azureml-contrib-dataset vs scikit-image — Trust Score Comparison
Side-by-side trust comparison of azureml-contrib-dataset and scikit-image. Scores based on security, compliance, maintenance, popularity, and ecosystem signals.
azureml-contrib-dataset — Nerq Trust Score 67.2/100 (B-). scikit-image — Nerq Trust Score 77.2/100 (B+). scikit-image leads by 10.0 points.
Detailed Score Analysis
| Dimension | azureml-contrib-dataset | scikit-image |
|---|---|---|
| Security | 90/100 | 90/100 |
| Maintenance | 100/100 | 100/100 |
| Popularity | 30/100 | 90/100 |
| Quality | 50/100 | 55/100 |
| Community | 35/100 | 35/100 |
Five-dimension Nerq trust breakdown (registries: pypi / pypi). Scored equally weighted across security, maintenance, popularity, quality, community.
Detailed Metric Comparison
| Metric | azureml-contrib-dataset | scikit-image |
|---|---|---|
| Trust Score | 53.0/100 | 67.5/100 |
| Grade | D | B- |
| Stars | 0 | 6,459 |
| Category | uncategorized | other |
| Security | N/A | 0 |
| Compliance | 100 | 100 |
| Maintenance | N/A | 0 |
| Documentation | N/A | 0 |
| EU AI Act Risk | N/A | N/A |
| Verified | No | No |
Verdict
scikit-image leads with a trust score of 67.5/100 compared to azureml-contrib-dataset's 53.0/100 (a 14.5-point difference). Both agents should be evaluated based on your specific requirements.
Detailed Analysis
Security
Security scores measure dependency vulnerabilities, CVE exposure, and security practices. azureml-contrib-dataset scores N/A and scikit-image scores 0 on this dimension.
Maintenance & Activity
Activity scores reflect how actively each project is maintained. azureml-contrib-dataset: N/A, scikit-image: 0.
Documentation
Documentation quality is evaluated based on README, API docs, and example coverage. azureml-contrib-dataset: N/A, scikit-image: 0.
Community & Adoption
azureml-contrib-dataset has 0 GitHub stars while scikit-image has 6,459. scikit-image has significantly broader community adoption, which typically means more Stack Overflow answers, more third-party tutorials, and faster ecosystem development.
When to Choose Each Tool
Choose azureml-contrib-dataset if you need:
- Consider if it better fits your specific use case
Choose scikit-image if you need:
- Higher overall trust score — more reliable for production use
- Larger community (6,459 vs 0 stars)
Switching from azureml-contrib-dataset to scikit-image (or vice versa)
When migrating between azureml-contrib-dataset and scikit-image, consider these factors:
- API Compatibility: azureml-contrib-dataset (uncategorized) and scikit-image (other) serve different categories, so migration may require significant refactoring.
- Security Review: Run a security audit after migration. Check the azureml-contrib-dataset safety report and scikit-image safety report for known issues.
- Testing: Ensure your test suite covers all integration points before switching in production.
- Community Support: azureml-contrib-dataset has 0 stars and scikit-image has 6,459. Larger communities typically mean better Stack Overflow answers and migration guides.
Related Pages
Frequently Asked Questions
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Last updated: 2026-05-09 | Data refreshed weekly
Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.