派生自 Algorithm/baseDetector
lib/detecter_tools/darknet/image.c
@@ -1,1683 +1,1706 @@ #ifndef _GNU_SOURCE #define _GNU_SOURCE #endif #include "image.h" #include "utils.h" #include "blas.h" #include "dark_cuda.h" #include <stdio.h> #ifndef _USE_MATH_DEFINES #define _USE_MATH_DEFINES #endif #include <math.h> #ifndef STB_IMAGE_IMPLEMENTATION #define STB_IMAGE_IMPLEMENTATION #include "stb_image.h" #endif #ifndef STB_IMAGE_WRITE_IMPLEMENTATION #define STB_IMAGE_WRITE_IMPLEMENTATION #include "stb_image_write.h" #endif extern int check_mistakes; //int windows = 0; float colors[6][3] = { {1,0,1}, {0,0,1},{0,1,1},{0,1,0},{1,1,0},{1,0,0} }; float get_color(int c, int x, int max) { float ratio = ((float)x/max)*5; int i = floor(ratio); int j = ceil(ratio); ratio -= i; float r = (1-ratio) * colors[i][c] + ratio*colors[j][c]; //printf("%f\n", r); 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; for(k = 0; k < source.c; ++k){ for(y = 0; y < source.h; ++y){ for(x = 0; x < source.w; ++x){ float val = get_pixel(source, x, y, k); float val2 = get_pixel_extend(dest, dx+x, dy+y, k); set_pixel(dest, dx+x, dy+y, k, val * val2); } } } } image border_image(image a, int border) { image b = make_image(a.w + 2*border, a.h + 2*border, a.c); int x,y,k; for(k = 0; k < b.c; ++k){ for(y = 0; y < b.h; ++y){ for(x = 0; x < b.w; ++x){ float val = get_pixel_extend(a, x - border, y - border, k); if(x - border < 0 || x - border >= a.w || y - border < 0 || y - border >= a.h) val = 1; set_pixel(b, x, y, k, val); } } } return b; } image tile_images(image a, image b, int dx) { if(a.w == 0) return copy_image(b); image c = make_image(a.w + b.w + dx, (a.h > b.h) ? a.h : b.h, (a.c > b.c) ? a.c : b.c); fill_cpu(c.w*c.h*c.c, 1, c.data, 1); embed_image(a, c, 0, 0); composite_image(b, c, a.w + dx, 0); return c; } image get_label(image **characters, char *string, int size) { 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; } 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*.05); free_image(label); return b; } void draw_label(image a, int r, int c, image label, const float *rgb) { int w = label.w; int h = label.h; if (r - h >= 0) r = r - h; int i, j, k; for(j = 0; j < h && j + r < a.h; ++j){ for(i = 0; i < w && i + c < a.w; ++i){ for(k = 0; k < label.c; ++k){ float val = get_pixel(label, i, j, k); set_pixel(a, i+c, j+r, k, rgb[k] * val); } } } } void draw_box_bw(image a, int x1, int y1, int x2, int y2, float brightness) { //normalize_image(a); int i; if (x1 < 0) x1 = 0; if (x1 >= a.w) x1 = a.w - 1; if (x2 < 0) x2 = 0; if (x2 >= a.w) x2 = a.w - 1; if (y1 < 0) y1 = 0; if (y1 >= a.h) y1 = a.h - 1; if (y2 < 0) y2 = 0; if (y2 >= a.h) y2 = a.h - 1; for (i = x1; i <= x2; ++i) { a.data[i + y1*a.w + 0 * a.w*a.h] = brightness; a.data[i + y2*a.w + 0 * a.w*a.h] = brightness; } for (i = y1; i <= y2; ++i) { a.data[x1 + i*a.w + 0 * a.w*a.h] = brightness; a.data[x2 + i*a.w + 0 * a.w*a.h] = brightness; } } void draw_box_width_bw(image a, int x1, int y1, int x2, int y2, int w, float brightness) { int i; for (i = 0; i < w; ++i) { float alternate_color = (w % 2) ? (brightness) : (1.0 - brightness); draw_box_bw(a, x1 + i, y1 + i, x2 - i, y2 - i, alternate_color); } } void draw_box(image a, int x1, int y1, int x2, int y2, float r, float g, float b) { //normalize_image(a); int i; if(x1 < 0) x1 = 0; if(x1 >= a.w) x1 = a.w-1; if(x2 < 0) x2 = 0; if(x2 >= a.w) x2 = a.w-1; if(y1 < 0) y1 = 0; if(y1 >= a.h) y1 = a.h-1; if(y2 < 0) y2 = 0; if(y2 >= a.h) y2 = a.h-1; for(i = x1; i <= x2; ++i){ a.data[i + y1*a.w + 0*a.w*a.h] = r; a.data[i + y2*a.w + 0*a.w*a.h] = r; a.data[i + y1*a.w + 1*a.w*a.h] = g; a.data[i + y2*a.w + 1*a.w*a.h] = g; a.data[i + y1*a.w + 2*a.w*a.h] = b; a.data[i + y2*a.w + 2*a.w*a.h] = b; } for(i = y1; i <= y2; ++i){ a.data[x1 + i*a.w + 0*a.w*a.h] = r; a.data[x2 + i*a.w + 0*a.w*a.h] = r; a.data[x1 + i*a.w + 1*a.w*a.h] = g; a.data[x2 + i*a.w + 1*a.w*a.h] = g; a.data[x1 + i*a.w + 2*a.w*a.h] = b; a.data[x2 + i*a.w + 2*a.w*a.h] = b; } } void draw_box_width(image a, int x1, int y1, int x2, int y2, int w, float r, float g, float b) { int i; for(i = 0; i < w; ++i){ draw_box(a, x1+i, y1+i, x2-i, y2-i, r, g, b); } } void draw_bbox(image a, box bbox, int w, float r, float g, float b) { int left = (bbox.x-bbox.w/2)*a.w; int right = (bbox.x+bbox.w/2)*a.w; int top = (bbox.y-bbox.h/2)*a.h; int bot = (bbox.y+bbox.h/2)*a.h; int i; for(i = 0; i < w; ++i){ draw_box(a, left+i, top+i, right-i, bot-i, r, g, b); } } image **load_alphabet() { int i, j; const int nsize = 8; image** alphabets = (image**)xcalloc(nsize, sizeof(image*)); for(j = 0; j < nsize; ++j){ alphabets[j] = (image*)xcalloc(128, sizeof(image)); for(i = 32; i < 127; ++i){ char buff[256]; sprintf(buff, "data/labels/%d_%d.png", i, j); alphabets[j][i] = load_image_color(buff, 0, 0); } } 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, char **names) { int selected_num = 0; detection_with_class* result_arr = (detection_with_class*)xcalloc(dets_num, sizeof(detection_with_class)); int i; for (i = 0; i < dets_num; ++i) { int best_class = -1; float best_class_prob = thresh; int j; for (j = 0; j < dets[i].classes; ++j) { int show = strncmp(names[j], "dont_show", 9); if (dets[i].prob[j] > best_class_prob && show) { 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) { static int frame_id = 0; frame_id++; int selected_detections_num; detection_with_class* selected_detections = get_actual_detections(dets, num, thresh, &selected_detections_num, names); // text output qsort(selected_detections, selected_detections_num, sizeof(*selected_detections), compare_by_lefts); int i; for (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_x: %4.0f top_y: %4.0f width: %4.0f height: %4.0f)\n", round((selected_detections[i].det.bbox.x - selected_detections[i].det.bbox.w / 2)*im.w), round((selected_detections[i].det.bbox.y - selected_detections[i].det.bbox.h / 2)*im.h), round(selected_detections[i].det.bbox.w*im.w), round(selected_detections[i].det.bbox.h*im.h)); else printf("\n"); int j; for (j = 0; j < classes; ++j) { if (selected_detections[i].det.prob[j] > thresh && j != best_class) { printf("%s: %.0f%%", names[j], selected_detections[i].det.prob[j] * 100); if (ext_output) printf("\t(left_x: %4.0f top_y: %4.0f width: %4.0f height: %4.0f)\n", round((selected_detections[i].det.bbox.x - selected_detections[i].det.bbox.w / 2)*im.w), round((selected_detections[i].det.bbox.y - selected_detections[i].det.bbox.h / 2)*im.h), round(selected_detections[i].det.bbox.w*im.w), round(selected_detections[i].det.bbox.h*im.h)); else printf("\n"); } } } // image output qsort(selected_detections, selected_detections_num, sizeof(*selected_detections), compare_by_probs); for (i = 0; i < selected_detections_num; ++i) { int width = im.h * .002; 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); // you should create directory: result_img //static int copied_frame_id = -1; //static image copy_img; //if (copied_frame_id != frame_id) { // copied_frame_id = frame_id; // if (copy_img.data) free_image(copy_img); // copy_img = copy_image(im); //} //image cropped_im = crop_image(copy_img, left, top, right - left, bot - top); //static int img_id = 0; //img_id++; //char image_name[1024]; //int best_class_id = selected_detections[i].best_class; //sprintf(image_name, "result_img/img_%d_%d_%d_%s.jpg", frame_id, img_id, best_class_id, names[best_class_id]); //save_image(cropped_im, image_name); //free_image(cropped_im); if (im.c == 1) { draw_box_width_bw(im, left, top, right, bot, width, 0.8); // 1 channel Black-White } else { draw_box_width(im, left, top, right, bot, width, red, green, blue); // 3 channels RGB } if (alphabet) { char labelstr[4096] = { 0 }; strcat(labelstr, names[selected_detections[i].best_class]); int j; for (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*.02)); 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_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){ width = pow(prob, 1./2.)