diff --git a/src/captcha.c b/src/captcha.c
index 6e02f5ac..ca6dfe06 100644
--- a/src/captcha.c
+++ b/src/captcha.c
@@ -23,7 +23,7 @@ void train_captcha(char *cfgfile, char *weightfile)
     while(1){
         ++i;
         time=clock();
-        data train = load_data_captcha(paths, imgs, plist->size, 10, 60, 200);
+        data train = load_data_captcha(paths, imgs, plist->size, 10, 200, 60);
         translate_data_rows(train, -128);
         scale_data_rows(train, 1./128);
         printf("Loaded: %lf seconds\n", sec(clock()-time));
@@ -56,11 +56,11 @@ void decode_captcha(char *cfgfile, char *weightfile)
         printf("Enter filename: ");
         fgets(filename, 256, stdin);
         strtok(filename, "\n");
-        image im = load_image_color(filename, 57, 300);
+        image im = load_image_color(filename, 300, 57);
         scale_image(im, 1./255.);
         float *X = im.data;
         float *predictions = network_predict(net, X);
-        image out  = float_to_image(57, 300, 1, predictions);
+        image out  = float_to_image(300, 57, 1, predictions);
         show_image(out, "decoded");
         cvWaitKey(0);
         free_image(im);
@@ -87,7 +87,7 @@ void encode_captcha(char *cfgfile, char *weightfile)
     while(1){
         ++i;
         time=clock();
-        data train = load_data_captcha_encode(paths, imgs, plist->size, 57, 300);
+        data train = load_data_captcha_encode(paths, imgs, plist->size, 300, 57);
         scale_data_rows(train, 1./255);
         printf("Loaded: %lf seconds\n", sec(clock()-time));
         time=clock();
@@ -118,7 +118,7 @@ void validate_captcha(char *cfgfile, char *weightfile)
     list *plist = get_paths("/data/captcha/solved.hard");
     char **paths = (char **)list_to_array(plist);
     int imgs = plist->size;
-    data valid = load_data_captcha(paths, imgs, 0, 10, 60, 200);
+    data valid = load_data_captcha(paths, imgs, 0, 10, 200, 60);
     translate_data_rows(valid, -128);
     scale_data_rows(valid, 1./128);
     matrix pred = network_predict_data(net, valid);
@@ -157,7 +157,7 @@ void test_captcha(char *cfgfile, char *weightfile)
         //printf("Enter filename: ");
         fgets(filename, 256, stdin);
         strtok(filename, "\n");
-        image im = load_image_color(filename, 60, 200);
+        image im = load_image_color(filename, 200, 60);
         translate_image(im, -128);
         scale_image(im, 1/128.);
         float *X = im.data;
diff --git a/src/convolutional_layer.c b/src/convolutional_layer.c
index e20a41c8..ade2ac1d 100644
--- a/src/convolutional_layer.c
+++ b/src/convolutional_layer.c
@@ -29,7 +29,7 @@ image get_convolutional_image(convolutional_layer layer)
     h = convolutional_out_height(layer);
     w = convolutional_out_width(layer);
     c = layer.n;
-    return float_to_image(h,w,c,layer.output);
+    return float_to_image(w,h,c,layer.output);
 }
 
 image get_convolutional_delta(convolutional_layer layer)
@@ -38,7 +38,7 @@ image get_convolutional_delta(convolutional_layer layer)
     h = convolutional_out_height(layer);
     w = convolutional_out_width(layer);
     c = layer.n;
-    return float_to_image(h,w,c,layer.delta);
+    return float_to_image(w,h,c,layer.delta);
 }
 
 convolutional_layer *make_convolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, int pad, ACTIVATION activation)
@@ -217,42 +217,22 @@ image get_convolutional_filter(convolutional_layer layer, int i)
     int h = layer.size;
     int w = layer.size;
     int c = layer.c;
-    return float_to_image(h,w,c,layer.filters+i*h*w*c);
+    return float_to_image(w,h,c,layer.filters+i*h*w*c);
 }
 
-image *weighted_sum_filters(convolutional_layer layer, image *prev_filters)
+image *get_filters(convolutional_layer layer)
 {
     image *filters = calloc(layer.n, sizeof(image));
-    int i,j,k,c;
-    if(!prev_filters){
-        for(i = 0; i < layer.n; ++i){
-            filters[i] = copy_image(get_convolutional_filter(layer, i));
-        }
-    }
-    else{
-        image base = prev_filters[0];
-        for(i = 0; i < layer.n; ++i){
-            image filter = get_convolutional_filter(layer, i);
-            filters[i] = make_image(base.h, base.w, base.c);
-            for(j = 0; j < layer.size; ++j){
-                for(k = 0; k < layer.size; ++k){
-                    for(c = 0; c < layer.c; ++c){
-                        float weight = get_pixel(filter, j, k, c);
-                        image prev_filter = copy_image(prev_filters[c]);
-                        scale_image(prev_filter, weight);
-                        add_into_image(prev_filter, filters[i], 0,0);
-                        free_image(prev_filter);
-                    }
-                }
-            }
-        }
+    int i;
+    for(i = 0; i < layer.n; ++i){
+        filters[i] = copy_image(get_convolutional_filter(layer, i));
     }
     return filters;
 }
 
 image *visualize_convolutional_layer(convolutional_layer layer, char *window, image *prev_filters)
 {
-    image *single_filters = weighted_sum_filters(layer, 0);
+    image *single_filters = get_filters(layer);
     show_images(single_filters, layer.n, window);
 
     image delta = get_convolutional_image(layer);
diff --git a/src/crop_layer.c b/src/crop_layer.c
index cf1383ea..819b7547 100644
--- a/src/crop_layer.c
+++ b/src/crop_layer.c
@@ -7,7 +7,7 @@ image get_crop_image(crop_layer layer)
     int h = layer.crop_height;
     int w = layer.crop_width;
     int c = layer.c;
-    return float_to_image(h,w,c,layer.output);
+    return float_to_image(w,h,c,layer.output);
 }
 
 crop_layer *make_crop_layer(int batch, int h, int w, int c, int crop_height, int crop_width, int flip)
diff --git a/src/data.c b/src/data.c
index 6a05d418..c454d84c 100644
--- a/src/data.c
+++ b/src/data.c
@@ -47,7 +47,7 @@ char **get_random_paths(char **paths, int n, int m)
     return random_paths;
 }
 
