diff --git a/Makefile b/Makefile index 366faef160f2fc04e732928649908890f375c38f..f3e4b792dd3dfefa9607dcbd28d7ad6088892133 100644 --- a/Makefile +++ b/Makefile @@ -1,5 +1,5 @@ GPU=1 -CUDNN=0 +CUDNN=1 OPENCV=1 DEBUG=0 diff --git a/src/coco_demo.c b/src/coco_demo.c index c516f783a52ec26b4a618e77ddc287fe3742aa44..e5e9087835a0aab2c98e58446cdc179210132d82 100644 --- a/src/coco_demo.c +++ b/src/coco_demo.c @@ -10,8 +10,8 @@ #define FRAMES 1 #ifdef OPENCV -#include "opencv2/highgui/highgui.hpp" -#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/highgui/highgui_c.h" +#include "opencv2/imgproc/imgproc_c.h" void convert_coco_detections(float *predictions, int classes, int num, int square, int side, int w, int h, float thresh, float **probs, box *boxes, int only_objectness); extern char *coco_classes[]; diff --git a/src/network.c b/src/network.c index 88b70857cdf314fbf17fdd14063f0cab71348d37..b617f7e8ab205dcbc2e36483ce8463304d837246 100644 --- a/src/network.c +++ b/src/network.c @@ -253,6 +253,7 @@ void backward_network(network net, network_state state) int i; float *original_input = state.input; float *original_delta = state.delta; + state.workspace = net.workspace; for(i = net.n-1; i >= 0; --i){ state.index = i; if(i == 0){ diff --git a/src/rnn.c b/src/rnn.c index 5e229baab6ce7f9d5833b0655797409ff98d7e78..cda38ef8ae49c0275d14570a790cad57772b0899 100644 --- a/src/rnn.c +++ b/src/rnn.c @@ -199,7 +199,7 @@ void train_char_rnn(char *cfgfile, char *weightfile, char *filename, int clear, } } - if(i%100==0){ + if(i%1000==0){ char buff[256]; sprintf(buff, "%s/%s_%d.weights", backup_directory, base, i); save_weights(net, buff); diff --git a/src/yolo_demo.c b/src/yolo_demo.c index 194a2362a28f5150eb3f7ceca419ae36e7e3bf1f..ec2998459db1a4226cd8d65b53ccf0fe6bcf7512 100644 --- a/src/yolo_demo.c +++ b/src/yolo_demo.c @@ -8,8 +8,8 @@ #include <sys/time.h> #ifdef OPENCV -#include "opencv2/highgui/highgui.hpp" -#include "opencv2/imgproc/imgproc.hpp" +#include "opencv2/highgui/highgui_c.h" +#include "opencv2/imgproc/imgproc_c.h" image ipl_to_image(IplImage* src); void convert_yolo_detections(float *predictions, int classes, int num, int square, int side, int w, int h, float thresh, float **probs, box *boxes, int only_objectness);