darknet_internal.hpp File Reference

Classes
struct	box_label
struct	boxabs
struct	contrastive_params
struct	Darknet::Output_Object
	This is used to help keep some state between calls to functions fill_network_boxes(), get_yolo_detections(), etc. More...
struct	data
struct	det_num_pair
struct	dxrep
struct	ious
struct	load_args
	Used when a secondary thread is created to load things, such as images. More...
struct	matrix
struct	update_args

Namespaces
namespace	Darknet
	The namespace for the C++ Darknet API.

Macros
#define	DARKNET_INCLUDE_ORIGINAL_API
	If you're using some old software that expects the original C API in the Darknet library, then make sure you "#define DARKNET_INCLUDE_ORIGINAL_API" before you include darknet.h.
#define	SECRET_NUM   -1234

Typedefs
typedef struct box_label	box_label
typedef struct boxabs	boxabs
typedef struct contrastive_params	contrastive_params
typedef struct data	data
typedef struct det_num_pair	det_num_pair
typedef struct dxrep	dxrep
typedef struct ious	ious
typedef struct load_args	load_args
	Used when a secondary thread is created to load things, such as images.
typedef struct matrix	matrix
using	Darknet::Output_Object_Cache = std::list< Output_Object >
typedef struct det_num_pair *	pdet_num_pair
typedef struct update_args	update_args
using	Darknet::VThreads = std::vector< std::thread >

Enumerations
enum	ACTIVATION {   LOGISTIC ,   RELU ,   RELU6 ,   RELIE ,   LINEAR ,   RAMP ,   TANH ,   PLSE ,   REVLEAKY ,   LEAKY ,   ELU ,   LOGGY ,   STAIR ,   HARDTAN ,   LHTAN ,   SELU ,   GELU ,   SWISH ,   MISH ,   HARD_MISH ,   NORM_CHAN ,   NORM_CHAN_SOFTMAX ,   NORM_CHAN_SOFTMAX_MAXVAL }
enum	BINARY_ACTIVATION {   MULT ,   ADD ,   SUB ,   DIV }
enum	COST_TYPE {   SSE ,   MASKED ,   L1 ,   SEG ,   SMOOTH ,   WGAN }
enum	data_type {   DETECTION_DATA ,   IMAGE_DATA ,   LETTERBOX_DATA }
	Things that we can do on a secondary thread. More...
enum	IMTYPE {   PNG ,   BMP ,   TGA ,   JPG }
enum	IOU_LOSS {   IOU ,   GIOU ,   MSE ,   DIOU ,   CIOU }
enum	learning_rate_policy {   CONSTANT ,   STEP ,   EXP ,   POLY ,   STEPS ,   SIG ,   RANDOM ,   SGDR }
enum	UNUSED_ENUM_TYPE { UNUSED_DEF_VAL }
enum	WEIGHTS_NORMALIZATION_T {   NO_NORMALIZATION ,   RELU_NORMALIZATION ,   SOFTMAX_NORMALIZATION }
enum	WEIGHTS_TYPE_T {   NO_WEIGHTS ,   PER_FEATURE ,   PER_CHANNEL }
enum	YOLO_POINT {   YOLO_CENTER = 1 << 0 ,   YOLO_LEFT_TOP = 1 << 1 ,   YOLO_RIGHT_BOTTOM = 1 << 2 }

Functions
void *	cuda_get_context ()
void	cuda_pull_array (float *x_gpu, float *x, size_t n)
void	cuda_pull_array_async (float *x_gpu, float *x, size_t n)
void	free_layer (Darknet::Layer &l)
void	free_layer_custom (Darknet::Layer &l, int keep_cudnn_desc)
int	get_yolo_detections_v3 (Darknet::Network *net, int w, int h, int netw, int neth, float thresh, int *map, int relative, Darknet::Detection *dets, int letter, Darknet::Output_Object_Cache &cache)
	Convert everything we've detected into bounding boxes and confidence scores for each class.
void	init_cpu ()
void	top_k (float *a, int n, int k, int *index)
int	yolo_num_detections_v3 (Darknet::Network *net, const int index, const float thresh, Darknet::Output_Object_Cache &cache)
	Count the number of objects found in the current image.

Macro Definition Documentation

DARKNET_INCLUDE_ORIGINAL_API

#define DARKNET_INCLUDE_ORIGINAL_API

If you're using some old software that expects the original C API in the Darknet library, then make sure you "#define DARKNET_INCLUDE_ORIGINAL_API" before you include darknet.h.

Internally, Darknet still uses the old C V2 API which is why it is defined in darknet_internal.hpp.