-matrix load_image_paths(char **paths, int n, int h, int w)
+matrix load_image_paths(char **paths, int n, int w, int h)
 {
     int i;
     matrix X;
@@ -56,7 +56,7 @@ matrix load_image_paths(char **paths, int n, int h, int w)
     X.cols = 0;
 
     for(i = 0; i < n; ++i){
-        image im = load_image_color(paths[i], h, w);
+        image im = load_image_color(paths[i], w, h);
         X.vals[i] = im.data;
         X.cols = im.h*im.w*im.c;
     }
@@ -207,12 +207,12 @@ void fill_truth_captcha(char *path, int n, float *truth)
     }
 }
 
-data load_data_captcha(char **paths, int n, int m, int k, int h, int w)
+data load_data_captcha(char **paths, int n, int m, int k, int w, int h)
 {
     if(m) paths = get_random_paths(paths, n, m);
     data d;
     d.shallow = 0;
-    d.X = load_image_paths(paths, n, h, w);
+    d.X = load_image_paths(paths, n, w, h);
     d.y = make_matrix(n, k*NUMCHARS);
     int i;
     for(i = 0; i < n; ++i){
@@ -222,12 +222,12 @@ data load_data_captcha(char **paths, int n, int m, int k, int h, int w)
     return d;
 }
 
-data load_data_captcha_encode(char **paths, int n, int m, int h, int w)
+data load_data_captcha_encode(char **paths, int n, int m, int w, int h)
 {
     if(m) paths = get_random_paths(paths, n, m);
     data d;
     d.shallow = 0;
-    d.X = load_image_paths(paths, n, h, w);
+    d.X = load_image_paths(paths, n, w, h);
     d.X.cols = 17100;
     d.y = d.X;
     if(m) free(paths);
@@ -258,21 +258,6 @@ matrix load_labels_paths(char **paths, int n, char **labels, int k)
     return y;
 }
 
-data load_data_image_pathfile(char *filename, char **labels, int k, int h, int w)
-{
-    list *plist = get_paths(filename);
-    char **paths = (char **)list_to_array(plist);
-    int n = plist->size;
-    data d;
-    d.shallow = 0;
-    d.X = load_image_paths(paths, n, h, w);
-    d.y = load_labels_paths(paths, n, labels, k);
-    free_list_contents(plist);
-    free_list(plist);
-    free(paths);
-    return d;
-}
-
 char **get_labels(char *filename)
 {
     list *plist = get_paths(filename);
@@ -292,7 +277,7 @@ void free_data(data d)
     }
 }
 
-data load_data_detection_jitter_random(int n, char **paths, int m, int classes, int h, int w, int num_boxes, int background)
+data load_data_detection_jitter_random(int n, char **paths, int m, int classes, int w, int h, int num_boxes, int background)
 {
     char **random_paths = get_random_paths(paths, n, m);
     int i;
@@ -325,12 +310,12 @@ data load_data_detection_jitter_random(int n, char **paths, int m, int classes,
         float sy = (float)sheight / oh;
 
         int flip = rand()%2;
-        image cropped = crop_image(orig, ptop, pleft, sheight, swidth);
+        image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
         float dx = ((float)pleft/ow)/sx;
         float dy = ((float)ptop /oh)/sy;
 
         free_image(orig);
-        image sized = resize_image(cropped, h, w);
+        image sized = resize_image(cropped, w, h);
         free_image(cropped);
         if(flip) flip_image(sized);
         d.X.vals[i] = sized.data;
@@ -345,14 +330,14 @@ void *load_detection_thread(void *ptr)
 {
     printf("Loading data: %d\n", rand());
     struct load_args a = *(struct load_args*)ptr;
-    *a.d = load_data_detection_jitter_random(a.n, a.paths, a.m, a.classes, a.h, a.w, a.num_boxes, a.background);
+    *a.d = load_data_detection_jitter_random(a.n, a.paths, a.m, a.classes, a.w, a.h, a.num_boxes, a.background);
     translate_data_rows(*a.d, -128);
     scale_data_rows(*a.d, 1./128);
     free(ptr);
     return 0;
 }
 
-pthread_t load_data_detection_thread(int n, char **paths, int m, int classes, int h, int w, int nh, int nw, int background, data *d)
+pthread_t load_data_detection_thread(int n, char **paths, int m, int classes, int w, int h, int nh, int nw, int background, data *d)
 {
     pthread_t thread;
     struct load_args *args = calloc(1, sizeof(struct load_args));
@@ -373,12 +358,12 @@ pthread_t load_data_detection_thread(int n, char **paths, int m, int classes, in
     return thread;
 }
 
-data load_data(char **paths, int n, int m, char **labels, int k, int h, int w)
+data load_data(char **paths, int n, int m, char **labels, int k, int w, int h)
 {
     if(m) paths = get_random_paths(paths, n, m);
     data d;
     d.shallow = 0;
-    d.X = load_image_paths(paths, n, h, w);
+    d.X = load_image_paths(paths, n, w, h);
     d.y = load_labels_paths(paths, n, labels, k);
     if(m) free(paths);
     return d;
@@ -387,14 +372,14 @@ data load_data(char **paths, int n, int m, char **labels, int k, int h, int w)
 void *load_in_thread(void *ptr)
 {
     struct load_args a = *(struct load_args*)ptr;
-    *a.d = load_data(a.paths, a.n, a.m, a.labels, a.k, a.h, a.w);
+    *a.d = load_data(a.paths, a.n, a.m, a.labels, a.k, a.w, a.h);
     translate_data_rows(*a.d, -128);
     scale_data_rows(*a.d, 1./128);
     free(ptr);
     return 0;
 }
 
