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Pascal VOC annotation to Apple createML annotations conversion tool
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| import argparse | |
| import json | |
| import logging | |
| import pathlib | |
| from xml.etree import ElementTree | |
| log = logging.getLogger(__name__) | |
| def _parse_arguments() -> argparse.Namespace: | |
| parser = argparse.ArgumentParser( | |
| description='Pascal VOC to Apple createML annotations converter') | |
| parser.add_argument('--verbose', '-v', action='store_true', | |
| help='Verbose mode') | |
| parser.add_argument('--source', '-s', default='./', type=str, help='Source path') | |
| parser.add_argument('--destination', '-d', default='./annotations.json', type=str, help='Destination file') | |
| return parser.parse_args() | |
| def _parse_annotation(box): | |
| label = box.find('name').text | |
| bndbox = box.find('bndbox') | |
| xmin = float(bndbox.find('xmin').text) | |
| ymin = float(bndbox.find('ymin').text) | |
| xmax = float(bndbox.find('xmax').text) | |
| ymax = float(bndbox.find('ymax').text) | |
| return { | |
| 'label': label, | |
| 'coordinates': { | |
| # Bounding box's origin is the center in createML | |
| # It is the top-left corner in VOC | |
| 'x': (xmin + xmax) / 2.0, | |
| 'y': (ymin + ymax) / 2.0, | |
| 'width': xmax - xmin, | |
| 'height': ymax - ymin, | |
| }, | |
| } | |
| def _process_single_image(xml_file: pathlib.Path): | |
| log.info("Processing: %s", xml_file) | |
| tree = ElementTree.parse(xml_file) | |
| root = tree.getroot() | |
| image_filename = root.find('filename').text | |
| boxes = root.iterfind('object') | |
| annotations = [_parse_annotation(box) for box in boxes] | |
| return { | |
| 'imagefilename': image_filename, | |
| 'annotation': annotations, | |
| } | |
| def main(): | |
| # Parsing script input parameters | |
| args = _parse_arguments() | |
| level = logging.DEBUG if args.verbose else logging.INFO | |
| logging.basicConfig(level=level) | |
| source_path = pathlib.Path(args.source) | |
| destination_file = pathlib.Path(args.destination) | |
| # Build content of the annotations.json | |
| images_content = [_process_single_image(xml_file) for xml_file in source_path.glob('*.xml')] | |
| # Save output annotation file | |
| with open(destination_file, 'w') as file: | |
| json.dump(images_content, file, indent=4) | |
| log.info("Saved %s annotated images in %s", len(images_content), destination_file) | |
| if __name__ == "__main__": | |
| main() |
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