Exporting Labels

Exporting labels from Annotation Projects (Workflows)

To train your models you must export your labels.

Only Project admins can export labels

Descriptions of all information contained in the export file can be found here.

Navigate to Labels and export on the Project Dashboard
Select the Data tab.
Select the data units you want to export labels for.
Click the Export and save button. A pop-up appears.

Give this label version a name.
Select whether you want your labels to be exported in JSON or COCO format.
Toggle this if you want to include signed URLs in your export.
Select which label status(es) to include in the export.
Select what objects to include in the export.
Click Export and save to export your labels.

Exporting labels from Manual QA Projects

Learn how to export data Manual QA Projects by watching this video.

The Export tab is where you export the labels and classifications created in a Project.

A. Select the files you want to export labels for by clicking the checkboxes next to the files you’d like to include in your export. Click the Export to export the selected data.

B. Select the format for your exported data; COCO or JSON.

C. Toggle this switch if you want to include signed URLs in your export.

D. Select the label status of the annotations you want to be included in the export.

E. Select the objects you want to include in the export.

F. Select which classifications to include in the export.

Download files are tagged with a unique id for the Project they are exported from and the time at which the export is made.

After the Export button is pressed, progress can be monitored using the notification bell icon in the top-right of the page.

Once the process completes a notification will appear in the top-right corner of your screen telling you the export is complete. Click Click to download to download your labels.

You can also download your labels in the notification menu (accessed using the bell icon in the top left corner of the platform) and clicking the export icon next to the export you want to download.

Label editor coordinates

Label coordinates are normalized to be between 0 and 1. This means that the corners of the frame or image correspond to the coordinates (1,1), (1,0), (0,0), (0,1) regardless of frame dimensions.

To get the pixel values of any normalized coordinates, multiply them by the width or height of the label (given in pixels).

“x” and “h” coordinates of a label should be multiplied by the pixel width.
“y” and “w” coordinates of a label should be multiplied by the pixel height.

Export data format

All labels export to a single JSON or COCO file and both formats contain the exact same information. The information below uses the JSON format as an example. Refer to the COCO documentation for details on the COCO format.

We recommend viewing the exported JSON using a web-browser or a JSON parser.

The tables below provide descriptions of all values contained in the exported files.

Exports of label versions for which the data unit has been deleted will vary from the examples shown below - the data_type is deleted, while image groups and image sequences will only contain a single data_unit.

Single images

The export contains a list of JSON objects, with each JSON object representing a single data unit and containing detailed information for all exported labels.

The example below describes all the keys for a single exported data unit.


[
  {
    "label_hash": "781dd0ff-e4c2-48f1-bcd1-09f2f0756701",
    "created_at": "2023-03-23 11:42:14",
    "last_edited_at": "2023-10-02 13:53:03",
    "dataset_hash": "4a4141ed-8d8b-4518-b1f7-97a5c53e992b",
    "dataset_title": "Cologne images",
    "data_title": "dom-hbf.jpg",
    "data_hash": "9c588f63-ad87-4987-a074-06ba0d6980cd",
    "data_type": "image",
    "is_image_sequence": null,
    "video_link": null,
    "data_units": { },
    "classification_answers": { },
    "object_actions": { },
    "label_status": "LABELLED",
    "export_history": [
      {
        "export_hash": "02b56519-9664-4e38-9713-4817a5caf648",
        "exported_at": "Mon, 02 Oct 2023 14:35:30 UTC",
        "user_email": "david.babuschkin@encord.com"
      }
    ],
    "export_hash": "02b56519-9664-4e38-9713-4817a5caf648",
    "exported_at": "Mon, 02 Oct 2023 14:35:30 UTC",
    "annotation_task_status": "COMPLETE"
  }
]

Key	Description	Notes
label_hash	The Label Row hash	The ‘hash’ represents a unique identifier
created_at	Time and date the label was created
last_edited_at	Time and date the label was last edited
dataset_hash	The Dataset’s hash	The ‘hash’ represents a unique identifier
data_type	The data unit’s file format	Always “video” for videos
is_image_sequence	“true” when the data unit is an image sequence	Always “null” for images
video_link	Contains a private cloud URL for videos	Always “null” for images
data_units	List of all files the data unit is composed of	Details of the export information for `data_units“ can be found below.
object_answers	All the attributes in this data unit	The object attributes are identified using their hash
classification_answers	All the classifications in a particular data unit	The classification labels are identified using their hash
object_actions	The number of states a dynamic attribute can be in.	A change in state occurs each time the attribute answer changes. The objectHash within the object_actions is the attribute answer’s ID.
label_status	Indicates whether the data unit has been labeled.
export_history	Contains a record of the export history for this data unit	Exporting labels to confirm export history generates an export history entry.
export_hash	The hash for this particular export instance	The ‘hash’ represents a unique identifier
exported_at	The date and time when a particular export instance took place.
annotation_task_status	Shows the task status of Manual QA Projects.	annotation_task_status is only applicable for Manual QA Projects and will be deprecated in January 2024.

The data_units key contains all files that compose the data unit. For a given image there will only ever be one element in this list. This element will contain the following information.

data_units here refer to individual files that compose a data unit, as defined in our glossary, and are not to be confused with data units elsewhere in the platform. Encord will update this nomenclature soon, but we always communicate changes to all customers first.