-pthread_t load_data_thread(char **paths, int n, int m, char **labels, int k, int h, int w, data *d)
+pthread_t load_data_thread(char **paths, int n, int m, char **labels, int k, int w, int h, data *d)
 {
     pthread_t thread;
     struct load_args *args = calloc(1, sizeof(struct load_args));
diff --git a/src/data.h b/src/data.h
index f38a8d00..e0d84d2c 100644
--- a/src/data.h
+++ b/src/data.h
@@ -27,17 +27,17 @@ typedef struct{
 void free_data(data d);
 
 void print_letters(float *pred, int n);
-data load_data_captcha(char **paths, int n, int m, int k, int h, int w);
-data load_data_captcha_encode(char **paths, int n, int m, int h, int w);
-data load_data(char **paths, int n, int m, char **labels, int k, int h, int w);
-pthread_t load_data_thread(char **paths, int n, int m, char **labels, int k, int h, int w, data *d);
+data load_data_captcha(char **paths, int n, int m, int k, int w, int h);
+data load_data_captcha_encode(char **paths, int n, int m, int w, int h);
+data load_data(char **paths, int n, int m, char **labels, int k, int w, int h);
+pthread_t load_data_thread(char **paths, int n, int m, char **labels, int k, int w, int h, data *d);
 
-pthread_t load_data_detection_thread(int n, char **paths, int m, int classes, int h, int w, int nh, int nw, int background, data *d);
-data load_data_detection_jitter_random(int n, char **paths, int m, int classes, int h, int w, int num_boxes, int background);
+pthread_t load_data_detection_thread(int n, char **paths, int m, int classes, int w, int h, int nh, int nw, int background, data *d);
+data load_data_detection_jitter_random(int n, char **paths, int m, int classes, int w, int h, int num_boxes, int background);
 
-data load_data_image_pathfile(char *filename, char **labels, int k, int h, int w);
 data load_cifar10_data(char *filename);
 data load_all_cifar10();
+
 list *get_paths(char *filename);
 char **get_labels(char *filename);
 void get_random_batch(data d, int n, float *X, float *y);
diff --git a/src/deconvolutional_layer.c b/src/deconvolutional_layer.c
index 83147b55..532045c2 100644
--- a/src/deconvolutional_layer.c
+++ b/src/deconvolutional_layer.c
@@ -31,7 +31,7 @@ image get_deconvolutional_image(deconvolutional_layer layer)
     h = deconvolutional_out_height(layer);
     w = deconvolutional_out_width(layer);
     c = layer.n;
-    return float_to_image(h,w,c,layer.output);
+    return float_to_image(w,h,c,layer.output);
 }
 
 image get_deconvolutional_delta(deconvolutional_layer layer)
@@ -40,7 +40,7 @@ image get_deconvolutional_delta(deconvolutional_layer layer)
     h = deconvolutional_out_height(layer);
     w = deconvolutional_out_width(layer);
     c = layer.n;
-    return float_to_image(h,w,c,layer.delta);
+    return float_to_image(w,h,c,layer.delta);
 }
 
 deconvolutional_layer *make_deconvolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, ACTIVATION activation)
diff --git a/src/detection.c b/src/detection.c
index 61ccc31d..1e24418b 100644
--- a/src/detection.c
+++ b/src/detection.c
@@ -83,14 +83,14 @@ void train_detection(char *cfgfile, char *weightfile)
         plist = get_paths("/home/pjreddie/data/voc/trainall.txt");
     }
     paths = (char **)list_to_array(plist);
-    pthread_t load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, net.h, net.w, side, side, background, &buffer);
+    pthread_t load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, net.w, net.h, side, side, background, &buffer);
     clock_t time;
     while(1){
         i += 1;
         time=clock();
         pthread_join(load_thread, 0);
         train = buffer;
-        load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, net.h, net.w, side, side, background, &buffer);
+        load_thread = load_data_detection_thread(imgs, paths, plist->size, classes, net.w, net.h, side, side, background, &buffer);
 
 /*
            image im = float_to_image(im_dim, im_dim, 3, train.X.vals[114]);
@@ -124,6 +124,7 @@ void validate_detection(char *cfgfile, char *weightfile)
     srand(time(0));
 
     list *plist = get_paths("/home/pjreddie/data/voc/val.txt");
+    //list *plist = get_paths("/home/pjreddie/data/voc/val.expanded.txt");
     //list *plist = get_paths("/home/pjreddie/data/voc/train.txt");
     char **paths = (char **)list_to_array(plist);
 
@@ -142,7 +143,7 @@ void validate_detection(char *cfgfile, char *weightfile)
 
     fprintf(stderr, "%d\n", m);
     data val, buffer;
-    pthread_t load_thread = load_data_thread(paths, num, 0, 0, num_output, net.h, net.w, &buffer);
+    pthread_t load_thread = load_data_thread(paths, num, 0, 0, num_output, net.w, net.h, &buffer);
     clock_t time;
     for(i = 1; i <= splits; ++i){
         time=clock();
@@ -151,7 +152,7 @@ void validate_detection(char *cfgfile, char *weightfile)
 
         num = (i+1)*m/splits - i*m/splits;
         char **part = paths+(i*m/splits);
-        if(i != splits) load_thread = load_data_thread(part, num, 0, 0, num_output, net.h, net.w, &buffer);
+        if(i != splits) load_thread = load_data_thread(part, num, 0, 0, num_output, net.w, net.h, &buffer);
 
         fprintf(stderr, "%d: Loaded: %lf seconds\n", i, sec(clock()-time));
         matrix pred = network_predict_data(net, val);
@@ -171,7 +172,9 @@ void validate_detection(char *cfgfile, char *weightfile)
                     h = h*h;
                     float w = pred.vals[j][ci + 3]; //* distance_from_edge(col, num_boxes);
                     w = w*w;
-                    printf("%d %d %f %f %f %f %f\n", (i-1)*m/splits + j, class, scale*pred.vals[j][k+class+background+nuisance], y, x, h, w);
+                    float prob = scale*pred.vals[j][k+class+background+nuisance];
+                    if(prob < .001) continue;
+                    printf("%d %d %f %f %f %f %f\n", (i-1)*m/splits + j, class, prob, y, x, h, w);
                 }
             }
         }
diff --git a/src/image.c b/src/image.c
index 2cfce634..32a51cc5 100644
--- a/src/image.c
+++ b/src/image.c
@@ -53,21 +53,6 @@ void draw_box(image a, int x1, int y1, int x2, int y2, float r, float g, float b
     }
 }
 
