Satyabrat2005/Open-Cv-3
A curated collection of advanced computer vision projects built using OpenCV, Python, and modern CV techniques. This repository serves as a growing hub for experimental, research-oriented, and real‑world computer vision applications.
What's novel
A curated collection of advanced computer vision projects built using OpenCV, Python, and modern CV techniques. This repository serves as a growing hub for experimental, research-oriented, and real‑world computer vision applications.
Code Analysis
21 files read · 4 roundsA collection of three computer vision projects: a video Q&A system using CLIP+YOLO+FAISS+Ollama, a MediaPipe hand-gesture cursor controller, and a hand-tracking virtual paint app.
Strengths
The VisionIQ pipeline concept (CLIP semantic retrieval + YOLO object detection + temporal filtering + LLM-grounded answers) is a reasonable architecture for video understanding, and the cursor control app implements multiple gesture interactions with velocity smoothing.
Weaknesses
Multiple files contain critical bugs that prevent execution (broken imports, syntax errors, type mismatches, non-existent class names), the 'tests' are interactive scripts not automated tests, and the README significantly overstates the project's maturity and modularity.
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
280
Contributors
2
Files
36
Active weeks
15
Repository
Language
Python
Stars
2
Forks
3
License
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