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Individual Video Annotations

For each video file, we store the annotations in a separate json file named image_name.image_format.json with the following file structure:
Example:
cudoid_3d example
Json format of annotation for video format:
{
    "size": {
        "height": 1080,
        "width": 1920
    },
    "description": "",
    "key": "c8168b43ae1b45c38930f456df9d0f2b",
    "tags": [],
    "objects": [
        {
            "key": "198f727d40c749eebcacc4aed299b39a",
            "classTitle": "rect",
            "tags": [],
            "labelerLogin": "alexxx",
            "updatedAt": "2020-08-23T12:06:11.963Z",
            "createdAt": "2020-08-23T12:06:11.963Z"
        }
    ],
    "frames": [
        {
            "index": 0,
            "figures": [
                {
                    "key": "65f21690780e43b49863c3cbd07eab3a",
                    "objectKey": "198f727d40c749eebcacc4aed299b39a",
                    "geometryType": "rectangle",
                    "geometry": {
                        "points": {
                            "exterior": [
                                [
                                    266,
                                    420
                                ],
                                [
                                    847,
                                    845
                                ]
                            ],
                            "interior": []
                        }
                    },
                    "labelerLogin": "alexxx",
                    "updatedAt": "2020-08-23T12:06:13.544Z",
                    "createdAt": "2020-08-23T12:06:13.544Z"
                }
            ]
        }
    ],
    "framesCount": 375
}
Fields definitions:
size - string - is equal to image(frame) size
description - string - (optional) - this field is used to store the text we want to assign to the video. In the labeling intrface it corresponds to the 'data' filed.
tags - list of strings that will be interpreted as video tags
key - string, unique key for a given video (used in key_id_map.json to get the video ID)
objects - list of objects that may be present on the video
frames - list of frames of which the video consists. List contains only frames with an object from the 'objects' field
index - integer - number of the current frame
figures - integer - list of objects which the current frame contains
framesCount - integer - total number of frames in the video
objectKey - string - unique key for a given object (used in key_id_map.json)
labelerLogin - string - the name of a user who created the current figure
geometryType - "cuboid_3d" - class shape
geometry - a dictionary containing indicators of location, rotation and dimensions of cuboids
Fields definitions for objects field:
key - string, a unique key for the given object (used in key_id_map.json to get the object ID)
classTitle - string - the title of a class. It's used to identify the class shape from the meta.json file
tags - list of strings that will be interpreted as object tags
labelerLogin - string - the name of the user that added this figure to the project
Fields description for figures field:
key - string, a unique key for the given figure (used in key_id_map.json to get the figure ID)
objectKey - string, a unique key for the given object (used in key_id_map.json to get the object ID).
geometryType - "rectangle" -class shape
geometry - geometry of the object
classTitle - string - the title of a class. It's used to identify the class shape from the meta.json file
labelerLogin - string - the name of the user that added this figure to the current frame
Key id map file
Key_id_map.json file is optional. It is created when annotating the video inside Supervisely interface and sets the correspondence between the unique identifiers of the video, object and the frame on which the object is located. If you annotate manually, you do not need to create this file. This will not affect the work being done.
Json format of key_id_map.json:
{
    "tags": {},
    "objects": {
        "198f727d40c749eebcacc4aed299b39a": 20520
    },
    "figures": {
        "65f21690780e43b49863c3cbd07eab3a": 503130811
    },
    "videos": {
        "c8168b43ae1b45c38930f456df9d0f2b": 157876296
    }
}
Fields definitions:
objects - dictionary, where the key is a unique string, generated inside Supervisely environment to set correspondence of current object in annotation, and values are unique integer ID corresponding to the current object
figures - dictionary, where the key is a unique string, generated inside Supervisely environment to set correspondence of object on current frame in annotation, and values are unique integer ID corresponding to the current frame
videos - dictionary, where the key is unique string, generated inside Supervisely environment to set correspondence of video in annotation, and value is a unique integer ID corresponding to the current video
tags - dictionary, where the keys are unique strings, generated inside Supervisely environment to set correspondence of tag on current frame in annotation, and values are a unique integer ID corresponding to the current tag
Individual Image Annotations
Point Cloud Episodes
Last modified 3yr ago