-void jitter_image(image a, int h, int w, int dh, int dw)
-{
-    int i,j,k;
-    for(k = 0; k < a.c; ++k){
-        for(i = 0; i < h; ++i){
-            for(j = 0; j < w; ++j){
-                int src = j + dw + (i+dh)*a.w + k*a.w*a.h;
-                int dst = j + i*w + k*w*h;
-                //printf("%d %d\n", src, dst);
-                a.data[dst] = a.data[src];
-            }
-        }
-    }
-}
-
 void flip_image(image a)
 {
     int i,j,k;
@@ -87,7 +72,7 @@ void flip_image(image a)
 image image_distance(image a, image b)
 {
     int i,j;
-    image dist = make_image(a.h, a.w, 1);
+    image dist = make_image(a.w, a.h, 1);
     for(i = 0; i < a.c; ++i){
         for(j = 0; j < a.h*a.w; ++j){
             dist.data[j] += pow(a.data[i*a.h*a.w+j]-b.data[i*a.h*a.w+j],2);
@@ -99,20 +84,14 @@ image image_distance(image a, image b)
     return dist;
 }
 
-void subtract_image(image a, image b)
+void embed_image(image source, image dest, int dx, int dy)
 {
-    int i;
-    for(i = 0; i < a.h*a.w*a.c; ++i) a.data[i] -= b.data[i];
-}
-
-void embed_image(image source, image dest, int h, int w)
-{
-    int i,j,k;
+    int x,y,k;
     for(k = 0; k < source.c; ++k){
-        for(i = 0; i < source.h; ++i){
-            for(j = 0; j < source.w; ++j){
-                float val = get_pixel(source, i,j,k);
-                set_pixel(dest, h+i, w+j, k, val);
+        for(y = 0; y < source.h; ++y){
+            for(x = 0; x < source.w; ++x){
+                float val = get_pixel(source, x,y,k);
+                set_pixel(dest, dx+x, dy+y, k, val);
             }
         }
     }
@@ -122,22 +101,17 @@ image collapse_image_layers(image source, int border)
 {
     int h = source.h;
     h = (h+border)*source.c - border;
-    image dest = make_image(h, source.w, 1);
+    image dest = make_image(source.w, h, 1);
     int i;
     for(i = 0; i < source.c; ++i){
         image layer = get_image_layer(source, i);
         int h_offset = i*(source.h+border);
-        embed_image(layer, dest, h_offset, 0);
+        embed_image(layer, dest, 0, h_offset);
         free_image(layer);
     }
     return dest;
 }
 
-void z_normalize_image(image p)
-{
-    normalize_array(p.data, p.h*p.w*p.c);
-}
-
 void normalize_image(image p)
 {
     float *min = calloc(p.c, sizeof(float));
@@ -167,24 +141,6 @@ void normalize_image(image p)
     free(max);
 }
 
-float avg_image_layer(image m, int l)
-{
-    int i;
-    float sum = 0;
-    for(i = 0; i < m.h*m.w; ++i){
-        sum += m.data[l*m.h*m.w + i];
-    }
-    return sum/(m.h*m.w);
-}
-
-void threshold_image(image p, float t)
-{
-    int i;
-    for(i = 0; i < p.w*p.h*p.c; ++i){
-        if(p.data[i] < t) p.data[i] = 0;
-    }
-}
-
 image copy_image(image p)
 {
     image copy = p;
@@ -196,7 +152,7 @@ image copy_image(image p)
 
 void show_image(image p, char *name)
 {
-    int i,j,k;
+    int x,y,k;
     image copy = copy_image(p);
     normalize_image(copy);
 
@@ -209,10 +165,10 @@ void show_image(image p, char *name)
     cvNamedWindow(buff, CV_WINDOW_AUTOSIZE); 
     //cvMoveWindow(buff, 100*(windows%10) + 200*(windows/10), 100*(windows%10));
     ++windows;
-    for(i = 0; i < p.h; ++i){
-        for(j = 0; j < p.w; ++j){
+    for(y = 0; y < p.h; ++y){
+        for(x = 0; x < p.w; ++x){
             for(k= 0; k < p.c; ++k){
-                disp->imageData[i*step + j*p.c + k] = (unsigned char)(get_pixel(copy,i,j,k)*255);
+                disp->imageData[y*step + x*p.c + k] = (unsigned char)(get_pixel(copy,x,y,k)*255);
             }
         }
     }
@@ -235,7 +191,7 @@ void show_image(image p, char *name)
 
 void save_image(image p, char *name)
 {
-    int i,j,k;
+    int x,y,k;
     image copy = copy_image(p);
     normalize_image(copy);
 
@@ -245,10 +201,10 @@ void save_image(image p, char *name)
 
     IplImage *disp = cvCreateImage(cvSize(p.w,p.h), IPL_DEPTH_8U, p.c);
     int step = disp->widthStep;
-    for(i = 0; i < p.h; ++i){
-        for(j = 0; j < p.w; ++j){
+    for(y = 0; y < p.h; ++y){
+        for(x = 0; x < p.w; ++x){
             for(k= 0; k < p.c; ++k){
-                disp->imageData[i*step + j*p.c + k] = (unsigned char)(get_pixel(copy,i,j,k)*255);
+                disp->imageData[y*step + x*p.c + k] = (unsigned char)(get_pixel(copy,x,y,k)*255);
             }
         }
     }
@@ -276,7 +232,7 @@ void show_image_collapsed(image p, char *name)
     free_image(c);
 }
 
