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:
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{
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"size": {
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"height": 1080,
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"width": 1920
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},
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"description": "",
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"key": "c8168b43ae1b45c38930f456df9d0f2b",
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"tags": [],
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"objects": [
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{
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"key": "198f727d40c749eebcacc4aed299b39a",
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"classTitle": "rect",
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"tags": [],
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"labelerLogin": "alexxx",
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"updatedAt": "2020-08-23T12:06:11.963Z",
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"createdAt": "2020-08-23T12:06:11.963Z"
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}
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],
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"frames": [
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{
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"index": 0,
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"figures": [
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{
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"key": "65f21690780e43b49863c3cbd07eab3a",
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"objectKey": "198f727d40c749eebcacc4aed299b39a",
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"geometryType": "rectangle",
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"geometry": {
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"points": {
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"exterior": [
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[
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266,
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420
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],
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[
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847,
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845
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]
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],
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"interior": []
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}
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},
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"labelerLogin": "alexxx",
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"updatedAt": "2020-08-23T12:06:13.544Z",
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"createdAt": "2020-08-23T12:06:13.544Z"
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}
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]
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}
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],
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"framesCount": 375
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}
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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:
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{
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"tags": {},
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"objects": {
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"198f727d40c749eebcacc4aed299b39a": 20520
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},
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"figures": {
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"65f21690780e43b49863c3cbd07eab3a": 503130811
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},
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"videos": {
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"c8168b43ae1b45c38930f456df9d0f2b": 157876296
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}
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}
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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
Last modified 11mo ago
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