*10+1; alphabet = 0; } 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 = boxes[i]; 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; 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_id], (im.h*.03)/10); draw_label(im, top + width, left, label, rgb); } } } } void transpose_image(image im) { assert(im.w == im.h); int n, m; int c; for(c = 0; c < im.c; ++c){ for(n = 0; n < im.w-1; ++n){ for(m = n + 1; m < im.w; ++m){ float swap = im.data[m + im.w*(n + im.h*c)]; im.data[m + im.w*(n + im.h*c)] = im.data[n + im.w*(m + im.h*c)]; im.data[n + im.w*(m + im.h*c)] = swap; } } } } void rotate_image_cw(image im, int times) { assert(im.w == im.h); times = (times + 400) % 4; int i, x, y, c; int n = im.w; for(i = 0; i < times; ++i){ for(c = 0; c < im.c; ++c){ for(x = 0; x < n/2; ++x){ for(y = 0; y < (n-1)/2 + 1; ++y){ float temp = im.data[y + im.w*(x + im.h*c)]; im.data[y + im.w*(x + im.h*c)] = im.data[n-1-x + im.w*(y + im.h*c)]; im.data[n-1-x + im.w*(y + im.h*c)] = im.data[n-1-y + im.w*(n-1-x + im.h*c)]; im.data[n-1-y + im.w*(n-1-x + im.h*c)] = im.data[x + im.w*(n-1-y + im.h*c)]; im.data[x + im.w*(n-1-y + im.h*c)] = temp; } } } } } void flip_image(image a) { int i,j,k; for(k = 0; k < a.c; ++k){ for(i = 0; i < a.h; ++i){ for(j = 0; j < a.w/2; ++j){ int index = j + a.w*(i + a.h*(k)); int flip = (a.w - j - 1) + a.w*(i + a.h*(k)); float swap = a.data[flip]; a.data[flip] = a.data[index]; a.data[index] = swap; } } } } image image_distance(image a, image b) { int i,j; 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); } } for(j = 0; j < a.h*a.w; ++j){ dist.data[j] = sqrt(dist.data[j]); } return dist; } void embed_image(image source, image dest, int dx, int dy) { int x,y,k; for(k = 0; k < source.c; ++k){ 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); } } } } image collapse_image_layers(image source, int border) { int h = source.h; h = (h+border)*source.c - border; 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, 0, h_offset); free_image(layer); } return dest; } void constrain_image(image im) { int i; for(i = 0; i < im.w*im.h*im.c; ++i){ if(im.data[i] < 0) im.data[i] = 0; if(im.data[i] > 1) im.data[i] = 1; } } void normalize_image(image p) { int i; float min = 9999999; float max = -999999; for(i = 0; i < p.h*p.w*p.c; ++i){ float v = p.data[i]; if(v < min) min = v; if(v > max) max = v; } if(max - min < .000000001){ min = 0; max = 1; } for(i = 0; i < p.c*p.w*p.h; ++i){ p.data[i] = (p.data[i] - min)/(max-min); } } void normalize_image2(image p) { float* min = (float*)xcalloc(p.c, sizeof(float)); float* max = (float*)xcalloc(p.c, sizeof(float)); int i,j; for(i = 0; i < p.c; ++i) min[i] = max[i] = p.data[i*p.h*p.w]; for(j = 0; j < p.c; ++j){ for(i = 0; i < p.h*p.w; ++i){ float v = p.data[i+j*p.h*p.w]; if(v < min[j]) min[j] = v; if(v > max[j]) max[j] = v; } } for(i = 0; i < p.c; ++i){ if(max[i] - min[i] < .000000001){ min[i] = 0; max[i] = 1; } } for(j = 0; j < p.c; ++j){ for(i = 0; i < p.w*p.h; ++i){ p.data[i+j*p.h*p.w] = (p.data[i+j*p.h*p.w] - min[j])/(max[j]-min[j]); } } free(min); free(max); } void copy_image_inplace(image src, image dst) { memcpy(dst.data, src.data, src.h*src.w*src.c * sizeof(float)); } image copy_image(image p) { image copy = p; copy.data = (float*)xcalloc(p.h * p.w * p.c, sizeof(float)); memcpy(copy.data, p.data, p.h*p.w*p.c*sizeof(float)); return copy; } void rgbgr_image(image im) { int i; for(i = 0; i < im.w*im.h; ++i){ float swap = im.data[i]; im.data[i] = im.data[i+im.w*im.h*2]; im.data[i+im.w*im.h*2] = swap; } } void show_image(image p, const char *name) { #ifdef OPENCV show_image_cv(p, name); #else fprintf(stderr, "Not compiled with OpenCV, saving to %s.png instead\n", name); save_image(p, name); #endif // OPENCV } void save_image_png(image im, const char *name) { char buff[256]; //sprintf(buff, "%s (%d)", name, windows); sprintf(buff, "%s.png", name); unsigned char* data = (unsigned char*)xcalloc(im.w * im.h * im.c, sizeof(unsigned char)); int i,k; for(k = 0; k < im.c; ++k){ for(i = 0; i < im.w*im.h; ++i){ data[i*im.c+k] = (unsigned char) (255*im.data[i + k*im.w*im.h]); } } int success = stbi_write_png(buff, im.w, im.h, im.c, data, im.w*im.c); free(data); if(!success) fprintf(stderr, "Failed to write image %s\n", buff); } void save_image_options(image im, const char *name, IMTYPE f, int quality) { char buff[256]; //sprintf(buff, "%s (%d)", name, windows); if (f == PNG) sprintf(buff, "%s.png", name); else if (f == BMP) sprintf(buff, "%s.bmp", name); else if (f == TGA) sprintf(buff, "%s.tga", name); else if (f == JPG) sprintf(buff, "%s.jpg", name); else sprintf(buff, "%s.png", name); unsigned char* data = (unsigned char*)xcalloc(im.w * im.h * im.c, sizeof(unsigned char)); int i, k; for (k = 0; k < im.c; ++k) { for (i = 0; i < im.w*im.h; ++i) { data[i*im.c + k] = (unsigned char)(255 * im.data[i + k*im.w*im.h]); } } int success = 0; if (f == PNG) success = stbi_write_png(buff, im.w, im.h, im.c, data, im.w*im.c); else if (f == BMP) success = stbi_write_bmp(buff, im.w, im.h, im.c, data); else if (f == TGA) success = stbi_write_tga(buff, im.w, im.h, im.c, data); else if (f == JPG) success = stbi_write_jpg(buff, im.w, im.h, im.c, data, quality); free(data); if (!success) fprintf(stderr, "Failed to write image %s\n", buff); } void save_image(image im, const char *name) { save_image_options(im, name, JPG, 80); } void save_image_jpg(image p, const char *name) { save_image_options(p, name, JPG, 80); } void show_image_layers(image p, char *name) { int i; char buff[256]; for(i = 0; i < p.c; ++i){ sprintf(buff, "%s - Layer %d", name, i); image layer = get_image_layer(p, i); show_image(layer, buff); free_image(layer); } } void show_image_collapsed(image p, char *name) { image c = collapse_image_layers(p, 1); show_image(c, name); free_image(c); } image make_empty_image(int w, int h, int c) { image out; out.data = 0; out.h = h; out.w = w; out.c = c; return out; } image make_image(int w, int h, int c) { image out = make_empty_image(w,h,c); out.data = (float*)xcalloc(h * w * c, sizeof(float)); return out; } image make_random_image(int w, int h, int c) { image out = make_empty_image(w,h,c); out.data = (float*)xcalloc(h * w * c, sizeof(float)); int i; for(i = 0; i < w*h*c; ++i){ out.data[i] = (rand_normal() * .25) + .5; } return out; } image float_to_image_scaled(int w, int h, int c, float *data) { image out = make_image(w, h, c); int abs_max = 0; int i = 0; for (i = 0; i < w*h*c; ++i) { if (fabs(data[i]) > abs_max) abs_max = fabs(data[i]); } for (i = 0; i < w*h*c; ++i) { out.data[i] = data[i] / abs_max; } return out; } image float_to_image(int w, int h, int c, float *data) { image out = make_empty_image(w,h,c); out.data = data; return out; } image rotate_crop_image(image im, float rad, float s, int w, int h, float dx, float dy, float aspect) { int x, y, c; float cx = im.w/2.; float cy = im.h/2.; image rot = make_image(w, h, im.c); for(c = 0; c < im.c; ++c){ for(y = 0; y < h; ++y){ for(x = 0; x < w; ++x){ float rx = cos(rad)*((x - w/2.)/s*aspect + dx/s*aspect) - sin(rad)*((y - h/2.)/s + dy/s) + cx; float ry = sin(rad)*((x - w/2.)/s*aspect + dx/s*aspect) + cos(rad)*((y - h/2.)