Label / Activity logs

Label logs serve as a comprehensive record of actions performed within the Encord platform’s Label Editor.

Viewing label logs

The following scripts show how to view label logs for:

• All data units of a Project in a specified time frame. The example specifies this time frame to be 1 week.
• A specific data unit, and made by a specific user.

In the following script, ensure that you:

• Replace <private_key_path> with the path to your private key.
• Replace <project_hash> with the hash of the Project you want to view label logs for
• If you are using the Time frame script, replace weeks=1 with the time frame you want to view label logs for.
• If you are using the User and Data unit script, replace <data_hash> with the hash of the data unit you want to view label logs for.

Time frame

# Import dependencies
from encord import EncordUserClient
import datetime

# Instantiate Encord client. Replace \<private_key_path> with your private key path
user_client = EncordUserClient.create_with_ssh_private_key(
  ssh_private_key_path="<private_key_path>"
  )

# Define your Project
project = user_client.get_project(project_hash="<project_hash>")

# Prints the label actions. Change the number of weeks if necessary.
for log_line in project.get_label_logs(after=datetime.datetime.now() - datetime.timedelta(weeks=1)):
    print(log_line)

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Label log content

Actions do not need to be submitted to appear in the log.

Logs are generated in chronological order and contain the following:

Log entry	Description	Note
log_hash	This log entry’s ID
user_hash	The user’s ID
user_email	The user’s email address
annotation_hash	The label instance’s ID	None for actions that are not labels or attributes. THIS FIELD IS DEPRECATED.
identifier	The label instance’s ID	None for actions that are not labels or attributes
data_hash	The data unit’s ID
feature_hash	The Ontology feature’s ID	A feature can have multiple instances. Equivalent to the featureNodeHash found in the ontology’s JSON
action	The action this log entry refers to	See the actions section for full details
label_name	The label’s name	As specified in the Ontology. Attributes are not named.
time_taken	The time taken to create the label (in milliseconds)	None for non-labeling related actions
created_at	The date and time the label action made	Date and time are given in the UTC time zone for all users
frame	The frame number the action was taken on	None refers to the first frame
branch_name	The name for each branch	Main branch always exists (non-consensus and Consensus). One branch is create for each annotator on Consensus tasks.
graph_node_uuid	The unique ID for each node in a Workflow

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Log actions

The table below provides descriptions of all log actions.

Action	Description
0	Add a label
1	Edit a label
2	Delete a label
3	Start labeling
4	End labeling
11	Submit a task
12	Approve a label
13	Reject a label
23	Add a classification or attribute
24	Edit a classification or attribute
25	Delete a classification or attribute
26	Approve a classification or attribute
27	Reject a classification or attribute
28	Submit an object or a classification label for review
29	Submit an attribute for review
30	The buffering icon appeared when the video was loading
31	A bitrate warning was shown
32	The ‘Seeking’ overlay method shown when skipping to a specific frame in a video
33	Approve a task.
34	Reject a task.
35	Approves a Consensus label. Logged when: 1. Approving a label in Review and Refine. 2. Choosing a winning set + click Consensus reached and when in Consensus Review. A log is created for each label in the winning label set .
36	Removes an Approved label from the Consensus Approved label list. Logged when you delete an Approved Label in Review and Refine .
37	Consensus reached on labels. Logged when choosing the winning label set + clicking Consensus reached. Logs also created for each of the label branches that are in agreement.

Use cases

Tutorial: Checking Rejection and Approval rates for a Project

Label logs provide a detailed record of actions taken during the labeling process. You can use these logs to analyze the rejection and approval rates of labels.

• Use the recipe provided above to view label logs.

• Filter log entries related to the actions “Approve a label” (Action 12) and “Reject a label” (Action 13).

• Calculate Rejection and Approval Rates.

  1. Divide the number of approved or rejected tasks by the total number of reviewed tasks.
  2. To see the rate as a percentage, multiply the result by 100.

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