From 1b5afb45838e603fa6780762eb8cc59246dc2d81 Mon Sep 17 00:00:00 2001
From: IlyaOvodov <b@ovdv.ru>
Date: Tue, 08 May 2018 11:09:35 +0000
Subject: [PATCH] Output improvements for detector results: When printing detector results, output was done in random order, obfuscating results for interpreting. Now: 1. Text output includes coordinates of rects in (left,right,top,bottom in pixels) along with label and score 2. Text output is sorted by rect lefts to simplify finding appropriate rects on image 3. If several class probs are > thresh for some detection, the most probable is written first and coordinates for others are not repeated 4. Rects are imprinted in image in order by their best class prob, so most probable rects are always on top and not overlayed by less probable ones 5. Most probable label for rect is always written first Also: 6. Message about low GPU memory include required amount
---
src/image.c | 510 +++++++++++++++++++++++++++++++++++++++++++++++++-------
1 files changed, 441 insertions(+), 69 deletions(-)
diff --git a/src/image.c b/src/image.c
index b063a68..14105c7 100644
--- a/src/image.c
+++ b/src/image.c
@@ -13,8 +13,14 @@
#ifdef OPENCV
#include "opencv2/highgui/highgui_c.h"
#include "opencv2/imgproc/imgproc_c.h"
+#include "opencv2/core/version.hpp"
+#ifndef CV_VERSION_EPOCH
+#include "opencv2/videoio/videoio_c.h"
+#include "opencv2/imgcodecs/imgcodecs_c.h"
+#include "http_stream.h"
#endif
-
+#include "http_stream.h"
+#endif
int windows = 0;
@@ -31,6 +37,35 @@
return r;
}
+static float get_pixel(image m, int x, int y, int c)
+{
+ assert(x < m.w && y < m.h && c < m.c);
+ return m.data[c*m.h*m.w + y*m.w + x];
+}
+static float get_pixel_extend(image m, int x, int y, int c)
+{
+ if (x < 0 || x >= m.w || y < 0 || y >= m.h) return 0;
+ /*
+ if(x < 0) x = 0;
+ if(x >= m.w) x = m.w-1;
+ if(y < 0) y = 0;
+ if(y >= m.h) y = m.h-1;
+ */
+ if (c < 0 || c >= m.c) return 0;
+ return get_pixel(m, x, y, c);
+}
+static void set_pixel(image m, int x, int y, int c, float val)
+{
+ if (x < 0 || y < 0 || c < 0 || x >= m.w || y >= m.h || c >= m.c) return;
+ assert(x < m.w && y < m.h && c < m.c);
+ m.data[c*m.h*m.w + y*m.w + x] = val;
+}
+static void add_pixel(image m, int x, int y, int c, float val)
+{
+ assert(x < m.w && y < m.h && c < m.c);
+ m.data[c*m.h*m.w + y*m.w + x] += val;
+}
+
void composite_image(image source, image dest, int dx, int dy)
{
int x,y,k;
@@ -87,6 +122,23 @@
return b;
}
+image get_label_v3(image **characters, char *string, int size)
+{
+ size = size / 10;
+ if (size > 7) size = 7;
+ image label = make_empty_image(0, 0, 0);
+ while (*string) {
+ image l = characters[size][(int)*string];
+ image n = tile_images(label, l, -size - 1 + (size + 1) / 2);
+ free_image(label);
+ label = n;
+ ++string;
+ }
+ image b = border_image(label, label.h*.25);
+ free_image(label);
+ return b;
+}
+
void draw_label(image a, int r, int c, image label, const float *rgb)
