Convert COCO annotations to xml format
COCO is a well-known detection dataset: http://cocodataset.org/
Overview: **
Annotation files are provided for train and validation images for COCO. These are in the form of .json files - 'JavaScript Object Notation' format- the information is in the form of key-value pairs, and if you are familiar with Python, you might recognize this as having a similar format to that of a Python dictionary. The code in this repository will convert that information to a PASCAL VOC -type .xml file.
Procedure: **
Annotations are read after the .json file is loaded. There are several annotations present, and it is important to note that each annotation doesn't correspond necessarily to one image, but to one object. This object again could be a single object, or an amalgamation of objects (in this case, the attribute 'iscrowd' is set to one). This code is agnostic to the 'iscrowd' parameter- but you might want to change this depending on your use-case. Xml files are generated for each image, after the annotations are pooled.
Why is this useful: **
Several reasons. -> You might want to train a detector like Yolov2, which uses .xml files https://github.com/thtrieu/darkflow
-> You might want to visualize annotations using tools like labelImg, which use .xml files https://github.com/tzutalin/labelImg
-> You might just want to do this for fun, and improve your Python skills :-)
USAGE **
-> Download the required annotation files- you may do so from the official COCO dataset (link given above)
-> Change the code accordingly based on whether the annotation is from train/val (or something else. If something else, the coco annotation format MUST be maintained, .json file and all)
-> Run coco_get_annotations_xml_format.py
-> Get your .xml files, and do what you need to do with them.
