roi-mapping

Match detections or tracks against predefined camera ROI polygons.

Updated Jun 2, 2026

Search Tags:#video surveillance #ROI matching #spatial event detection #polygon processing #track matching

Ready to run

npx skills add https://github.com/bettercallfan/deerflow --skill roi-mapping

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: roi-mapping
Source: https://github.com/bettercallfan/deerflow/tree/main/skills/custom/video_surveillance/roi-mapping
Command: npx skills add https://github.com/bettercallfan/deerflow --skill roi-mapping

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill automatically matches detections or tracks against configured camera ROI polygons, providing the necessary spatial event detection before further processing.

Core Features & Use Cases

ROI Matching: Match detections or tracks to predefined camera ROI polygons.
Spatial Event Detection: Facilitate spatial event detection for scenarios like no-parking zones, sidewalks, roads, or public areas.
Use Case: Before analyzing video surveillance data, use this Skill to ensure that only relevant regions of interest are considered, enhancing the accuracy of spatial event detection.

Quick Start

Run the roi-mapping skill to match tracks against ROI polygons using the following command:

Run the script directly with the provided arguments: python roi-mapping/scripts/run.py --tracks-json <tracks.json> --camera-id <camera_id> --config <config.json> --output <roi_matches.json>

Frequently Asked Questions about roi-mapping

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I match object tracks against camera ROI polygons for video surveillance?▼

You match tracks against camera ROI polygons by running a Python script that processes tracks JSON and config files, comparing spatial data like bounding boxes against the polygons and outputting ROI matches.

What is spatial event detection and when do I need ROI matching?▼

Spatial event detection identifies activities in specific camera regions like no-parking zones or sidewalks. You need ROI matching to filter detections or tracks so only relevant regions of interest are considered before further analysis.

Can I use this ROI matching script with pre-existing tracks and bounding box data?▼

Yes, you can use pre-existing tracks and bounding box data. The script accepts a tracks JSON file and a camera configuration file as input arguments to process and compare spatial data against predefined polygons.

Does video surveillance ROI matching require any external dependencies?▼

No external dependencies are required for this video surveillance ROI matching script. It operates independently using a provided Python script to process spatial data and output ROI matches.

What's the best way to filter detections for no-parking zones or sidewalks?▼

The best way to filter detections for no-parking zones or sidewalks is to match them against predefined camera ROI polygons, ensuring only relevant regions of interest are considered to enhance spatial event detection accuracy.

Why should I not use raw bounding box detections without ROI mapping?▼

Using raw bounding box detections without ROI mapping risks processing irrelevant areas, which reduces accuracy. Matching against ROI polygons ensures spatial event detection focuses only on configured regions before further processing.