darknet.h File Reference

Include dependency graph for darknet.h:

This graph shows which files directly or indirectly include this file:

Classes
struct	metadata
struct	tree
struct	contrastive_params
struct	update_args
struct	layer
struct	network
struct	network_state
struct	image
struct	box
struct	boxabs
struct	dxrep
struct	ious
struct	detection
struct	det_num_pair
struct	matrix
struct	data
struct	load_args
	Used when a secondary thread is created to load things, such as images. More...
struct	box_label

Macros
#define	SECRET_NUM   -1234

Typedefs
typedef struct network	network
typedef struct network_state	network_state
typedef struct layer	layer
typedef struct image	image
typedef struct detection	detection
typedef struct load_args	load_args
	Used when a secondary thread is created to load things, such as images. More...
typedef struct data	data
typedef struct metadata	metadata
typedef struct tree	tree
typedef struct contrastive_params	contrastive_params
typedef struct update_args	update_args
typedef struct box	box
typedef struct boxabs	boxabs
typedef struct dxrep	dxrep
typedef struct ious	ious
typedef struct det_num_pair	det_num_pair
typedef struct det_num_pair *	pdet_num_pair
typedef struct matrix	matrix
typedef struct box_label	box_label

Enumerations
enum	UNUSED_ENUM_TYPE { UNUSED_DEF_VAL }
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	IOU_LOSS {   IOU ,   GIOU ,   MSE ,   DIOU ,   CIOU }
enum	NMS_KIND {   DEFAULT_NMS ,   GREEDY_NMS ,   DIOU_NMS ,   CORNERS_NMS }
enum	YOLO_POINT {   YOLO_CENTER = 1 << 0 ,   YOLO_LEFT_TOP = 1 << 1 ,   YOLO_RIGHT_BOTTOM = 1 << 2 }
enum	WEIGHTS_TYPE_T {   NO_WEIGHTS ,   PER_FEATURE ,   PER_CHANNEL }
enum	WEIGHTS_NORMALIZATION_T {   NO_NORMALIZATION ,   RELU_NORMALIZATION ,   SOFTMAX_NORMALIZATION }
enum	IMTYPE {   PNG ,   BMP ,   TGA ,   JPG }
enum	BINARY_ACTIVATION {   MULT ,   ADD ,   SUB ,   DIV }
enum	LAYER_TYPE {   CONVOLUTIONAL ,   DECONVOLUTIONAL ,   CONNECTED ,   MAXPOOL ,   LOCAL_AVGPOOL ,   SOFTMAX ,   DETECTION ,   DROPOUT ,   CROP ,   ROUTE ,   COST ,   NORMALIZATION ,   AVGPOOL ,   LOCAL ,   SHORTCUT ,   SCALE_CHANNELS ,   SAM ,   ACTIVE ,   RNN ,   GRU ,   LSTM ,   CONV_LSTM ,   HISTORY ,   CRNN ,   BATCHNORM ,   NETWORK ,   XNOR ,   REGION ,   YOLO ,   GAUSSIAN_YOLO ,   ISEG ,   REORG ,   REORG_OLD ,   UPSAMPLE ,   LOGXENT ,   L2NORM ,   EMPTY ,   BLANK ,   CONTRASTIVE ,   IMPLICIT }
enum	COST_TYPE {   SSE ,   MASKED ,   L1 ,   SEG ,   SMOOTH ,   WGAN }
enum	learning_rate_policy {   CONSTANT ,   STEP ,   EXP ,   POLY ,   STEPS ,   SIG ,   RANDOM ,   SGDR }
enum	data_type {   CLASSIFICATION_DATA ,   DETECTION_DATA ,   REGION_DATA ,   IMAGE_DATA ,   COMPARE_DATA ,   WRITING_DATA ,   TAG_DATA ,   OLD_CLASSIFICATION_DATA ,   SUPER_DATA ,   LETTERBOX_DATA }
	Things that we can do on a secondary thread. More...

