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import argparse |
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import os.path as osp |
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import xml.etree.ElementTree as ET |
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import mmcv |
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import numpy as np |
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from mmdet.core import voc_classes |
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label_ids = {name: i for i, name in enumerate(voc_classes())} |
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def parse_xml(args): |
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xml_path, img_path = args |
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tree = ET.parse(xml_path) |
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root = tree.getroot() |
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size = root.find('size') |
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w = int(size.find('width').text) |
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h = int(size.find('height').text) |
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bboxes = [] |
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labels = [] |
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bboxes_ignore = [] |
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labels_ignore = [] |
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for obj in root.findall('object'): |
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name = obj.find('name').text |
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label = label_ids[name] |
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difficult = int(obj.find('difficult').text) |
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bnd_box = obj.find('bndbox') |
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bbox = [ |
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int(bnd_box.find('xmin').text), |
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int(bnd_box.find('ymin').text), |
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int(bnd_box.find('xmax').text), |
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int(bnd_box.find('ymax').text) |
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] |
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if difficult: |
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bboxes_ignore.append(bbox) |
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labels_ignore.append(label) |
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else: |
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bboxes.append(bbox) |
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labels.append(label) |
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if not bboxes: |
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bboxes = np.zeros((0, 4)) |
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labels = np.zeros((0, )) |
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else: |
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bboxes = np.array(bboxes, ndmin=2) - 1 |
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labels = np.array(labels) |
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if not bboxes_ignore: |
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bboxes_ignore = np.zeros((0, 4)) |
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labels_ignore = np.zeros((0, )) |
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else: |
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bboxes_ignore = np.array(bboxes_ignore, ndmin=2) - 1 |
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labels_ignore = np.array(labels_ignore) |
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annotation = { |
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'filename': img_path, |
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'width': w, |
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'height': h, |
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'ann': { |
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'bboxes': bboxes.astype(np.float32), |
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'labels': labels.astype(np.int64), |
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'bboxes_ignore': bboxes_ignore.astype(np.float32), |
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'labels_ignore': labels_ignore.astype(np.int64) |
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} |
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} |
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return annotation |
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def cvt_annotations(devkit_path, years, split, out_file): |
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if not isinstance(years, list): |
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years = [years] |
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annotations = [] |
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for year in years: |
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filelist = osp.join(devkit_path, |
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f'VOC{year}/ImageSets/Main/{split}.txt') |
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if not osp.isfile(filelist): |
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print(f'filelist does not exist: {filelist}, ' |
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f'skip voc{year} {split}') |
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return |
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img_names = mmcv.list_from_file(filelist) |
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xml_paths = [ |
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osp.join(devkit_path, f'VOC{year}/Annotations/{img_name}.xml') |
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for img_name in img_names |
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] |
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img_paths = [ |
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f'VOC{year}/JPEGImages/{img_name}.jpg' for img_name in img_names |
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] |
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part_annotations = mmcv.track_progress(parse_xml, |
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list(zip(xml_paths, img_paths))) |
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annotations.extend(part_annotations) |
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if out_file.endswith('json'): |
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annotations = cvt_to_coco_json(annotations) |
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mmcv.dump(annotations, out_file) |
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return annotations |
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def cvt_to_coco_json(annotations): |
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image_id = 0 |
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annotation_id = 0 |
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coco = dict() |
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coco['images'] = [] |
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coco['type'] = 'instance' |
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coco['categories'] = [] |
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coco['annotations'] = [] |
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image_set = set() |
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def addAnnItem(annotation_id, image_id, category_id, bbox, difficult_flag): |
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annotation_item = dict() |
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annotation_item['segmentation'] = [] |
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seg = [] |
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seg.append(int(bbox[0])) |
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seg.append(int(bbox[1])) |
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seg.append(int(bbox[0])) |
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seg.append(int(bbox[3])) |
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seg.append(int(bbox[2])) |
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seg.append(int(bbox[3])) |
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seg.append(int(bbox[2])) |
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seg.append(int(bbox[1])) |
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annotation_item['segmentation'].append(seg) |
