Metadata-Version: 2.1
Name: pascal_voc
Version: 2.1.11
Summary: Tool to work with annotation formats
Author: Alexander Barmin
Author-email: Alexander Barmin <barmin1@mail.ru>
License: MIT License
        
        Copyright (c) 2023 Alexandr
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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        SOFTWARE.
        
Project-URL: Homepage, https://github.com/Alek-dr/PascalVOC
Project-URL: Issues, https://github.com/Alek-dr/PascalVOC/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: Pillow>=8.1.0
Requires-Dist: transliterate>=1.10.2
Requires-Dist: xmlobj>=1.2.2
Requires-Dist: typing_extensions>=4.1.0

### pascal

Python utility to work with PascalVoc annotation format

Image examples from [PascalVoc2007](hhttp://host.robots.ox.ac.uk/pascal/VOC/voc2007/) dataset

##### Code Example

```
import json
from pathlib import Path

from PIL import Image

from pascal import annotation_from_xml
from pascal.utils import save_xml

ds_path = Path("/home/VOCtest_06-Nov-2007/VOCdevkit/VOC2007")

img_src = ds_path / "JPEGImages"
ann_src = ds_path / "Annotations"

out_labelme = ds_path / "converted_labelme"

attr_type_spec = {"truncated": bool, "difficult": bool}

label_map = {"car": 1, "dog": 0, "person": 2, "train": 3}

if __name__ == "__main__":
    for file in img_src.glob("*.jpg"):
        # Get annotation file path
        ann_file = (ann_src / file.name).with_suffix(".xml")
        # Make pascal annotation object
        ann = annotation_from_xml(ann_file, attr_type_spec)
        print(ann)
        # Save to xml file (same as ann_file)
        xml = ann.to_xml()
        out_xml_name = file.with_suffix(".xml").name
        save_xml(out_xml_name, xml)
        # Save yolo annotation
        yolo_ann = ann.to_yolo(label_map)
        out_yolo_name = file.with_suffix(".txt").name
        with open(out_yolo_name, "w") as f:
            f.write(yolo_ann)
        # Convert to labelme and save json file
        res = ann.to_labelme(file, save_img_data=False)
        with open((out_labelme / file.name).with_suffix(".json"), "w") as f:
            json.dump(res, f, indent=2)
        # Draw objects
        img = Image.open(file)
        draw_img = ann.draw_boxes(img)
        draw_img.show()
```

##### Visualization example:
```
draw_img = ann.draw_boxes(img)
draw_img.show()
```
![vis_example](examples/vis.png)

#### Installation
From source 
```
python setup.py install
```
Using pip
```
pip install pascal-voc
```