{
int w = label.w;
@@ -177,15 +229,162 @@
return alphabets;
}
+
+
+// Creates array of detections with prob > thresh and fills best_class for them
+detection_with_class* get_actual_detections(detection *dets, int dets_num, float thresh, int* selected_detections_num)
+{
+ int selected_num = 0;
+ detection_with_class* result_arr = calloc(dets_num, sizeof(detection_with_class));
+ for (int i = 0; i < dets_num; ++i) {
+ int best_class = -1;
+ float best_class_prob = thresh;
+ for (int j = 0; j < dets[i].classes; ++j) {
+ if (dets[i].prob[j] > best_class_prob ) {
+ best_class = j;
+ best_class_prob = dets[i].prob[j];
+ }
+ }
+ if (best_class >= 0) {
+ result_arr[selected_num].det = dets[i];
+ result_arr[selected_num].best_class = best_class;
+ ++selected_num;
+ }
+ }
+ if (selected_detections_num)
+ *selected_detections_num = selected_num;
+ return result_arr;
+}
+
+// compare to sort detection** by bbox.x
+int compare_by_lefts(const void *a_ptr, const void *b_ptr) {
+ const detection_with_class* a = (detection_with_class*)a_ptr;
+ const detection_with_class* b = (detection_with_class*)b_ptr;
+ const float delta = (a->det.bbox.x - a->det.bbox.w/2) - (b->det.bbox.x - b->det.bbox.w/2);
+ return delta < 0 ? -1 : delta > 0 ? 1 : 0;
+}
+
+// compare to sort detection** by best_class probability
+int compare_by_probs(const void *a_ptr, const void *b_ptr) {
+ const detection_with_class* a = (detection_with_class*)a_ptr;
+ const detection_with_class* b = (detection_with_class*)b_ptr;
+ float delta = a->det.prob[a->best_class] - b->det.prob[b->best_class];
+ return delta < 0 ? -1 : delta > 0 ? 1 : 0;
+}
+
+void draw_detections_v3(image im, detection *dets, int num, float thresh, char **names, image **alphabet, int classes, int ext_output)
+{
+ int selected_detections_num;
+ detection_with_class* selected_detections = get_actual_detections(dets, num, thresh, &selected_detections_num);
+
+ // text output
+ qsort(selected_detections, selected_detections_num, sizeof(*selected_detections), compare_by_lefts);
+ for (int i = 0; i < selected_detections_num; ++i) {
+ const int best_class = selected_detections[i].best_class;
+ printf("%s: %.0f%%", names[best_class], selected_detections[i].det.prob[best_class] * 100);
+ if (ext_output)
+ printf("\t(left: %.0f\ttop: %.0f\tw: %0.f\th: %0.f)\n",
+ (selected_detections[i].det.bbox.x - selected_detections[i].det.bbox.w / 2)*im.w,
+ (selected_detections[i].det.bbox.y - selected_detections[i].det.bbox.h / 2)*im.h,
+ selected_detections[i].det.bbox.w*im.w, selected_detections[i].det.bbox.h*im.h);
+ else
+ printf("\n");
+ for (int j = 0; j < classes; ++j) {
+ if (selected_detections[i].det.prob[j] > thresh && j != best_class) {
+ printf("%s: %.0f%%\n", names[j], selected_detections[i].det.prob[j] * 100);
+ }
+ }
+ }
+
+ // image output
+ qsort(selected_detections, selected_detections_num, sizeof(*selected_detections), compare_by_probs);
