) -> Result<()>

Returns input and output shapes for all layers in loaded model; preliminary inferencing isn’t necessary.

§Parameters
  • netInputShapes: shapes for all input blobs in net input layer.
  • layersIds: output parameter for layer IDs.
  • inLayersShapes: output parameter for input layers shapes; order is the same as in layersIds
  • outLayersShapes: output parameter for output layers shapes; order is the same as in layersIds
§Overloaded parameters
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fn get_layer_shapes( &self, net_input_shape: &MatShape, layer_id: i32, in_layer_shapes: &mut Vector<MatShape>, out_layer_shapes: &mut Vector<MatShape>, ) -> Result<()>

Returns input and output shapes for layer with specified id in loaded model; preliminary inferencing isn’t necessary.

§Parameters
  • netInputShape: shape input blob in net input layer.
  • layerId: id for layer.
  • inLayerShapes: output parameter for input layers shapes; order is the same as in layersIds
  • outLayerShapes: output parameter for output layers shapes; order is the same as in layersIds
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fn get_layer_shapes_1( &self, net_input_shapes: &Vector<MatShape>, layer_id: i32, in_layer_shapes: &mut Vector<MatShape>, out_layer_shapes: &mut Vector<MatShape>, ) -> Result<()>

Returns input and output shapes for layer with specified id in loaded model; preliminary inferencing isn’t necessary.

§Parameters
  • netInputShape: shape input blob in net input layer.
  • layerId: id for layer.
  • inLayerShapes: output parameter for input layers shapes; order is the same as in layersIds
  • outLayerShapes: output parameter for output layers shapes; order is the same as in layersIds
§Overloaded parameters
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fn get_flops(&self, net_input_shapes: &Vector<MatShape>) -> Result<i64>

Computes FLOP for whole loaded model with specified input shapes.

§Parameters
  • netInputShapes: vector of shapes for all net inputs.
§Returns

computed FLOP.

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fn get_flops_1(&self, net_input_shape: &MatShape) -> Result<i64>

Computes FLOP for whole loaded model with specified input shapes.

§Parameters
  • netInputShapes: vector of shapes for all net inputs.
§Returns

computed FLOP.

§Overloaded parameters
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fn get_flops_2( &self, layer_id: i32, net_input_shapes: &Vector<MatShape>, ) -> Result<i64>

Computes FLOP for whole loaded model with specified input shapes.

§Parameters
  • netInputShapes: vector of shapes for all net inputs.
§Returns

computed FLOP.

§Overloaded parameters
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fn get_flops_3(&self, layer_id: i32, net_input_shape: &MatShape) -> Result<i64>

Computes FLOP for whole loaded model with specified input shapes.

§Parameters
  • netInputShapes: vector of shapes for all net inputs.
§Returns

computed FLOP.

§Overloaded parameters
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fn get_layer_types(&self, layers_types: &mut Vector<String>) -> Result<()>

Returns list of types for layer used in model.

§Parameters
  • layersTypes: output parameter for returning types.
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fn get_layers_count(&self, layer_type: &str) -> Result<i32>

Returns count of layers of specified type.

§Parameters
  • layerType: type.
§Returns

count of layers

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fn get_memory_consumption( &self, net_input_shapes: &Vector<MatShape>, weights: &mut size_t, blobs: &mut size_t, ) -> Result<()>

Computes bytes number which are required to store all weights and intermediate blobs for model.

§Parameters
  • netInputShapes: vector of shapes for all net inputs.
  • weights: output parameter to store resulting bytes for weights.
  • blobs: output parameter to store resulting bytes for intermediate blobs.
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fn get_memory_consumption_1( &self, net_input_shape: &MatShape, weights: &mut size_t, blobs: &mut size_t, ) -> Result<()>

Computes bytes number which are required to store all weights and intermediate blobs for model.

§Parameters
  • netInputShapes: vector of shapes for all net inputs.
  • weights: output parameter to store resulting bytes for weights.
  • blobs: output parameter to store resulting bytes for intermediate blobs.
§Overloaded parameters
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fn get_memory_consumption_for_layer( &self, layer_id: i32, net_input_shapes: &Vector<MatShape>, weights: &mut size_t, blobs: &mut size_t, ) -> Result<()>

Computes bytes number which are required to store all weights and intermediate blobs for model.

§Parameters
  • netInputShapes: vector of shapes for all net inputs.
  • weights: output parameter to store resulting bytes for weights.
  • blobs: output parameter to store resulting bytes for intermediate blobs.
§Overloaded parameters
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fn get_memory_consumption_2( &self, layer_id: i32, net_input_shape: &MatShape, weights: &mut size_t, blobs: &mut size_t, ) -> Result<()>

Computes bytes number which are required to store all weights and intermediate blobs for model.

§Parameters
  • netInputShapes: vector of shapes for all net inputs.
  • weights: output parameter to store resulting bytes for weights.
  • blobs: output parameter to store resulting bytes for intermediate blobs.
§Overloaded parameters
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fn get_memory_consumption_for_layers( &self, net_input_shapes: &Vector<MatShape>, layer_ids: &mut Vector<i32>, weights: &mut Vector<size_t>, blobs: &mut Vector<size_t>, ) -> Result<()>

Computes bytes number which are required to store all weights and intermediate blobs for each layer.

§Parameters
  • netInputShapes: vector of shapes for all net inputs.
  • layerIds: output vector to save layer IDs.
  • weights: output parameter to store resulting bytes for weights.
  • blobs: output parameter to store resulting bytes for intermediate blobs.
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fn get_memory_consumption_3( &self, net_input_shape: &MatShape, layer_ids: &mut Vector<i32>, weights: &mut Vector<size_t>, blobs: &mut Vector<size_t>, ) -> Result<()>

Computes bytes number which are required to store all weights and intermediate blobs for each layer.

§Parameters
  • netInputShapes: vector of shapes for all net inputs.
  • layerIds: output vector to save layer IDs.
  • weights: output parameter to store resulting bytes for weights.
  • blobs: output parameter to store resulting bytes for intermediate blobs.
§Overloaded parameters

Object Safety§

This trait is not object safe.

Implementors§