Darknet::ONNXExport Class Reference

Everthing we need to convert .cfg and .weights to .onnx is contained within this class. More...

#include "darknet_onnx.hpp"

Collaboration diagram for Darknet::ONNXExport:

Public Member Functions
	ONNXExport (const std::filesystem::path &cfg_filename, const std::filesystem::path &weights_filename, const std::filesystem::path &onnx_filename)
	Constructor.
	~ONNXExport ()
	Destructor.
ONNXExport &	add_node_activation (const size_t index, Darknet::CfgSection &section)
ONNXExport &	add_node_bn (const size_t index, Darknet::CfgSection &section)
ONNXExport &	add_node_conv (const size_t index, Darknet::CfgSection &section)
ONNXExport &	add_node_maxpool (const size_t index, Darknet::CfgSection &section)
ONNXExport &	add_node_resize (const size_t index, Darknet::CfgSection &section)
ONNXExport &	add_node_route_concat (const size_t index, Darknet::CfgSection &section)
ONNXExport &	add_node_route_split (const size_t index, Darknet::CfgSection &section)
ONNXExport &	add_node_shortcut (const size_t index, Darknet::CfgSection &section)
ONNXExport &	add_node_yolo (const size_t index, Darknet::CfgSection &section)
ONNXExport &	build_model ()
ONNXExport &	check_activation (const size_t index, Darknet::CfgSection &section)
ONNXExport &	display_summary ()
	Display some general information about the protocol buffer model.
ONNXExport &	initialize_model ()
	Initialize some of the simple protobuffer model fields.
ONNXExport &	load_network ()
	Use Darknet to load the neural network.
ONNXExport &	populate_graph_initializer (const float *f, const size_t n, const size_t idx, const Darknet::Layer &l, const std::string &name, const bool simple=false)
ONNXExport &	populate_graph_input_frame ()
ONNXExport &	populate_graph_nodes ()
ONNXExport &	populate_graph_output ()
ONNXExport &	populate_input_output_dimensions (onnx::ValueInfoProto *proto, const std::string &name, const int v1, const int v2=-1, const int v3=-1, const int v4=-1, const size_t line_number=0)
ONNXExport &	save_output_file ()
	Save the entire model as an .onnx file.

Static Public Member Functions
static void	log_handler (google::protobuf::LogLevel level, const char *filename, int line, const std::string &message)
	Callback function that Protocol Buffers calls to log messages.

Public Attributes
Darknet::CfgFile	cfg
std::filesystem::path	cfg_fn
bool	fuse_batchnorm
	Whether or not we need to fuse batchnorm (fuse and dontfuse on the CLI).
onnx::GraphProto *	graph
std::string	input_string
	The dimensions used in populate_graph_input_frame().
onnx::ModelProto	model
std::map< int, std::string >	most_recent_output_per_index
	Keep track of the single most recent output name for each of the layers.
std::map< std::string, size_t >	number_of_floats_exported
	The key is the last part of the string, and the value is the number of floats.
std::filesystem::path	onnx_fn
int	opset_version
	Which opset version to use (10, 18, ...)?
std::string	output_string
	The output nodes for this neural network.
std::filesystem::path	weights_fn

Detailed Description

Everthing we need to convert .cfg and .weights to .onnx is contained within this class.

Constructor & Destructor Documentation

ONNXExport()

Darknet::ONNXExport::ONNXExport	(	const std::filesystem::path &	cfg_filename,
		const std::filesystem::path &	weights_filename,
		const std::filesystem::path &	onnx_filename
	)

Constructor.

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~ONNXExport()

Darknet::ONNXExport::~ONNXExport

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Destructor.

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Member Function Documentation

add_node_activation()

Darknet::ONNXExport & Darknet::ONNXExport::add_node_activation	(	const size_t	index,
		Darknet::CfgSection &	section
	)

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add_node_bn()

Darknet::ONNXExport & Darknet::ONNXExport::add_node_bn	(	const size_t	index,
		Darknet::CfgSection &	section
	)

add_node_conv()

Darknet::ONNXExport & Darknet::ONNXExport::add_node_conv	(	const size_t	index,
		Darknet::CfgSection &	section
	)

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add_node_maxpool()

Darknet::ONNXExport & Darknet::ONNXExport::add_node_maxpool	(	const size_t	index,
		Darknet::CfgSection &	section
	)

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add_node_resize()

Darknet::ONNXExport & Darknet::ONNXExport::add_node_resize	(	const size_t	index,
		Darknet::CfgSection &	section
	)

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add_node_route_concat()

Darknet::ONNXExport & Darknet::ONNXExport::add_node_route_concat	(	const size_t	index,
		Darknet::CfgSection &	section
	)

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add_node_route_split()

Darknet::ONNXExport & Darknet::ONNXExport::add_node_route_split	(	const size_t	index,
		Darknet::CfgSection &	section
	)

<

Todo:

V5: is this logic correct? This is only a guess as to how this works.

