Computer vision on images + video with OpenCV (docs.opencv.org/4.x/): core (Mat / ndarray, linalg), imgproc (filtering, morphology, geometric transforms, color conv, histograms, contours), imgcodecs (imread/imwrite — PNG, JPEG, TIFF, WebP, EXR), videoio (VideoCapture / VideoWriter — FFMPEG, GStreamer, V4L2, AVFoundation, MSMF backends), calib3d (camera calibration, stereo, solvePnP, homography), features2d (ORB, AKAZE, BRISK, KAZE, SIFT), objdetect (FaceDetectorYN, FaceRecognizerSF, HOG, ArUco, QRCode), dnn (ONNX/TF/Caffe/Darknet, CUDA + OpenVINO + Vulkan backends, model zoo at github.com/opencv/opencv_zoo), photo (inpainting, denoising, HDR Debevec/Robertson), stitching (panorama), video (optical flow Farneback/LK/DIS, BackgroundSubtractorMOG2/KNN, tracking KCF/CSRT/MIL/Nano/Vit/DaSiamRPN). Python-first via cv2. Use when the user asks to detect faces, track objects, run YOLO inference, capture + process webcam frames, calibrate a camera, stitch a panorama, or use OpenCV from Python/C++.
How to install cv-opencv?
damionrashford/media-os/cv-opencv
$npx -y skills add damionrashford/media-os --skill cv-opencvInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/damionrashford/media-os" --skill "damionrashford/media-os/cv-opencv"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/damionrashford/media-os" that are relevant to the current task. Run `npx skills add "https://github.com/damionrashford/media-os"` and select the relevant skills, then follow their instructions.
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