What the Data for This Category Looks Like
Image annotation project data primarily comes from image samples uploaded to annotation platforms, bounding box results produced by annotators, preset category dictionaries, and quality inspection reports and rework lists generated during sampling inspections. Data is updated daily or synchronized per annotation batch. Daily reference documents include annotation specification descriptions, bounding box sample reference files, batch quality inspection statistics tables, and rework task details. Data fields include bounding box coordinates of visual targets, category labels, annotator IDs, and sampling inspection judgment results. No additional custom statistical numeric fields are included.
How These Characteristics Impact Workflow Orchestration
Image annotation project data sources and update patterns impose multiple constraints on workflow orchestration. First, data includes both image files and structured annotation tables. Workflows must support parsing and transfer of mixed-type inputs. Second, data volume updated per batch or daily is large. The most time-consuming steps, including bounding box annotation and occlusion judgment, take extended execution time. Workflows must support batch task splitting to avoid single-node execution timeouts. Third, reference documents such as annotation specifications and bounding box samples must be passed as fixed parameters to the workflow. This ensures consistent annotation logic across runs. Fourth, associated processing of rework lists and quality inspection results requires workflows to support cross-node data linkage verification. This prevents missed rework tasks.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Timeout Settings | 1200–1800 seconds | Matches the maximum execution duration of the most time-consuming steps such as target bounding box annotation and occlusion sample judgment, to avoid forced platform termination due to overly long single tasks |
| Batch Task Chunking | Split into chunks of 50–100 images per batch | Adapts to the single-batch data scale of annotation projects. Splitting enables parallel execution of time-consuming subtasks, reducing overall timeout risks |
variables | Pass annotation specification document ID, category dictionary ID | Ensures the workflow calls unified annotation rules and category definitions, preventing inconsistent annotation logic |
nodeId | Bind to the predecessor node ID of the quality inspection node | Ensures quality inspection link verification and rework pushes are only triggered after annotation tasks are completed |
| Retry Mechanism | Retry 2 times after failure, with a 60-second interval | Addresses task failures caused by temporary interface fluctuations of annotation platforms, reducing manual intervention costs |
Three Common Configuration Errors
- Phenomenon: Workflow execution is forcibly terminated after exceeding 1200 seconds, returning status code 504 or the platform's built-in timeout termination prompt. Cause: The timeout setting is not adjusted for the single-node duration of image annotation tasks, and the short timeout configuration of general tasks is used instead.
- Phenomenon: Uploaded image files cannot be passed as variables to the workflow, and the interface call returns a parameter missing error. Cause: The
variablesparameter is not configured correctly, and the output of the file upload node is not bound to the workflow variable pool. - Phenomenon: Workflow execution is triggered and submitted before form input is completed. Cause: Node trigger dependencies are not configured via
nodeId, and the workflow is not restricted to start only after all preceding form nodes are completed.
How to Verify Correct Configuration
The workflow editor in FastGPT v4.17.0 is used to check the timeout configuration. The configured value is confirmed to match the actual duration of annotation tasks. This can be verified via the execution logs of a single test task. A batch annotation task is triggered. Whether it is split and executed according to the preset chunking rules is observed. This can be checked via the subtask count in the workflow's node running logs. Test annotation specification documents and image samples are uploaded. The workflow is confirmed to normally read and apply the passed variables parameters. A scenario where form input is incomplete is simulated. Whether workflow execution can be triggered is verified. This can be confirmed via the trigger button status on the interface.
The values provided are common starting points and should be measured against the user’s own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.