| | |
| | | return X; |
| | | } |
| | | |
| | | matrix load_image_augment_paths(char **paths, int n, int min, int max, int size, float angle, float exposure, float saturation) |
| | | matrix load_image_augment_paths(char **paths, int n, int min, int max, int size, float angle, float hue, float saturation, float exposure) |
| | | { |
| | | int i; |
| | | matrix X; |
| | |
| | | image crop = random_augment_image(im, angle, min, max, size); |
| | | int flip = rand_r(&data_seed)%2; |
| | | if (flip) flip_image(crop); |
| | | float exp = rand_uniform(1./exposure, exposure); |
| | | float sat = rand_uniform(1./saturation, saturation); |
| | | exposure_image(crop, exp); |
| | | exposure_image(crop, sat); |
| | | random_distort_image(crop, hue, saturation, exposure); |
| | | |
| | | /* |
| | | show_image(im, "orig"); |
| | |
| | | labelpath = find_replace(labelpath, "JPEGImages", "labels"); |
| | | |
| | | labelpath = find_replace(labelpath, ".jpg", ".txt"); |
| | | labelpath = find_replace(labelpath, ".png", ".txt"); |
| | | labelpath = find_replace(labelpath, ".JPG", ".txt"); |
| | | labelpath = find_replace(labelpath, ".JPEG", ".txt"); |
| | | int count = 0; |
| | |
| | | labelpath = find_replace(labelpath, "JPEGImages", "labels"); |
| | | |
| | | labelpath = find_replace(labelpath, ".jpg", ".txt"); |
| | | labelpath = find_replace(labelpath, ".png", ".txt"); |
| | | labelpath = find_replace(labelpath, ".JPG", ".txt"); |
| | | labelpath = find_replace(labelpath, ".JPEG", ".txt"); |
| | | int count = 0; |
| | |
| | | } |
| | | } |
| | | |
| | | data load_data_region(int n, char **paths, int m, int w, int h, int size, int classes, float jitter) |
| | | data load_data_region(int n, char **paths, int m, int w, int h, int size, int classes, float jitter, float hue, float saturation, float exposure) |
| | | { |
| | | char **random_paths = get_random_paths(paths, n, m); |
| | | int i; |
| | |
| | | |
| | | image sized = resize_image(cropped, w, h); |
| | | if(flip) flip_image(sized); |
| | | random_distort_image(sized, hue, saturation, exposure); |
| | | d.X.vals[i] = sized.data; |
| | | |
| | | fill_truth_region(random_paths[i], d.y.vals[i], classes, size, flip, dx, dy, 1./sx, 1./sy); |
| | |
| | | return d; |
| | | } |
| | | |
| | | data load_data_detection(int n, char **paths, int m, int w, int h, int boxes, int classes, float jitter) |
| | | data load_data_detection(int n, char **paths, int m, int w, int h, int boxes, int classes, float jitter, float hue, float saturation, float exposure) |
| | | { |
| | | char **random_paths = get_random_paths(paths, n, m); |
| | | int i; |
| | |
| | | |
| | | image sized = resize_image(cropped, w, h); |
| | | if(flip) flip_image(sized); |
| | | random_distort_image(sized, hue, saturation, exposure); |
| | | d.X.vals[i] = sized.data; |
| | | |
| | | fill_truth_detection(random_paths[i], boxes, d.y.vals[i], classes, flip, dx, dy, 1./sx, 1./sy); |
| | |
| | | if (a.type == OLD_CLASSIFICATION_DATA){ |
| | | *a.d = load_data(a.paths, a.n, a.m, a.labels, a.classes, a.w, a.h); |
| | | } else if (a.type == CLASSIFICATION_DATA){ |
| | | *a.d = load_data_augment(a.paths, a.n, a.m, a.labels, a.classes, a.min, a.max, a.size, a.angle, a.exposure, a.saturation); |
| | | *a.d = load_data_augment(a.paths, a.n, a.m, a.labels, a.classes, a.min, a.max, a.size, a.angle, a.hue, a.saturation, a.exposure); |
| | | } else if (a.type == SUPER_DATA){ |
| | | *a.d = load_data_super(a.paths, a.n, a.m, a.w, a.h, a.scale); |
| | | } else if (a.type == STUDY_DATA){ |
| | | *a.d = load_data_study(a.paths, a.n, a.m, a.labels, a.classes, a.min, a.max, a.size, a.angle, a.exposure, a.saturation); |