/s + dy/s) + cy; float val = bilinear_interpolate(im, rx, ry, c); set_pixel(rot, x, y, c, val); } } } return rot; } image rotate_image(image im, float rad) { int x, y, c; float cx = im.w/2.; float cy = im.h/2.; image rot = make_image(im.w, im.h, im.c); for(c = 0; c < im.c; ++c){ for(y = 0; y < im.h; ++y){ for(x = 0; x < im.w; ++x){ float rx = cos(rad)*(x-cx) - sin(rad)*(y-cy) + cx; float ry = sin(rad)*(x-cx) + cos(rad)*(y-cy) + cy; float val = bilinear_interpolate(im, rx, ry, c); set_pixel(rot, x, y, c, val); } } } return rot; } void translate_image(image m, float s) { int i; for(i = 0; i < m.h*m.w*m.c; ++i) m.data[i] += s; } void scale_image(image m, float s) { int i; for(i = 0; i < m.h*m.w*m.c; ++i) m.data[i] *= s; } image crop_image(image im, int dx, int dy, int w, int h) { 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 + dy; int c = i + dx; float val = 0; r = constrain_int(r, 0, im.h-1); c = constrain_int(c, 0, im.w-1); if (r >= 0 && r < im.h && c >= 0 && c < im.w) { val = get_pixel(im, c, r, k); } set_pixel(cropped, i, j, k, val); } } } return cropped; } int best_3d_shift_r(image a, image b, int min, int max) { if(min == max) return min; int mid = floor((min + max) / 2.); image c1 = crop_image(b, 0, mid, b.w, b.h); image c2 = crop_image(b, 0, mid+1, b.w, b.h); float d1 = dist_array(c1.data, a.data, a.w*a.h*a.c, 10); float d2 = dist_array(c2.data, a.data, a.w*a.h*a.c, 10); free_image(c1); free_image(c2); if(d1 < d2) return best_3d_shift_r(a, b, min, mid); else return best_3d_shift_r(a, b, mid+1, max); } int best_3d_shift(image a, image b, int min, int max) { int i; int best = 0; float best_distance = FLT_MAX; for(i = min; i <= max; i += 2){ image c = crop_image(b, 0, i, b.w, b.h); float d = dist_array(c.data, a.data, a.w*a.h*a.c, 100); if(d < best_distance){ best_distance = d; best = i; } printf("%d %f\n", i, d); free_image(c); } return best; } void composite_3d(char *f1, char *f2, char *out, int delta) { if(!out) out = "out"; image a = load_image(f1, 0,0,0); image b = load_image(f2, 0,0,0); int shift = best_3d_shift_r(a, b, -a.h/100, a.h/100); image c1 = crop_image(b, 10, shift, b.w, b.h); float d1 = dist_array(c1.data, a.data, a.w*a.h*a.c, 100); image c2 = crop_image(b, -10, shift, b.w, b.h); float d2 = dist_array(c2.data, a.data, a.w*a.h*a.c, 100); if(d2 < d1 && 0){ image swap = a; a = b; b = swap; shift = -shift; printf("swapped, %d\n", shift); } else{ printf("%d\n", shift); } image c = crop_image(b, delta, shift, a.w, a.h); int i; for(i = 0; i < c.w*c.h; ++i){ c.data[i] = a.data[i]; } #ifdef OPENCV save_image_jpg(c, out); #else save_image(c, out); #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; int h = im.h; if(w > h){ h = (h * max) / w; w = max; } else { w = (w * max) / h; h = max; } if(w == im.w && h == im.h) return im; image resized = resize_image(im, w, h); return resized; } image resize_min(image im, int min) { int w = im.w; int h = im.h; if(w < h){ h = (h * min) / w; w = min; } else { w = (w * min) / h; h = min; } if(w == im.w && h == im.h) return im; image resized = resize_image(im, w, h); return resized; } image random_crop_image(image im, int w, int h) { int dx = rand_int(0, im.w - w); int dy = rand_int(0, im.h - h); image crop = crop_image(im, dx, dy, w, h); return crop; } image random_augment_image(image im, float angle, float aspect, int low, int high, int size) { aspect = rand_scale(aspect); int r = rand_int(low, high); int min = (im.h < im.w*aspect) ? im.h : im.w*aspect; float scale = (float)r / min; float rad = rand_uniform(-angle, angle) * 2.0 * M_PI / 360.; float dx = (im.w*scale/aspect - size) / 2.; float dy = (im.h*scale - size) / 2.; if(dx < 0) dx = 0; if(dy < 0) dy = 0; dx = rand_uniform(-dx, dx); dy = rand_uniform(-dy, dy); image crop = rotate_crop_image(im, rad, scale, size, size, dx, dy, aspect); return crop; } float three_way_max(float a, float b, float c) { return (a > b) ? ( (a > c) ? a : c) : ( (b > c) ? b : c) ; } float three_way_min(float a, float b, float c) { return (a < b) ? ( (a < c) ? a : c) : ( (b < c) ? b : c) ; } // http://www.cs.rit.edu/~ncs/color/t_convert.html void rgb_to_hsv(image im) { assert(im.c == 3); int i, j; float r, g, b; float h, s, v; for(j = 0; j < im.h; ++j){ for(i = 0; i < im.w; ++i){ r = get_pixel(im, i , j, 0); g = get_pixel(im, i , j, 1); b = get_pixel(im, i , j, 2); float max = three_way_max(r,g,b); float min = three_way_min(r,g,b); float delta = max - min; v = max; if(max == 0){ s = 0; h = 0; }else{ s = delta/max; if(r == max){ h = (g - b) / delta; } else if (g == max) { h = 2 + (b - r) / delta; } else { h = 4 + (r - g) / delta; } if (h < 0) h += 6; h = h/6.; } set_pixel(im, i, j, 0, h); set_pixel(im, i, j, 1, s); set_pixel(im, i, j, 2, v); } } } void hsv_to_rgb(image im) { assert(im.c == 3); int i, j; float r, g, b; float h, s, v; float f, p, q, t; for(j = 0; j < im.h; ++j){ for(i = 0; i < im.w; ++i){ h = 6 * get_pixel(im, i , j, 0); s = get_pixel(im, i , j, 1); v = get_pixel(im, i , j, 2); if (s == 0) { r = g = b = v; } else { int index = floor(h); f = h - index; p = v*(1-s); q = v*(1-s*f); t = v*(1-s*(1-f)); if(index == 0){ r = v; g = t; b = p; } else if(index == 1){ r = q; g = v; b = p; } else if(index == 2){ r = p; g = v; b = t; } else if(index == 3){ r = p; g = q; b = v; } else if(index == 4){ r = t; g = p; b = v; } else { r = v; g = p; b = q; } } set_pixel(im, i, j, 0, r); set_pixel(im, i, j, 1, g); set_pixel(im, i, j, 2, b); } } } image grayscale_image(image im) { assert(im.c == 3); int i, j, k; image gray = make_image(im.w, im.h, 1); float scale[] = {0.587, 0.299, 0.114}; for(k = 0; k < im.c; ++k){ for(j = 0; j < im.h; ++j){ for(i = 0; i < im.w; ++i){ gray.data[i+im.w*j] += scale[k]*get_pixel(im, i, j, k); } } } return gray; } image threshold_image(image im, float thresh) { int i; image t = make_image(im.w, im.h, im.c); for(i = 0; i < im.w*im.h*im.c; ++i){ t.data[i] = im.data[i]>thresh ? 1 : 0; } return t; } image blend_image(image fore, image back, float alpha) { assert(fore.w == back.w && fore.h == back.h && fore.c == back.c); image blend = make_image(fore.w, fore.h, fore.c); int i, j, k; for(k = 0; k < fore.c; ++k){ for(j = 0; j < fore.h; ++j){ for(i = 0; i < fore.w; ++i){ float val = alpha * get_pixel(fore, i, j, k) + (1 - alpha)* get_pixel(back, i, j, k); set_pixel(blend, i, j, k, val); } } } return blend; } void scale_image_channel(image im, int c, float v) { int i, j; for(j = 0; j < im.h; ++j){ for(i = 0; i < im.w; ++i){ float pix = get_pixel(im, i, j, c); pix = pix*v; set_pixel(im, i, j, c, pix); } } } void translate_image_channel(image im, int c, float v) { int i, j; for(j = 0; j < im.h; ++j){ for(i = 0; i < im.w; ++i){ float pix = get_pixel(im, i, j, c); pix = pix+v; set_pixel(im, i, j, c, pix); } } } image binarize_image(image im) { image c = copy_image(im); int i; for(i = 0; i < im.w * im.h * im.c; ++i){ if(c.data[i] > .5) c.data[i] = 1; else c.data[i] = 0; } return c; } void saturate_image(image im, float sat) { rgb_to_hsv(im); scale_image_channel(im, 1, sat); hsv_to_rgb(im); constrain_image(im); } void hue_image(image im, float hue) { rgb_to_hsv(im); int i; for(i = 0; i < im.w*im.h; ++i){ im.data[i] = im.data[i] + hue; if (im.data[i] > 1) im.data[i] -= 1; if (im.data[i] < 0) im.data[i] += 1; } hsv_to_rgb(im); constrain_image(im); } void exposure_image(image im, float sat) { rgb_to_hsv(im); scale_image_channel(im, 2, sat); hsv_to_rgb(im); constrain_image(im); } void distort_image(image im, float hue, float sat, float val) { if (im.c >= 3) { rgb_to_hsv(im); scale_image_channel(im, 1, sat); scale_image_channel(im, 2, val); int i; for(i = 0; i < im.w*im.h; ++i){ im.data[i] = im.data[i] + hue; if (im.data[i] > 1) im.data[i] -= 1; if (im.data[i] < 0) im.data[i] += 1; } hsv_to_rgb(im); } else { scale_image_channel(im, 0, val); } constrain_image(im); } void random_distort_image(image im, float hue, float saturation, float exposure) { float dhue = rand_uniform_strong(-hue, hue); float dsat = rand_scale(saturation); float dexp = rand_scale(exposure); distort_image(im, dhue, dsat, dexp); } void saturate_exposure_image(image im, float sat, float exposure) { rgb_to_hsv(im); scale_image_channel(im, 1, sat); scale_image_channel(im, 2, exposure); hsv_to_rgb(im); constrain_image(im); } float bilinear_interpolate(image im, float x, float y, int c) { int ix = (int) floorf(x); int iy = (int) floorf(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; } void quantize_image(image im) { int size = im.c * im.w * im.h; int i; for (i = 0; i < size; ++i) im.data[i] = (int)(im.data[i] * 255) / 255. + (0.5/255); } void make_image_red(image im) { int r, c, k; for (r = 0; r < im.h; ++r) { for (c = 0; c < im.w; ++c) { float val = 0; for (k = 0; k < im.c; ++k) { val += get_pixel(im, c, r, k); set_pixel(im, c, r, k, 0); } for (k = 0; k < im.c; ++k) { //set_pixel(im, c, r, k, val); } set_pixel(im, c, r, 0, val); } } } image make_attention_image(int img_size, float *original_delta_cpu, float *original_input_cpu, int w, int h, int c) { image attention_img; attention_img.w = w; attention_img.h = h; attention_img.c = c; attention_img.data = original_delta_cpu; make_image_red(attention_img); int k; float min_val = 999999, mean_val = 0, max_val = -999999; for (k = 0; k < img_size; ++k) { if (original_delta_cpu[k] < min_val) min_val = original_delta_cpu[k]; if (original_delta_cpu[k] > max_val) max_val = original_delta_cpu[k]; mean_val += original_delta_cpu[k]; } mean_val = mean_val / img_size; float range = max_val - min_val; for (k = 0; k < img_size; ++k) { float val = original_delta_cpu[k]; val = fabs(mean_val - val) / range; original_delta_cpu[k] = val * 4; } image resized = resize_image(attention_img, w / 4, h / 4); attention_img = resize_image(resized, w, h); free_image(resized); for (k = 0; k < img_size; ++k) attention_img.data[k] += original_input_cpu[k]; //normalize_image(attention_img); //show_image(attention_img, "delta"); return attention_img; } image resize_image(image im, int w, int h) { if (im.w == w && im.h == h) return copy_image(im); image resized = make_image(w, h, im.c); image part = make_image(w, im.h, im.c); int r, c, k; 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 < im.h; ++r){ for(c = 0; c < w; ++c){ float val = 0; if(c == w-1 || im.w == 1){ val = get_pixel(im, im.w-1, r, k); } else { float sx = c*w_scale; int ix = (int) sx; float dx = sx - ix; val = (1 - dx) * get_pixel(im, ix, r, k) + dx * get_pixel(im, ix+1, r, k); } set_pixel(part, c, r, k, val); } } } for(k = 0; k < im.c; ++k){ for(r = 0; r < h; ++r){ float sy = r*h_scale; int iy = (int) sy; float dy = sy - iy; for(c = 0; c < w; ++c){ float val = (1-dy) * get_pixel(part, c, iy, k); set_pixel(resized, c, r, k, val); } if(r == h-1 || im.h == 1) continue; for(c = 0; c < w; ++c){ float val = dy * get_pixel(part, c, iy+1, k); add_pixel(resized, c, r, k, val); } } } free_image(part); return resized; } void test_resize(char *filename) { image im = load_image(filename, 0,0, 3); float mag = mag_array(im.data, im.w*im.h*im.c); printf("L2 Norm: %f\n", mag); image gray = grayscale_image(im); image c1 = copy_image(im); image c2 = copy_image(im); image c3 = copy_image(im); image c4 = copy_image(im); distort_image(c1, .1, 1.5, 1.5); distort_image(c2, -.1, .66666, .66666); distort_image(c3, .1, 1.5, .66666); distort_image(c4, .1, .66666, 1.5); show_image(im, "Original"); show_image(gray, "Gray"); show_image(c1, "C1"); show_image(c2, "C2"); show_image(c3, "C3"); show_image(c4, "C4"); #ifdef OPENCV while(1){ image aug = random_augment_image(im, 0, .75, 320, 448, 320); show_image(aug, "aug"); free_image(aug); float exposure = 1.15; float saturation = 1.15; float hue = .05; image c = copy_image(im); float dexp = rand_scale(exposure); float dsat = rand_scale(saturation); float dhue = rand_uniform(-hue, hue); distort_image(c, dhue, dsat, dexp); show_image(c, "rand"); printf("%f %f %f\n", dhue, dsat, dexp); free_image(c); wait_until_press_key_cv(); } #endif } image load_image_stb(char *filename, int channels) { int w, h, c; unsigned char *data = stbi_load(filename, &w, &h, &c, channels); if (!data) { char shrinked_filename[1024]; if (strlen(filename) >= 1024) sprintf(shrinked_filename, "name is too long"); else sprintf(shrinked_filename, "%s", filename); fprintf(stderr, "Cannot load image \"%s\"\nSTB Reason: %s\n", shrinked_filename, stbi_failure_reason()); FILE* fw = fopen("bad.list", "a"); fwrite(shrinked_filename, sizeof(char), strlen(shrinked_filename), fw); char *new_line = "\n"; fwrite(new_line, sizeof(char), strlen(new_line), fw); fclose(fw); if (check_mistakes) { printf("\n Error in load_image_stb() \n"); getchar(); } return make_image(10, 10, 3); //exit(EXIT_FAILURE); } if(channels) c = channels; int i,j,k; image im = make_image(w, h, c); for(k = 0; k < c; ++k){ for(j = 0; j < h; ++j){ for(i = 0; i < w; ++i){ int dst_index = i + w*j + w*h*k; int src_index = k + c*i + c*w*j; im.data[dst_index] = (float)data[src_index]/255.; } } } free(data); return im; } image load_image_stb_resize(char *filename, int w, int h, int c) { image out = load_image_stb(filename, c); // without OpenCV if ((h && w) && (h != out.h || w != out.w)) { image resized = resize_image(out, w, h); free_image(out); out = resized; } return out; } image load_image(char *filename, int w, int h, int c) { #ifdef OPENCV //image out = load_image_stb(filename, c); image out = load_image_cv(filename, c); #else image out = load_image_stb(filename, c); // without OpenCV #endif // OPENCV if((h && w) && (h != out.h || w != out.w)){ image resized = resize_image(out, w, h); free_image(out); out = resized; } return out; } image load_image_color(char *filename, int w, int h) { return load_image(filename, w, h, 3); } image get_image_layer(image m, int l) { 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; } void print_image(image m) { int i, j, k; for(i =0 ; i < m.c; ++i){ for(j =0 ; j < m.h; ++j){ for(k = 0; k < m.w; ++k){ printf("%.2lf, ", m.data[i*m.h*m.w + j*m.w + k]); if(k > 30) break; } printf("\n"); if(j > 30) break; } printf("\n"); } printf("\n"); } image collapse_images_vert(image *ims, int n) { int color = 1; int border = 1; int h,w,c; w = ims[0].w; h = (ims[0].h + border) * n - border; c = ims[0].c; if(c != 3 || !color){ w = (w+border)*c - border; c = 1; } 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, 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, w_offset, h_offset); free_image(layer); } } free_image(copy); } return filters; } image collapse_images_horz(image *ims, int n) { int color = 1; int border = 1; int h,w,c; int size = ims[0].h; h = size; w = (ims[0].w + border) * n - border; c = ims[0].c; if(c != 3 || !color){ h = (h+border)*c - border; c = 1; } 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, 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, w_offset, h_offset); free_image(layer); } } free_image(copy); } return filters; } void show_image_normalized(image im, const char *name) { image c = copy_image(im); normalize_image(c); show_image(c, name); free_image(c); } void show_images(image *ims, int n, char *window) { image m = collapse_images_vert(ims, n); /* int w = 448; int h = ((float)m.h/m.w) * 448; if(h > 896){ h = 896; w = ((float)m.w/m.h) * 896; } image sized = resize_image(m, w, h); */ normalize_image(m); save_image(m, window); show_image(m, window); free_image(m); } void free_image(image m) { if(m.data){ free(m.data); } } // Fast copy data from a contiguous byte array into the image. LIB_API void copy_image_from_bytes(image im, char *pdata) { unsigned char *data = (unsigned char*)pdata; int i, k, j; int w = im.w; int h = im.h; int c = im.c; for (k = 0; k < c; ++k) { for (j = 0; j < h; ++j) { for (i = 0; i < w; ++i) { int dst_index = i + w * j + w * h*k; int src_index = k + c * i + c * w*j; im.data[dst_index] = (float)data[src_index] / 255.; } } } } #ifndef _GNU_SOURCE #define _GNU_SOURCE #endif #include "image.h" #include "utils.h" #include "blas.h" #include "dark_cuda.h" #include <stdio.h> #ifndef _USE_MATH_DEFINES #define _USE_MATH_DEFINES #endif #include <math.h> #ifndef STB_IMAGE_IMPLEMENTATION #define STB_IMAGE_IMPLEMENTATION #include "stb_image.h" #endif #ifndef