kalenforn/clip-based-cross-modal-hash
This project summarizes the CLIP-based cross-modal hashing methods. Including DCMHT, MITH, DSPH, DNPH, TwDH (Two-Step Discrete Hashing for Cross-Modal Retrieval), DIMCH(Cross-modal Hashing via Diverse Instances Matching), UMoED(A Unified Generative Hashing for Cross-Modal Retrieval).
55
Stars
0
Forks
21.5
Radar Score
Declining
Momentum
Scoring Breakdown
Impact13.5
Velocity18.8
Health38.0
Growth Metrics
7-Day Stars
+0
30-Day Stars
+0
Acceleration
x
Language
Python
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🛡️ Enterprise Readiness & Commercial Safety
Organic Growth
95%
High Confidence
Growth pattern looks organic.
License
Permissive (Commercial Friendly)
Safe for commercial use, modification, and distribution.
Health Grade
C
Based on maintenance, issue response, and release cadence.
Radar Score
21.5
Composite of Impact, Velocity, and Health.
Disclaimer: This is an automated heuristic assessment based on public GitHub signals. Always perform your own security audit, dependency review, and legal compliance check before production deployment.
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