Learn how to export data from the Encord web-app by watching this video. For more details, read on below!
The 'Export' tab is where you export the labels and classifications created in a project.
A. Select the files you'd like to export data 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'd like to include signed URLs in your export.
D. Select the label status of the annotations you would like to be included in the data export.
E. Select the objects you would like to include in the data export.
F. Select which classifications to include in the data 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 icon in the top-right of the page.
Once the process has completed, the symbol will appear. Click it to download your data.
All Labels will be exported in a single JSON or COCO file. Both export formats contain the exact same information.
See the table below for a description of all the values contained in the exported files.
|label_hash||The label's ID|
|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 ID|
|dataset_title||The dataset title|
|data_title||Name of the task or data unit the label belongs to|
|data_hash||the task's ID|
|is_image_sequence||"true" for image sequences||"none" for all other file types|
|video_link||Link to the video or image sequence||"none" if file isn't a video or image sequence|
|data_units||The files that the task is composed of|
|data_type||The file format|
|data_sequence||The data unit's sequence number.||Only image groups and image sequences will have non 0 values, since these are composed of multiple data units compressed into a single task.|
|labels||The labels and classifications on this data unit|
|objects||The labels on this data unit|
|name||The ontology object's name|
|color||The ontology object's color|
|shape||Which ontology object is being used|
|value||Same as the 'name' but in lowercase and with spaces removed|
|bitmask||Contains information about bitmask labels||Only visible for bitmask ontology objects|
|top (bitmask)||The top-left corner's top coordinate|
|left (bitmask)||The top-left corner's left coordinate|
|width (bitmask)||The bitmask label's width (in pixels)|
|height (bitmask)||The bitmask label's height (in pixels)|
|rleString||A base 64 run length encoded string encoding the bitmask||This is automatically decoded when using the Encord SDK. Alternatively the pycoco framework can be used.|
|createdAt||Time and date this label instance was created|
|createdBy||The email of the user that created this label instance|
|confidence||The label instance's confidence score|
|objectHash||The label instance's ID||Only refers to one specific label or classification|
|featureHash||The ontology object's ID||Identifies this particular ontology object type|
|manualAnnotation||"true" for all manually created labels. "false" for all labels created with automated labeling techniques|
|boundingBox||Contains the normalized coordinates of the label instance|
|h, y, x, y||The coordinates of this label instance, normalized to be between 0 and 1|
|classifications||The classifications in this data unit|
|name||The ontology object's name|
|value||The ontology object's name in lowercase and with spaces removed|
|createdAt||The date and time this classification instance was created|
|createdBy||The email of the user that created this classification instance|
|lastEditedAt||The date and time this classification instance was last edited|
|classificationHash||The ID for this classification instance|
|data_link||A link to the data unit|
|width||The data unit's width (in pixels)|
|height||The data unit's height (in pixels)|
|object_answers||All the labels in a particular data unit||The labels will be referred to by their hash / ID|
|classification_answers||All the classifications in a particular data unit||The classifications will be referred to by their hash / ID|
|name||The classification's name|
|value||The classification's name in lowercase and with spaces removed|
|answers||The classification values|
|name||The classification value|
|value||The classification value in lowercase, and with spaces removed|
|featureHash||The classification value's ID||Identifies this particular classification answer|
|featureHash||The classification object's ID||Identifies the classification|
|object_actions||The number of states a dynamic classification is in||A change in state occurs each time the classification answer changes. The objectHash within the object_actions is the classification answer's ID.|
|range||The range of frames a given state occurs in|
|value||The dynamic classification answer||The featureHash refers to the specific classification answer's ID|
|dynamic||"true" for dynamic classifications|
|trackHash||The current state's ID, for a given range of frames|
|shouldPropagate||"true" if 'Preserve current state' has been turned on for this classification|
|label_status||Shows whether the data unit has been labeled, or not|
|export_history||Contains records of every time this project was exported||The act of exporting labels to confirm export history will itself generate an export history entry.|
|export_hash||The ID for a particular export instance||The final 'export_hash" will always refer to the export you are viewing.|
|exported_at||The date and time for a particular export instance took place|
|annotation_task_status||Shows the task status|
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) - as seen in the image below.
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 height.
- "y" and "w" coordinates of a label should be multiplied by the pixel width.
See here to learn how to export JSON files from Encord's Python SDK. Please reach out to us to request for exporting COCO labels.
If you choose to export bitmasks from the webapp, you will need to use the pycoco framework to decode the rleString into a useful binary mask. This process can be laborious, and Encord can't guarantee interoperability for each version of pycoco.
Updated 5 days ago