+ for (int i = 0; i < selected_detections_num; ++i) {
+ int width = im.h * .006;
+ if (width < 1)
+ width = 1;
+
+ /*
+ if(0){
+ width = pow(prob, 1./2.)*10+1;
+ alphabet = 0;
+ }
+ */
+
+ //printf("%d %s: %.0f%%\n", i, names[selected_detections[i].best_class], prob*100);
+ int offset = selected_detections[i].best_class * 123457 % classes;
+ float red = get_color(2, offset, classes);
+ float green = get_color(1, offset, classes);
+ float blue = get_color(0, offset, classes);
+ float rgb[3];
+
+ //width = prob*20+2;
+
+ rgb[0] = red;
+ rgb[1] = green;
+ rgb[2] = blue;
+ box b = selected_detections[i].det.bbox;
+ //printf("%f %f %f %f\n", b.x, b.y, b.w, b.h);
+
+ int left = (b.x - b.w / 2.)*im.w;
+ int right = (b.x + b.w / 2.)*im.w;
+ int top = (b.y - b.h / 2.)*im.h;
+ int bot = (b.y + b.h / 2.)*im.h;
+
+ if (left < 0) left = 0;
+ if (right > im.w - 1) right = im.w - 1;
+ if (top < 0) top = 0;
+ if (bot > im.h - 1) bot = im.h - 1;
+
+ //int b_x_center = (left + right) / 2;
+ //int b_y_center = (top + bot) / 2;
+ //int b_width = right - left;
+ //int b_height = bot - top;
+ //sprintf(labelstr, "%d x %d - w: %d, h: %d", b_x_center, b_y_center, b_width, b_height);
+
+ draw_box_width(im, left, top, right, bot, width, red, green, blue);
+ if (alphabet) {
+ char labelstr[4096] = { 0 };
+ strcat(labelstr, names[selected_detections[i].best_class]);
+ for (int j = 0; j < classes; ++j) {
+ if (selected_detections[i].det.prob[j] > thresh && j != selected_detections[i].best_class) {
+ strcat(labelstr, ", ");
+ strcat(labelstr, names[j]);
+ }
+ }
+ image label = get_label_v3(alphabet, labelstr, (im.h*.03));
+ draw_label(im, top + width, left, label, rgb);
+ free_image(label);
+ }
+ if (selected_detections[i].det.mask) {
+ image mask = float_to_image(14, 14, 1, selected_detections[i].det.mask);
+ image resized_mask = resize_image(mask, b.w*im.w, b.h*im.h);
+ image tmask = threshold_image(resized_mask, .5);
+ embed_image(tmask, im, left, top);
+ free_image(mask);
+ free_image(resized_mask);
+ free_image(tmask);
+ }
+ }
+ free(selected_detections);
+}
+
void draw_detections(image im, int num, float thresh, box *boxes, float **probs, char **names, image **alphabet, int classes)
{
int i;
for(i = 0; i < num; ++i){
- int class = max_index(probs[i], classes);
- float prob = probs[i][class];
+ int class_id = max_index(probs[i], classes);
+ float prob = probs[i][class_id];
if(prob > thresh){
+ //// for comparison with OpenCV version of DNN Darknet Yolo v2
+ //printf("\n %f, %f, %f, %f, ", boxes[i].x, boxes[i].y, boxes[i].w, boxes[i].h);
+ // int k;
+ //for (k = 0; k < classes; ++k) {
+ // printf("%f, ", probs[i][k]);
+ //}
+ //printf("\n");
+
int width = im.h * .012;
if(0){
@@ -193,8 +392,7 @@
alphabet = 0;
}
- printf("%s: %.0f%%\n", names[class], prob*100);
- int offset = class*123457 % classes;
+ int offset = class_id*123457 % classes;
float red = get_color(2,offset,classes);
