| | |
| | | int h, w, c; |
| | | int max_crop; |
| | | int min_crop; |
| | | int flip; // horizontal flip 50% probability augmentaiont for classifier training (default = 1) |
| | | float angle; |
| | | float aspect; |
| | | float exposure; |
| | |
| | | void set_batch_network(network *net, int b); |
| | | int get_network_input_size(network net); |
| | | float get_network_cost(network net); |
| | | YOLODLL_API layer* get_network_layer(network* net, int i); |
| | | YOLODLL_API detection *get_network_boxes(network *net, int w, int h, float thresh, float hier, int *map, int relative, int *num, int letter); |
| | | YOLODLL_API detection *make_network_boxes(network *net, float thresh, int *num); |
| | | YOLODLL_API void free_detections(detection *dets, int n); |
| | | YOLODLL_API void reset_rnn(network *net); |
| | | YOLODLL_API network *load_network_custom(char *cfg, char *weights, int clear, int batch); |
| | | YOLODLL_API network *load_network(char *cfg, char *weights, int clear); |
| | | YOLODLL_API float *network_predict_image(network *net, image im); |
| | | YOLODLL_API void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, int ngpus, int clear, int dont_show); |
| | | YOLODLL_API int network_width(network *net); |
| | | YOLODLL_API int network_height(network *net); |
| | | |
| | | YOLODLL_API void optimize_picture(network *net, image orig, int max_layer, float scale, float rate, float thresh, int norm); |
| | | |
| | | int get_network_nuisance(network net); |
| | | int get_network_background(network net); |
| | | void fuse_conv_batchnorm(network net); |
| | | YOLODLL_API void fuse_conv_batchnorm(network net); |
| | | |
| | | #ifdef __cplusplus |
| | | } |