Functions
network *	load_network (char *cfg, char *weights, int clear)
network *	load_network_custom (char *cfg, char *weights, int clear, int batch)
void	free_network (network net)
void	free_network_ptr (network *net)
load_args	get_base_args (network *net)
void	do_nms_sort (detection *dets, int total, int classes, float thresh)
void	do_nms_obj (detection *dets, int total, int classes, float thresh)
void	diounms_sort (detection *dets, int total, int classes, float thresh, NMS_KIND nms_kind, float beta1)
float *	network_predict (network net, float *input)
float *	network_predict_ptr (network *net, float *input)
detection *	get_network_boxes (network *net, int w, int h, float thresh, float hier, int *map, int relative, int *num, int letter)
det_num_pair *	network_predict_batch (network *net, image im, int batch_size, int w, int h, float thresh, float hier, int *map, int relative, int letter)
void	free_detections (detection *dets, int n)
void	free_batch_detections (det_num_pair *det_num_pairs, int n)
void	fuse_conv_batchnorm (network net)
void	calculate_binary_weights (network net)
char *	detection_to_json (detection *dets, int nboxes, int classes, char **names, long long int frame_id, char *filename)
layer *	get_network_layer (network *net, int i)
detection *	make_network_boxes (network *net, float thresh, int *num)
void	reset_rnn (network *net)
float *	network_predict_image (network *net, image im)
float *	network_predict_image_letterbox (network *net, image im)
float	validate_detector_map (char *datacfg, char *cfgfile, char *weightfile, float thresh_calc_avg_iou, const float iou_thresh, const int map_points, int letter_box, network *existing_net)
void	train_detector (char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int dont_show, int calc_map, float thresh, float iou_thresh, int mjpeg_port, int show_imgs, int benchmark_layers, char *chart_path)
void	test_detector (char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, float hier_thresh, int dont_show, int ext_output, int save_labels, char *outfile, int letter_box, int benchmark_layers)
int	network_width (network *net)
int	network_height (network *net)
void	optimize_picture (network *net, image orig, int max_layer, float scale, float rate, float thresh, int norm)
void	make_image_red (image im)
image	make_attention_image (int img_size, float *original_delta_cpu, float *original_input_cpu, int w, int h, int c, float alpha)
image	resize_image (image im, int w, int h)
void	quantize_image (image im)
void	copy_image_from_bytes (image im, char *pdata)
image	letterbox_image (image im, int w, int h)
void	rgbgr_image (image im)
image	make_image (int w, int h, int c)
image	load_image (char *filename, int w, int h, int c)
void	free_image (image m)
image	crop_image (image im, int dx, int dy, int w, int h)
image	resize_min (image im, int min)
void	free_layer_custom (layer l, int keep_cudnn_desc)
void	free_layer (layer l)
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	cuda_set_device (int n)
void *	cuda_get_context ()
void	free_ptrs (void **ptrs, int n)
void	top_k (float *a, int n, int k, int *index)
tree *	read_tree (char *filename)
metadata	get_metadata (char *file)
void	delete_json_sender ()
void	send_json_custom (char const *send_buf, int port, int timeout)
double	get_time_point ()
void	start_timer ()
void	stop_timer ()
double	get_time ()
void	stop_timer_and_show ()
void	stop_timer_and_show_name (char *name)
void	show_total_time ()
void	set_track_id (detection *new_dets, int new_dets_num, float thresh, float sim_thresh, float track_ciou_norm, int deque_size, int dets_for_track, int dets_for_show)
int	fill_remaining_id (detection *new_dets, int new_dets_num, int new_track_id, float thresh)
void	init_cpu ()

Macro Definition Documentation

SECRET_NUM

#define SECRET_NUM   -1234

Todo:

what is this?

Typedef Documentation

network

typedef struct network network

network_state

typedef struct network_state network_state

layer

typedef struct layer layer

image

typedef struct image image

detection

typedef struct detection detection

load_args

typedef struct load_args load_args

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

See also

load_image()