float green = get_color(1,offset,classes);
float blue = get_color(0,offset,classes);
@@ -216,10 +414,15 @@
if(right > im.w-1) right = im.w-1;
if(top < 0) top = 0;
if(bot > im.h-1) bot = im.h-1;
+ printf("%s: %.0f%%", names[class_id], prob * 100);
+
+ //printf(" - id: %d, x_center: %d, y_center: %d, width: %d, height: %d",
+ // class_id, (right + left) / 2, (bot - top) / 2, right - left, bot - top);
+ printf("\n");
draw_box_width(im, left, top, right, bot, width, red, green, blue);
if (alphabet) {
- image label = get_label(alphabet, names[class], (im.h*.03)/10);
+ image label = get_label(alphabet, names[class_id], (im.h*.03)/10);
draw_label(im, top + width, left, label, rgb);
}
}
@@ -227,13 +430,106 @@
}
#ifdef OPENCV
+
+void draw_detections_cv_v3(IplImage* show_img, detection *dets, int num, float thresh, char **names, image **alphabet, int classes)
+{
+ int i, j;
+ if (!show_img) return;
+
+ for (i = 0; i < num; ++i) {
+ char labelstr[4096] = { 0 };
+ int class_id = -1;
+ for (j = 0; j < classes; ++j) {
+ if (dets[i].prob[j] > thresh) {
+ if (class_id < 0) {
+ strcat(labelstr, names[j]);
+ class_id = j;
+ }
+ else {
+ strcat(labelstr, ", ");
+ strcat(labelstr, names[j]);
+ }
+ printf("%s: %.0f%%\n", names[j], dets[i].prob[j] * 100);
+ }
+ }
+ if (class_id >= 0) {
+ int width = show_img->height * .006;
+
+ /*
+ if(0){
+ width = pow(prob, 1./2.)*10+1;
+ alphabet = 0;
+ }
+ */
+
+ //printf("%d %s: %.0f%%\n", i, names[class_id], prob*100);
+ int offset = class_id * 123457 % classes;
+ float red = get_color(2, offset, classes);
+ float green = get_color(1, offset, classes);
+ float blue = get_color(0, offset, classes);
+ float rgb[3];
+
+ //width = prob*20+2;
+
+ rgb[0] = red;
+ rgb[1] = green;
+ rgb[2] = blue;
+ box b = dets[i].bbox;
+ //printf("%f %f %f %f\n", b.x, b.y, b.w, b.h);
+
+ int left = (b.x - b.w / 2.)*show_img->width;
+ int right = (b.x + b.w / 2.)*show_img->width;
+ int top = (b.y - b.h / 2.)*show_img->height;
+ int bot = (b.y + b.h / 2.)*show_img->height;
+
+ if (left < 0) left = 0;
+ if (right > show_img->width - 1) right = show_img->width - 1;
+ if (top < 0) top = 0;
+ if (bot > show_img->height - 1) bot = show_img->height - 1;
+
+ //int b_x_center = (left + right) / 2;
+ //int b_y_center = (top + bot) / 2;
+ //int b_width = right - left;
+ //int b_height = bot - top;
+ //sprintf(labelstr, "%d x %d - w: %d, h: %d", b_x_center, b_y_center, b_width, b_height);
+
+ float const font_size = show_img->height / 1000.F;
+ CvPoint pt1, pt2, pt_text, pt_text_bg1, pt_text_bg2;
+ pt1.x = left;
+ pt1.y = top;
+ pt2.x = right;
+ pt2.y = bot;
+ pt_text.x = left;
+ pt_text.y = top - 12;
+ pt_text_bg1.x = left;
+ pt_text_bg1.y = top - (10 + 25 * font_size);
+ pt_text_bg2.x = right;
+ pt_text_bg2.y = top;
+ CvScalar color;
+ color.val[0] = red * 256;
+ color.val[1] = green * 256;
+ color.val[2] = blue * 256;
+
+ cvRectangle(show_img, pt1, pt2, color, width, 8, 0);
