Loading...
Loading...
Found 9 Skills
Expert guidance for computer vision development using OpenCV, PyTorch, and modern deep learning techniques for image and video processing.
Open Source Computer Vision Library (OpenCV) for real-time image processing, video analysis, object detection, face recognition, and camera calibration. Use when working with images, videos, cameras, edge detection, contours, feature detection, image transformations, object tracking, optical flow, or any computer vision task.
Guide for video analysis and frame-level event detection tasks using OpenCV and similar libraries. This skill should be used when detecting events in videos (jumps, movements, gestures), extracting frames, analyzing motion patterns, or implementing computer vision algorithms on video data. It provides verification strategies and helps avoid common pitfalls in video processing workflows.
Remove Gemini logos, watermarks, or AI-generated image markers using OpenCV inpainting. Use this skill when the user asks to remove Gemini logo, AI watermark, or any logo/watermark from images.
Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib
World-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems. Expertise in PyTorch, OpenCV, YOLO, SAM, diffusion models, and vision transformers. Includes 3D vision, video analysis, real-time processing, and production deployment. Use when building vision AI systems, implementing object detection, training custom vision models, or optimizing inference pipelines.
Cross-platform operating system automation and screen control toolkit. Use when users need screenshots, mouse/keyboard control, visual recognition, window management, browser automation, or desktop automation tasks. Supports macOS 12+ and Windows 10+. On macOS, uses AppleScript, pyautogui, and OpenCV. On Windows, uses pywinauto, pyautogui, and OpenCV (no Hammerspoon equivalent).
Remove backgrounds from images using segmentation. Support for color-based, edge detection, and AI-assisted removal methods. Batch processing available.
Corrección de perspectiva del documento fotografiado en ángulo mediante transformación homográfica