"data_units": {
      "9c588f63-ad87-4987-a074-06ba0d6980cd": {
        "data_hash": "9c588f63-ad87-4987-a074-06ba0d6980cd",
        "data_title": "dom-hbf.jpg",
        "data_type": "image",
        "data_sequence": 0,
        "labels": { },
        "data_fps": "23.976023976023978" ,
        "data_duration": "29.0786",
        "data_link": "www.my-private-cloud.com/how-to-make-apple-pie.mp4",
        "width": 512,
        "height": 512
      }
}

Key	Description	Notes
data_hash	The file’s hash	The ‘hash’ represents a unique identifier
data_title	The file’s title
data_type	The file type
data_sequence	The sequence number of this file within the data unit	Always `0` for images, as single images are composed of a single file by definition
labels	A container for the image’s label information	This contains the label information for the image.
data_link	A link to the file stored in your private cloud
width	The width of the image in pixel (px)
height	The height of the image in pixel (px)

labels contains all object labels, classification labels, and attributes present in the image.


"labels": {
      "0": {
        "objects": { },
        "classifications": [ ]
      }
}

Key	Description	Notes
objects	A list of label objects in this frame	Contains geometric information for object labels
classifications	A list of classifications applying to image as a whole

objects contains all object label information for the image. A key with the name of the object shape is always present - bounding_box in the example below. All shapes contain coordinates for each vertex.

Navigate to the ontology shapes section to see how all ontology classes are represented in the exported file.

The example below shows a single object instance.

"objects": [
  {
        "name": "Apple",
        "color": "#D33115",
        "shape":"bounding_box",
        "value": "car",
        "boundingBox": {
          "0": {
            "h": 0.3235,
            "w": 0.1697,
            "x": 0.0153,
            "y": 0.254,   
          }
        },
        "createdAt": "Thu, 07 Sep 2023 09:47:35 GMT",
        "createdBy": "david.babuschkin@encord.com",
        "confidence": "1",
        "objectHash": "P6gqJT/3",
        "featureHash": "jiOiEq76",
        "manualAnnotation": true
      }
]

Key	Description	Notes
name	The object’s name	As specified in the ontology
color	The color used to draw the object	As specified in the ontology
shape	The Ontology class used to create the object	As specified in the ontology
value	The name given to the object
createdAt	Date and time the object was created
createdBy	The email of the user that created this object
confidence	The confidence score for this object	A confidence score of 1 is given for all labels created manually. More info can be found here
objectHash	The specific label’s hash	The ‘hash’ represents a unique identifier
featureHash	The Ontology object’s hash	Corresponds to the FeatureNodeHash in the ontology
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique
boundingBox	A list containing the coordinates for the bounding box	Refer to the ontology shapes section for more details

classifications contains all classification information for the image.

The following example shows a single object instance.

"classifications": [
  {
        "name": "Time of day",
        "value": "time_of_day",
        "createdAt":"Tue, 10 Oct 2023 14:16:14 GMT",
        "createdBy": "david.babuschkin@encord.com",
        "confidence": "1",
        "featureHash": "wUS7p9B6",
        "lastEditedAt": "Tue, 10 Oct 2023 14:16:14 GMT",
        "classificationHash": "jiOiEq76",
        "manualAnnotation": true
      }
]

Key	Description	Notes
name	The classification’s name	As specified in the ontology
value	The classification value	Same as the `name`
createdAt	Time and day the classification was created
createdBy	The email of the user that created this classification
confidence	The confidence score for this classification	A confidence score of 1 is given for all labels created manually. More info can be found here
featureHash	The classification instance hash	Corresponds to the FeatureNodeHash in the Ontology
lastEditedAt	Time and date of the last time this classification was edited
classificationHash	The classification instance hash hash
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique

object_answers is a list of objects that have at least one nested attribute and contains information for all attributes. Expanding object_answers reveals the following:

"object_answers": {
  "Gqh06ypx"
      "objectHash": "Gqh06ypx",
      "classifications" [ 
        "name": "Size",
        "value": "size",
        "answers": "Medium",
        "featureHash": "GZnFumFq",
        "manualAnnotation": true
      ]
}

Key	Description	Notes
objectHash	The hash of the object containing the attributes	The ‘hash’ represents a unique identifier
classifications	A list of attributes related to the object. Will include Dynamic attributes and Relation attributes	Not to be confused with classifications as defined in our glossary, which apply to a frame
name	The attribute name
value	The attribute value	Always the same as the name
answers	The value(s) the attribute(s) were set to	If the attribute was a radio button, the answer will be the option selected by the annotator
featureHash	The attribute’s hash	The ‘hash’ represents a unique identifier
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique

Contains a list of classifications that apply to entire frames or slices. classification_answer is represented by its hash. Expanding classification_answers reveals the following:

"classification_answers": {
  "OFX2jzwE": {
    "classificationHash": "OFX2jzwE", 
    "classifications": [{
      "name": "Time of day", 
      "value": "time_of_day", 
      "answers": [{
        "name": "Night", 
        "value": "night", 
        "featureHash": "j/7dpSmi"}],    
    "featureHash": "uZmB5YZC", 
    "manualAnnotation": true
    }]
  }
}

Key	Description	Notes
classificationHash	The classification’s hash	Corresponds to the featureNodeHash in the Ontology
classifications	A list of classification information
name	The classification name	As set in the Ontology (Quality in the example above)
value	The classification value	Always the same as the classification name
answers	A list of all classification answers	“answers” refer to the values the classification were set to.
name	The name of the classification answer	“Night” in the example above
value	The classification answer’s value	Always the same as the classifications answer’s name
featureHash	The hash for the particular classification answer	Included in `answers`
featureHash	The hash for the particular classification
manualAnnotation	“true” for all manually created labels. “false” for all labels created with automated labeling techniques

The export_history contains a list of all exports for this data unit, the first entry being the current export. Each instance contains the following:

"export_history": {
  "0"
      "export_hash": "Gqh06ypx",
      "exported_at": "Mon, 02 Oct 2023 13:47:45 UTC",
      "user_email": "david.babuschkin@encord.com"
}

Key	Description	Notes
export_hash	The export instance’s hash	The ‘hash’ represents a unique identifier
exported_at	Date and time of the export
user_email	The email of the user that made this export

Image groups and image sequences

Confused about the difference between image groups and image sequences? See our documentation here to learn about different data types in Encord.