+ //printf("left=%d, right=%d, top=%d, bottom=%d, obj_id=%d, obj=%s \n", left, right, top, bot, class_id, names[class_id]);
+ cvRectangle(show_img, pt_text_bg1, pt_text_bg2, color, width, 8, 0);
+ cvRectangle(show_img, pt_text_bg1, pt_text_bg2, color, CV_FILLED, 8, 0); // filled
+ CvScalar black_color;
+ black_color.val[0] = 0;
+ CvFont font;
+ cvInitFont(&font, CV_FONT_HERSHEY_SIMPLEX, font_size, font_size, 0, font_size * 3, 8);
+ cvPutText(show_img, labelstr, pt_text, &font, black_color);
+ }
+ }
+}
+
void draw_detections_cv(IplImage* show_img, int num, float thresh, box *boxes, float **probs, char **names, image **alphabet, int classes)
{
int i;
for (i = 0; i < num; ++i) {
- int class = max_index(probs[i], classes);
- float prob = probs[i][class];
+ int class_id = max_index(probs[i], classes);
+ float prob = probs[i][class_id];
if (prob > thresh) {
int width = show_img->height * .012;
@@ -243,8 +539,8 @@
alphabet = 0;
}
- printf("%s: %.0f%%\n", names[class], prob * 100);
- int offset = class * 123457 % classes;
+ printf("%s: %.0f%%\n", names[class_id], prob * 100);
+ int offset = class_id * 123457 % classes;
float red = get_color(2, offset, classes);
float green = get_color(1, offset, classes);
float blue = get_color(0, offset, classes);
@@ -285,18 +581,88 @@
color.val[2] = blue * 256;
cvRectangle(show_img, pt1, pt2, color, width, 8, 0);
-
+ //printf("left=%d, right=%d, top=%d, bottom=%d, obj_id=%d, obj=%s \n", left, right, top, bot, class_id, names[class_id]);
cvRectangle(show_img, pt_text_bg1, pt_text_bg2, color, width, 8, 0);
cvRectangle(show_img, pt_text_bg1, pt_text_bg2, color, CV_FILLED, 8, 0); // filled
CvScalar black_color;
black_color.val[0] = 0;
CvFont font;
- cvInitFont(&font, CV_FONT_HERSHEY_COMPLEX, font_size, font_size, 0, font_size*3, 8);
- cvPutText(show_img, names[class], pt_text, &font, black_color);
+ cvInitFont(&font, CV_FONT_HERSHEY_SIMPLEX, font_size, font_size, 0, font_size * 3, 8);
+ cvPutText(show_img, names[class_id], pt_text, &font, black_color);
}
}
}
-#endif
+
+IplImage* draw_train_chart(float max_img_loss, int max_batches, int number_of_lines, int img_size)
+{
+ int img_offset = 50;
+ int draw_size = img_size - img_offset;
+ IplImage* img = cvCreateImage(cvSize(img_size, img_size), 8, 3);
+ cvSet(img, CV_RGB(255, 255, 255), 0);
+ CvPoint pt1, pt2, pt_text;
+ CvFont font;
+ cvInitFont(&font, CV_FONT_HERSHEY_COMPLEX_SMALL, 0.7, 0.7, 0, 1, CV_AA);
+ char char_buff[100];
+ int i;
+ // vertical lines
+ pt1.x = img_offset; pt2.x = img_size, pt_text.x = 10;
+ for (i = 1; i <= number_of_lines; ++i) {
+ pt1.y = pt2.y = (float)i * draw_size / number_of_lines;
+ cvLine(img, pt1, pt2, CV_RGB(224, 224, 224), 1, 8, 0);
+ if (i % 10 == 0) {
+ sprintf(char_buff, "%2.1f", max_img_loss*(number_of_lines - i) / number_of_lines);
+ pt_text.y = pt1.y + 5;
+ cvPutText(img, char_buff, pt_text, &font, CV_RGB(0, 0, 0));
+ cvLine(img, pt1, pt2, CV_RGB(128, 128, 128), 1, 8, 0);
