I will develop an ai vision inspection system for automated defect
About this Gig
Streamline your quality control pipeline and eliminate costly manual error with a production-grade, high-precision Computer Vision Inspection System. I design and build automated deep learning pipelines tailored to detect defects, surface cracks, missing components, and assembly anomalies in real time.
Leveraging specialized expertise in industrial machine learning, I transform your raw camera feeds into intelligent inspection tools that protect your product quality and optimize operational overhead.
What I Offer:
- Custom Defect Detection: Built using state-of-the-art models like YOLOv8, PyTorch, and custom CNNs.
- Multi-Class Classification: Accurately isolate scratches, dents, color variances, or structural issues.
- Edge & On-Premise Deployment: Optimized for smooth performance on NVIDIA Jetson, local PCs, or Cloud nodes.
- API & Dashboard Integration: FastAPI / Flask backends featuring clean integration for real-time monitoring.
- Source Code & Documentation: Well-commented, production-ready code with complete deployment guides.
My Core Tech Stack:
- Programming: Python, C++
- Frameworks: PyTorch, TensorFlow, OpenCV, Ultralytics YOLO
- Tools & APIs: Docker, Git, FastAPI
APIs:
Microsoft Computer Vision AI
Expertise:
Image processing
•
Feature learning
•
Object detection
Programming language:
Python
Tools:
OpenCV
Frameworks:
Keras
•
PyTorch
FAQ
What hardware or devices can this vision system run on?
The system can be deployed on local Windows/Linux PCs, cloud servers, or edge devices like the NVIDIA Jetson series, depending on your processing speed and hardware setup requirements.
Do you provide the complete source code?
Yes! All packages include the full, well-documented source code so you or your team can run, maintain, and scale the system independently.
