Table of Contents
- Python -- one of the following:
- CPython : 3.6 and newer
- Pillow : Latest 8.x version
- lxml : Latest 4.x version
- tqdm : Latest 4.x version
- defusedxml : Latest 0.x version
Package is uploaded on PyPI.
You can install it with pip:
$ python3 -m pip install yolo2voc
The following examples show how to transform the dataset annotation
#import the yolo2voc
import Yolo2Voc
# setting args
annotation_path = "~/Pictures/yolo-labels" #where are the dataset annotations.
source = "Personal Dataset" #contains base dataset name.
output = "~/Pictures/voc-labels" #where it will be saved to new annotations.
Yolo2Voc.convert(annotations_path=annotation_path, source=source, output=output)
#Get version on Yolo2Voc
print(Yolo2Voc.__version__)
#Get Author Name
print(Yolo2Voc.__author__)
#Get Author Contact
print(Yolo2Voc.__email__)This example will print:
Loading your dataset....
100%|███████████████████████████████| 16/16 [00:00<?, ? file/s]
Please wait for all labels to be processed....
100%|███████████████████████████████| 8/8 [00:00<00:00, 21.39 label/s]
1.0.3
Willian Antunes
[email protected]Documentation is available online: https://yolo2voc.readthedocs.io/
Yolo2Voc is released under the MIT License. See LICENSE for more information.