SECRET_NUM

#define SECRET_NUM   -1234

Todo:

V2 what is SECRET_NUM? And/or move to a different header.

Typedef Documentation

box_label

typedef struct box_label box_label

boxabs

typedef struct boxabs boxabs

contrastive_params

typedef struct contrastive_params contrastive_params

data

typedef struct data data

det_num_pair

typedef struct det_num_pair det_num_pair

dxrep

typedef struct dxrep dxrep

ious

typedef struct ious ious

load_args

typedef struct load_args load_args

Used when a secondary thread is created to load things, such as images.

See also

Darknet::load_single_image_data()

data_type

matrix

typedef struct matrix matrix

pdet_num_pair

typedef struct det_num_pair * pdet_num_pair

update_args

typedef struct update_args update_args

Enumeration Type Documentation

ACTIVATION

enum ACTIVATION

Enumerator
LOGISTIC
RELU
RELU6
RELIE
LINEAR
RAMP
TANH
PLSE
REVLEAKY
LEAKY
ELU
LOGGY
STAIR
HARDTAN
LHTAN
SELU
GELU
SWISH
MISH
HARD_MISH
NORM_CHAN
NORM_CHAN_SOFTMAX
NORM_CHAN_SOFTMAX_MAXVAL

BINARY_ACTIVATION

enum BINARY_ACTIVATION

Enumerator
MULT
ADD
SUB
DIV

COST_TYPE

enum COST_TYPE

Enumerator
SSE
MASKED
L1
SEG
SMOOTH
WGAN

data_type

enum data_type

Things that we can do on a secondary thread.

See also

Darknet::load_single_image_data()

load_args::type

Enumerator
DETECTION_DATA
IMAGE_DATA	causes Darknet::load_image() and Darknet::resize_image() to be called
LETTERBOX_DATA	causes Darknet::load_image() and Darknet::letterbox_image() to be called

IMTYPE

enum IMTYPE

Enumerator
PNG
BMP
TGA
JPG

IOU_LOSS

enum IOU_LOSS

Enumerator
IOU
GIOU
MSE
DIOU
CIOU

learning_rate_policy

enum learning_rate_policy

Enumerator
CONSTANT
STEP
EXP
POLY
STEPS
SIG
RANDOM
SGDR

UNUSED_ENUM_TYPE

enum UNUSED_ENUM_TYPE

Todo:

V3 Need to get rid of UNUSED_ENUM_TYPE. And/or move to a different header.

Enumerator
UNUSED_DEF_VAL

WEIGHTS_NORMALIZATION_T

enum WEIGHTS_NORMALIZATION_T

Enumerator
NO_NORMALIZATION
RELU_NORMALIZATION
SOFTMAX_NORMALIZATION

WEIGHTS_TYPE_T

enum WEIGHTS_TYPE_T

Enumerator
NO_WEIGHTS
PER_FEATURE
PER_CHANNEL

YOLO_POINT

enum YOLO_POINT

Enumerator
YOLO_CENTER
YOLO_LEFT_TOP
YOLO_RIGHT_BOTTOM

Function Documentation

cuda_get_context()

void * cuda_get_context

(

)

cuda_pull_array()

void cuda_pull_array	(	float *	x_gpu,
		float *	x,
		size_t	n
	)

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cuda_pull_array_async()

void cuda_pull_array_async	(	float *	x_gpu,
		float *	x,
		size_t	n
	)

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free_layer()

void free_layer

(

Darknet::Layer &

l

)

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free_layer_custom()

void free_layer_custom	(	Darknet::Layer &	l,
		int	keep_cudnn_desc
	)

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get_yolo_detections_v3()

int get_yolo_detections_v3	(	Darknet::Network *	net,
		int	w,
		int	h,
		int	netw,
		int	neth,
		float	thresh,
		int *	map,
		int	relative,
		Darknet::Detection *	dets,
		int	letter,
		Darknet::Output_Object_Cache &	cache
	)

Convert everything we've detected into bounding boxes and confidence scores for each class.

Todo:

V3 what is this and where does it get used?

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init_cpu()

void init_cpu

(

)

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top_k()

void top_k	(	float *	a,
		int	n,
		int	k,
		int *	index
	)

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yolo_num_detections_v3()

int yolo_num_detections_v3	(	Darknet::Network *	net,
		const int	index,
		const float	thresh,
		Darknet::Output_Object_Cache &	cache
	)

Count the number of objects found in the current image.

Only looks at the YOLO layer at index within the network. Starting with V3 JAZZ, this will also populate (appends, does not clear!) the object cache with the location of all objects found so we don't have to look through the entire YOLO output again when creating the boxes.

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