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xywh = np.array( |
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[bbox[0], bbox[1], bbox[2] - bbox[0], bbox[3] - bbox[1]]) |
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annotation_item['area'] = int(xywh[2] * xywh[3]) |
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if difficult_flag == 1: |
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annotation_item['ignore'] = 0 |
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annotation_item['iscrowd'] = 1 |
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else: |
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annotation_item['ignore'] = 0 |
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annotation_item['iscrowd'] = 0 |
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annotation_item['image_id'] = int(image_id) |
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annotation_item['bbox'] = xywh.astype(int).tolist() |
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annotation_item['category_id'] = int(category_id) |
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annotation_item['id'] = int(annotation_id) |
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coco['annotations'].append(annotation_item) |
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return annotation_id + 1 |
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for category_id, name in enumerate(voc_classes()): |
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category_item = dict() |
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category_item['supercategory'] = str('none') |
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category_item['id'] = int(category_id) |
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category_item['name'] = str(name) |
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coco['categories'].append(category_item) |
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for ann_dict in annotations: |
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file_name = ann_dict['filename'] |
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ann = ann_dict['ann'] |
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assert file_name not in image_set |
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image_item = dict() |
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image_item['id'] = int(image_id) |
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image_item['file_name'] = str(file_name) |
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image_item['height'] = int(ann_dict['height']) |
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image_item['width'] = int(ann_dict['width']) |
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coco['images'].append(image_item) |
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image_set.add(file_name) |
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bboxes = ann['bboxes'][:, :4] |
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labels = ann['labels'] |
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for bbox_id in range(len(bboxes)): |
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bbox = bboxes[bbox_id] |
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label = labels[bbox_id] |
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annotation_id = addAnnItem( |
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annotation_id, image_id, label, bbox, difficult_flag=0) |
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bboxes_ignore = ann['bboxes_ignore'][:, :4] |
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labels_ignore = ann['labels_ignore'] |
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for bbox_id in range(len(bboxes_ignore)): |
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bbox = bboxes_ignore[bbox_id] |
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label = labels_ignore[bbox_id] |
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annotation_id = addAnnItem( |
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annotation_id, image_id, label, bbox, difficult_flag=1) |
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image_id += 1 |
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return coco |
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def parse_args(): |
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parser = argparse.ArgumentParser( |
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description='Convert PASCAL VOC annotations to mmdetection format') |
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parser.add_argument('devkit_path', help='pascal voc devkit path') |
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parser.add_argument('-o', '--out-dir', help='output path') |
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parser.add_argument( |
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'--out-format', |
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default='pkl', |
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choices=('pkl', 'coco'), |
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help='output format, "coco" indicates coco annotation format') |
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args = parser.parse_args() |
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return args |
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def main(): |
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args = parse_args() |
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devkit_path = args.devkit_path |
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out_dir = args.out_dir if args.out_dir else devkit_path |
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mmcv.mkdir_or_exist(out_dir) |
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years = [] |
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if osp.isdir(osp.join(devkit_path, 'VOC2007')): |
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years.append('2007') |
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if osp.isdir(osp.join(devkit_path, 'VOC2012')): |
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years.append('2012') |
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if '2007' in years and '2012' in years: |
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years.append(['2007', '2012']) |
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if not years: |
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raise IOError(f'The devkit path {devkit_path} contains neither ' |
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'"VOC2007" nor "VOC2012" subfolder') |
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out_fmt = f'.{args.out_format}' |
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if args.out_format == 'coco': |
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out_fmt = '.json' |
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for year in years: |
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if year == '2007': |
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prefix = 'voc07' |
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elif year == '2012': |
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prefix = 'voc12' |
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elif year == ['2007', '2012']: |
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prefix = 'voc0712' |
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for split in ['train', 'val', 'trainval']: |
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dataset_name = prefix + '_' + split |
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print(f'processing {dataset_name} ...') |
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cvt_annotations(devkit_path, year, split, |
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osp.join(out_dir, dataset_name + out_fmt)) |
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if not isinstance(year, list): |
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dataset_name = prefix + '_test' |
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print(f'processing {dataset_name} ...') |
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cvt_annotations(devkit_path, year, 'test', |
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osp.join(out_dir, dataset_name + out_fmt)) |
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print('Done!') |
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if __name__ == '__main__': |
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main() |
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