'opencv' 검색 결과

使用Python和OpenCV库对图像进行骨架提取，要求细化后的骨架宽度严格为一个像素，且保持连通性。

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使用OpenCV对图像进行骨架化处理，并去除游离孤点及基于距离阈值过滤连接时的异常点。

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使用Python和OpenCV库对图像进行骨架提取，要求细化后的骨架宽度严格为一个像素，且保持连通性。

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使用OpenCV对图像进行骨架化处理，并去除游离孤点及基于距离阈值过滤连接时的异常点。

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Create YAML test scenarios for web applications and run them in a real browser with Playwright. Use image matching and text recognition to check screens, then organize failure findings for investigation.

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• Test a checkout flow in a real browser
• Check screens with image matching and text recognition
• Investigate browser test failures

Computer vision for bio-image preprocessing, feature detection, real-time microscopy. Color conversion, morphology, contour/blob detection, template matching, optical flow on fluorescence/brightfield. 10-100× faster than pure Python via C++. Use scikit-image for scientific morphometry/regionprops; OpenCV for real-time, video, classical feature extraction.

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Computer Vision Specialist IA — Expert en vision par ordinateur (YOLO, OpenCV, object detection, OCR, segmentation)

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Python 앱을 Windows에 배포하도록 Nuitka 컴파일, 불필요한 파일과 DLL 용량 분석, Inno Setup을 통한 가벼운 설치 프로그램 제작을 지원합니다.

• Python 앱을 Windows용으로 배포하기
• 배포 용량이 큰 의존성 조사하기
• 새 Windows 환경의 실행 오류 조사하기

버튼과 메뉴 등 화면의 애니메이션을 설계·구현·검토해 반응과 움직임을 다듬습니다. 녹화에서 속도 변화와 스프링 움직임을 분석하고 재현 코드와 구현 명세를 정리합니다.

• 버튼과 메뉴에 움직임 추가
• 녹화 속 화면 애니메이션 재현
• 느린 반응과 끊김 원인 조사

Coordinate AI agents to create short videos, from copy and storyboards to images, narration, subtitles, and MP4 assembly. The workflow includes quality checks, revision requests, and production data reviews to guide later improvements.

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• Creating a 30-second product introduction video
• Coordinating agents across video production tasks
• Checking images and audio sync before delivery

Create videos based on 『三体』 through a structured workflow covering source-setting research, scripts, storyboards, character consistency, audio, and final assembly. It also checks story consistency and technical quality, and prepares titles, covers, and tags for B站.

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• Plan a video about the deterrence era in 『三体』
• Write character dialogue consistent with the source
• Design consistent scenes, characters, and storyboards

Analyze a reference video's visual style, colors, composition, and pacing, then develop a new video with generated images, narration, sound, and subtitles. The workflow combines assets into an MP4 and supports resuming failed production steps.

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• Analyze the style and pacing of a reference video
• Plan a new video from reference analysis
• Combine images, narration, and subtitles into an MP4

Plan and assemble original videos with images, voiceovers, sound effects, music, and subtitles. The suite also extracts frames from existing videos, analyzes their visual style, and produces shot references and prompts for new versions.

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• Create an original video from an initial idea
• Rework a reference video in a different visual style
• Extract shot references and prompts from video frames

Turn product information into a promotional MP4 through a staged workflow covering sales copy, story planning, shot descriptions, generated scene images, subtitles, and audio recommendations. A Python script combines the prepared materials into the final video.

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• Create a 30-second promotional video for a new product
• Plan a 60-second skincare brand video
• Produce a 15-second snack video for social media

Extract still frames from videos at chosen intervals, then use an AI model that understands images to analyze scenes, people, and composition. Get structured descriptions and creative prompts for video planning and storyboard reference.

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• Study scenes and composition in reference videos
• Extract still images for storyboard reference
• Build creative prompts from video imagery

Interpret Culture Index behavioral profiles to understand individual traits, team balance, and possible strain from workplace adaptation. Use PDF or JSON data to inform hiring discussions, management approaches, onboarding plans, and conflict mediation.

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• Understanding an individual’s behavioral profile
• Assessing team balance and missing roles
• Exploring strain from Survey and Job differences

图片增强 / 放大 / 变清晰：高质量放大（Lanczos 2x/4x）+ 去噪 + 锐化 + 自动对比度/饱和度，改善偏糊、偏暗、噪点多的图片。当用户说 图片放大、图片变清晰、提高清晰度、图片增强、去噪点、锐化、图片太糊了、放大到高清、提升画质、优化图片、图片调亮调色 时使用。基于 shared/scripts/img_enhance.py（Pillow+OpenCV）。注意：这是传统增强非 AI 超分，凭空生成细节请用 ai-image-gen 图生图。与 image-editing 区别：那个做缩放/裁切/水印等常规操作，本 SKILL 专做画质提升。

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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.

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Combine visual features (face detection, lip movement analysis) with audio features to improve speaker diarization accuracy in video files. Use OpenCV for face detection and lip movement tracking, then fuse visual cues with audio-based speaker embeddings. Essential when processing video files with multiple visible speakers or when audio-only diarization needs visual validation.

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Extract frames from video files and save them as images using OpenCV

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使用Python从视频中平均截取9帧画面，并将它们合并成一张图片。

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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

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Python image processing for microscopy and bioimage analysis. Read/write images, filter (Gaussian, median, LoG), segment (thresholding, watershed, active contours), measure region properties, detect features. SciPy/NumPy ecosystem. Use OpenCV for real-time video; CellPose for DL cell segmentation; napari for visualization.

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Comprehensive best practices for robot perception systems covering cameras, LiDARs, depth sensors, IMUs, and multi-sensor setups. Use this skill when working with RGB image processing, depth maps, point clouds, sensor calibration (intrinsic, extrinsic, hand-eye), object detection, semantic segmentation, 3D reconstruction, visual servoing, or perception pipeline optimization. Trigger whenever the user mentions OpenCV, Open3D, PCL, RealSense, ZED, OAK-D, camera calibration, AprilTags, ArUco markers, stereo vision, RGBD, point cloud filtering, ICP registration, coordinate transforms, camera intrinsics, distortion correction, image undistortion, sensor streaming, frame synchronization, or any computer vision task in a robotics context. Also covers multi-camera rigs, time synchronization across sensors, perception latency budgets, and production deployment of perception pipelines.

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