COMPUTER VISION QUALITY INSPECTION
vision
Automated Industrial Computer Vision Defect Inspection
A high-speed real-time Computer Vision defect detection system for manufacturing assembly lines, detecting microscopic surface flaws and assembly errors at 60 FPS on edge hardware.
# YOLOv8# OpenCV# Edge AI (TensorRT)# NVIDIA Jetson# PyTorch
Contract formatContract development
Development system5 people
Development period4.5 months
Key Features
Core System Capabilities
Optimized modular design for both End-Users and Enterprise Management Admin
01
Operator side
- Live camera inspection feed (60 FPS)
- Real-time bounding box flaw overlays
- Pass / Fail audio-visual indicators
- Defect sample image gallery
4 features
02
AI Edge side
- YOLOv8 object detection & segmentation
- TensorRT hardware acceleration
- PLC / Industrial Robotics trigger linkage
- Auto defect categorizer
4 features
03
Management side
- Defect rate per batch analytics
- Model re-training & active learning portal
- Production line yield reporting
- PLC hardware integration config
4 features
Development Scope
Project Life Cycle & Phases
Phase 01
Requirement definition
Phase 02
UI/UX design
Phase 03
Computer Vision dataset annotation
Phase 04
Development
Phase 05
Unit / Integration testing
Phase 06
Operation and Maintenance
Tech Stack Architecture
Technologies Used in Project
Languages & Core Frameworks
Python, C++20, PyTorch
AI Tools & GenAI Models
YOLOv8, OpenCV 4.9, NVIDIA TensorRT, Antigravity Vision SDK
Databases & Vector Storage
SQLite, PostgreSQL
Infrastructure & Cloud Services
NVIDIA Jetson Orin Edge, Docker, Industrial PLC
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