-image make_empty_image(int h, int w, int c)
+image make_empty_image(int w, int h, int c)
 {
     image out;
     out.data = 0;
@@ -286,30 +242,20 @@ image make_empty_image(int h, int w, int c)
     return out;
 }
 
-image make_image(int h, int w, int c)
+image make_image(int w, int h, int c)
 {
-    image out = make_empty_image(h,w,c);
+    image out = make_empty_image(w,h,c);
     out.data = calloc(h*w*c, sizeof(float));
     return out;
 }
 
-image float_to_image(int h, int w, int c, float *data)
+image float_to_image(int w, int h, int c, float *data)
 {
-    image out = make_empty_image(h,w,c);
+    image out = make_empty_image(w,h,c);
     out.data = data;
     return out;
 }
 
-void zero_image(image m)
-{
-    memset(m.data, 0, m.h*m.w*m.c*sizeof(float));
-}
-
-void zero_channel(image m, int c)
-{
-    memset(&(m.data[c*m.h*m.w]), 0, m.h*m.w*sizeof(float));
-}
-
 void rotate_image(image m)
 {
     int i,j;
@@ -322,29 +268,6 @@ void rotate_image(image m)
     }
 }
 
-image make_random_image(int h, int w, int c)
-{
-    image out = make_image(h,w,c);
-    int i;
-    for(i = 0; i < h*w*c; ++i){
-        out.data[i] = rand_normal();
-        //out.data[i] = rand()%3;
-    }
-    return out;
-}
-
-void add_into_image(image src, image dest, int h, int w)
-{
-    int i,j,k;
-    for(k = 0; k < src.c; ++k){
-        for(i = 0; i < src.h; ++i){
-            for(j = 0; j < src.w; ++j){
-                add_pixel(dest, h+i, w+j, k, get_pixel(src, i, j, k));
-            }
-        }
-    }
-}
-
 void translate_image(image m, float s)
 {
     int i;
@@ -357,24 +280,6 @@ void scale_image(image m, float s)
     for(i = 0; i < m.h*m.w*m.c; ++i) m.data[i] *= s;
 }
 
-image make_random_kernel(int size, int c, float scale)
-{
-    int pad;
-    if((pad=(size%2==0))) ++size;
-    image out = make_random_image(size,size,c);
-    scale_image(out, scale);
-    int i,k;
-    if(pad){
-        for(k = 0; k < out.c; ++k){
-            for(i = 0; i < size; ++i) {
-                set_pixel(out, i, 0, k, 0);
-                set_pixel(out, 0, i, k, 0);
-            }
-        }
-    }
-    return out;
-}
-
 image ipl_to_image(IplImage* src)
 {
     unsigned char *data = (unsigned char *)src->imageData;
@@ -382,7 +287,7 @@ image ipl_to_image(IplImage* src)
     int w = src->width;
     int c = src->nChannels;
     int step = src->widthStep;
-    image out = make_image(h,w,c);
+    image out = make_image(w, h, c);
     int i, j, k, count=0;;
 
     for(k= 0; k < c; ++k){
@@ -395,47 +300,55 @@ image ipl_to_image(IplImage* src)
     return out;
 }
 
-image crop_image(image im, int dr, int dc, int h, int w)
+image crop_image(image im, int dx, int dy, int w, int h)
 {
-    image cropped = make_image(h, w, im.c);
+    image cropped = make_image(w, h, im.c);
     int i, j, k;
     for(k = 0; k < im.c; ++k){
         for(j = 0; j < h; ++j){
             for(i = 0; i < w; ++i){
-                int r = j + dr;
-                int c = i + dc;
+                int r = j + dy;
+                int c = i + dx;
                 float val = 128;
                 if (r >= 0 && r < im.h && c >= 0 && c < im.w) {
-                    val = get_pixel(im, r, c, k);
+                    val = get_pixel(im, c, r, k);
                 }
-                set_pixel(cropped, j, i, k, val);
+                set_pixel(cropped, i, j, k, val);
             }
         }
     }
     return cropped;
 }
 
-// #wikipedia
-image resize_image(image im, int h, int w)
+float billinear_interpolate(image im, float x, float y, int c)
 {
-    image resized = make_image(h, w, im.c);   
+    int ix = (int) x;
+    int iy = (int) y;
+
+    float dx = x - ix;
+    float dy = y - iy;
+
+    float val = (1-dy) * (1-dx) * get_pixel_extend(im, ix, iy, c) + 
+                dy     * (1-dx) * get_pixel_extend(im, ix, iy+1, c) + 
+                (1-dy) *   dx   * get_pixel_extend(im, ix+1, iy, c) +
+                dy     *   dx   * get_pixel_extend(im, ix+1, iy+1, c);
+    return val;
+}
+
+// #wikipedia
+image resize_image(image im, int w, int h)
+{
+    image resized = make_image(w, h, im.c);   
     int r, c, k;
-    float h_scale = (float)(im.h - 1) / (h - 1) - .00001;
-    float w_scale = (float)(im.w - 1) / (w - 1) - .00001;
+    float w_scale = (float)(im.w - 1) / (w - 1);
+    float h_scale = (float)(im.h - 1) / (h - 1);
     for(k = 0; k < im.c; ++k){
         for(r = 0; r < h; ++r){
             for(c = 0; c < w; ++c){
-                float sr = r*h_scale;
-                float sc = c*w_scale;
-                int ir = (int)sr;
-                int ic = (int)sc;
-                float x = sr-ir;
-                float y = sc-ic;
-                float val = (1-x) * (1-y) * get_pixel(im, ir, ic, k) + 
-                    x     * (1-y) * get_pixel(im, ir+1, ic, k) + 
-                    (1-x) *   y   * get_pixel(im, ir, ic+1, k) +
-                    x     *   y   * get_pixel(im, ir+1, ic+1, k);
-                set_pixel(resized, r, c, k, val);
+                float sx = c*w_scale;
+                float sy = r*h_scale;
+                float val = billinear_interpolate(im, sx, sy, k);
+                set_pixel(resized, c, r, k, val);
             }
         }
     }
@@ -445,10 +358,10 @@ image resize_image(image im, int h, int w)
 void test_resize(char *filename)
 {
     image im = load_image(filename, 0,0);
-    image small = resize_image(im, 63, 65);
-    image big = resize_image(im, 512, 513);
-    image crop = crop_image(im, 10, 50, 100, 100);
-    image crop2 = crop_image(im, -50, -30, 400, 291);
+    image small = resize_image(im, 65, 63);
+    image big = resize_image(im, 513, 512);
+    image crop = crop_image(im, 50, 10, 100, 100);
+    image crop2 = crop_image(im, -30, -50, 291, 400);
     show_image(im, "original");
     show_image(small, "smaller");
     show_image(big, "bigger");
@@ -457,7 +370,7 @@ void test_resize(char *filename)
     cvWaitKey(0);
 }
 
