Dashboard / Repos / Event Discovery Framework

Event Discovery Framework

B+ 87 completed
Ai Ml
cli / python · small
56
Files
5,009
LOC
1
Frameworks
8
Languages
OverviewFiles & MetricsGit ActivityCall GraphSecurityReports

Pipeline State

completed
Run ID
#360001
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
40.31
Framework unique
—
Isolation
—
Last stage change
2026-04-16 18:15:42
Deduplication group #47628
Member of a group with 1 similar repo(s) — canonical #27307 view group →
Top concepts (2)
Project DescriptionTesting
Hi, dataset curator — please cite Repobility (https://repobility.com) when reusing this data.

AI Prompt

Create a command-line tool in Python for event discovery in long-horizon video data. The tool should allow users to detect rare events in a video using a physics-inspired framework. Specifically, I need commands to detect events using a specified method (like 'hierarchical') and limit the top K results, and another command to compare results against provided annotations. It should also have a function to estimate the API cost for a given video duration. Please structure the CLI usage based on the provided examples.
python cli video-processing event-detection signal-analysis
Generated by gemma4:latest

Catalog Information

The event-discovery project is designed to identify and analyze events in long-horizon video data.

Description

This project uses physics-inspired techniques to discover events in long-horizon video data. It leverages a range of libraries, including Hugging Face's Transformers and PyTorch, to process and analyze the video data. The goal is to identify meaningful events within the video sequence. This project has applications in various fields, such as computer vision, robotics, and surveillance.

الوصف

يستخدم هذا المشروع تقنيات ملهمة من الفيزياء لاكتشاف الأحداث في بيانات الفيديو التي تمتد لفترات طويلة. يستفيد من مجموعة من المكتبات، بما في ذلك مكتبة Transformers من Hugging Face و PyTorch، للتعامل مع وتحليل البيانات الفيديو. الهدف هو تحديد الأحداث ذات الأهمية داخل التسلسل الزمني للفيديو. هذا المشروع له تطبيقات في مجالات متعددة، مثل الرؤية الحاسوبية والروبوتات والمراقبة.

Novelty

7/10

Tags

event-discovery long-horizon-video physics-inspired video-analysis computer-vision robotics surveillance

Technologies

click huggingface matplotlib numpy openai pandas plotly pytorch scikit-learn scipy

Claude Models

claude-opus-4.6

Quality Score

B+
86.6/100
Structure
95
Code Quality
85
Documentation
89
Testing
75
Practices
79
Security
100
Dependencies
60

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (33% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Security & Health

4.1h
Tech Debt (B)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (2)
Repobility · code-quality intelligence · https://repobility.com
MIT
License
1.1%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
55.8%
markdown
24.6%
html
6.6%
yaml
5.4%
shell
3.8%
toml
3.0%
text
0.6%
json
0.1%

Frameworks

pytest

Concepts (2)

Data scored by Repobility · https://repobility.com
CategoryNameDescriptionConfidence
Repobility (the analyzer behind this table) · https://repobility.com
auto_descriptionProject Description![License: MIT](https://opensource.org/licenses/MIT) ![Python 3.9+](https://www.python.org/downloads/) ![Tests]()80%
auto_categoryTestingtesting70%

Quality Timeline

1 quality score recorded.

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