The export contains a list of JSON objects, with each JSON object representing a single image group or image sequence, and containing detailed information for all exported labels.

The example below describes all the keys for a single exported data unit.

[
  {
    "label_hash": "781dd0ff-e4c2-48f1-bcd1-09f2f0756701",
    "created_at": "2023-03-23 11:42:14",
    "last_edited_at": "2023-10-02 13:53:03",
    "dataset_hash": "4a4141ed-8d8b-4518-b1f7-97a5c53e992b",
    "dataset_title": "cooking_image_sequences",
    "data_title": "image-group-67bdc95d",
    "data_hash": "9c588f63-ad87-4987-a074-06ba0d6980cd",
    "data_type": "image_group",
    "is_image_sequence": null,
    "image_sequence_link": "www.my-private-cloud.com/how-to-make-apple-pie.mp4",
    "data_units": { },
    "classification_answers": { },
    "object_actions": { },
    "label_status": "LABELLED",
    "export_history": [
      {
        "export_hash": "02b56519-9664-4e38-9713-4817a5caf648",
        "exported_at": "Mon, 02 Oct 2023 14:35:30 UTC",
        "user_email": "david.babuschkin@encord.com"
      },
      {
        "export_hash": "2e0ee531-41ce-4ce9-a859-b6b47697e5d2",
        "exported_at": "Mon, 02 Oct 2023 13:47:45 UTC",
        "user_email": "david.babuschkin@encord.com"
      }
    ],
    "export_hash": "02b56519-9664-4e38-9713-4817a5caf648",
    "exported_at": "Mon, 02 Oct 2023 14:35:30 UTC",
    "annotation_task_status": "COMPLETE"
  }
]

Key	Description	Notes
label_hash	The Label Row hash	The ‘hash’ represents a unique identifier
created_at	Time and date the label was created
last_edited_at	Time and date the label was last edited
dataset_hash	The dataset’s hash	The ‘hash’ represents a unique identifier
data_type	The data unit’s file format	Always “img_group” for image groups and image sequences
is_image_sequence	`true` when the data unit is an image sequence	`false` for all other types of data, including image groups. This is what distinguishes image groups and image sequences in your export
video_link	Contains a link to file storage location if file is a video	Always “null” for image groups and image sequences
data_units	List of all files the data unit is composed of	Details of the export information for data units can be found below.
object_answers	All the attributes in this data unit	The object attributes are identified using their hash
classification_answers	All the classifications in a particular data unit	The classification labels are identified using their hash
object_actions	The number of states a dynamic attribute can be in.	A change in state occurs each time the attribute answer changes. The objectHash within the object_actions is the attribute answer’s ID.
label_status	Indicates whether the data unit has been labeled.
export_history	Contains a record of the export history for this data unit	Exporting labels to confirm export history generates an export history entry.
export_hash	The hash for this particular export instance	The ‘hash’ represents a unique identifier
exported_at	The date and time when a particular export instance took place.
annotation_task_status	Shows the task status of Manual QA Projects.	annotation_task_status is only applicable for Manual QA Projects and will be deprecated in January 2024.

The data_units key contains a list of all files that compose the image group or image sequence (sometimes referred to as frames). It contains the following information.


"data_units": {
      "9c588f63-ad87-4987-a074-06ba0d6980cd": {
        "data_hash": "9c588f63-ad87-4987-a074-06ba0d6980cd",
        "data_title": "rhein-hafen.jpg4",
        "data_type": "image/jpg",
        "data_sequence": 0,
        "labels": { },
        "data_link": "www.my-private-cloud.com/how-to-make-apple-pie.mp4",
        "width": 512,
        "height": 512
      }
}

Key	Description	Notes
data_hash	The file’s hash	The ‘hash’ represents a unique identifier
data_title	The file’s title
data_type	The file type
data_sequence	The sequence number of this file within the data unit	0 represents the first file
labels	A list of all frames contained in image group or sequence, and any labels on each frame	This contains the label information for each frame.
width	The width of the frame in pixel (px)
height	The height of the frame in pixel (px)

Each number within labels represents an individual frame within the image group or sequence. Each frame contains the following:


"labels": {
      "0": {
        "objects": { },
        "classifications": [ ],
        "metadata":{ }
      }
}

Key	Description	Notes
objects	A list of label objects in this frame	Contains geometric information for object labels
classifications	A list of classifications applying to the entire frame	Will be the same value for all instances of this classification.

objects contains label information for all object instances in a frame. A key with the name of the object shape is always present - bounding_box in the example below. All shapes contain coordinates for each vertex.

Navigate to the ontology shapes section to see how all ontology classes are represented in the exported file.

The example below shows a single object instance.

"objects": [
      {
        "name": "Apple",
        "color": "#D33115",
        "shape":"bounding_box",
        "value": "apple",
        "boundingBox": {
          "0": {
            "h": 0.3235,
            "w": 0.1697,
            "x": 0.0153,
            "y": 0.254,   
          }
        },
        "createdAt": "Thu, 07 Sep 2023 09:47:35 GMT",
        "createdBy": "david.babuschkin@encord.com",
        "confidence": "1",
        "objectHash": "P6gqJT/3",
        "featureHash": "jiOiEq76",
        "manualAnnotation": true
      }
]

Key	Description	Notes
name	The object’s name	As specified in the ontology
color	The color used to draw the object	As specified in the ontology
shape	The Ontology class used to create the object	As specified in the ontology
value	The name given to the object
createdAt	Date and time the object was created
createdBy	The email of the user that created this object
confidence	The confidence score for this object	A confidence score of 1 is given for all labels created manually. More info can be found here
objectHash	The specific label’s hash	The ‘hash’ represents a unique identifier
featureHash	The Ontology object’s hash	Corresponds to the FeatureNodeHash in the ontology
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique
boundingBox	A list containing the coordinates for the bounding box	Refer to the ontology shapes section for more details

classifications contains all frame level classification information for the image group or sequence.