+ }
+ }
+ // horizontal lines
+ pt1.y = draw_size; pt2.y = 0, pt_text.y = draw_size + 15;
+ for (i = 0; i <= number_of_lines; ++i) {
+ pt1.x = pt2.x = img_offset + (float)i * draw_size / number_of_lines;
+ cvLine(img, pt1, pt2, CV_RGB(224, 224, 224), 1, 8, 0);
+ if (i % 10 == 0) {
+ sprintf(char_buff, "%d", max_batches * i / number_of_lines);
+ pt_text.x = pt1.x - 20;
+ cvPutText(img, char_buff, pt_text, &font, CV_RGB(0, 0, 0));
+ cvLine(img, pt1, pt2, CV_RGB(128, 128, 128), 1, 8, 0);
+ }
+ }
+ cvPutText(img, "Iteration number", cvPoint(draw_size / 2, img_size - 10), &font, CV_RGB(0, 0, 0));
+ cvPutText(img, "Press 's' to save: chart.jpg", cvPoint(5, img_size - 10), &font, CV_RGB(0, 0, 0));
+ printf(" If error occurs - run training with flag: -dont_show \n");
+ cvNamedWindow("average loss", CV_WINDOW_NORMAL);
+ cvMoveWindow("average loss", 0, 0);
+ cvResizeWindow("average loss", img_size, img_size);
+ cvShowImage("average loss", img);
+ cvWaitKey(20);
+ return img;
+}
+
+void draw_train_loss(IplImage* img, int img_size, float avg_loss, float max_img_loss, int current_batch, int max_batches)
+{
+ int img_offset = 50;
+ int draw_size = img_size - img_offset;
+ CvFont font;
+ cvInitFont(&font, CV_FONT_HERSHEY_COMPLEX_SMALL, 0.7, 0.7, 0, 1, CV_AA);
+ char char_buff[100];
+ CvPoint pt1, pt2;
+ pt1.x = img_offset + draw_size * (float)current_batch / max_batches;
+ pt1.y = draw_size * (1 - avg_loss / max_img_loss);
+ if (pt1.y < 0) pt1.y = 1;
+ cvCircle(img, pt1, 1, CV_RGB(0, 0, 255), CV_FILLED, 8, 0);
+
+ sprintf(char_buff, "current avg loss = %2.4f", avg_loss);
+ pt1.x = img_size / 2, pt1.y = 30;
+ pt2.x = pt1.x + 250, pt2.y = pt1.y + 20;
+ cvRectangle(img, pt1, pt2, CV_RGB(255, 255, 255), CV_FILLED, 8, 0);
+ pt1.y += 15;
+ cvPutText(img, char_buff, pt1, &font, CV_RGB(0, 0, 0));
+ cvShowImage("average loss", img);
+ int k = cvWaitKey(20);
+ if (k == 's' || current_batch == (max_batches-1)) cvSaveImage("chart.jpg", img, 0);
+}
+#endif // OPENCV
void transpose_image(image im)
{
@@ -524,30 +890,7 @@
//cvMoveWindow(buff, 100*(windows%10) + 200*(windows/10), 100*(windows%10));
++windows;
cvShowImage(buff, disp);
-
-
- {
- CvSize size;
- {
- size.width = disp->width, size.height = disp->height;
- }
-
- static CvVideoWriter* output_video = NULL; // cv::VideoWriter output_video;
- if (output_video == NULL)
- {
- //printf("\n SRC output_video = %p \n", output_video);
- const char* output_name = "test_dnn_out.avi";
- //output_video = cvCreateVideoWriter(output_name, CV_FOURCC('H', '2', '6', '4'), 25, size, 1);
- output_video = cvCreateVideoWriter(output_name, CV_FOURCC('D', 'I', 'V', 'X'), 25, size, 1);
- //output_video = cvCreateVideoWriter(output_name, CV_FOURCC('M', 'J', 'P', 'G'), 25, size, 1);
- //printf("\n cvCreateVideoWriter, DST output_video = %p \n", output_video);
- }
-
- //cvWriteFrame(output_video, disp); // comment this line to improve FPS !!!