| | | *a.d = load_data_study(a.paths, a.n, a.m, a.labels, a.classes, a.min, a.max, a.size, a.angle, a.hue, a.saturation, a.exposure); |
| | | } else if (a.type == WRITING_DATA){ |
| | | *a.d = load_data_writing(a.paths, a.n, a.m, a.w, a.h, a.out_w, a.out_h); |
| | | } else if (a.type == REGION_DATA){ |
| | | *a.d = load_data_region(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter); |
| | | *a.d = load_data_region(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure); |
| | | } else if (a.type == DETECTION_DATA){ |
| | | *a.d = load_data_detection(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter); |
| | | *a.d = load_data_detection(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure); |
| | | } else if (a.type == SWAG_DATA){ |
| | | *a.d = load_data_swag(a.paths, a.n, a.classes, a.jitter); |
| | | } else if (a.type == COMPARE_DATA){ |
| | |
| | | *(a.im) = load_image_color(a.path, 0, 0); |
| | | *(a.resized) = resize_image(*(a.im), a.w, a.h); |
| | | } else if (a.type == TAG_DATA){ |
| | | *a.d = load_data_tag(a.paths, a.n, a.m, a.classes, a.min, a.max, a.size, a.angle, a.exposure, a.saturation); |
| | | *a.d = load_data_tag(a.paths, a.n, a.m, a.classes, a.min, a.max, a.size, a.angle, a.hue, a.saturation, a.exposure); |
| | | //*a.d = load_data(a.paths, a.n, a.m, a.labels, a.classes, a.w, a.h); |
| | | } |
| | | free(ptr); |
| | |
| | | return d; |
| | | } |
| | | |
| | | data load_data_study(char **paths, int n, int m, char **labels, int k, int min, int max, int size, float angle, float exposure, float saturation) |
| | | data load_data_study(char **paths, int n, int m, char **labels, int k, int min, int max, int size, float angle, float hue, float saturation, float exposure) |
| | | { |
| | | data d = {0}; |
| | | d.indexes = calloc(n, sizeof(int)); |
| | | if(m) paths = get_random_paths_indexes(paths, n, m, d.indexes); |
| | | d.shallow = 0; |
| | | d.X = load_image_augment_paths(paths, n, min, max, size, angle, exposure, saturation); |
| | | d.X = load_image_augment_paths(paths, n, min, max, size, angle, hue, saturation, exposure); |
| | | d.y = load_labels_paths(paths, n, labels, k); |
| | | if(m) free(paths); |
| | | return d; |
| | |
| | | return d; |
| | | } |
| | | |
| | | data load_data_augment(char **paths, int n, int m, char **labels, int k, int min, int max, int size, float angle, float exposure, float saturation) |
| | | data load_data_augment(char **paths, int n, int m, char **labels, int k, int min, int max, int size, float angle, float hue, float saturation, float exposure) |
| | | { |
| | | if(m) paths = get_random_paths(paths, n, m); |
| | | data d = {0}; |
| | | d.shallow = 0; |
| | | d.X = load_image_augment_paths(paths, n, min, max, size, angle, exposure, saturation); |
| | | d.X = load_image_augment_paths(paths, n, min, max, size, angle, hue, saturation, exposure); |
| | | d.y = load_labels_paths(paths, n, labels, k); |
| | | if(m) free(paths); |
| | | return d; |
| | | } |
| | | |
| | | data load_data_tag(char **paths, int n, int m, int k, int min, int max, int size, float angle, float exposure, float saturation) |
| | | data load_data_tag(char **paths, int n, int m, int k, int min, int max, int size, float angle, float hue, float saturation, float exposure) |
| | | { |
| | | if(m) paths = get_random_paths(paths, n, m); |
| | | data d = {0}; |
| | | d.w = size; |
| | | d.h = size; |
| | | d.shallow = 0; |
| | | d.X = load_image_augment_paths(paths, n, min, max, size, angle, exposure, saturation); |
| | | d.X = load_image_augment_paths(paths, n, min, max, size, angle, hue, saturation, exposure); |
| | | d.y = load_tags_paths(paths, n, k); |
| | | if(m) free(paths); |
| | | return d; |