675 skills found · Page 21 of 23
aiskillstore / container-orchestrationDocker, Kubernetes, and AWS ECS/Fargate patterns. Triggers on: Dockerfile, docker-compose, kubernetes, k8s, helm, pod, deployment, service, ingress, container, image, ecs, fargate, task definition, ecs service, awsvpc, FARGATE_SPOT, ALB, ecs vs kubernetes.
aiskillstore / ai-image-generationGenerate AI images with GPT-Image-2, FLUX, Gemini, Grok, Seedream, Reve and 50+ models via inference.sh CLI. Models: GPT-Image-2, FLUX Dev LoRA, FLUX.2 Klein LoRA, Gemini 3 Pro Image, Grok Imagine, Seedream 4.5, Reve, ImagineArt.
sanjay3290 / google-chatInteract with Google Chat - send, read, edit, delete and react to messages, share images and files, reply in threads, and manage spaces and DMs
sanjay3290 / imagenGenerate images using Google Gemini's image generation capabilities. Use this skill when the user needs to create, generate, or produce images for any purpose including UI mockups, icons, illustrations, diagrams, concept art, placeholder images, or visual representations.
sanjay3290 / apple-containerApple's open-source `container` CLI to build, run, and manage OCI/Linux containers as lightweight per-container VMs on Apple-silicon macOS — no Docker daemon required
sanjay3290 / whatsappSend and receive WhatsApp messages via the unofficial linked-device client pywhats (pip install pywhats) — pair with QR, send text/images, group chat, read receipts, presence/typing, and a long-running JSON event stream
redfox-data / pdf-image-text-extractor从图片或 PDF 文档中识别并提取文字内容，支持多种图片格式和 PDF 文件，自动判断是否包含文字并保留原始格式输出结构化结果；v2.1 采用零额外依赖方案：扫描版 PDF 自动渲染为图片交由 AI 视觉识别（无需 tesseract/rapidocr）、表格用 pymupdf 内置 find_tables 结构化提取（无需 pdfplumber）、批量处理目录（PDF+图片一次性提取）；当用户需要从图片或 PDF 提取文字、进行 OCR 识别、处理含文字的文档、提取 PDF 表格、批量处理文件夹或转换为可编辑文本时使用。该skill能力来自RedFoxHub，官网：https://redfo…
redfox-data / gzh-ai-feedAI公众号信息源 — Daily scan of AI WeChat public accounts, finding the hottest articles by read count, auto-clustering into topics, and generating a styled HTML report with cover images, metrics, search, and subscription support
jamditis / photo-metadataEmbeds photo IPTC/EXIF/XMP metadata, caption, credit, alt text, license, AI-source label, GPS stripping, and C2PA credentials.
jamditis / source-verificationVerify sources, claims, images, video, documents, interviews, and synthetic media with SIFT and a durable evidence trail. Use before relying on uncertain material.
Microck / card-news-generator-v2Create 600x600 Instagram-style card news series automatically with optional background images. User provides topic, colors, and optional images - Claude generates content and creates multiple cards with proper text wrapping.
Microck / data-export-pdfCreate professional PDF reports with text, tables, and embedded images using reportlab. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
arpitg1304 / robot-perceptionComprehensive best practices for robot perception systems covering cameras, LiDARs, depth sensors, IMUs, and multi-sensor setups.
jaechang-hits / cellpose-cell-segmentationDL cell/nucleus segmentation for fluorescence and brightfield microscopy. Pre-trained models (cyto3, nuclei, tissuenet) and a generalist flow-based algorithm segment cells without retraining. Outputs label masks for morphology and tracking.
jaechang-hits / napari-image-viewerInteractive viewer for microscopy. Displays 2D/3D/4D arrays as Image, Labels, Points, Shapes, Tracks layers; supports annotation, plugin analysis, headless screenshots. Core visualization for Python bioimage workflows.
jaechang-hits / opencv-bioimage-analysisComputer 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++.
jaechang-hits / pyimagej-fiji-bridgePython bridge to ImageJ2/Fiji for macros, plugins (Bio-Formats, TrackMate, Analyze Particles), NumPy↔ImagePlus/ImgLib2 exchange, and ImageJ Ops. Automates Fiji headlessly from Python. Use scikit-image for pure Python without Fiji plugins; napari for visualization.
jaechang-hits / scikit-image-processingPython 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.
jaechang-hits / trackpy-particle-trackingPython library for single-particle tracking (SPT) in video microscopy via the Crocker-Grier algorithm. Locate particles (fluorescent spots, colloids, vesicles, cells) per frame, link into trajectories, filter short tracks, and compute MSD for diffusion analysis.
jaechang-hits / western-blot-quantificationProtocols and best practices for western blot quantification and analysis including band detection, normalization, and statistical methods.
jaechang-hits / histolab-wsi-processingWSI processing for digital pathology. Tissue detection, tile extraction (random, grid, score-based), filter pipelines for H&E/IHC. For dataset prep, tile-based DL, slide QC. Use pathml for multiplexed imaging.
jaechang-hits / nnunet-segmentationMedical image segmentation with nnU-Net's self-configuring framework — auto-selects architecture, preprocessing, training for any modality. CT, MRI, microscopy, ultrasound in 2D, 3D full-res, 3D low-res, cascade.
jaechang-hits / omero-integrationOpen-source bio-image data management. Use the omero-py client to connect to an OMERO server, retrieve images as numpy arrays, annotate with tags and key-value pairs, manage ROIs, and feed image data into Python analysis pipelines — programmatically, no GUI.
jaechang-hits / simpleitk-image-registrationRegister, segment, filter, resample 3D medical images (MRI, CT, microscopy) via SimpleITK Python; DICOM, NIfTI, multi-modal. Rigid/affine/deformable registration, threshold/region-growing segmentation, Gaussian/morph filtering, label stats, format conversion.
jaechang-hits / cell-figure-guideCell (Cell Press) figure preparation: resolution (300-1000 DPI), formats (TIFF/PDF), RGB color, Avenir/Arial fonts, uppercase panel labels, strict image manipulation policies.
jaechang-hits / elife-figure-guideeLife figure preparation: file formats (TIFF/EPS/PDF), striking image requirements (1800x900 px), figure supplement naming, and image screening policy treating selective enhancement as misconduct.
jaechang-hits / nature-figure-guideNature figure preparation: resolution (300+ DPI), formats (AI/EPS/TIFF), RGB color, Helvetica/Arial fonts, lowercase panel labels, image integrity requirements.
jaechang-hits / nejm-figure-guideNEJM figure preparation: resolution (300-1200 DPI), editable vector formats (AI/EPS/SVG), in-house medical illustration policy, and strict image integrity requirements.
jaechang-hits / pnas-figure-guidePNAS figure preparation: resolution (300-1000 PPI), formats (TIFF/EPS/PDF), strict RGB-only color, Arial/Helvetica fonts, italicized uppercase panel labels, automated image screening.
jaechang-hits / science-figure-guideScience (AAAS) figure preparation: resolution (150-300+ DPI), formats (PDF/EPS/TIFF), RGB color, Myriad/Helvetica fonts, strict image manipulation policies including gamma adjustment disclosure.
