Framework to collect dataset in COCO format for images/videos using pretrained neural networks.
Framework to collect dataset in COCO format for images/videos using pretrained neural networks.
There are supported datasets.
Annotation example
{ "videos" : [video], "annotations" : [annotation], "categories" : [category], } video{ "id" : int, "width" : int, "height" : int, "length" : int, "file_names" : [file_name], } annotation{ "id" : int, "video_id" : int, "category_id" : int, "segmentations" : [RLE or [polygon] or None], "areas" : [float or None], "bboxes" : [[x,y,width,height] or None], "iscrowd" : 0 or 1, } category{ "id" : int, "name" : str, "supercategory" : str, }Annotation example
{ "images": [image], "annotations": [annotation], "categories": [category], } image{ "id": int, "width": int, "height": int, "file_name": str, } annotation{ "id": int, "image_id": int, "category_id": int, "segmentation": RLE or [polygon], "area": float, "bbox": [x,y,width,height], "iscrowd": 0 or 1, } category{ "id": int, "name": str, "supercategory": str, }git clone https://github.com/msb-tech/dataset-collection.git
cd dataset-collectionBefore running you should change the default values in docker_names.sh. After that type
source docker/docker_names.sh
bash docker/build+run.sh
python3 tools/process_data.py -c config.py -sTo see help info about the script, type
python3 tools/process_data.py --helppip install pre-commit
pre-commit install