STB_IMAGE_WRITE_IMPLEMENTATION #define STB_IMAGE_WRITE_IMPLEMENTATION #include "stb_image_write.h" #endif extern int check_mistakes; //int windows = 0; float colors[6][3] = { {1,0,1}, {0,0,1},{0,1,1},{0,1,0},{1,1,0},{1,0,0} }; float get_color(int c, int x, int max) { float ratio = ((float)x/max)*5; int i = floor(ratio); int j = ceil(ratio); ratio -= i; float r = (1-ratio) * colors[i][c] + ratio*colors[j][c]; //printf("%f\n", r); 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; for(k = 0; k < source.c; ++k){ for(y = 0; y < source.h; ++y){ for(x = 0; x < source.w; ++x){ float val = get_pixel(source, x, y, k); float val2 = get_pixel_extend(dest, dx+x, dy+y, k); set_pixel(dest, dx+x, dy+y, k, val * val2); } } } } image border_image(image a, int border) { image b = make_image(a.w + 2*border, a.h + 2*border, a.c); int x,y,k; for(k = 0; k < b.c; ++k){ for(y = 0; y < b.h; ++y){ for(x = 0; x < b.w; ++x){ float val = get_pixel_extend(a, x - border, y - border, k); if(x - border < 0 || x - border >= a.w || y - border < 0 || y - border >= a.h) val = 1; set_pixel(b, x, y, k, val); } } } return b; } image tile_images(image a, image b, int dx) { if(a.w == 0) return copy_image(b); image c = make_image(a.w + b.w + dx, (a.h > b.h) ? a.h : b.h, (a.c > b.c) ? a.c : b.c); fill_cpu(c.w*c.h*c.c, 1, c.data, 1); embed_image(a, c, 0, 0); composite_image(b, c, a.w + dx, 0); return c; } image get_label(image **characters, char *string, int size) { 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; } 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*.05); free_image(label); return b; } void draw_label(image a, int r, int c, image label, const float *rgb) { int w = label.w; int h = label.h; if (r - h >= 0) r = r - h; int i, j, k; for(j = 0; j < h && j + r < a.h; ++j){ for(i = 0; i < w && i + c < a.w; ++i){ for(k = 0; k < label.c; ++k){ float val = get_pixel(label, i, j, k); set_pixel(a, i+c, j+r, k, rgb[k] * val); } } } } void draw_weighted_label(image a, int r, int c, image label, const float *rgb, const float alpha) { int w = label.w; int h = label.h; if (r - h >= 0) r = r - h; int i, j, k; for (j = 0; j < h && j + r < a.h; ++j) { for (i = 0; i < w && i + c < a.w; ++i) { for (k = 0; k < label.c; ++k) { float val1 = get_pixel(label, i, j, k); float val2 = get_pixel(a, i + c, j + r, k); float val_dst = val1 * rgb[k] * alpha + val2 * (1 - alpha); set_pixel(a, i + c, j + r, k, val_dst); } } } } void draw_box_bw(image a, int x1, int y1, int x2, int y2, float brightness) { //normalize_image(a); int i; if (x1 < 0) x1 = 0; if (x1 >= a.w) x1 = a.w - 1; if (x2 < 0) x2 = 0; if (x2 >= a.w) x2 = a.w - 1; if (y1 < 0) y1 = 0; if (y1 >= a.h) y1 = a.h - 1; if (y2 < 0) y2 = 0; if (y2 >= a.h) y2 = a.h - 1; for (i = x1; i <= x2; ++i) { a.data[i + y1*a.w + 0 * a.w*a.h] = brightness; a.data[i + y2*a.w + 0 * a.w*a.h] = brightness; } for (i = y1; i <= y2; ++i) { a.data[x1 + i*a.w + 0 * a.w*a.h] = brightness; a.data[x2 + i*a.w + 0 * a.w*a.h] = brightness; } } void draw_box_width_bw(image a, int x1, int y1, int x2, int y2, int w, float brightness) { int i; for (i = 0; i < w; ++i) { float alternate_color = (w % 2) ? (brightness) : (1.0 - brightness); draw_box_bw(a, x1 + i, y1 + i, x2 - i, y2 - i, alternate_color); } } void draw_box(image a, int x1, int y1, int x2, int y2, float r, float g, float b) { //normalize_image(a); int i; if(x1 < 0) x1 = 0; if(x1 >= a.w) x1 = a.w-1; if(x2 < 0) x2 = 0; if(x2 >= a.w) x2 = a.w-1; if(y1 < 0) y1 = 0; if(y1 >= a.h) y1 = a.h-1; if(y2 < 0) y2 = 0; if(y2 >= a.h) y2 = a.h-1; for(i = x1; i <= x2; ++i){ a.data[i + y1*a.w + 0*a.w*a.h] = r; a.data[i + y2*a.w + 0*a.w*a.h] = r; a.data[i + y1*a.w + 1*a.w*a.h] = g; a.data[i + y2*a.w + 1*a.w*a.h] = g; a.data[i + y1*a.w + 2*a.w*a.h] = b; a.data[i + y2*a.w + 2*a.w*a.h] = b; } for(i = y1; i <= y2; ++i){ a.data[x1 + i*a.w + 0*a.w*a.h] = r; a.data[x2 + i*a.w + 0*a.w*a.h] = r; a.data[x1 + i*a.w + 1*a.w*a.h] = g; a.data[x2 + i*a.w + 1*a.w*a.h] = g; a.data[x1 + i*a.w + 2*a.w*a.h] = b; a.data[x2 + i*a.w + 2*a.w*a.h] = b; } } void draw_box_width(image a, int x1, int y1, int x2, int y2, int w, float r, float g, float b) { int i; for(i = 0; i < w; ++i){ draw_box(a, x1+i, y1+i, x2-i, y2-i, r, g, b); } } void draw_bbox(image a, box bbox, int w, float r, float g, float b) { int left = (bbox.x-bbox.w/2)*a.w; int right = (bbox.x+bbox.w/2)*a.w; int top = (bbox.y-bbox.h/2)*a.h; int bot = (bbox.y+bbox.h/2)*a.h; int i; for(i = 0; i < w; ++i){ draw_box(a, left+i, top+i, right-i, bot-i, r, g, b); } } image **load_alphabet() { int i, j; const int nsize = 8; image** alphabets = (image**)xcalloc(nsize, sizeof(image*)); for(j = 0; j < nsize; ++j){ alphabets[j] = (image*)xcalloc(128, sizeof(image)); for(i = 32; i < 127; ++i){ char buff[256]; sprintf(buff, "data/labels/%d_%d.png", i, j); alphabets[j][i] = load_image_color(buff, 0, 0); } } 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, char **names) { int selected_num = 0; detection_with_class* result_arr = (detection_with_class*)xcalloc(dets_num, sizeof(detection_with_class)); int i; for (i = 0; i < dets_num; ++i) { int best_class = -1; float best_class_prob = thresh; int j; for (j = 0; j < dets[i].classes; ++j) { int show = strncmp(names[j], "dont_show", 9); if (dets[i].prob[j] > best_class_prob && show) { 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) { static int frame_id = 0; frame_id++; int selected_detections_num; detection_with_class* selected_detections = get_actual_detections(dets, num, thresh, &selected_detections_num, names); // text output qsort(selected_detections, selected_detections_num, sizeof(*selected_detections), compare_by_lefts); int i; for (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_x: %4.0f top_y: %4.0f width: %4.0f height: %4.0f)\n", round((selected_detections[i].det.bbox.x - selected_detections[i].det.bbox.w / 2)*im.w), round((selected_detections[i].det.bbox.y - selected_detections[i].det.bbox.h / 2)*im.h), round(selected_detections[i].det.bbox.w*im.w), round(selected_detections[i].det.bbox.h*im.h)); else printf("\n"); int j; for (j = 0; j < classes; ++j) { if (selected_detections[i].det.prob[j] > thresh && j != best_class) { printf("%s: %.0f%%", names[j], selected_detections[i].det.prob[j] * 100); if (ext_output) printf("\t(left_x: %4.0f top_y: %4.0f width: %4.0f height: %4.0f)\n", round((selected_detections[i].det.bbox.x - selected_detections[i].det.bbox.w / 2)*im.w), round((selected_detections[i].det.bbox.y - selected_detections[i].det.bbox.h / 2)*im.h), round(selected_detections[i].det.bbox.w*im.w), round(selected_detections[i].det.bbox.h*im.h)); else printf("\n"); } } } // image output qsort(selected_detections, selected_detections_num, sizeof(*selected_detections), compare_by_probs); for (i = 0; i < selected_detections_num; ++i) { int width = im.h * .002; 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); // you should create directory: result_img //static int copied_frame_id = -1; //static image copy_img; //if (copied_frame_id != frame_id) { // copied_frame_id = frame_id; // if (copy_img.data) free_image(copy_img); // copy_img = copy_image(im); //} //image cropped_im = crop_image(copy_img, left, top, right - left, bot - top); //static int img_id = 0; //img_id++; //char image_name[1024]; //int best_class_id = selected_detections[i].best_class; //sprintf(image_name, "result_img/img_%d_%d_%d_%s.jpg", frame_id, img_id, best_class_id, names[best_class_id]); //save_image(cropped_im, image_name); //free_image(cropped_im); if (im.c == 1) { draw_box_width_bw(im, left, top, right, bot, width, 0.8); // 1 channel Black-White } else { draw_box_width(im, left, top, right, bot, width, red, green, blue); // 3 channels RGB } if (alphabet) { char labelstr[4096] = { 0 }; strcat(labelstr, names[selected_detections[i].best_class]); char prob_str[10]; sprintf(prob_str, ": %.2f", selected_detections[i].det.prob[selected_detections[i].best_class]); strcat(labelstr, prob_str); int j; for (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*.02)); //draw_label(im, top + width, left, label, rgb); draw_weighted_label(im, top + width, left, label, rgb, 0.7); 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_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){ width = pow(prob, 1./2.)