rvardiashvili/GSIP
60
A high-performance, model-agnostic geospatial inference pipeline for gigapixel satellite imagery. Features a memory-efficient chunking engine, flexible batch processing, and a unified CLI/GUI ecosystem for seamless deep learning integration on standard hardware.
What's novel
A high-performance, model-agnostic geospatial inference pipeline for gigapixel satellite imagery. Features a memory-efficient chunking engine, flexible batch processing, and a unified CLI/GUI ecosystem for seamless deep learning integration on standard hardware.
Score Breakdown
Innovation
4 (25%)
Craft
49 (35%)
Traction
8 (15%)
Scope
69 (25%)
Signal breakdown
Innovation
Not Fork+1
Code Novelty+0
Unique Niche+1
Concept Novelty+2
Craft
Ci-1
Tests-2
Polish+1
Releases+0
Has License+5
Code Quality+12
Readme Quality+12
Recent Activity+7
Structure Quality+5
Commit Consistency+5
Has Dependency Mgmt+5
Traction
Forks+0
Stars+6
Hn Points+0
Watchers+0
Early Traction+0
Devto Reactions+0
Community Contribs+2
Scope
Commits+8
Languages+5
Subsystems+10
Bloat Penalty+0
Completeness+7
Contributors+6
Authored Files+15
Readme Code Match+3
Architecture Depth+7
Implementation Depth+8
Evidence
Commits
82
Contributors
2
Files
81
Active weeks
13
TestsCI/CDREADMELicenseContributing
Repository
Language
Python
Stars
1
Forks
0
License
MIT