microsoft / annotation-factory

Simple Python package for converting between CustomVision <-> Pascal VOC <-> YOLO annotations

Introduction

Annotation-Factory Python SDK. This package works specifically with Microsoft Cognitive Services detection results. AnnotationWriter takes a JSON object received from Cognitive Services and produces annotation files in both VOC and YOLO formats for use in training machine learning models.

Getting Started

1. Install annotationfactory package via pip:

   pip install annotationfactory
   

Sample to use

from annotationfactory.annotationwriter import AnnotationWriter
import annotationfactory.annotationconverter as converter

example = {
    'tagId': 0,
    'tagName': 'Apples',
    'region': {
        'left': 0.288039029,
        'top': 0.411838,
        'width': 0.291451037,
        'height': 0.4237842
    }
}

# Initialise AnnotationWriter.
writer = AnnotationWriter()

# Initialise annotation handlers.
writer.initVoc("test.jpg", 608, 608)
writer.initYolo()

# Add VOC object to writer.
writer.addVocObject(example)
writer.addVocObject(example)

# Add YOLO object to writer.
writer.addYoloObject(example)
writer.addYoloObject(example)

# Output VOC annotations to file.
writer.saveVoc("myannotation.xml")

# Output YOLO annotations to file.
writer.saveYolo("myannotation.txt")

# Converts VOC annotations back to CustomVision annotation format.
voc2cv = converter.convertVocFromPath("myannotation.xml")

# Converts YOLO annotations back to CustomVision annotation format.
# Requires a txt file with list of label names as an input.
yolo2cv = converter.convertYoloFromPath("myannotation.txt", "class.names")

Run locally

pip install -r requirements.txt 
python example/test.py

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

annotation-factory's Issues

Possible to update for custom vision?

The json response I receive from custom vision detection project (v3.0 api) does not seem to work with annotation-factory.

I receive this error:
Failed validating 'type' in schema:

Is this correct or my error? Possible to update annotation-factory for the current custom vision api?

This repo is missing important files

There are important files that Microsoft projects should all have that are not present in this repository. A pull request has been opened to add the missing file(s). When the pr is merged this issue will be closed automatically.

Microsoft teams can learn more about this effort and share feedback within the open source guidance available internally.

Merge this pull request

The conversion to VOC is wrong

Check the example/test.py :

example = {
    'tagId': 0,
    'tagName': 'Apple',
    'region': {
        'left': 0.288039029,
        'top': 0.411838,
        'width': 0.291451037,
        'height': 0.4237842
    }
}

and in the result VOC file myannotation.xml:
175.127729632
250.397504
177.20223049600003
257.6607936

It's obviously wrong unless 'xmax' here means 'width', and ‘ymax' means 'height'.