| from tqdm import tqdm |
| import json |
| import cv2 |
| from os.path import join as pjoin |
|
|
| from config.CONFIG_UIED import Config |
| C = Config() |
|
|
|
|
| def draw_bounding_box_class(org, components, color=C.COLOR, line=2, show=False, write_path=None): |
| """ |
| Draw bounding box of components with their classes on the original image |
| :param org: original image |
| :param components: bbox [(column_min, row_min, column_max, row_max)] |
| -> top_left: (column_min, row_min) |
| -> bottom_right: (column_max, row_max) |
| :param color_map: colors mapping to different components |
| :param line: line thickness |
| :param compo_class: classes matching the corners of components |
| :param show: show or not |
| :return: labeled image |
| """ |
| board = org.copy() |
| bboxes = components['bboxes'] |
| categories = components['categories'] |
| for i in range(len(bboxes)): |
| bbox = bboxes[i] |
| category = categories[i] |
| board = cv2.rectangle(board, (bbox[0], bbox[1]), (bbox[2], bbox[3]), color[C.CLASS_MAP[str(category)]], line) |
| board = cv2.putText(board, C.CLASS_MAP[str(category)], (bbox[0]+5, bbox[1]+20), cv2.FONT_HERSHEY_SIMPLEX, 0.8, color[C.CLASS_MAP[str(category)]], 2) |
| if show: |
| cv2.imshow('a', cv2.resize(board, (500, 1000))) |
| cv2.waitKey(0) |
| if write_path is not None: |
| cv2.imwrite(write_path, board) |
| return board |
|
|
|
|
| def load_ground_truth_json(gt_file, no_text=True): |
| def get_img_by_id(img_id): |
| for image in images: |
| if image['id'] == img_id: |
| return image['file_name'].split('/')[-1][:-4], (image['height'], image['width']) |
|
|
| def cvt_bbox(bbox): |
| ''' |
| :param bbox: [x,y,width,height] |
| :return: [col_min, row_min, col_max, row_max] |
| ''' |
| bbox = [int(b) for b in bbox] |
| return [bbox[0], bbox[1], bbox[0] + bbox[2], bbox[1] + bbox[3]] |
|
|
| data = json.load(open(gt_file, 'r')) |
| images = data['images'] |
| annots = data['annotations'] |
| compos = {} |
| print('Loading %d ground truth' % len(annots)) |
| for annot in tqdm(annots): |
| img_name, size = get_img_by_id(annot['image_id']) |
| if no_text and int(annot['category_id']) == 14: |
| compos[img_name] = {'bboxes': [], 'categories': [], 'size': size} |
| continue |
| if img_name not in compos: |
| compos[img_name] = {'bboxes': [cvt_bbox(annot['bbox'])], 'categories': [annot['category_id']], 'size':size} |
| else: |
| compos[img_name]['bboxes'].append(cvt_bbox(annot['bbox'])) |
| compos[img_name]['categories'].append(annot['category_id']) |
| return compos |
|
|
|
|
| def view_gt_all(gt, img_root): |
| for img_id in gt: |
| compos = gt[img_id] |
| img = cv2.imread(pjoin(img_root, img_id + '.jpg')) |
| print(pjoin(img_root, img_id + '.jpg')) |
| draw_bounding_box_class(img, compos, show=True) |
|
|
|
|
| def view_gt_single(gt, img_root, img_id): |
| img_id = str(img_id) |
| compos = gt[img_id] |
| img = cv2.imread(pjoin(img_root, img_id + '.jpg')) |
| print(pjoin(img_root, img_id + '.jpg')) |
| draw_bounding_box_class(img, compos, show=True) |
|
|
|
|
| gt = load_ground_truth_json('E:\\Mulong\\Datasets\\rico\\instances_test.json', no_text=False) |
| |
| view_gt_single(gt, 'E:\\Mulong\\Datasets\\rico\\combined', 670) |
|
|