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add_node_shortcut()

Darknet::ONNXExport & Darknet::ONNXExport::add_node_shortcut	(	const size_t	index,
		Darknet::CfgSection &	section
	)

Todo:

V5: unused? Do we have weights for shortcuts?

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add_node_yolo()

Darknet::ONNXExport & Darknet::ONNXExport::add_node_yolo	(	const size_t	index,
		Darknet::CfgSection &	section
	)

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build_model()

Darknet::ONNXExport & Darknet::ONNXExport::build_model

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)

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check_activation()

Darknet::ONNXExport & Darknet::ONNXExport::check_activation	(	const size_t	index,
		Darknet::CfgSection &	section
	)

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display_summary()

Darknet::ONNXExport & Darknet::ONNXExport::display_summary

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)

Display some general information about the protocol buffer model.

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initialize_model()

Darknet::ONNXExport & Darknet::ONNXExport::initialize_model

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)

Initialize some of the simple protobuffer model fields.

Todo:

We need a command-line parameter for this field.

Todo:

We need a command-line parameter for this field.

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load_network()

Darknet::ONNXExport & Darknet::ONNXExport::load_network

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Use Darknet to load the neural network.

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log_handler()

void Darknet::ONNXExport::log_handler ( google::protobuf::LogLevel  level, const char *  filename, int  line, const std::string &  message  )

static

Callback function that Protocol Buffers calls to log messages.

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populate_graph_initializer()

Darknet::ONNXExport & Darknet::ONNXExport::populate_graph_initializer	(	const float *	f,
		const size_t	n,
		const size_t	idx,
		const Darknet::Layer &	l,
		const std::string &	name,
		const bool	simple = false
	)

Todo:

V5 2025-08-13: This is black magic! I actually have no idea how the DIMS work. I saw some example Darknet/YOLO weights converted to ONNX and attempted to figure out the patern. While this seems to work for the few examples I have, I would be extremely happy if someone can point out to me exactly how this works so I can implement it correctly!

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populate_graph_input_frame()

Darknet::ONNXExport & Darknet::ONNXExport::populate_graph_input_frame

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populate_graph_nodes()

Darknet::ONNXExport & Darknet::ONNXExport::populate_graph_nodes

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populate_graph_output()

Darknet::ONNXExport & Darknet::ONNXExport::populate_graph_output

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populate_input_output_dimensions()

Darknet::ONNXExport & Darknet::ONNXExport::populate_input_output_dimensions	(	onnx::ValueInfoProto *	proto,
		const std::string &	name,
		const int	v1,
		const int	v2 = -1,
		const int	v3 = -1,
		const int	v4 = -1,
		const size_t	line_number = 0
	)

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save_output_file()

Darknet::ONNXExport & Darknet::ONNXExport::save_output_file

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Save the entire model as an .onnx file.

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Member Data Documentation

cfg

Darknet::CfgFile Darknet::ONNXExport::cfg

cfg_fn

std::filesystem::path Darknet::ONNXExport::cfg_fn

fuse_batchnorm

bool Darknet::ONNXExport::fuse_batchnorm

Whether or not we need to fuse batchnorm (fuse and dontfuse on the CLI).

graph

onnx::GraphProto* Darknet::ONNXExport::graph

input_string

std::string Darknet::ONNXExport::input_string

The dimensions used in populate_graph_input_frame().

model

onnx::ModelProto Darknet::ONNXExport::model

most_recent_output_per_index

std::map<int, std::string> Darknet::ONNXExport::most_recent_output_per_index

Keep track of the single most recent output name for each of the layers.

number_of_floats_exported

std::map<std::string, size_t> Darknet::ONNXExport::number_of_floats_exported

The key is the last part of the string, and the value is the number of floats.

For example, for "000_conv_bias", we store the key as "bias".

onnx_fn

std::filesystem::path Darknet::ONNXExport::onnx_fn

opset_version

int Darknet::ONNXExport::opset_version

Which opset version to use (10, 18, ...)?

output_string

std::string Darknet::ONNXExport::output_string

The output nodes for this neural network.

weights_fn

std::filesystem::path Darknet::ONNXExport::weights_fn

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The documentation for this class was generated from the following files:

• darknet_onnx.hpp
• darknet_onnx.cpp