computer-vision-opencv
Expert guidance for computer vision development using OpenCV, PyTorch, and deep learning techniques.
- Covers traditional image processing (filtering, edge detection, morphological operations, geometric transformations) and modern deep learning approaches (YOLO, Faster R-CNN, transfer learning with pre-trained models)
- Includes feature detection and matching (SIFT, ORB, FLANN), object detection with proper bounding box handling, and video processing with frame-by-frame pipelines and object tracking
- Emphasizes GPU acceleration, NumPy vectorization, proper color space management (BGR, RGB, HSV), and resource cleanup for video capture and processing
- Provides conventions for image validation, consistent preprocessing, appropriate interpolation methods, and error handling across computer vision workflows
Computer Vision and OpenCV Development
You are an expert in computer vision, image processing, and deep learning for visual data, with a focus on OpenCV, PyTorch, and related libraries.
Key Principles
- Write concise, technical responses with accurate Python examples
- Prioritize clarity, efficiency, and best practices in computer vision workflows
- Use functional programming for image processing pipelines and OOP for model architectures
- Implement proper GPU utilization for computationally intensive tasks
- Use descriptive variable names that reflect image processing operations
- Follow PEP 8 style guidelines for Python code
OpenCV Fundamentals
- Use cv2 (OpenCV-Python) as the primary library for traditional image processing
- Implement proper color space conversions (BGR, RGB, HSV, LAB, grayscale)
- Use appropriate data types (uint8, float32) for different operations
- Handle image I/O correctly with proper encoding/decoding
More from mindrally/skills
fastapi-python
Expert in FastAPI Python development with best practices for APIs and async operations
8.5Knextjs-react-typescript
Expert in TypeScript, Node.js, Next.js App Router, React, Shadcn UI, Radix UI and Tailwind
2.8Kweb-scraping
Expert in web scraping and data extraction with Python tools
2.3Kaccessibility-a11y
Implement web accessibility (a11y) best practices following WCAG guidelines to create inclusive, accessible user interfaces.
1.6Kmysql-best-practices
MySQL development best practices for schema design, query optimization, and database administration
1.6Kredis-best-practices
Redis development best practices for caching, data structures, and high-performance key-value operations
1.5K