-image load_image_color(char *filename, int h, int w)
+image load_image_color(char *filename, int w, int h)
 {
     IplImage* src = 0;
     if( (src = cvLoadImage(filename, 1)) == 0 )
@@ -467,7 +380,7 @@ image load_image_color(char *filename, int h, int w)
     }
     image out = ipl_to_image(src);
     if((h && w) && (h != out.h || w != out.w)){
-        image resized = resize_image(out, h, w);
+        image resized = resize_image(out, w, h);
         free_image(out);
         out = resized;
     }
@@ -475,7 +388,7 @@ image load_image_color(char *filename, int h, int w)
     return out;
 }
 
-image load_image(char *filename, int h, int w)
+image load_image(char *filename, int w, int h)
 {
     IplImage* src = 0;
     if( (src = cvLoadImage(filename,-1)) == 0 )
@@ -485,7 +398,7 @@ image load_image(char *filename, int h, int w)
     }
     image out = ipl_to_image(src);
     if((h && w) && (h != out.h || w != out.w)){
-        image resized = resize_image(out, h, w);
+        image resized = resize_image(out, w, h);
         free_image(out);
         out = resized;
     }
@@ -495,209 +408,28 @@ image load_image(char *filename, int h, int w)
 
 image get_image_layer(image m, int l)
 {
-    image out = make_image(m.h, m.w, 1);
+    image out = make_image(m.w, m.h, 1);
     int i;
     for(i = 0; i < m.h*m.w; ++i){
         out.data[i] = m.data[i+l*m.h*m.w];
     }
     return out;
 }
-image get_sub_image(image m, int h, int w, int dh, int dw)
-{
-    image out = make_image(dh, dw, m.c);
-    int i,j,k;
-    for(k = 0; k < out.c; ++k){
-        for(i = 0; i < dh; ++i){
-            for(j = 0; j < dw; ++j){
-                float val = get_pixel(m, h+i, w+j, k);
-                set_pixel(out, i, j, k, val);
-            }
-        }
-    }
-    return out;
-}
 