The example below shows a single classification instance.

"classifications": [
      {
        "name": "Time of day",
        "value": "time_of_day",
        "createdAt":"Tue, 10 Oct 2023 14:16:14 GMT",
        "createdBy": "david.babuschkin@encord.com",
        "confidence": "1",
        "featureHash": "wUS7p9B6",
        "lastEditedAt": "Tue, 10 Oct 2023 14:16:14 GMT",
        "classificationHash": "jiOiEq76",
        "manualAnnotation": true
      }
]

Key	Description	Notes
name	The classification’s name	As specified in the ontology
value	The classification value	Same as the `name`
createdAt	Time and day the classification was created
createdBy	The email of the user that created this classification
confidence	The confidence score for this classification	A confidence score of 1 is given for all labels created manually. More info can be found here
featureHash	The classification instance hash	Corresponds to the FeatureNodeHash in the Ontology
lastEditedAt	Time and date of the last time this classification was edited
classificationHash	The classification instance hash hash
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique

object_answers is a list of objects that have at least one nested attribute and contains information for all attributes. Expanding object_answers reveals the following:

"object_answers": {
  "Gqh06ypx"
      "objectHash": "Gqh06ypx",
      "classifications" [{ 
        "name": "Size",
        "value": "size",
        "answers": "Medium",
        "featureHash": "GZnFumFq",
        "manualAnnotation": true
  }]
}

Key	Description	Notes
objectHash	The hash of the object containing the attributes	The ‘hash’ represents a unique identifier
classifications	A list of attributes related to the object. Will include Dynamic attributes and Relation attributes	Not to be confused with classifications as defined in our glossary, which apply to a frame
name	The attribute name
value	The attribute value	Always the same as the name
answers	The value(s) the attribute(s) were set to	If the attribute was a radio button, the answer will be the option selected by the annotator
featureHash	The attribute’s hash	The ‘hash’ represents a unique identifier
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique

Contains a list of classifications that apply to entire frames or slices. classification_answer is represented by its hash. Expanding classification_answers reveals the following:

"classification_answers": {
  "OFX2jzwE": {
    "classificationHash": "OFX2jzwE", 
    "classifications": [{
      "name": "Quality", 
      "value": "quality", 
      "answers": [{
        "name": "out of focus", 
        "value": "out_of_focus", 
        "featureHash": "j/7dpSmi"}],    
    "featureHash": "uZmB5YZC", 
    "manualAnnotation": true
    }]
  }
}

Key	Description	Notes
classificationHash	The classification’s hash	The ‘hash’ represents a unique identifier
classifications	A list of classifications information
name	The classification name	As set in the Ontology (Quality in the example above)
value	The classification value	Always the same as the classification name
answers	A list of all classification answers	“answers” refer to the values the classifications were set to.
name	The name of the classification answer	“out of focus” in the example above
value	The classification answer’s value	Always the same as the classification answer’s name
featureHash	The hash for the particular classification answer	Included in `answers`
featureHash	The hash for the particular classification
manualAnnotation	“true” for all manually created labels. “false” for all labels created with automated labeling techniques

The export_history contains a list of all exports for this data unit, the first entry being the current export. Each instance contains the following:

"export_history": {
  "0"
      "export_hash": "Gqh06ypx",
      "exported_at": "Mon, 02 Oct 2023 13:47:45 UTC",
      "user_email": "david.babuschkin@encord.com"
}

Key	Description	Notes
export_hash	The export instance’s hash	The ‘hash’ represents a unique identifier
exported_at	Date and time of the export
user_email	The email of the user that made this export

Videos

The export contains a list of JSON objects, with each JSON object representing a single data unit and containing detailed information for all exported labels.

The example below describes all the keys for a single exported data unit.


[
  {
    "label_hash": "781dd0ff-e4c2-48f1-bcd1-09f2f0756701",
    "created_at": "2023-03-23 11:42:14",
    "last_edited_at": "2023-10-02 13:53:03",
    "dataset_hash": "4a4141ed-8d8b-4518-b1f7-97a5c53e992b",
    "dataset_title": "cooking_videos",
    "data_title": "how-to-make-apple-pie.mp4",
    "data_hash": "9c588f63-ad87-4987-a074-06ba0d6980cd",
    "data_type": "video",
    "is_image_sequence": null,
    "video_link": "www.my-private-cloud.com/how-to-make-apple-pie.mp4",
    "data_units": { },
    "classification_answers": { },
    "object_actions": { },
    "label_status": "LABELLED",
    "export_history": [
      {
        "export_hash": "02b56519-9664-4e38-9713-4817a5caf648",
        "exported_at": "Mon, 02 Oct 2023 14:35:30 UTC",
        "user_email": "david.babuschkin@encord.com"
      },
      {
        "export_hash": "2e0ee531-41ce-4ce9-a859-b6b47697e5d2",
        "exported_at": "Mon, 02 Oct 2023 13:47:45 UTC",
        "user_email": "david.babuschkin@encord.com"
      }
    ],
    "export_hash": "02b56519-9664-4e38-9713-4817a5caf648",
    "exported_at": "Mon, 02 Oct 2023 14:35:30 UTC",
    "annotation_task_status": "COMPLETE"
  }
]