data_type

data

typedef struct data data

metadata

typedef struct metadata metadata

tree

typedef struct tree tree

contrastive_params

typedef struct contrastive_params contrastive_params

update_args

typedef struct update_args update_args

box

typedef struct box box

boxabs

typedef struct boxabs boxabs

dxrep

typedef struct dxrep dxrep

ious

typedef struct ious ious

det_num_pair

typedef struct det_num_pair det_num_pair

pdet_num_pair

typedef struct det_num_pair * pdet_num_pair

matrix

typedef struct matrix matrix

box_label

typedef struct box_label box_label

Enumeration Type Documentation

UNUSED_ENUM_TYPE

enum UNUSED_ENUM_TYPE

Enumerator
UNUSED_DEF_VAL

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

IOU_LOSS

enum IOU_LOSS

Enumerator
IOU
GIOU
MSE
DIOU
CIOU

NMS_KIND

enum NMS_KIND

Enumerator
DEFAULT_NMS
GREEDY_NMS
DIOU_NMS
CORNERS_NMS

YOLO_POINT

enum YOLO_POINT

Enumerator
YOLO_CENTER
YOLO_LEFT_TOP
YOLO_RIGHT_BOTTOM

WEIGHTS_TYPE_T

enum WEIGHTS_TYPE_T

Enumerator
NO_WEIGHTS
PER_FEATURE
PER_CHANNEL

WEIGHTS_NORMALIZATION_T

enum WEIGHTS_NORMALIZATION_T

Enumerator
NO_NORMALIZATION
RELU_NORMALIZATION
SOFTMAX_NORMALIZATION

IMTYPE

enum IMTYPE

Enumerator
PNG
BMP
TGA
JPG

BINARY_ACTIVATION

enum BINARY_ACTIVATION

Enumerator
MULT
ADD
SUB
DIV

LAYER_TYPE

enum LAYER_TYPE

Enumerator
CONVOLUTIONAL
DECONVOLUTIONAL
CONNECTED
MAXPOOL
LOCAL_AVGPOOL
SOFTMAX
DETECTION
DROPOUT
CROP
ROUTE
COST
NORMALIZATION
AVGPOOL
LOCAL
SHORTCUT
SCALE_CHANNELS
SAM
ACTIVE
RNN
GRU
LSTM
CONV_LSTM
HISTORY
CRNN
BATCHNORM
NETWORK
XNOR
REGION
YOLO
GAUSSIAN_YOLO
ISEG
REORG
REORG_OLD
UPSAMPLE
LOGXENT
L2NORM
EMPTY
BLANK
CONTRASTIVE
IMPLICIT

COST_TYPE

enum COST_TYPE

Enumerator
SSE
MASKED
L1
SEG
SMOOTH
WGAN

learning_rate_policy

enum learning_rate_policy

Enumerator
CONSTANT
STEP
EXP
POLY
STEPS
SIG
RANDOM
SGDR

data_type

enum data_type

Things that we can do on a secondary thread.

See also

load_thread()

load_args::type

Enumerator
CLASSIFICATION_DATA
DETECTION_DATA
REGION_DATA
IMAGE_DATA	causes load_image() and resize_image() to be called
COMPARE_DATA
WRITING_DATA
TAG_DATA
OLD_CLASSIFICATION_DATA
SUPER_DATA
LETTERBOX_DATA

Function Documentation

load_network()

network* load_network	(	char *	cfg,
		char *	weights,
		int	clear
	)

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load_network_custom()

network* load_network_custom	(	char *	cfg,
		char *	weights,
		int	clear,
		int	batch
	)

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free_network()

void free_network

(

network

net

)

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free_network_ptr()

void free_network_ptr

(

network *

net

)

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get_base_args()

load_args get_base_args

(

network *

net

)

do_nms_sort()

void do_nms_sort	(	detection *	dets,
		int	total,
		int	classes,
		float	thresh
	)

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do_nms_obj()

void do_nms_obj	(	detection *	dets,
		int	total,
		int	classes,
		float	thresh
	)

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diounms_sort()

void diounms_sort	(	detection *	dets,
		int	total,
		int	classes,
		float	thresh,
		NMS_KIND	nms_kind,
		float	beta1
	)

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network_predict()

float* network_predict	(	network	net,
		float *	input
	)

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network_predict_ptr()

float* network_predict_ptr	(	network *	net,
		float *	input
	)

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get_network_boxes()

detection* get_network_boxes	(	network *	net,
		int	w,
		int	h,
		float	thresh,
		float	hier,
		int *	map,
		int	relative,
		int *	num,
		int	letter
	)

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network_predict_batch()

det_num_pair* network_predict_batch	(	network *	net,
		image	im,
		int	batch_size,
		int	w,
		int	h,
		float	thresh,
		float	hier,
		int *	map,
		int	relative,
		int	letter
	)

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free_detections()

void free_detections	(	detection *	dets,
		int	n
	)

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free_batch_detections()

void free_batch_detections	(	det_num_pair *	det_num_pairs,
		int	n
	)

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fuse_conv_batchnorm()

void fuse_conv_batchnorm

(

network

net

)

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calculate_binary_weights()

void calculate_binary_weights

(

network

net

)

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detection_to_json()

char* detection_to_json	(	detection *	dets,
		int	nboxes,
		int	classes,
		char **	names,
		long long int	frame_id,
		char *	filename
	)

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get_network_layer()

layer* get_network_layer	(	network *	net,
		int	i
	)

make_network_boxes()

detection* make_network_boxes	(	network *	net,
		float	thresh,
		int *	num
	)

See also

make_network_boxes_batch()

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reset_rnn()

void reset_rnn

(

network *

net

)

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network_predict_image()

float* network_predict_image	(	network *	net,
		image	im
	)

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network_predict_image_letterbox()

float* network_predict_image_letterbox	(	network *	net,
		image	im
	)

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validate_detector_map()

float validate_detector_map	(	char *	datacfg,
		char *	cfgfile,
		char *	weightfile,
		float	thresh_calc_avg_iou,
		const float	iou_thresh,
		const int	map_points,
		int	letter_box,
		network *	existing_net
	)

Todo:

how many cores do we have available?