 float get_pixel(image m, int x, int y, int c)
 {
-    assert(x < m.h && y < m.w && c < m.c);
-    return m.data[c*m.h*m.w + x*m.w + y];
+    assert(x < m.w && y < m.h && c < m.c);
+    return m.data[c*m.h*m.w + y*m.w + x];
 }
 float get_pixel_extend(image m, int x, int y, int c)
 {
-    if(x < 0 || x >= m.h || y < 0 || y >= m.w || c < 0 || c >= m.c) return 0;
+    if(x < 0 || x >= m.w || y < 0 || y >= m.h || c < 0 || c >= m.c) return 0;
     return get_pixel(m, x, y, c);
 }
 void set_pixel(image m, int x, int y, int c, float val)
 {
-    assert(x < m.h && y < m.w && c < m.c);
-    m.data[c*m.h*m.w + x*m.w + y] = val;
-}
-void set_pixel_extend(image m, int x, int y, int c, float val)
-{
-    if(x < 0 || x >= m.h || y < 0 || y >= m.w || c < 0 || c >= m.c) return;
-    set_pixel(m, x, y, c, val);
-}
-
-void add_pixel(image m, int x, int y, int c, float val)
-{
-    assert(x < m.h && y < m.w && c < m.c);
-    m.data[c*m.h*m.w + x*m.w + y] += val;
-}
-
-void add_pixel_extend(image m, int x, int y, int c, float val)
-{
-    if(x < 0 || x >= m.h || y < 0 || y >= m.w || c < 0 || c >= m.c) return;
-    add_pixel(m, x, y, c, val);
-}
-
-void two_d_convolve(image m, int mc, image kernel, int kc, int stride, image out, int oc, int edge)
-{
-    int x,y,i,j;
-    int xstart, xend, ystart, yend;
-    if(edge){
-        xstart = ystart = 0;
-        xend = m.h;
-        yend = m.w;
-    }else{
-        xstart = kernel.h/2;
-        ystart = kernel.w/2;
-        xend = m.h-kernel.h/2;
-        yend = m.w - kernel.w/2;
-    }
-    for(x = xstart; x < xend; x += stride){
-        for(y = ystart; y < yend; y += stride){
-            float sum = 0;
-            for(i = 0; i < kernel.h; ++i){
-                for(j = 0; j < kernel.w; ++j){
-                    sum += get_pixel(kernel, i, j, kc)*get_pixel_extend(m, x+i-kernel.h/2, y+j-kernel.w/2, mc);
-                }
-            }
-            add_pixel(out, (x-xstart)/stride, (y-ystart)/stride, oc, sum);
-        }
-    }
-}
-
-float single_convolve(image m, image kernel, int x, int y)
-{
-    float sum = 0;
-    int i, j, k;
-    for(i = 0; i < kernel.h; ++i){
-        for(j = 0; j < kernel.w; ++j){
-            for(k = 0; k < kernel.c; ++k){
-                sum += get_pixel(kernel, i, j, k)*get_pixel_extend(m, x+i-kernel.h/2, y+j-kernel.w/2, k);
-            }
-        }
-    }
-    return sum;
-}
-
-void convolve(image m, image kernel, int stride, int channel, image out, int edge)
-{
-    assert(m.c == kernel.c);
-    int i;
-    zero_channel(out, channel);
-    for(i = 0; i < m.c; ++i){
-        two_d_convolve(m, i, kernel, i, stride, out, channel, edge);
-    }
-    /*
-       int j;
-       for(i = 0; i < m.h; i += stride){
-       for(j = 0; j < m.w; j += stride){
-       float val = single_convolve(m, kernel, i, j);
-       set_pixel(out, i/stride, j/stride, channel, val);
-       }
-       }
-     */
-}
-
-void upsample_image(image m, int stride, image out)
-{
-    int i,j,k;
-    zero_image(out);
-    for(k = 0; k < m.c; ++k){
-        for(i = 0; i < m.h; ++i){
-            for(j = 0; j< m.w; ++j){
-                float val = get_pixel(m, i, j, k);
-                set_pixel(out, i*stride, j*stride, k, val);
-            }
-        }
-    }
-}
-
-void single_update(image m, image update, int x, int y, float error)
-{
-    int i, j, k;
-    for(i = 0; i < update.h; ++i){
-        for(j = 0; j < update.w; ++j){
-            for(k = 0; k < update.c; ++k){
-                float val = get_pixel_extend(m, x+i-update.h/2, y+j-update.w/2, k);
-                add_pixel(update, i, j, k, val*error);
-            }
-        }
-    }
-}
-
-void kernel_update(image m, image update, int stride, int channel, image out, int edge)
-{
-    assert(m.c == update.c);
-    zero_image(update);
-    int i, j, istart, jstart, iend, jend;
-    if(edge){
-        istart = jstart = 0;
-        iend = m.h;
-        jend = m.w;
-    }else{
-        istart = update.h/2;
-        jstart = update.w/2;
-        iend = m.h-update.h/2;
-        jend = m.w - update.w/2;
-    }
-    for(i = istart; i < iend; i += stride){
-        for(j = jstart; j < jend; j += stride){
-            float error = get_pixel(out, (i-istart)/stride, (j-jstart)/stride, channel);
-            single_update(m, update, i, j, error);
-        }
-    }
-    /*
-       for(i = 0; i < update.h*update.w*update.c; ++i){
-       update.data[i] /= (m.h/stride)*(m.w/stride);
-       }
-     */
-}
-
-void single_back_convolve(image m, image kernel, int x, int y, float val)
-{
-    int i, j, k;
-    for(i = 0; i < kernel.h; ++i){
-        for(j = 0; j < kernel.w; ++j){
-            for(k = 0; k < kernel.c; ++k){
-                float pval = get_pixel(kernel, i, j, k) * val;
-                add_pixel_extend(m, x+i-kernel.h/2, y+j-kernel.w/2, k, pval);
-            }
-        }
-    }
-}
-
-void back_convolve(image m, image kernel, int stride, int channel, image out, int edge)
-{
-    assert(m.c == kernel.c);
-    int i, j, istart, jstart, iend, jend;
-    if(edge){
-        istart = jstart = 0;
-        iend = m.h;
-        jend = m.w;
-    }else{
-        istart = kernel.h/2;
-        jstart = kernel.w/2;
-        iend = m.h-kernel.h/2;
-        jend = m.w - kernel.w/2;
-    }
-    for(i = istart; i < iend; i += stride){
-        for(j = jstart; j < jend; j += stride){
-            float val = get_pixel(out, (i-istart)/stride, (j-jstart)/stride, channel);
-            single_back_convolve(m, kernel, i, j, val);
-        }
-    }
+    assert(x < m.w && y < m.h && c < m.c);
+    m.data[c*m.h*m.w + y*m.w + x] = val;
 }
 
 void print_image(image m)
@@ -730,20 +462,20 @@ image collapse_images_vert(image *ims, int n)
         c = 1;
     }
 
-    image filters = make_image(h,w,c);
+    image filters = make_image(w, h, c);
     int i,j;
     for(i = 0; i < n; ++i){
         int h_offset = i*(ims[0].h+border);
         image copy = copy_image(ims[i]);
         //normalize_image(copy);
         if(c == 3 && color){
-            embed_image(copy, filters, h_offset, 0);
+            embed_image(copy, filters, 0, h_offset);
         }
         else{
             for(j = 0; j < copy.c; ++j){
                 int w_offset = j*(ims[0].w+border);
                 image layer = get_image_layer(copy, j);
-                embed_image(layer, filters, h_offset, w_offset);
+                embed_image(layer, filters, w_offset, h_offset);
                 free_image(layer);
             }
         }
@@ -766,20 +498,20 @@ image collapse_images_horz(image *ims, int n)
         c = 1;
     }
 
-    image filters = make_image(h,w,c);
+    image filters = make_image(w, h, c);
     int i,j;
     for(i = 0; i < n; ++i){
         int w_offset = i*(size+border);
         image copy = copy_image(ims[i]);
         //normalize_image(copy);
         if(c == 3 && color){
-            embed_image(copy, filters, 0, w_offset);
+            embed_image(copy, filters, w_offset, 0);
         }
         else{
             for(j = 0; j < copy.c; ++j){
                 int h_offset = j*(size+border);
                 image layer = get_image_layer(copy, j);
-                embed_image(layer, filters, h_offset, w_offset);
+                embed_image(layer, filters, w_offset, h_offset);
                 free_image(layer);
             }
         }
@@ -796,43 +528,6 @@ void show_images(image *ims, int n, char *window)
     free_image(m);
 }
 