Key	Description	Notes
label_hash	The Label Row hash	The ‘hash’ represents a unique identifier
created_at	Time and date the label was created
last_edited_at	Time and date the label was last edited
dataset_hash	The Dataset’s hash	The ‘hash’ represents a unique identifier
data_type	The data unit’s file format	Always “video” for videos
is_image_sequence	“true” when the data unit is an image sequence	Always “null” for videos
video_link	Link to the video saved on your private cloud	Always “null” for all other file types
data_units	List of all files the data unit is composed of	Details of the export information for `data_units“ can be found below.
object_answers	All the attributes in this data unit	The object attributes are identified using their hash
classification_answers	All the classifications in a particular data unit	The classification labels are identified using their hash
object_actions	The number of states a dynamic attribute can be in.	A change in state occurs each time the attribute answer changes. The objectHash within the object_actions is the attribute answer’s ID.
label_status	Indicates whether the data unit has been labeled.
export_history	Contains a record of the export history for this data unit	Exporting labels to confirm export history generates an export history entry.
export_hash	The hash for this particular export instance	The ‘hash’ represents a unique identifier
exported_at	The date and time when a particular export instance took place.
annotation_task_status	Shows the task status of Manual QA Projects.	annotation_task_status is only applicable for Manual QA Projects and will be deprecated in January 2024.

The data_units key contains all files that compose the data unit. For a given video there will only ever be one element in this list. This element will contain the following information.

data_units here refer to individual files that compose a data unit, as defined in our glossary, and are not to be confused with data unit elsewhere in the platform. Encord will update this nomenclature soon, but we always communicate changes to all customers first.


"data_units": {
      "9c588f63-ad87-4987-a074-06ba0d6980cd": {
        "data_hash": "9c588f63-ad87-4987-a074-06ba0d6980cd",
        "data_title": "how-to-make-apple-pie.mp4",
        "data_type": "video/mp4",
        "data_sequence": 0,
        "labels": { },
        "data_fps": "23.976023976023978" ,
        "data_duration": "29.0786",
        "data_link": "www.my-private-cloud.com/how-to-make-apple-pie.mp4",
        "width": 512,
        "height": 512
      }
}

Key	Description	Notes
data_hash	The file’s hash	The ‘hash’ represents a unique identifier
data_title	The file’s title
data_type	The file type
data_sequence	The sequence number of this file within the data unit	0 represents the first file
labels	A list of all frames contained in the video and any labels on each frame	This contains the label information for each frame.
data_fps	The frames per second for this video
data_duration	The video length	In seconds
data_link	A link to the file stored in your private cloud
width	The width of the frame in pixel (px)
height	The height of the frame in pixel (px)

Each number within labels represents an individual frame within the data unit. Each frame contains the following:


"labels": {
      "0": {
        "objects": { },
        "classifications": [ ],
        "metadata":{ }
      }
}

Key	Description	Notes
objects	A list of label objects in this frame	Contains geometric information for object labels
classifications	A list of classifications applying to the entire frame	Will be the same value for all instances of this classification.

Navigate to the ontology shapes section to see how all ontology classes are represented in the exported file.

The following example shows a single object instance.

"objects": [
  {
        "name": "Apple",
        "color": "#D33115",
        "shape":"bounding_box",
        "value": "apple",
        "boundingBox": {
          "0": {
            "h": 0.3235,
            "w": 0.1697,
            "x": 0.0153,
            "y": 0.254,   
          }
        },
        "createdAt": "Thu, 07 Sep 2023 09:47:35 GMT",
        "createdBy": "david.babuschkin@encord.com",
        "confidence": "1",
        "objectHash": "P6gqJT/3",
        "featureHash": "jiOiEq76",
        "manualAnnotation": true
      }
]

Key	Description	Notes
name	The object’s name	As specified in the ontology
color	The color used to draw the object	As specified in the ontology
shape	The ontology class used to create the object	As specified in the ontology
value	The name given to the object
createdAt	Date and time the object was created
createdBy	The email of the user that created this object
confidence	The confidence score for this object	A confidence score of 1 is given for all labels created manually. More info can be found here
objectHash	The specific label’s hash	The ‘hash’ represents a unique identifier
featureHash	The Ontology object’s hash	Corresponds to the FeatureNodeHash in the ontology
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique
boundingBox	A list containing the coordinates for the bounding box	Refer to the ontology shapes section for more details

classifications contains all frame level classification information for the video.

The example below shows a single classification instance.

"classifications": [
  {
        "name": "Time of day",
        "value": "time_of_day",
        "createdAt":"Tue, 10 Oct 2023 14:16:14 GMT",
        "createdBy": "david.babuschkin@encord.com",
        "confidence": "1",
        "featureHash": "wUS7p9B6",
        "lastEditedAt": "Tue, 10 Oct 2023 14:16:14 GMT",
        "classificationHash": "jiOiEq76",
        "manualAnnotation": true
      }
]

Key	Description	Notes
name	The classification’s name	As specified in the ontology
value	The classification value	Same as the `name`
createdAt	Time and day the classification was created
createdBy	The email of the user that created this classification
confidence	The confidence score for this classification	A confidence score of 1 is given for all labels created manually. More info can be found here
featureHash	The classification instance hash	Corresponds to the FeatureNodeHash in the Ontology
lastEditedAt	Time and date of the last time this classification was edited
classificationHash	The classification instance hash hash
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique

object_answers is a list of objects that have at least one nested attribute and contains information for all attributes. Expanding object_answers reveals the following:

"object_answers": {
  "Gqh06ypx"
      "objectHash": "Gqh06ypx",
      "classifications" [ 
        "name": "Size",
        "value": "size",
        "answers": "Medium",
        "featureHash": "GZnFumFq",
        "manualAnnotation": true
      ]
}

