What the data for this category looks like
Core data for image annotation projects comes from image samples, annotation platforms, category dictionaries, and inspection results. Regularly maintained documents include annotation specifications, bounding box examples, quality inspection reports, and rework lists. Data is updated daily or per annotation batch. Core fields include unique image identifiers, pixel coordinates of target bounding boxes, category labels, quality inspection status, and rework markers. Core processing focuses on visual target position and category determination, differing from the semantic processing logic of text annotation projects.
What constraints these characteristics impose on the "HTTP Interfaces and External Systems" link
Data sources for image annotation projects include image binary streams or URLs, and structured annotation metadata. This requires HTTP interfaces to support multiple request body types and binary stream transmission. The daily or batch update rhythm requires interfaces to support batch pulling and incremental synchronization, to avoid excessive data volume in a single request. Pixel coordinates and visual category labels in core fields require request and response formats of the interface to align with the field definitions of the annotation platform, ensuring consistency in data flow. The synchronization requirements for rework lists and quality inspection reports require interfaces to have idempotency, avoiding annotation conflicts caused by repeated processing of rework data.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Authorization | Bearer ${valid token} | Complies with HTTP interface authentication standards to ensure secure transmission of annotation data |
variables | {"batch_limit": "100 items/request", "sync_cycle": "86400 seconds"} | Matches the conventional data scale of annotation batches and daily update frequency, avoiding interface overload |
responseData | {"image_id": "", "bbox": [], "label": "", "quality_status": ""} | Matches the core data structure of image annotation projects, aligns with the return format of the annotation platform |
| Timeout duration | 600 seconds | Addresses interface response delays to ensure successful completion of single requests |
| Exception retry count | 3 times | Addresses temporary network fluctuations to ensure stability of data synchronization |
Three common configuration mistakes
- Truncated error messages are returned when calling the interface, such as
{"error":{"code":"Invalid. This occurs because theAuthorizationparameter is not configured correctly, the token format does not meet requirements, or the token has expired. - Insufficient number of returned results when pulling annotation data in batches. This occurs because a reasonable batch limit is not set via
variables, and the request data volume exceeds the interface's bearing threshold and is automatically truncated. - Bounding box fields are empty in synchronized annotation data. This occurs because the mapping rule for the corresponding field is not configured in
responseData, and the return format of the annotation platform is not aligned.
How to confirm the configuration is complete
Use FastGPT v4.17.0 configuration items and perform the following verification actions:
- Call the authentication interface with the configured
Authorizationparameter, verify that the returned status code is 200, and confirm that the authentication configuration is valid. - Initiate a single data request, check that the
responseDataincludes core fields such as image_id, bbox, and label, and confirm that the data format meets requirements. - Trigger a batch request according to the configured synchronization cycle, check that the number of returned results matches the batch limit set in
variables, and confirm that the batch request configuration is effective. - Simulate a request carrying an invalid token, verify that the interface returns an expected error format, and confirm that the exception handling configuration is correct.
The values provided are common starting points and should be measured against the reader'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.