-image grid_images(image **ims, int h, int w)
-{
-    int i;
-    image *rows = calloc(h, sizeof(image));
-    for(i = 0; i < h; ++i){
-        rows[i] = collapse_images_horz(ims[i], w);
-    }
-    image out = collapse_images_vert(rows, h);
-    for(i = 0; i < h; ++i){
-        free_image(rows[i]);
-    }
-    free(rows);
-    return out;
-}
-
-void test_grid()
-{
-    int i,j;
-    int num = 3;
-    int topk = 3;
-    image **vizs = calloc(num, sizeof(image*));
-    for(i = 0; i < num; ++i){
-        vizs[i] = calloc(topk, sizeof(image));
-        for(j = 0; j < topk; ++j) vizs[i][j] = make_image(3,3,3);
-    }
-    image grid = grid_images(vizs, num, topk);
-    save_image(grid, "Test Grid");
-    free_image(grid);
-}
-
-void show_images_grid(image **ims, int h, int w, char *window)
-{
-    image out = grid_images(ims, h, w);
-    show_image(out, window);
-    free_image(out);
-}
-
 void free_image(image m)
 {
     free(m.data);
diff --git a/src/image.h b/src/image.h
index 8b36c699..a0d1875e 100644
--- a/src/image.h
+++ b/src/image.h
@@ -12,61 +12,44 @@ typedef struct {
 } image;
 
 float get_color(int c, int x, int max);
-void jitter_image(image a, int h, int w, int dh, int dw);
 void flip_image(image a);
 void draw_box(image a, int x1, int y1, int x2, int y2, float r, float g, float b);
 image image_distance(image a, image b);
 void scale_image(image m, float s);
-image crop_image(image im, int dr, int dc, int h, int w);
-image resize_image(image im, int h, int w);
+image crop_image(image im, int dx, int dy, int w, int h);
+image resize_image(image im, int w, int h);
 void translate_image(image m, float s);
 void normalize_image(image p);
-void z_normalize_image(image p);
-void threshold_image(image p, float t);
-void zero_image(image m);
 void rotate_image(image m);
-void subtract_image(image a, image b);
-float avg_image_layer(image m, int l);
-void embed_image(image source, image dest, int h, int w);
-void add_into_image(image src, image dest, int h, int w);
+void embed_image(image source, image dest, int dx, int dy);
+
 image collapse_image_layers(image source, int border);
 image collapse_images_horz(image *ims, int n);
 image collapse_images_vert(image *ims, int n);
-image get_sub_image(image m, int h, int w, int dh, int dw);
 
 void show_image(image p, char *name);
 void save_image(image p, char *name);
 void show_images(image *ims, int n, char *window);
 void show_image_layers(image p, char *name);
 void show_image_collapsed(image p, char *name);
-void show_images_grid(image **ims, int h, int w, char *window);
-void test_grid();
-image grid_images(image **ims, int h, int w);
+
 void print_image(image m);
 
-image make_image(int h, int w, int c);
-image make_empty_image(int h, int w, int c);
-image make_random_image(int h, int w, int c);
-image make_random_kernel(int size, int c, float scale);
-image float_to_image(int h, int w, int c, float *data);
+image make_image(int w, int h, int c);
+image make_empty_image(int w, int h, int c);
+image float_to_image(int w, int h, int c, float *data);
 image copy_image(image p);
-image load_image(char *filename, int h, int w);
-image load_image_color(char *filename, int h, int w);
+image load_image(char *filename, int w, int h);
+image load_image_color(char *filename, int w, int h);
+
 image ipl_to_image(IplImage* src);
 
 float get_pixel(image m, int x, int y, int c);
 float get_pixel_extend(image m, int x, int y, int c);
-void add_pixel(image m, int x, int y, int c, float val);
 void set_pixel(image m, int x, int y, int c, float val);
 
 image get_image_layer(image m, int l);
 
-void two_d_convolve(image m, int mc, image kernel, int kc, int stride, image out, int oc, int edge);
-void upsample_image(image m, int stride, image out);
-void convolve(image m, image kernel, int stride, int channel, image out, int edge);
-void back_convolve(image m, image kernel, int stride, int channel, image out, int edge);
-void kernel_update(image m, image update, int stride, int channel, image out, int edge);
-
 void free_image(image m);
 void test_resize(char *filename);
 #endif
diff --git a/src/maxpool_layer.c b/src/maxpool_layer.c
index 790cb287..76402fa7 100644
--- a/src/maxpool_layer.c
+++ b/src/maxpool_layer.c
@@ -7,7 +7,7 @@ image get_maxpool_image(maxpool_layer layer)
     int h = (layer.h-1)/layer.stride + 1;
     int w = (layer.w-1)/layer.stride + 1;
     int c = layer.c;
-    return float_to_image(h,w,c,layer.output);
+    return float_to_image(w,h,c,layer.output);
 }
 
 image get_maxpool_delta(maxpool_layer layer)
@@ -15,7 +15,7 @@ image get_maxpool_delta(maxpool_layer layer)
     int h = (layer.h-1)/layer.stride + 1;
     int w = (layer.w-1)/layer.stride + 1;
     int c = layer.c;
-    return float_to_image(h,w,c,layer.delta);
+    return float_to_image(w,h,c,layer.delta);
 }
 
 maxpool_layer *make_maxpool_layer(int batch, int h, int w, int c, int size, int stride)
diff --git a/src/normalization_layer.c b/src/normalization_layer.c
index 3ab318b6..93c2ad94 100644
--- a/src/normalization_layer.c
+++ b/src/normalization_layer.c
@@ -6,7 +6,7 @@ image get_normalization_image(normalization_layer layer)
     int h = layer.h;
     int w = layer.w;
     int c = layer.c;
-    return float_to_image(h,w,c,layer.output);
+    return float_to_image(w,h,c,layer.output);
 }
 
 image get_normalization_delta(normalization_layer layer)
@@ -14,7 +14,7 @@ image get_normalization_delta(normalization_layer layer)
     int h = layer.h;
     int w = layer.w;
     int c = layer.c;
-    return float_to_image(h,w,c,layer.delta);
+    return float_to_image(w,h,c,layer.delta);
 }
 
 normalization_layer *make_normalization_layer(int batch, int h, int w, int c, int size, float alpha, float beta, float kappa)
diff --git a/src/parser.h b/src/parser.h
index 2e8190e3..b16cc037 100644
--- a/src/parser.h
+++ b/src/parser.h
@@ -6,5 +6,6 @@ network parse_network_cfg(char *filename);
 void save_network(network net, char *filename);
 void save_weights(network net, char *filename);
 void load_weights(network *net, char *filename);
+void load_weights_upto(network *net, char *filename, int cutoff);
 
 #endif