Key	Description	Notes
objectHash	The hash of the object containing the attributes	The ‘hash’ represents a unique identifier
classifications	A list of attributes related to the object	Not to be confused with classifications as defined in our glossary, which apply to a frame
name	The attribute name
value	The attribute value	Always the same as the name
answers	The value(s) the attribute(s) were set to	If the attribute was a radio button, the answer will be the option selected by the annotator
featureHash	The attribute’s hash	The ‘hash’ represents a unique identifier
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique

Contains a list of classifications that apply to entire frames or slices. classification_answer is represented by its hash. Expanding classification_answers reveals the following:

"classification_answers": {
  "OFX2jzwE": {
    "classificationHash": "OFX2jzwE", 
    "classifications": [{
      "name": "Quality", 
      "value": "quality", 
      "answers": [{
        "name": "out of focus", 
        "value": "out_of_focus", 
        "featureHash": "j/7dpSmi"}],    
    "featureHash": "uZmB5YZC", 
    "manualAnnotation": true
    }]
  }
}

Key	Description	Notes
classificationHash	The classification’s hash	The ‘hash’ represents a unique identifier
classifications	A list of classifications information
name	The classification name	As set in the ontology (Quality in the example above)
value	The classification value	Always the same as the classification name
answers	A list of all classification answers	“answers” refer to the values the classifications were set to.
name	The name of the classification answer	“out of focus” in the example above
value	The classification answer’s value	Always the same as the classification answer’s name
featureHash	The hash for the particular classification answer	Included in `answers`
featureHash	The hash for the particular classification
manualAnnotation	“true” for all manually created labels. “false” for all labels created with automated labeling techniques

The export_history contains a list of all exports for this data unit, the first entry being the current export. Each instance contains the following:

"export_history": {
  "0"
      "export_hash": "Gqh06ypx",
      "exported_at": "Mon, 02 Oct 2023 13:47:45 UTC",
      "user_email": "david.babuschkin@encord.com"
}

Key	Description	Notes
export_hash	The export instance’s hash	The ‘hash’ represents a unique identifier
exported_at	Date and time of the export
user_email	The email of the user that made this export

DICOM

The export contains a list of JSON objects, with each JSON object representing a single data unit and containing detailed information for all exported labels.

The following example describes all the keys for a single exported data unit.


[
  {
    "label_hash": "781dd0ff-e4c2-48f1-bcd1-09f2f0756701",
    "created_at": "2023-03-23 11:42:14",
    "last_edited_at": "2023-10-02 13:53:03",
    "dataset_hash": "4a4141ed-8d8b-4518-b1f7-97a5c53e992b",
    "dataset_title": "BB: CT thin slices",
    "data_title": "9c58",
    "data_hash": "9c588f63-ad87-4987-a074-06ba0d6980cd",
    "data_type": "dicom",
    "is_image_sequence": null,
    "video_link": null,
    "data_units": { },
    "classification_answers": { },
    "object_actions": { },
    "label_status": "LABELLED",
    "export_history": [
      {
        "export_hash": "02b56519-9664-4e38-9713-4817a5caf648",
        "exported_at": "Mon, 02 Oct 2023 14:35:30 UTC",
        "user_email": "david.babuschkin@encord.com"
      },
      {
        "export_hash": "2e0ee531-41ce-4ce9-a859-b6b47697e5d2",
        "exported_at": "Mon, 02 Oct 2023 13:47:45 UTC",
        "user_email": "david.babuschkin@encord.com"
      }
    ],
    "export_hash": "02b56519-9664-4e38-9713-4817a5caf648",
    "exported_at": "Mon, 02 Oct 2023 14:35:30 UTC",
    "annotation_task_status": "RETURNED"
  }
]

Key	Description	Notes
label_hash	The Label Row hash	The ‘hash’ represents a unique identifier
created_at	Time and date the label was created
last_edited_at	Time and date the label was last edited
dataset_hash	The dataset’s hash	The ‘hash’ represents a unique identifier
data_type	The data unit’s file format	Always “dicom” in a DICOM series
is_image_sequence	“true” when the data unit is an image sequence	Always “null” for a DICOM series
video_link	Link to the video or image sequence	Always “null” for a DICOM series
data_units	List of all files the data unit is composed of	Details of the export information for `data_units“ can be found below.
object_answers	All the object attributes in this data unit	The object attribute are identified using their hash
classification_answers	All the classifications in a particular data unit	The classification labels are identified using their hash
object_actions	The number of states a dynamic attribute can be in.	A change in state occurs each time the attribute answer changes. The objectHash within the object_actions is the attribute answer’s ID.
label_status	Indicates whether the data unit has been labeled.
export_history	Contains a record of the export history for the data unit	Exporting labels to confirm export history generates an export history entry.
export_hash	The hash for this particular export instance	The ‘hash’ represents a unique identifier
exported_at	The date and time when a particular export instance took place.
annotation_task_status	Shows the task status of Manual QA Projects.	annotation_task_status is only applicable for Manual QA Projects and will be deprecated in January 2024.

The data_units key contains all files that compose the data unit.


"data_units": {
      "9c588f63-ad87-4987-a074-06ba0d6980cd": {
        "data_hash": "9c588f63-ad87-4987-a074-06ba0d6980cd",
        "data_title": "9c58",
        "data_type": "application/dicom",
        "data_sequence": 0,
        "labels": { },
        "metadata": {  },
        "data_links": { },
        "width": 512,
        "height": 512
      }
}

Key	Description	Notes
data_hash	The file’s hash	The ‘hash’ represents a unique identifier
data_title	The file’s title
data_type	The file type
data_sequence	The sequence number of this file within the data unit	0 represents the first file
labels	A list of all slices contained in the series and any labels on each slice	This contains the label information for each slice.
metadata	The DICOM series metadata.	Contains the ID for the patient, the study, and the series.
data_links	Links to all slices within the series, ordered by their sequence number
width	The width of the slice in pixel (px)
height	The height of the slice in pixel (px)

Each number within labels represents an individual slice or frame within the data unit. Each slice or frame contains the following:


"labels": {
      "0": {
        "objects": { },
        "classifications": [ ],
        "metadata":{ }
      }
}

Key	Description	Notes
objects	A list of label objects on this slice	Contains geometric information for object labels
classifications	A list of classifications applying to the entire slice or frame	This will be the same value for all instances of this classification.
metadata	Slice specific metadata

objects contains label information for all object instances in a frame. A key with the name of the object shape is always present - polygon in the example below. All shapes contain coordinates for each vertex.

