Export Labels

The Encord SDK is designed to offer a versatile and targeted approach to accessing label information. This approach allows for a more customized handling of label information, catering to various needs and scenarios in data processing.

The following table describes all values exported by the scripts on this page.

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Export labels as JSON

The following script prints a JSON file containing all the labels in your Project.

Make sure you substitute:

• The <file-path-to-ssh-key> with the full path to your SSH private key.
• The <project_unique-id> with the hash of your Project.
• The <file-path> with the file path to save the JSON file, with your labels.

# Import dependencies
from encord import EncordUserClient
import json

SSH_PATH= "<file-path-to-ssh-key>"
PROJECT_ID= "<project-unique-id>"

# Instantiate client. Replace <private_key_path> with the path to the file containing your private key.
user_client = EncordUserClient.create_with_ssh_private_key(
    ssh_private_key_path=SSH_PATH
)

# Specify Project. Replace <project_hash> with the hash of the Project you want to export labels for.
project = user_client.get_project(PROJECT_ID)

# Get label rows for your Project.
label_rows = project.list_label_rows_v2()

# Create a list to store all label row data
all_label_rows = []

for label_row in label_rows:
    # Download label information
    label_row.initialise_labels()
    # Add the label data to the list
    all_label_rows.append(label_row.to_encord_dict())

# Save the collected label rows data to a JSON file
output_file = "<file-path>label_rows.json"
with open(output_file, "w") as file:
    json.dump(all_label_rows, file, indent=4)

print(f"Label rows have been saved to {output_file}.")

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Export attributes

The following scripts get the attributes for all labels in a Project, as well as the frames that the attributes appear on. Single images only have a single frame.

In the following scripts, ensure that you:

• Replace <private_key_path> with the full path to your private key.
• Replace <project_hash> with the hash of the Project you want to export attributes for.
• Replace <task_name> with the name of the data unit you want to export attributes for. Remove data_title_eq="<task_name>" if you want to export attributes for all tasks.

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Export objects, classifications, and attributes by frame

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Range of consecutive frames

The following scripts download and print the labels for a specified range of frames in videos.

Make sure you substitute:

• The <private_key_path> with the full path to your private key.
• The <project_hash> with the hash of your Project.
• The <task_name> with the name of the task you want to export labels for (if using the task-specific script).
• The <start_frame_number> with the first frame of the range you want to export labels for.
• The <end_frame_number> with the last frame of the range you want to export labels for.

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List of non-consecutive frames

The following scripts download and print the labels for specific frames in videos.

Make sure you substitute:

• The <private_key_path> with the full path to your private key.
• The <project_hash> with the hash of your Project.
• The <task_name> with the name of the file (in Encord) you want to export labels for (if using the task-specific script).
• Replace the numbers in the list [10, 20, 30, 40] with the frames you want to export labels for.

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Saving frames with labels on them

ffmpeg can be used to save all frames with labels as an image, to be used in machine learning applications. The script below shows how this is done when exporting a list of non-consecutive frames from a specific video.

Make sure you substitute:

• The <output_folder_path> with the full path to the output folder you want the output image files to be saved.
• The <private_key_path> with the full path to your private key.
• The <project_hash> with the hash of your Project.
• The <task_name> with the name of the file in Encord you want to export labels for.
• The <path_to_your_video_file> with the full path to the video file you are exporting labels for.
• Replace the numbers in the list [10, 20, 30, 40] with the frames you want to export labels for.

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Label editor coordinates

All label locations are exported as normalized coordinates ranging from 0 to 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.

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Export all Consensus labels

Consensus Projects introduce the concept of BRANCHES within the task workflow. A Consensus annotation task consists of a MAIN branch and one sub-branch for each Annotator. Each time an annotator saves or submits a task, the annotator creates their own branch on a task. The MAIN branch remains empty of labels until a reviewer specifies that a task is in consensus. When consensus is reached, the labels that are the best representative set move to the MAIN branch. To export all labels (labels generated for every branch on every data unit) from your Consensus Project, use include_all_branches=True.

Make sure you:

• Substitute the <private_key_path> with the full path to your private key.
• Substitute the <project_hash> with the hash of your Project.
• If you only want to export the MAIN branch, remove include_all_label_branches=True.

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Export labels in bulk

Use the bundle function to significantly improve export performance.