Blueprintvalidation

C+ 71 completed
Ai Ml
cli / python · small
110
Files
12,537
LOC
1
Frameworks
6
Languages

Pipeline State

completed
Run ID
#366952
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
50.00
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
Repobility (the analyzer behind this table) · https://repobility.com

AI Prompt

Create a command-line tool in Python for validating robot world models using Gaussian splats. The tool should manage a multi-stage pipeline that takes a PLY file as input. I need commands to run preflight checks, and then execute the full pipeline, or run individual stages like rendering, compositing, enriching, fine-tuning, and evaluating the policy. The configuration should be managed via a YAML file, and the final output should generate a validation report in Markdown and JSON format.
python cli robotics validation gaussian-splats pipeline yaml scripting
Generated by gemma4:latest

Catalog Information

The blueprint-validation project is a tool for validating robot world models using Gaussian splats.

Description

This project implements a validation pipeline for robot world models using Gaussian splats. It provides a framework for evaluating the accuracy of these models in various scenarios. The pipeline can be used to validate models created with different tools and techniques, making it a versatile tool for researchers and developers working on robotics and computer vision projects.

الوصف

هذا المشروع يimplements خطوط التحقق من صحة النماذج العالمي للروبوت باستخدام Gaussian splats. يوفر إطارًا لتقويم دقة هذه النماذج في مختلف السيناريوهات. يمكن استخدام الملف الشخصي لتقييم النماذج التي تم إنشاؤها بطرق و أدوات مختلفة، مما يجعلها أداة متعددة الاستخدام للباحثين والمطورين الذين يعملون على مشاريع الروبوتية والرؤية الحاسوبية.

Novelty

7/10

Tags

robot-world-models validation-pipeline gaussian-splats computer-vision machine-learning robotics

Technologies

click huggingface matplotlib numpy pytorch scipy tensorflow

Claude Models

claude-opus-4.6

Quality Score

C+
71.4/100
Structure
87
Code Quality
61
Documentation
58
Testing
75
Practices
69
Security
84
Dependencies
60

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (45% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Containerized deployment (Docker)
  • Properly licensed project

Weaknesses

  • 703 duplicate lines detected \u2014 consider DRY refactoring
  • 1 'god files' with >500 LOC need decomposition

Security & Health

10.6h
Tech Debt (C)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (2)
Repobility · severity-and-effort ranking · https://repobility.com
MIT
License
8.6%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
93.5%
yaml
2.8%
shell
1.8%
markdown
1.0%
toml
0.6%
json
0.4%

Frameworks

pytest

Concepts (2)

Data scored by Repobility · https://repobility.com
CategoryNameDescriptionConfidence
Powered by Repobility — scan your code at https://repobility.com
auto_descriptionProject DescriptionGaussian splat to robot world model validation pipeline. Proves that scanning a facility and turning it into training data makes robot policies perform better in a world model that knows that specific site.80%
auto_categoryTestingtesting70%

Quality Timeline

1 quality score recorded.

View File Metrics

Embed Badge

Add to your README:

![Quality](https://repos.aljefra.com/badge/91141.svg)
Quality BadgeSecurity Badge
Export Quality CSVDownload SBOMExport Findings CSV