cocojson
Utility functions for COCO json annotation format. The COCO Format is defined here.
Install
cocojsonis available on pypi throughpip3 install cocojson- or if you prefer, clone this repo and it can be installed through
pip3 install -e .(editable install) orpip3 install .as well.
Usage
Please click into each for more details (if applicable). Links works only if you're viewing from the github homepage.
Utility Tools
COCO Categori-fy
Convert your custom dataset into COCO categories. Usually used for testing a coco-pretrained model against a custom dataset with overlapping categories with the 80 COCO classes.
python3 -m cocojson.run.coco_catify -h
Extract only Annotations
Get annotations/predictions only from a COCO JSON. Usually used to generate a list of predictions for COCO evaluation.
python3 -m cocojson.run.pred_only -h
Filter Categories
Filter categories from COCO JSON.
python3 -m cocojson.run.filter_cat -h
Insert Images Meta-Information
Insert any extra attributes/image meta information associated with the images into the coco json file.
python3 -m cocojson.run.insert_img_meta -h
Map Categories
Mapping categories to a new dataset. Usually used for converting annotation labels to actual class label for training.
python3 -m cocojson.run.map_cat -h
Match Images between 2 COCO JSONs
Match images between a reference COCO JSON A and COCO JSON B (to be trimmed). Any images in JSON B that is not found in JSON A will be removed (along with associated annotations)
python3 -m cocojson.run.match_imgs -h
Merge
Merges multiple datasets
python3 -m cocojson.run.merge -h
Merge from file
Merges multiple datasets
python3 -m cocojson.run.merge_from_file -h
Prune Ignores
Remove images annotated with certain "ignore" category labels. This is usually used for removing rubbish images that are pointed out by annotators to ignore frame.
python3 -m cocojson.run.ignore_prune -h
Remove Empty
Remove empty/negative images from COCO JSON, aka images without associated annotations.
python3 -m cocojson.run.remove_empty -h
Sample
Samples k images from a dataset
python3 -m cocojson.run.sample -h
Sample by Category
Samples images from each category for given sample number(s).
python3 -m cocojson.run.sample_by_class -h
Split
Split up a COCO JSON file by images into N sets defined by ratio of total images
python3 -m cocojson.run.split -h
Split by Image Meta-Information
Split up a COCO JSON file by images' meta-information/attributes
python3 -m cocojson.run.split_by_meta -h
Visualise
Visualise annotations onto images. Best used for sanity check.
python3 -m cocojson.run.viz -h
Converters
CVAT Video XML to COCO JSON
Convert CVAT Video XML to COCO JSON whilst preserving track information.
python3 -m cocojson.run.cvatvid2coco -h
CVAT Image XML to COCO JSON
TODO
CrowdHuman odgt to COCO JSON
Converts CrowdHuman's odgt annotation format to COCO JSON format.
python3 -m cocojson.run.crowdhuman2coco -h
Custom Object Detection Logging format to COCO JSON
Converts Custom Object Detection Logging format to COCO JSON format.
python3 -m cocojson.run.log2coco -h
COCO to Darknet
TODO
COCO Eval
Please use https://github.com/levan92/cocoapi.
1 maintainer
Metadata
1 maintainer
Release files for cocojson 0.1.1
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| File | Size | Uploaded | Provenance | Actions |
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