voc2coco
This is script for converting VOC format XMLs to COCO format json(ex. coco_eval.json).
Why we need to convert VOC xmls to COCO format json ?
We can use COCO API, this is very useful(ex. calculating mAP).
How to use
1. Make labels.txt
labels.txt if need for making dictionary for converting label to id.
Sample labels.txt
Label1
Label2
...In order to get all labels from your *.xml files, you can use this command in shell:
grep -REoh '<name>.*</name>' /Path_to_Folder | sort | uniq
This will search for all name tags in VOC.xml files, then show unique ones. You can also go further and create labels.txt file.
grep -ERoh '<name>(.*)</name>' /Path_to_folder | sort | uniq | sed 's/<name>//g' | sed 's/<\/name>//g' > labels.txt
2. Run script
2.1 Usage 1(Use ids list)
$ python voc2coco.py \
--ann_dir /path/to/annotation/dir \
--ann_ids /path/to/annotations/ids/list.txt \
--labels /path/to/labels.txt \
--output /path/to/output.json \
<option> --ext xml2.2 Usage 2(Use annotation paths list)
Sample paths.txt
/path/to/annotation/file.xml
/path/to/annotation/file2.xml
...$ python voc2coco.py \
--ann_paths_list /path/to/annotation/paths.txt \
--labels /path/to/labels.txt \
--output /path/to/output.json \
<option> --ext xml3. Example of usage
In this case, you can convert Shenggan/BCCD_Dataset: BCCD Dataset is a small-scale dataset for blood cells detection. by this script.
$ python voc2coco.py
--ann_dir sample/Annotations \
--ann_ids sample/dataset_ids/test.txt \
--labels sample/labels.txt \
--output sample/bccd_test_cocoformat.json \
--ext xml
# Check output
$ ls sample/ | grep bccd_test_cocoformat.json
bccd_test_cocoformat.json
# Check output
cut -f -4 -d , sample/bccd_test_cocoformat.json
{"images": [{"file_name": "BloodImage_00007.jpg", "height": 480, "width": 640, "id": "BloodImage_00007"}