*10+1; alphabet = 0; } 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 = boxes[i]; 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; 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_id], (im.h*.03)/10); draw_label(im, top + width, left, label, rgb); } } } } void transpose_image(image im) { assert(im.w == im.h); int n, m; int c; for(c = 0; c < im.c; ++c){ for(n = 0; n < im.w-1; ++n){ for(m = n + 1; m < im.w; ++m){ float swap = im.data[m + im.w*(n + im.h*c)]; im.data[m + im.w*(n + im.h*c)] = im.data[n + im.w*(m + im.h*c)]; im.data[n + im.w*(m + im.h*c)] = swap; } } } } void rotate_image_cw(image im, int times) { assert(im.w == im.h); times = (times + 400) % 4; int i, x, y, c; int n = im.w; for(i = 0; i < times; ++i){ for(c = 0; c < im.c; ++c){ for(x = 0; x < n/2; ++x){ for(y = 0; y < (n-1)/2 + 1; ++y){ float temp = im.data[y + im.w*(x + im.h*c)]; im.data[y + im.w*(x + im.h*c)] = im.data[n-1-x + im.w*(y + im.h*c)]; im.data[n-1-x + im.w*(y + im.h*c)] = im.data[n-1-y + im.w*(n-1-x + im.h*c)]; im.data[n-1-y + im.w*(n-1-x + im.h*c)] = im.data[x + im.w*(n-1-y + im.h*c)]; im.data[x + im.w*(n-1-y + im.h*c)] = temp; } } } } } void flip_image(image a) { int i,j,k; for(k = 0; k < a.c; ++k){ for(i = 0; i < a.h; ++i){ for(j = 0; j < a.w/2; ++j){ int index = j + a.w*(i + a.h*(k)); int flip = (a.w - j - 1) + a.w*(i + a.h*(k)); float swap = a.data[flip]; a.data[flip] = a.data[index]; a.data[index] = swap; } } } } image image_distance(image a, image b) { int i,j; 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); } } for(j = 0; j < a.h*a.w; ++j){ dist.data[j] = sqrt(dist.data[j]); } return dist; } void embed_image(image source, image dest, int dx, int dy) { int x,y,k; for(k = 0; k < source.c; ++k){ 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); } } } } image collapse_image_layers(image source, int border) { int h = source.h; h = (h+border)*source.c - border; 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, 0, h_offset); free_image(layer); } return dest; } void constrain_image(image im) { int i; for(i = 0; i < im.w*im.h*im.c; ++i){ if(im.data[i] < 0) im.data[i] = 0; if(im.data[i] > 1) im.data[i] = 1; } } void normalize_image(image p) { int i; float min = 9999999; float max = -999999; for(i = 0; i < p.h*p.w*p.c; ++i){ float v = p.data[i]; if(v < min) min = v; if(v > max) max = v; } if(max - min < .000000001){ min = 0; max = 1; } for(i = 0; i < p.c*p.w*p.h; ++i){ p.data[i] = (p.data[i] - min)/(max-min); } } void normalize_image2(image p) { float* min = (float*)xcalloc(p.c, sizeof(float)); float* max = (float*)xcalloc(p.c, sizeof(float)); int i,j; for(i = 0; i < p.c; ++i) min[i] = max[i] = p.data[i*p.h*p.w]; for(j = 0; j < p.c; ++j){ for(i = 0; i < p.h*p.w; ++i){ float v = p.data[i+j*p.h*p.w]; if(v < min[j]) min[j] = v; if(v > max[j]) max[j] = v; } } for(i = 0; i < p.c; ++i){ if(max[i] - min[i] < .000000001){ min[i] = 0; max[i] = 1; } } for(j = 0; j < p.c; ++j){ for(i = 0; i < p.w*p.h; ++i){ p.data[i+j*p.h*p.w] = (p.data[i+j*p.h*p.w] - min[j])/(max[j]-min[j]); } } free(min); free(max); } void copy_image_inplace(image src, image dst) { memcpy(dst.data, src.data, src.h*src.w*src.c * sizeof(float)); } image copy_image(image p) { image copy = p; copy.data = (float*)xcalloc(p.h * p.w * p.c, sizeof(float)); memcpy(copy.data, p.data, p.h*p.w*p.c*sizeof(float)); return copy; } void rgbgr_image(image im) { int i; for(i = 0; i < im.w*im.h; ++i){ float swap = im.data[i]; im.data[i] = im.data[i+im.w*im.h*2]; im.data[i+im.w*im.h*2] = swap; } } void show_image(image p, const char *name) { #ifdef OPENCV show_image_cv(p, name); #else fprintf(stderr, "Not compiled with OpenCV, saving to %s.png instead\n", name); save_image(p, name); #endif // OPENCV } void save_image_png(image im, const char *name) { char buff[256]; //sprintf(buff, "%s (%d)", name, windows); sprintf(buff, "%s.png", name); unsigned char* data = (unsigned char*)xcalloc(im.w * im.h * im.c, sizeof(unsigned char)); int i,k; for(k = 0; k < im.c; ++k){ for(i = 0; i < im.w*im.h; ++i){ data[i*im.c+k] = (unsigned char) (255*im.data[i + k*im.w*im.h]); } } int success = stbi_write_png(buff, im.w, im.h, im.c, data, im.w*im.c); free(data); if(!success) fprintf(stderr, "Failed to write image %s\n", buff); } void save_image_options(image im, const char *name, IMTYPE f, int quality) { char buff[256]; //sprintf(buff, "%s (%d)", name, windows); if (f == PNG) sprintf(buff, "%s.png", name); else if (f == BMP) sprintf(buff, "%s.bmp", name); else if (f == TGA) sprintf(buff, "%s.tga", name); else if (f == JPG) sprintf(buff, "%s.jpg", name); else sprintf(buff, "%s.png", name); unsigned char* data = (unsigned char*)xcalloc(im.w * im.h * im.c, sizeof(unsigned char)); int i, k; for (k = 0; k < im.c; ++k) { for (i = 0; i < im.w*im.h; ++i) { data[i*im.c + k] = (unsigned char)(255 * im.data[i + k*im.w*im.h]); } } int success = 0; if (f == PNG) success = stbi_write_png(buff, im.w, im.h, im.c, data, im.w*im.c); else if (f == BMP) success = stbi_write_bmp(buff, im.w, im.h, im.c, data); else if (f == TGA) success = stbi_write_tga(buff, im.w, im.h, im.c, data); else if (f == JPG) success = stbi_write_jpg(buff, im.w, im.h, im.c, data, quality); free(data); if (!success) fprintf(stderr, "Failed to write image %s\n", buff); } void save_image(image im, const char *name) { save_image_options(im, name, JPG, 80); } void save_image_jpg(image p, const char *name) { save_image_options(p, name, JPG, 80); } void show_image_layers(image p, char *name) { int i; char buff[256]; for(i = 0; i < p.c; ++i){ sprintf(buff, "%s - Layer %d", name, i); image layer = get_image_layer(p, i); show_image(layer, buff); free_image(layer); } } void show_image_collapsed(image p, char *name) { image c = collapse_image_layers(p, 1); show_image(c, name); free_image(c); } image make_empty_image(int w, int h, int c) { image out; out.data = 0; out.h = h; out.w = w; out.c = c; return out; } image make_image(int w, int h, int c) { image out = make_empty_image(w,h,c); out.data = (float*)xcalloc(h * w * c, sizeof(float)); return out; } image make_random_image(int w, int h, int c) { image out = make_empty_image(w,h,c); out.data = (float*)xcalloc(h * w * c, sizeof(float)); int i; for(i = 0; i < w*h*c; ++i){ out.data[i] = (rand_normal() * .25) + .5; } return out; } image float_to_image_scaled(int w, int h, int c, float *data) { image out = make_image(w, h, c); int abs_max = 0; int i = 0; for (i = 0; i < w*h*c; ++i) { if (fabs(data[i]) > abs_max) abs_max = fabs(data[i]); } for (i = 0; i < w*h*c; ++i) { out.data[i] = data[i] / abs_max; } return out; } image float_to_image(int w, int h, int c, float *data) { image out = make_empty_image(w,h,c); out.data = data; return out; } image rotate_crop_image(image im, float rad, float s, int w, int h, float dx, float dy, float aspect) { int x, y, c; float cx = im.w/2.; float cy = im.h/2.; image rot = make_image(w, h, im.c); for(c = 0; c < im.c; ++c){ for(y = 0; y < h; ++y){ for(x = 0; x < w; ++x){ float rx = cos(rad)*((x - w/2.)/s*aspect + dx/s*aspect) - sin(rad)*((y - h/2.)/s + dy/s) + cx; float ry = sin(rad)*((x - w/2.)/s*aspect + dx/s*aspect) + cos(rad)*((y - h/2.)