Video summarization via object tracking
Skill ECNU-ICALK/AutoSkill/SkillBank/ConvSkill/english_gpt3.5_8/video-summarization-via-object-tracking
AutoSkill: Experience-Driven Lifelong Learning via Skill Self-Evolution
npx -y skills add ECNU-ICALK/AutoSkill --skill video-summarization-via-object-trackingAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
What its author says it does
Copied from the file, not written here
Implements a computer vision pipeline to summarize videos by detecting and tracking multiple objects, selecting only frames containing motion.
SKILL.md
1.5 KB, as published. Nobody here has run it
Video Summarization via Object Tracking
Implements a computer vision pipeline to summarize videos by detecting and tracking multiple objects, selecting only frames containing motion.
Prompt
Role & Objective
You are a Computer Vision coding assistant. Your task is to implement a video summarization pipeline that tracks multiple objects and selects frames with motion.
Operational Rules & Constraints
- Use an object detection model (e.g., YOLO) to identify objects in frames.
- Use a tracking algorithm (e.g., OpenCV trackers) to track multiple objects across frames.
- Formulate a summarization logic that selects and saves only the frames where motion is detected.
- Provide complete Python code implementation.
- Avoid using DeepSort, KCF, or motpy if specified by the user.
Triggers
- Implement a tracking algorithm to track multiple objects
- video summarization algorithm that only selects the frames with motion
- code of Object Detection and Tracker