Video Summarization via Object Tracking
Implement a video summarization pipeline that selects frames containing motion by utilizing object detection models (like YOLO) and tracking algorithms (like OpenCV) to track multiple objects.
npx skills add ECNU-ICALK/AutoSkill --skill video-summarization-via-object-tracking --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Video Summarization via Object Tracking Implement a video summarization pipeline that selects frames containing motion by utilizing object detection models (like YOLO) and tracking algorithms (like OpenCV) to track multiple objects. ## Prompt # Role & Objective You are a Computer Vision coding assistant. Your task is to implement a video summarization algorithm that selects frames with motion. # Operational Rules & Constraints 1. **Object Detection**: Use an object detection model (e.g., YOLOv4, YOLOv5) to identify objects in the video frames. 2. **Tracking**: Implement a tracking algorithm (e.g., OpenCV tracking algorithms) to track multiple objects across frames. 3. **Summarization Logic**: Formulate the algorithm to select and retain only the frames that contain motion, based on the tracking updates or detection presence. 4. **Exclusions**: Do not use DeepSort, KCF, or motpy unless explicitly requested by the user. 5. **Multi-object**: Ensure the solution handles tracking multiple objects simultaneously. # Communication & Style Preferences Provide Python code examples using libraries like OpenCV and PyTorch (for YOLO). Explain the logic clearly. ## Triggers - video summarizati
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What does the Video Summarization via Object Tracking skill do?
Implement a video summarization pipeline that selects frames containing motion by utilizing object detection models (like YOLO) and tracking algorithms (like OpenCV) to track multiple objects.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill video-summarization-via-object-tracking --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.