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| import xml.etree.ElementTree as ET | |
| from tqdm import tqdm | |
| import os | |
| import shutil | |
| import argparse | |
| # VOC dataset (refer https://github.com/ultralytics/yolov5/blob/master/data/VOC.yaml) | |
| # VOC2007 trainval: 446MB, 5012 images | |
| # VOC2007 test: 438MB, 4953 images | |
| # VOC2012 trainval: 1.95GB, 17126 images | |
| VOC_NAMES = ['aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', | |
| 'horse', 'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor'] | |
| def convert_label(path, lb_path, year, image_id): | |
| def convert_box(size, box): | |
| dw, dh = 1. / size[0], 1. / size[1] | |
| x, y, w, h = (box[0] + box[1]) / 2.0 - 1, (box[2] + box[3]) / 2.0 - 1, box[1] - box[0], box[3] - box[2] | |
| return x * dw, y * dh, w * dw, h * dh | |
| in_file = open(os.path.join(path, f'VOC{year}/Annotations/{image_id}.xml')) | |
| out_file = open(lb_path, 'w') | |
| tree = ET.parse(in_file) | |
| root = tree.getroot() | |
| size = root.find('size') | |
| w = int(size.find('width').text) | |
| h = int(size.find('height').text) | |
| for obj in root.iter('object'): | |
| cls = obj.find('name').text | |
| if cls in VOC_NAMES and not int(obj.find('difficult').text) == 1: | |
| xmlbox = obj.find('bndbox') | |
| bb = convert_box((w, h), [float(xmlbox.find(x).text) for x in ('xmin', 'xmax', 'ymin', 'ymax')]) | |
| cls_id = VOC_NAMES.index(cls) # class id | |
| out_file.write(" ".join([str(a) for a in (cls_id, *bb)]) + '\n') | |
| def gen_voc07_12(voc_path): | |
| ''' | |
| Generate voc07+12 setting dataset: | |
| train: # train images 16551 images | |
| - images/train2012 | |
| - images/train2007 | |
| - images/val2012 | |
| - images/val2007 | |
| val: # val images (relative to 'path') 4952 images | |
| - images/test2007 | |
| ''' | |
| dataset_root = os.path.join(voc_path, 'voc_07_12') | |
| if not os.path.exists(dataset_root): | |
| os.makedirs(dataset_root) | |
| dataset_settings = {'train': ['train2007', 'val2007', 'train2012', 'val2012'], 'val':['test2007']} | |
| for item in ['images', 'labels']: | |
| for data_type, data_list in dataset_settings.items(): | |
| for data_name in data_list: | |
| ori_path = os.path.join(voc_path, item, data_name) | |
| new_path = os.path.join(dataset_root, item, data_type) | |
| if not os.path.exists(new_path): | |
| os.makedirs(new_path) | |
| print(f'[INFO]: Copying {ori_path} to {new_path}') | |
| for file in os.listdir(ori_path): | |
| shutil.copy(os.path.join(ori_path, file), new_path) | |
| def main(args): | |
| voc_path = args.voc_path | |
| for year, image_set in ('2012', 'train'), ('2012', 'val'), ('2007', 'train'), ('2007', 'val'), ('2007', 'test'): | |
| imgs_path = os.path.join(voc_path, 'images', f'{image_set}') | |
| lbs_path = os.path.join(voc_path, 'labels', f'{image_set}') | |
| try: | |
| with open(os.path.join(voc_path, f'VOC{year}/ImageSets/Main/{image_set}.txt'), 'r') as f: | |
| image_ids = f.read().strip().split() | |
| if not os.path.exists(imgs_path): | |
| os.makedirs(imgs_path) | |
| if not os.path.exists(lbs_path): | |
| os.makedirs(lbs_path) | |
| for id in tqdm(image_ids, desc=f'{image_set}{year}'): | |
| f = os.path.join(voc_path, f'VOC{year}/JPEGImages/{id}.jpg') # old img path | |
| lb_path = os.path.join(lbs_path, f'{id}.txt') # new label path | |
| convert_label(voc_path, lb_path, year, id) # convert labels to YOLO format | |
| if os.path.exists(f): | |
| shutil.move(f, imgs_path) # move image | |
| except Exception as e: | |
| print(f'[Warning]: {e} {year}{image_set} convert fail!') | |
| gen_voc07_12(voc_path) | |
| if __name__ == '__main__': | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--voc_path', default='VOCdevkit') | |
| args = parser.parse_args() | |
| print(args) | |
| main(args) |