Todo:

I think this is TP + FN (where the object actually exists, and we either found it, or missed it)

Todo:

would we save anything if net was passed in by reference?

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train_detector()

void train_detector	(	char *	datacfg,
		char *	cfgfile,
		char *	weightfile,
		int *	gpus,
		int	ngpus,
		int	clear,
		int	dont_show,
		int	calc_map,
		float	thresh,
		float	iou_thresh,
		int	mjpeg_port,
		int	show_imgs,
		int	benchmark_layers,
		char *	chart_path
	)

Todo:

copy the weights...?

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test_detector()

void test_detector	(	char *	datacfg,
		char *	cfgfile,
		char *	weightfile,
		char *	filename,
		float	thresh,
		float	hier_thresh,
		int	dont_show,
		int	ext_output,
		int	save_labels,
		char *	outfile,
		int	letter_box,
		int	benchmark_layers
	)

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network_width()

int network_width

(

network *

net

)

network_height()

int network_height

(

network *

net

)

optimize_picture()

void optimize_picture	(	network *	net,
		image	orig,
		int	max_layer,
		float	scale,
		float	rate,
		float	thresh,
		int	norm
	)

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make_image_red()

void make_image_red

(

image

im

)

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make_attention_image()

image make_attention_image	(	int	img_size,
		float *	original_delta_cpu,
		float *	original_input_cpu,
		int	w,
		int	h,
		int	c,
		float	alpha
	)

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resize_image()

image resize_image	(	image	im,
		int	w,
		int	h
	)

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quantize_image()

void quantize_image

(

image

im

)

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copy_image_from_bytes()

void copy_image_from_bytes	(	image	im,
		char *	pdata
	)

letterbox_image()

image letterbox_image	(	image	im,
		int	w,
		int	h
	)

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rgbgr_image()

void rgbgr_image

(

image

im

)

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make_image()

image make_image	(	int	w,
		int	h,
		int	c
	)

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load_image()

image load_image	(	char *	filename,
		int	w,
		int	h,
		int	c
	)

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free_image()

void free_image

(

image

m

)

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crop_image()

image crop_image	(	image	im,
		int	dx,
		int	dy,
		int	w,
		int	h
	)

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resize_min()

image resize_min	(	image	im,
		int	min
	)

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free_layer_custom()

void free_layer_custom	(	layer	l,
		int	keep_cudnn_desc
	)

Todo:

2023-06-26 For now I'd rather ignore this warning than to try and mess with this old code and risk breaking things.

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free_layer()

void free_layer

(

layer

l

)

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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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cuda_set_device()

void cuda_set_device

(

int

n

)

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cuda_get_context()

void* cuda_get_context

(

)

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free_ptrs()

void free_ptrs	(	void **	ptrs,
		int	n
	)

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top_k()

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

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read_tree()

tree* read_tree

(

char *

filename

)

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get_metadata()

metadata get_metadata

(

char *

file

)

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delete_json_sender()

void delete_json_sender

(

)

send_json_custom()

void send_json_custom	(	char const *	send_buf,
		int	port,
		int	timeout
	)

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get_time_point()

double get_time_point

(

)

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start_timer()

void start_timer

(

)

stop_timer()

void stop_timer

(

)

get_time()

double get_time

(

)

stop_timer_and_show()

void stop_timer_and_show

(

)

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stop_timer_and_show_name()

void stop_timer_and_show_name

(

char *

name

)

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show_total_time()

void show_total_time

(

)

set_track_id()

void set_track_id	(	detection *	new_dets,
		int	new_dets_num,
		float	thresh,
		float	sim_thresh,
		float	track_ciou_norm,
		int	deque_size,
		int	dets_for_track,
		int	dets_for_show
	)

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fill_remaining_id()

int fill_remaining_id	(	detection *	new_dets,
		int	new_dets_num,
		int	new_track_id,
		float	thresh
	)

init_cpu()

void init_cpu

(

)

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