/s + dy/s) + cy; float val = bilinear_interpolate(im, rx, ry, c); set_pixel(rot, x, y, c, val); } } } return rot; } image rotate_image(image im, float rad) { int x, y, c; float cx = im.w/2.; float cy = im.h/2.; image rot = make_image(im.w, im.h, im.c); for(c = 0; c < im.c; ++c){ for(y = 0; y < im.h; ++y){ for(x = 0; x < im.w; ++x){ float rx = cos(rad)*(x-cx) - sin(rad)*(y-cy) + cx; float ry = sin(rad)*(x-cx) + cos(rad)*(y-cy) + cy; float val = bilinear_interpolate(im, rx, ry, c); set_pixel(rot, x, y, c, val); } } } return rot; } void translate_image(image m, float s) { int i; for(i = 0; i < m.h*m.w*m.c; ++i) m.data[i] += s; } void scale_image(image m, float s) { int i; for(i = 0; i < m.h*m.w*m.c; ++i) m.data[i] *= s; } image crop_image(image im, int dx, int dy, int w, int h) { 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 + dy; int c = i + dx; float val = 0; r = constrain_int(r, 0, im.h-1); c = constrain_int(c, 0, im.w-1); if (r >= 0 && r < im.h && c >= 0 && c < im.w) { val = get_pixel(im, c, r, k); } set_pixel(cropped, i, j, k, val); } } } return cropped; } int best_3d_shift_r(image a, image b, int min, int max) { if(min == max) return min; int mid = floor((min + max) / 2.); image c1 = crop_image(b, 0, mid, b.w, b.h); image c2 = crop_image(b, 0, mid+1, b.w, b.h); float d1 = dist_array(c1.data, a.data, a.w*a.h*a.c, 10); float d2 = dist_array(c2.data, a.data, a.w*a.h*a.c, 10); free_image(c1); free_image(c2); if(d1 < d2) return best_3d_shift_r(a, b, min, mid); else return best_3d_shift_r(a, b, mid+1, max); } int best_3d_shift(image a, image b, int min, int max) { int i; int best = 0; float best_distance = FLT_MAX; for(i = min; i <= max; i += 2){ image c = crop_image(b, 0, i, b.w, b.h); float d = dist_array(c.data, a.data, a.w*a.h*a.c, 100); if(d < best_distance){ best_distance = d; best = i; } printf("%d %f\n", i, d); free_image(c); } return best; } void composite_3d(char *f1, char *f2, char *out, int delta) { if(!out) out = "out"; image a = load_image(f1, 0,0,0); image b = load_image(f2, 0,0,0); int shift = best_3d_shift_r(a, b, -a.h/100, a.h/100); image c1 = crop_image(b, 10, shift, b.w, b.h); float d1 = dist_array(c1.data, a.data, a.w*a.h*a.c, 100); image c2 = crop_image(b, -10, shift, b.w, b.h); float d2 = dist_array(c2.data, a.data, a.w*a.h*a.c, 100); if(d2 < d1 && 0){ image swap = a; a = b; b = swap; shift = -shift; printf("swapped, %d\n", shift); } else{ printf("%d\n", shift); } image c = crop_image(b, delta, shift, a.w, a.h); int i; for(i = 0; i < c.w*c.h; ++i){ c.data[i] = a.data[i]; } #ifdef OPENCV save_image_jpg(c, out); #else save_image(c, out); #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; int h = im.h; if(w > h){ h = (h * max) / w; w = max; } else { w = (w * max) / h; h = max; } if(w == im.w && h == im.h) return im; image resized = resize_image(im, w, h); return resized; } image resize_min(image im, int min) { int w = im.w; int h = im.h; if(w < h){ h = (h * min) / w; w = min; } else { w = (w * min) / h; h = min; } if(w == im.w && h == im.h) return im; image resized = resize_image(im, w, h); return resized; } image random_crop_image(image im, int w, int h) { int dx = rand_int(0, im.w - w); int dy = rand_int(0, im.h - h); image crop = crop_image(im, dx, dy, w, h); return crop; } image random_augment_image(image im, float angle, float aspect, int low, int high, int size) { aspect = rand_scale(aspect); int r = rand_int(low, high); int min = (im.h < im.w*aspect) ? im.h : im.w*aspect; float scale = (float)r / min; float rad = rand_uniform(-angle, angle) * 2.0 * M_PI / 360.; float dx = (im.w*scale/aspect - size) / 2.; float dy = (im.h*scale - size) / 2.; if(dx < 0) dx = 0; if(dy < 0) dy = 0; dx = rand_uniform(-dx, dx); dy = rand_uniform(-dy, dy); image crop = rotate_crop_image(im, rad, scale, size, size, dx, dy, aspect); return crop; } float three_way_max(float a, float b, float c) { return (a > b) ? ( (a > c) ? a : c) : ( (b > c) ? b : c) ; } float three_way_min(float a, float b, float c) { return (a < b) ? ( (a < c) ? a : c) : ( (b < c) ? b : c) ; } // http://www.cs.rit.edu/~ncs/color/t_convert.html void rgb_to_hsv(image im) { assert(im.c == 3); int i, j; float r, g, b; float h, s, v; for(j = 0; j < im.h; ++j){ for(i = 0; i < im.w; ++i){ r = get_pixel(im, i , j, 0); g = get_pixel(im, i , j, 1); b = get_pixel(im, i , j, 2); float max = three_way_max(r,g,b); float min = three_way_min(r,g,b); float delta = max - min; v = max; if(max == 0){ s = 0; h = 0; }else{ s = delta/max; if(r == max){ h = (g - b) / delta; } else if (g == max) { h = 2 + (b - r) / delta; } else { h = 4 + (r - g) / delta; } if (h < 0) h += 6; h = h/6.; } set_pixel(im, i, j, 0, h); set_pixel(im, i, j, 1, s); set_pixel(im, i, j, 2, v); } } } void hsv_to_rgb(image im) { assert(im.c == 3); int i, j; float r, g, b; float h, s, v; float f, p, q, t; for(j = 0; j < im.h; ++j){ for(i = 0; i < im.w; ++i){ h = 6 * get_pixel(im, i , j, 0); s = get_pixel(im, i , j, 1); v = get_pixel(im, i , j, 2); if (s == 0) { r = g = b = v; } else { int index = floor(h); f = h - index; p = v*(1-s); q = v*(1-s*f); t = v*(1-s*(1-f)); if(index == 0){ r = v; g = t; b = p; } else if(index == 1){ r = q; g = v; b = p; } else if(index == 2){ r = p; g = v; b = t; } else if(index == 3){ r = p; g = q; b = v; } else if(index == 4){ r = t; g = p; b = v; } else { r = v; g = p; b = q; } } set_pixel(im, i, j, 0, r); set_pixel(im, i, j, 1, g); set_pixel(im, i, j, 2, b); } } } image grayscale_image(image im) { assert(im.c == 3); int i, j, k; image gray = make_image(im.w, im.h, 1); float scale[] = {0.587, 0.299, 0.114}; for(k = 0; k < im.c; ++k){ for(j = 0; j < im.h; ++j){ for(i = 0; i < im.w; ++i){ gray.data[i+im.w*j] += scale[k]*get_pixel(im, i, j, k); } } } return gray; } image threshold_image(image im, float thresh) { int i; image t = make_image(im.w, im.h, im.c); for(i = 0; i < im.w*im.h*im.c; ++i){ t.data[i] = im.data[i]>thresh ? 1 : 0; } return t; } image blend_image(image fore, image back, float alpha) { assert(fore.w == back.w && fore.h == back.h && fore.c == back.c); image blend = make_image(fore.w, fore.h, fore.c); int i, j, k; for(k = 0; k < fore.c; ++k){ for(j = 0; j < fore.h; ++j){ for(i = 0; i < fore.w; ++i){ float val = alpha * get_pixel(fore, i, j, k) + (1 - alpha)* get_pixel(back, i, j, k); set_pixel(blend, i, j, k, val); } } } return blend; } void scale_image_channel(image im, int c, float v) { int i, j; for(j = 0; j < im.h; ++j){ for(i = 0; i < im.w; ++i){ float pix = get_pixel(im, i, j, c); pix = pix*v; set_pixel(im, i, j, c, pix); } } } void translate_image_channel(image im, int c, float v) { int i, j; for(j = 0; j < im.h; ++j){ for(i = 0; i < im.w; ++i){ float pix = get_pixel(im, i, j, c); pix = pix+v; set_pixel(im, i, j, c, pix); } } } image binarize_image(image im) { image c = copy_image(im); int i; for(i = 0; i < im.w * im.h * im.c; ++i){ if(c.data[i] > .5) c.data[i] = 1; else c.data[i] = 0; } return c; } void saturate_image(image im, float sat) { rgb_to_hsv(im); scale_image_channel(im, 1, sat); hsv_to_rgb(im); constrain_image(im); } void hue_image(image im, float hue) { rgb_to_hsv(im); int i; for(i = 0; i < im.w*im.h; ++i){ im.data[i] = im.data[i] + hue; if (im.data[i] > 1) im.data[i] -= 1; if (im.data[i] < 0) im.data[i] += 1; } hsv_to_rgb(im); constrain_image(im); } void exposure_image(image im, float sat) { rgb_to_hsv(im); scale_image_channel(im, 2, sat); hsv_to_rgb(im); constrain_image(im); } void distort_image(image im, float hue, float sat, float val) { if (im.c >= 3) { rgb_to_hsv(im); scale_image_channel(im, 1, sat); scale_image_channel(im, 2, val); int i; for(i = 0; i < im.w*im.h; ++i){ im.data[i] = im.data[i] + hue; if (im.data[i] > 1) im.data[i] -= 1; if (im.data[i] < 0) im.data[i] += 1; } hsv_to_rgb(im); } else { scale_image_channel(im, 0, val); } constrain_image(im); } void random_distort_image(image im, float hue, float saturation, float exposure) { float dhue = rand_uniform_strong(-hue, hue); float dsat = rand_scale(saturation); float dexp = rand_scale(exposure); distort_image(im, dhue, dsat, dexp); } void saturate_exposure_image(image im, float sat, float exposure) { rgb_to_hsv(im); scale_image_channel(im, 1, sat); scale_image_channel(im, 2, exposure); hsv_to_rgb(im); constrain_image(im); } float bilinear_interpolate(image im, float x, float y, int c) { int ix = (int) floorf(x); int iy = (int) floorf(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; } void quantize_image(image im) { int size = im.c * im.w * im.h; int i; for (i = 0; i < size; ++i) im.data[i] = (int)(im.data[i] * 255) / 255. + (0.5/255); } void make_image_red(image im) { int r, c, k; for (r = 0; r < im.h; ++r) { for (c = 0; c < im.w; ++c) { float val = 0; for (k = 0; k < im.c; ++k) { val += get_pixel(im, c, r, k); set_pixel(im, c, r, k, 0); } for (k = 0; k < im.c; ++k) { //set_pixel(im, c, r, k, val); } set_pixel(im, c, r, 0, val); } } } image make_attention_image(int img_size, float *original_delta_cpu, float *original_input_cpu, int w, int h, int c) { image attention_img; attention_img.w = w; attention_img.h = h; attention_img.c = c; attention_img.data = original_delta_cpu; make_image_red(attention_img); int k; float min_val = 999999, mean_val = 0, max_val = -999999; for (k = 0; k < img_size; ++k) { if (original_delta_cpu[k] < min_val) min_val = original_delta_cpu[k]; if (original_delta_cpu[k] > max_val) max_val = original_delta_cpu[k]; mean_val += original_delta_cpu[k]; } mean_val = mean_val / img_size; float range = max_val - min_val; for (k = 0; k < img_size; ++k) { float val = original_delta_cpu[k]; val = fabs(mean_val - val) / range; original_delta_cpu[k] = val * 4; } image resized = resize_image(attention_img, w / 4, h / 4); attention_img = resize_image(resized, w, h); free_image(resized); for (k = 0; k < img_size; ++k) attention_img.data[k] += original_input_cpu[k]; //normalize_image(attention_img); //show_image(attention_img, "delta"); return attention_img; } image resize_image(image im, int w, int h) { if (im.w == w && im.h == h) return copy_image(im); image resized = make_image(w, h, im.c); image part = make_image(w, im.h, im.c); int r, c, k; 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 < im.h; ++r){ for(c = 0; c < w; ++c){ float val = 0; if(c == w-1 || im.w == 1){ val = get_pixel(im, im.w-1, r, k); } else { float sx = c*w_scale; int ix = (int) sx; float dx = sx - ix; val = (1 - dx) * get_pixel(im, ix, r, k) + dx * get_pixel(im, ix+1, r, k); } set_pixel(part, c, r, k, val); } } } for(k = 0; k < im.c; ++k){ for(r = 0; r < h; ++r){ float sy = r*h_scale; int iy = (int) sy; float dy = sy - iy; for(c = 0; c < w; ++c){ float val = (1-dy) * get_pixel(part, c, iy, k); set_pixel(resized, c, r, k, val); } if(r == h-1 || im.h == 1) continue; for(c = 0; c < w; ++c){ float val = dy * get_pixel(part, c, iy+1, k); add_pixel(resized, c, r, k, val); } } } free_image(part); return resized; } void test_resize(char *filename) { image im = load_image(filename, 0,0, 3); float mag = mag_array(im.data, im.w*im.h*im.c); printf("L2 Norm: %f\n", mag); image gray = grayscale_image(im); image c1 = copy_image(im); image c2 = copy_image(im); image c3 = copy_image(im); image c4 = copy_image(im); distort_image(c1, .1, 1.5, 1.5); distort_image(c2, -.1, .66666, .66666); distort_image(c3, .1, 1.5, .66666); distort_image(c4, .1, .66666, 1.5); show_image(im, "Original"); show_image(gray, "Gray"); show_image(c1, "C1"); show_image(c2, "C2"); show_image(c3, "C3"); show_image(c4, "C4"); #ifdef OPENCV while(1){ image aug = random_augment_image(im, 0, .75, 320, 448, 320); show_image(aug, "aug"); free_image(aug); float exposure = 1.15; float saturation = 1.15; float hue = .05; image c = copy_image(im); float dexp = rand_scale(exposure); float dsat = rand_scale(saturation); float dhue = rand_uniform(-hue, hue); distort_image(c, dhue, dsat, dexp); show_image(c, "rand"); printf("%f %f %f\n", dhue, dsat, dexp); free_image(c); wait_until_press_key_cv(); } #endif } image load_image_stb(char *filename, int channels) { int w, h, c; unsigned char *data = stbi_load(filename, &w, &h, &c, channels); if (!data) { char shrinked_filename[1024]; if (strlen(filename) >= 1024) sprintf(shrinked_filename, "name is too long"); else sprintf(shrinked_filename, "%s", filename); fprintf(stderr, "Cannot load image \"%s\"\nSTB Reason: %s\n", shrinked_filename, stbi_failure_reason()); FILE* fw = fopen("bad.list", "a"); fwrite(shrinked_filename, sizeof(char), strlen(shrinked_filename), fw); char *new_line = "\n"; fwrite(new_line, sizeof(char), strlen(new_line), fw); fclose(fw); if (check_mistakes) { printf("\n Error in load_image_stb() \n"); getchar(); } return make_image(10, 10, 3); //exit(EXIT_FAILURE); } if(channels) c = channels; int i,j,k; image im = make_image(w, h, c); for(k = 0; k < c; ++k){ for(j = 0; j < h; ++j){ for(i = 0; i < w; ++i){ int dst_index = i + w*j + w*h*k; int src_index = k + c*i + c*w*j; im.data[dst_index] = (float)data[src_index]/255.; } } } free(data); return im; } image load_image_stb_resize(char *filename, int w, int h, int c) { image out = load_image_stb(filename, c); // without OpenCV if ((h && w) && (h != out.h || w != out.w)) { image resized = resize_image(out, w, h); free_image(out); out = resized; } return out; } image load_image(char *filename, int w, int h, int c) { #ifdef OPENCV //image out = load_image_stb(filename, c); image out = load_image_cv(filename, c); #else image out = load_image_stb(filename, c); // without OpenCV #endif // OPENCV if((h && w) && (h != out.h || w != out.w)){ image resized = resize_image(out, w, h); free_image(out); out = resized; } return out; } image load_image_color(char *filename, int w, int h) { return load_image(filename, w, h, 3); } image get_image_layer(image m, int l) { 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; } void print_image(image m) { int i, j, k; for(i =0 ; i < m.c; ++i){ for(j =0 ; j < m.h; ++j){ for(k = 0; k < m.w; ++k){ printf("%.2lf, ", m.data[i*m.h*m.w + j*m.w + k]); if(k > 30) break; } printf("\n"); if(j > 30) break; } printf("\n"); } printf("\n"); } image collapse_images_vert(image *ims, int n) { int color = 1; int border = 1; int h,w,c; w = ims[0].w; h = (ims[0].h + border) * n - border; c = ims[0].c; if(c != 3 || !color){ w = (w+border)*c - border; c = 1; } 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, 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, w_offset, h_offset); free_image(layer); } } free_image(copy); } return filters; } image collapse_images_horz(image *ims, int n) { int color = 1; int border = 1; int h,w,c; int size = ims[0].h; h = size; w = (ims[0].w + border) * n - border; c = ims[0].c; if(c != 3 || !color){ h = (h+border)*c - border; c = 1; } 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, 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, w_offset, h_offset); free_image(layer); } } free_image(copy); } return filters; } void show_image_normalized(image im, const char *name) { image c = copy_image(im); normalize_image(c); show_image(c, name); free_image(c); } void show_images(image *ims, int n, char *window) { image m = collapse_images_vert(ims, n); /* int w = 448; int h = ((float)m.h/m.w) * 448; if(h > 896){ h = 896; w = ((float)m.w/m.h) * 896; } image sized = resize_image(m, w, h); */ normalize_image(m); save_image(m, window); show_image(m, window); free_image(m); } void free_image(image m) { if(m.data){ free(m.data); } } // Fast copy data from a contiguous byte array into the image. LIB_API void copy_image_from_bytes(image im, char *pdata) { unsigned char *data = (unsigned char*)pdata; int i, k, j; int w = im.w; int h = im.h; int c = im.c; for (k = 0; k < c; ++k) { for (j = 0; j < h; ++j) { for (i = 0; i < w; ++i) { int dst_index = i + w * j + w * h*k; int src_index = k + c * i + c * w*j; im.data[dst_index] = (float)data[src_index] / 255.; } } } }