Navigate to the ontology shapes section to see how all ontology classes are represented in the exported file.

The example below shows a single object instance.

"objects": [
  {
        "name": "lungs",
        "color": "#D33115",
        "shape":"polygon",
        "value": "lungs",
        "polygon": {
          "0": {
            "x": 0.2423,
            "y": 0.5115,
          },
          "1": {
            "x": 0.4167,
            "y": 0.4218,   
          }
        },
        "createdAt": "Thu, 07 Sep 2023 09:47:35 GMT",
        "createdBy": "david.babuschkin@encord.com",
        "confidence": "1",
        "objectHash": "mQ+yKcF5",
        "featureHash": "pRwpsg1H",
        "manualAnnotation": true
      }
]

Key	Description	Notes
name	The object’s name	As specified in the ontology
color	The color used to draw the object	As specified in the ontology
shape	The ontology class used to create the object	As specified in the ontology
value	The name given to the object
polygon	A list containing the x and y coordinates of each vertex on the polygon	Refer to the ontology shapes section for more details
createdAt	Date and time the object was created
createdBy	The email of the user that created this object
confidence	The confidence score for this object	A confidence score of 1 is given for all labels created manually. More info can be found here
objectHash	The specific label’s hash	The ‘hash’ represents a unique identifier
featureHash	The ontology object’s hash	Corresponds to the FeatureNodeHash in the ontology
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique

classifications contains all frame level classification information for the slice.

The example below shows a single classification instance.

"classifications": [
  {
        "name": "State",
        "value": "state",
        "createdAt":"Tue, 10 Oct 2023 14:16:14 GMT",
        "createdBy": "david.babuschkin@encord.com",
        "confidence": "1",
        "featureHash": "wUS7p9B6",
        "lastEditedAt": "Tue, 10 Oct 2023 14:16:14 GMT",
        "classificationHash": "jiOiEq76",
        "manualAnnotation": true
      }
]

Key	Description	Notes
name	The classification’s name	As specified in the ontology
value	The classification value	Same as the `name`
createdAt	Time and day the classification was created
createdBy	The email of the user that created this classification
confidence	The confidence score for this classification	A confidence score of 1 is given for all labels created manually. More info can be found here
featureHash	The classification instance hash	Corresponds to the FeatureNodeHash in the ontology
lastEditedAt	Time and date of the last time this classification was edited
classificationHash	The classification instance hash hash
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique

"metadata": {
      "dicom_instance_uid": "1.3.9.1.4.7.14219.5.2.8.1600.1202.0357967439694942",
      "multiframe_frame_number": "null",
      "file_uri":"cord-dicoms/H7sLTXjYbrou3GhfmHRiuE5m92/5adba3dd-09f6-5c95-b954-e76542fe0ed7",
      "width": "512",
      "height": "512",
}

Key	Description	Notes
dicom_instance_uid	The DICOM instance UID	DICOM tag value (0008,0018). More information can be found here
multiframe_frame_number	A field indicating the frame number when the JSON contains only a single `label`	Displays `null` when each slice has its only expandable `labels` instance
file_uri	This slice’s URI	Identifies this slice
height	The slice’s height (in pixel)	DICOM tag value (0028,0010). More information can be found here
width	The slice’s width (in pixel)	DICOM tag value (0028,0011). More information can be found here

The slice metadata contains information on the DICOM study, the DICOM series, as well as the patient.

"metadata": {
      "patient_id": "ENC-ORD-LUV-031023",
      "study_uid": "null",
      "series_uid":"cord-dicoms/H7sLTXjYbrou3GhfmHRiuE5m92/5adba3dd-09f6-5c95-b954-e76542fe0ed7",
}

Key	Description	Notes
patient_id	The patient ID	DICOM tag value (0010,0020). More information can be found here
study_uid	The DICOM study’s ID	DICOM tag value (0020,000D). More information can be found here
series_uid	The DICOM series’ ID	DICOM tag value (0020,000E). More information can be found here

object_answers is a list of objects that have at least one nested attribute and contains information for all attributes. Expanding object_answers reveals the following:

"object_answers": {
  "Gqh06ypx"
      "objectHash": "Gqh06ypx",
      "classifications" [ 
        "name": "Size",
        "value": "size",
        "answers": "Medium",
        "featureHash": "GZnFumFq",
        "manualAnnotation": true
      ]
}

Key	Description	Notes
objectHash	The hash of the object containing the attributes	The ‘hash’ represents a unique identifier
classifications	A list of attributes related to the object. Will include Dynamic attributes and Relation attributes.	Not to be confused with classifications as defined in our glossary, which apply to a frame
name	The attribute name
value	The attribute value	Always the same as the name
answers	The value(s) the attribute(s) were set to	If the attribute was a radio button, the answer will be the option selected by the annotator
featureHash	The attribute’s hash	The ‘hash’ represents a unique identifier
manualAnnotation	A field indicating whether the object was drawn manually or not	`true` means it was drawn manually, while `false` means it was created using a model or an automated labeling technique

classification_answers a list of frame classifications in which each classification is represented by its hash. Expanding classification_answers reveals the following:

