What This Category’s Data Looks Like
Image annotation project data primarily comes from image samples exported from annotation platforms, bounding box results completed by annotators, preset category dictionaries, and spot-check quality inspection results. Daily output documents include annotation specifications, bounding box examples, quality inspection reports, and rework lists. Data updates follow a daily or single-batch annotation task schedule. Core fields include target bounding box pixel coordinates, category labels, annotator IDs, and rework counts. No general statistical percentage fields are included.
Constraints on HTTP Interfaces and External Systems From These Characteristics
Core data for image annotation projects relies on pixel-level coordinates linked to images. HTTP interfaces must support passing parameters for image binary streams or accessible image URLs. Data updates occur daily or per single batch. Interfaces must support pulling annotation results by task batch to avoid overloading single requests with data volume. Core fields include bounding box coordinates and category labels. Interface parameters must clearly specify field units and format requirements to prevent increased rework rates from format mismatches. Annotation documents and quality inspection reports must also be synchronized to external systems via interfaces. Interfaces must support configuration for bulk document transfers.
How to Configure Settings
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Authorization header configuration | Use Bearer Token format | Complies with FastGPT official interface authentication specifications, and adapts to general external system authentication logic |
variables parameter binding | Bind annotation task ID and image URL variables | Adapts to the business requirement of pulling data by task for image annotation projects |
responseData return format | Return structured annotation result fields | Facilitates direct parsing of bounding box coordinates and category labels by external systems |
| Request timeout period | 60–120 seconds | Matches the transmission and processing duration of single-batch annotation data |
| Bulk request limit | Process 50 annotation tasks per single request | Avoids overloading external systems with concurrent requests |
| Interface retry count | Calibrate based on actual measurements | Adapts to unstable scenarios in annotation data transmission, reducing call failure rates |
Three Common Configuration Mistakes
- An interface call returns a 401 unauthorized error. The cause is incorrect configuration of the Token format in the
Authorizationheader, leading to failed authentication processes. - The annotation result fields returned by the interface are empty. The cause is failure to bind the correct annotation task ID via
variables, resulting in the request not matching annotation data for the corresponding batch. - A cross-domain error occurs when calling the interface directly from the frontend. The cause is failure to add allowed frontend domain names in the FastGPT external system configuration. Directly exposing the interface authentication logic triggers browser interception.
How to Confirm Configuration Is Complete
- Initiate an interface call using a test image URL. Verify that the
responseDataincludes bounding box coordinates and category label fields. - Review interface logs to confirm the
Authorizationheader is correctly parsed, with no authentication failure records. - Submit a bulk request. Confirm that the number of returned results matches the bound
variablesparameters. - Simulate annotation data transmission. Confirm that field formats received by the external system comply with annotation specifications.
The values provided are common starting points and should be measured against corresponding sample data.
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.