- printf("\n cvWriteFrame \n");
- }
-
- cvReleaseImage(&disp);
+ //cvReleaseImage(&disp);
}
#endif
@@ -618,9 +961,12 @@
return im;
}
-image get_image_from_stream_resize(CvCapture *cap, int w, int h, IplImage** in_img)
+image get_image_from_stream_resize(CvCapture *cap, int w, int h, IplImage** in_img, int use_webcam)
{
- IplImage* src = cvQueryFrame(cap);
+ IplImage* src;
+ if (use_webcam) src = get_webcam_frame(cap);
+ else src = cvQueryFrame(cap);
+
if (!src) return make_empty_image(0, 0, 0);
IplImage* new_img = cvCreateImage(cvSize(w, h), IPL_DEPTH_8U, 3);
*in_img = cvCreateImage(cvSize(src->width, src->height), IPL_DEPTH_8U, 3);
@@ -877,6 +1223,51 @@
#endif
}
+void fill_image(image m, float s)
+{
+ int i;
+ for (i = 0; i < m.h*m.w*m.c; ++i) m.data[i] = s;
+}
+
+void letterbox_image_into(image im, int w, int h, image boxed)
+{
+ int new_w = im.w;
+ int new_h = im.h;
+ if (((float)w / im.w) < ((float)h / im.h)) {
+ new_w = w;
+ new_h = (im.h * w) / im.w;
+ }
+ else {
+ new_h = h;
+ new_w = (im.w * h) / im.h;
+ }
+ image resized = resize_image(im, new_w, new_h);
+ embed_image(resized, boxed, (w - new_w) / 2, (h - new_h) / 2);
+ free_image(resized);
+}
+
+image letterbox_image(image im, int w, int h)
+{
+ int new_w = im.w;
+ int new_h = im.h;
+ if (((float)w / im.w) < ((float)h / im.h)) {
+ new_w = w;
+ new_h = (im.h * w) / im.w;
+ }
+ else {
+ new_h = h;
+ new_w = (im.w * h) / im.h;
+ }
+ image resized = resize_image(im, new_w, new_h);
+ image boxed = make_image(w, h, im.c);
+ fill_image(boxed, .5);
+ //int i;
+ //for(i = 0; i < boxed.w*boxed.h*boxed.c; ++i) boxed.data[i] = 0;
+ embed_image(resized, boxed, (w - new_w) / 2, (h - new_h) / 2);
+ free_image(resized);
+ return boxed;
+}
+
image resize_max(image im, int max)
{
int w = im.w;
@@ -1151,7 +1542,7 @@
void random_distort_image(image im, float hue, float saturation, float exposure)
{
- float dhue = rand_uniform(-hue, hue);
+ float dhue = rand_uniform_strong(-hue, hue);
float dsat = rand_scale(saturation);
float dexp = rand_scale(exposure);
distort_image(im, dhue, dsat, dexp);
@@ -1303,9 +1694,16 @@
image load_image(char *filename, int w, int h, int c)
{
#ifdef OPENCV
- image out = load_image_cv(filename, c);
+
+#ifndef CV_VERSION_EPOCH
+ //image out = load_image_stb(filename, c); // OpenCV 3.x
+ image out = load_image_cv(filename, c);
#else
- image out = load_image_stb(filename, c);
+ image out = load_image_cv(filename, c); // OpenCV 2.4.x
+#endif
+
+#else
+ image out = load_image_stb(filename, c); // without OpenCV
#endif
if((h && w) && (h != out.h || w != out.w)){
@@ -1331,32 +1729,6 @@
return out;
}
-float get_pixel(image m, int x, int y, int c)
-{
- 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 = 0;
- if(x >= m.w) x = m.w-1;
- if(y < 0) y = 0;
- if(y >= m.h) y = m.h-1;
- if(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)
-{
- if (x < 0 || y < 0 || c < 0 || x >= m.w || y >= m.h || c >= m.c) return;
- assert(x < m.w && y < m.h && c < m.c);
- m.data[c*m.h*m.w + y*m.w + x] = val;
-}
-void add_pixel(image m, int x, int y, int c, float 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)
{
int i, j, k;
--
Gitblit v1.10.0