"classification_answers": {
  "OFX2jzwE": {
    "classificationHash": "OFX2jzwE", 
    "classifications": [{
      "name": "Quality", 
      "value": "quality", 
      "answers": [{
        "name": "out of focus", 
        "value": "out_of_focus", 
        "featureHash": "j/7dpSmi"}],    
    "featureHash": "uZmB5YZC", 
    "manualAnnotation": true
    }]
  }
}

Key	Description	Notes
classificationHash	The classification’s hash	The ‘hash’ represents a unique identifier
classifications	A list of information about the classification
name	The classification name	As set in the ontology (Quality in the example above)
value	The classification value	Always the same as the classification name
answers	A list of all classification answers	“answers” refer to the values the classification were set to.
name	The name of the classification answer	“out of focus” in the example above
value	The classification answer’s value	Always the same as the classification answer’s name
featureHash	The hash for the particular classification answer	Included in `answers`
featureHash	The hash for the particular classification
manualAnnotation	`true` for all manually created labels. `false` for all labels created with automated labeling techniques

The export_history contains a list of all exports for this data unit, the first entry being the current export. Each instance contains the following:

"export_history": {
  "0"
      "export_hash": "Gqh06ypx",
      "exported_at": "Mon, 02 Oct 2023 13:47:45 UTC",
      "user_email": "david.babuschkin@encord.com"
}

Key	Description	Notes
export_hash	The export instance’s hash	The ‘hash’ represents a unique identifier
exported_at	Date and time of the export
user_email	The email of the user that made this export

Ontology shapes

All ontology shapes can be represented within an export.

x and y represent coordinates of the top-left corner of the box. h and w respectively represent the height and width of the box.

 "boundingBox": {
    "h": 0.118,
    "w": 0.1643,
    "x": 0.6985,
    "y": 6204
 }

Polygons contain the x and y coordinates for each vertex.

 "polygon": {
  "0": {
    "x": 0.2423,
    "y": 0.5115,
  },
  "1": {
    "x": 0.4167,
    "y": 0.4218,   
          },
  "2": {
    "x": 0.5821,
    "y": 0.4641,   
          },
  "3": {
    "x": 0.5808,
    "y": 0.5756,   
          },
  "4": {
    "x": 0.4564,
    "y": 0.6397,   
          }
  }

Polylines contain the x and y coordinates for each vertex.

 "polyline": {
  "0": {
    "x": 0.2423,
    "y": 0.5115,
  },
  "1": {
    "x": 0.4167,
    "y": 0.4218,   
          },
  "2": {
    "x": 0.5821,
    "y": 0.4641,   
          },
  "3": {
    "x": 0.5808,
    "y": 0.5756,   
          },
  "4": {
    "x": 0.4564,
    "y": 0.6397,   
          }
  }

x and y represent the coordinates of the top-left corner of the unrotated box. h and w respectively represent the height and width of the box, while theta represents the angle of clockwise rotation of the bounding box about the centre of the box.

 "rotatableBoundingBox": {
    "h": 0.118,
    "w": 0.1643,
    "x": 0.6985,
    "y": 6204,
    "theta": 305.7762
 }

The rleString encodes the Bitmask label, and has to be decoded. See our SDK documentation to learn how to decode an rleString.

"objects": [
      {
        "bitmask": {
          "rleString": "02220N:0F20N",
          "top": 0,
          "left": 0,
          "width": 6,
          "height": 6
        }
      }
  ]

Object primitives are referred to as skeletons in the export. Each point on the object primitive is represented in the export using x and y coordinates.

Below is an example of an object primitive with 3 points.


"skeleton": {
  "0": {
    "x": 0.5719,
    "y": 0.7615,
    "name": "point_0",
    "color": "#fcc400",
    "value": "point_0",
    "featureHash": "qPCTeIci"
    },
    "1": {
    "x": 0.5428,
    "y": 0.6734,
    "name": "point_1",
    "color": "#fcc400",
    "value": "point_1",
    "featureHash": "o1NKWqKP"
    },
    "2": {
    "x": 0.4865,
    "y": 0.6464,
    "name": "point_2",
    "color": "#fcc400",
    "value": "point_2",
    "featureHash": "9bgJBA85"
    }
}

Key	Description	Notes
name	Name of this point	As set in the Ontology
color	The hexadecimal color code used to represent this point	As set in the Ontology
featureHash	The hash for this particular point	the ‘hash’ is a unique identifier

Exporting Bitmasks

Bitmask labels are exported as rleStrings. See our SDK documentation to learn how to decode an rleString.

We strongly recommend exporting Bitmask labels using the Encord SDK. Bitmasks are exported in the JSON format.

Use the COCO API to decode Bitmasks when using the COCO export format.

Exporting data using the Python SDK

Go here to learn how to export JSON files from Encord’s Python SDK. Reach out to us to if you need to export COCO labels.

Get started

General

Index

Annotate

Active

Other

Exporting Labels

Exporting labels from Annotation Projects (Workflows)

Exporting labels from Manual QA Projects

Label editor coordinates

Export data format

Single images

Image groups and image sequences

Videos

DICOM

Ontology shapes

Exporting Bitmasks

Exporting data using the Python SDK

Get started

General

Index

Annotate

Active

Other

​Exporting labels from Annotation Projects (Workflows)

​Exporting labels from Manual QA Projects

​Label editor coordinates

​Export data format

​Single images

​Image groups and image sequences

​Videos

​DICOM

​Ontology shapes

​Exporting Bitmasks

​Exporting data using the Python SDK

Exporting labels from Annotation Projects (Workflows)

Exporting labels from Manual QA Projects

Label editor coordinates

Export data format

Single images

Image groups and image sequences

Videos

DICOM

Ontology shapes

Exporting Bitmasks

Exporting data using the Python SDK