pub fn read_net(model: &str, config: &str, framework: &str) -> Result<crate::dnn::Net> {
	string_arg!(model);
	string_arg!(config);
	string_arg!(framework);
	unsafe { sys::cv_dnn_readNet_const_StringX_const_StringX_const_StringX(model.as_ptr(), config.as_ptr(), framework.as_ptr()) }.into_result().map(|ptr| unsafe { crate::dnn::Net::from_raw(ptr) })
}
/// Read deep learning network represented in one of the supported formats.
/// ## Parameters
/// * model: Binary file contains trained weights. The following file
///                  extensions are expected for models from different frameworks:
///                  * `*.caffemodel` (Caffe, http://caffe.berkeleyvision.org/)
///                  * `*.pb` (TensorFlow, https://www.tensorflow.org/)
///                  * `*.t7` | `*.net` (Torch, http://torch.ch/)
///                  * `*.weights` (Darknet, https://pjreddie.com/darknet/)
///                  * `*.bin` (DLDT, https://software.intel.com/openvino-toolkit)
///                  * `*.onnx` (ONNX, https://onnx.ai/)
/// * config: Text file contains network configuration. It could be a
///                   file with the following extensions:
///                  * `*.prototxt` (Caffe, http://caffe.berkeleyvision.org/)
///                  * `*.pbtxt` (TensorFlow, https://www.tensorflow.org/)
///                  * `*.cfg` (Darknet, https://pjreddie.com/darknet/)
///                  * `*.xml` (DLDT, https://software.intel.com/openvino-toolkit)
/// * framework: Explicit framework name tag to determine a format.
/// ## Returns
/// Net object.
/// 
/// This function automatically detects an origin framework of trained model
/// and calls an appropriate function such @ref readNetFromCaffe, @ref readNetFromTensorflow,
/// @ref readNetFromTorch or @ref readNetFromDarknet. An order of @p model and @p config
/// arguments does not matter.
/// 
/// ## C++ default parameters
/// * config: ""
/// * framework: ""
Read deep learning network represented in one of the supported formats.
Read deep learning network represented in one of the supported formats .
pub fn read_net(model: &str, config: &str, framework: &str) -> Result<crate::dnn::Net> {
	string_arg!(model);
	string_arg!(config);
	string_arg!(framework);
	unsafe { sys::cv_dnn_readNet_const_StringX_const_StringX_const_StringX(model.as_ptr(), config.as_ptr(), framework.as_ptr()) }.into_result().map(|ptr| unsafe { crate::dnn::Net::from_raw(ptr) })
}
pub fn read_net ( model : & str , config : & str , framework : & str ) -> Result < crate :: dnn :: Net > { string_arg ! ( model ) ; string_arg ! ( config ) ; string_arg ! ( framework ) ; unsafe { sys :: cv_dnn_readNet_const_StringX_const_StringX_const_StringX ( model . as_ptr ( ) , config . as_ptr ( ) , framework . as_ptr ( ) ) } . into_result ( ) . map ( | ptr | unsafe { crate :: dnn :: Net :: from_raw ( ptr ) } ) }
Read deep learning network represented in one of the supported formats.
Read deep learning network represented in one of the supported formats .
Net object.

This function automatically detects an origin framework of trained model
and calls an appropriate function such @ref readNetFromCaffe, @ref readNetFromTensorflow,
@ref readNetFromTorch or @ref readNetFromDarknet. An order of @p model and @p config
arguments does not matter.
Net object . This function automatically detects an origin framework of trained model and calls an appropriate function such @ref readNetFromCaffe @ref readNetFromTensorflow @ref readNetFromTorch or @ref readNetFromDarknet . An order of @p model and @p config arguments does not matter .
model
&str
config
&str
framework
&str
c++ default parameters
None