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---
name: attribute-search
description: Search video archives by visual appearance attributes — clothing, colors, physical features. Use when asked to find a person by what they look like (no action involved): "person wearing red jacket", "man with blue backpack", "woman with long hair". Does not use embedding search — queries the CV attribute index directly.
metadata:
  { "openclaw": { "os": ["linux"] } }
---

Attribute Search

Alpha Feature — not recommended for production use.

Direct access to the CV attribute search API. Finds objects/people by visual appearance attributes (clothing, colors, physical features) without semantic embedding — queries the behavior index directly.

Use the video-search skill instead for general natural language queries. Use this only when the user explicitly wants to call the attribute search API directly.

When to Use

  • "Try the attribute search API for person wearing red jacket"
  • "Run an attribute search for blue backpack"
  • "Hit the attribute search endpoint directly"

Not for: "find a person running" (has action — use video-search) or general queries.

API

POST http://localhost:8000/api/v1/attribute_search

Parameters

Field Type Default Description
query string or array required Attribute description(s) — e.g. "person wearing red jacket" or ["person", "red hat"]
source_type string "video_file" "video_file" for uploaded videos, "rtsp" for live streams
top_k int 1 Max results to return
min_similarity float 0.3 Minimum cosine similarity, 0.0–1.0
fuse_multi_attribute bool false See below
video_sources array null Filter by source names or sensor IDs
timestamp_start string null ISO 8601 start time filter
timestamp_end string null ISO 8601 end time filter
exclude_videos array [] List of {sensor_id, start_timestamp, end_timestamp} to exclude

fuse_multi_attribute

  • false (default for direct use) — returns top_k results independently per attribute. Use this when calling attribute search directly.
  • true (used by fusion search) — combines object IDs found across attributes into a single result when they appear in the same frame. Only meaningful over a narrow time window where the same objects can co-occur in a single frame. Do not set true over large time ranges.

Examples

Single attribute, video file

curl -s -X POST http://localhost:8000/api/v1/attribute_search \
  -H 'Content-Type: application/json' \
  -d '{
    "query": "person wearing red jacket",
    "source_type": "video_file",
    "top_k": 5,
    "min_similarity": 0.3,
    "fuse_multi_attribute": false
  }' | python3 -m json.tool

Multiple attributes (independent results per attribute)

curl -s -X POST http://localhost:8000/api/v1/attribute_search \
  -H 'Content-Type: application/json' \
  -d '{
    "query": ["person wearing red jacket", "person wearing blue jeans"],
    "source_type": "video_file",
    "top_k": 5,
    "min_similarity": 0.3,
    "fuse_multi_attribute": false
  }' | python3 -m json.tool

RTSP stream with time filter

curl -s -X POST http://localhost:8000/api/v1/attribute_search \
  -H 'Content-Type: application/json' \
  -d '{
    "query": "person wearing beige shirt",
    "source_type": "rtsp",
    "top_k": 5,
    "min_similarity": 0.3,
    "fuse_multi_attribute": false,
    "video_sources": ["warehouse_cam_1"],
    "timestamp_start": "2025-01-01T13:00:00Z",
    "timestamp_end": "2025-01-01T14:00:00Z"
  }' | python3 -m json.tool

Tips

  • Works best with specific visual descriptions: clothing color, item type, physical features
  • Pass multiple attributes as an array to get independent top_k results per attribute
  • Lower min_similarity (e.g. 0.1) returns more results; raise it (e.g. 0.6) to filter noise
  • Use video_sources to limit search to specific cameras or uploaded files
  • Keep fuse_multi_attribute: false unless calling from a fusion pipeline with a narrow time window