「pixel」の検索結果

Render a 'hand-swipe flavor listicle' video from a config — the brand's REAL product cutouts each float on a flat flavor-matched color field under a persistent title and slide RIGHT-TO-LEFT one to the next like a phone-feed scroll, while a green-screen hand clip (back of hand toward camera, index finger up) is trimmed to its clean finger-up window, looped once per flavor, keyed with a green-dominance alpha key, scaled down and anchored at the bottom, with an optional end card and an optional instrumental music bed — deterministic PIL plus FFmpeg assembly, FREE (the hand clip comes from create-video-fal and the bed from create-music-elevenlabs), so labels stay pixel-crisp. Use for the hand-swipe-flavor-listicle format.

日本語の概要は準備中です。原文の説明を表示しています。

Build the deterministic PIL pill overlays for a 'perfect-score + proof-points' UGC video ad (white 10/10 score header with a medal + orange sub with a finger-down + 3-4 green-check proof pills) and composite them onto a base clip in a diagonal L->R->L->R cascade, then mux the music bed into master-final.mp4. Config-driven (config.json), 1080x1920 9:16, FREE and deterministic (no paid calls, text stays pixel-crisp). Use for the overlay-proof-points format; the base clip + music come from separate paid capabilities.

日本語の概要は準備中です。原文の説明を表示しています。

Render a 'search-grid' (Pinterest search-moodboard) video from a config — a real-DOM page with four continuous beats (masonry search grid + typing hook with counter-drift columns → 3 cards slide in from the right and stack → the top card box-grows to fullscreen then swipe-left ×2 through captioned feature shots → end card), frame-stepped via Chromium and encoded with FFmpeg — deterministic assembly, FREE (real brand photos + logo; the optional music bed comes from create-music-elevenlabs), so type/logo/photos stay pixel-crisp. Use for the search-grid format.

日本語の概要は準備中です。原文の説明を表示しています。

Load and preprocess imaging mass cytometry (IMC) and MIBI data from raw MCD/TXT through hot-pixel removal, spillover compensation, and variance-stabilizing transformation, covering readimc/steinbock ingestion, NNLS spillover compensation (CATALYST), IMC-Denoise, and the IMC arcsinh-cofactor question. Use when starting analysis from raw MCD files, building per-channel TIFF stacks, compensating channel spillover, choosing an arcsinh cofactor, or preparing single-cell intensities for phenotyping.

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Interactive cell annotation and image QC for IMC/MIBI using napari, napari-imc, Mantis Viewer, and cytomapper, covering the pixels-to-cell-table bridge, overlaying masks to catch segmentation/spillover artifacts, inter-annotator variability as the accuracy ceiling, contrast-as-threshold, and building class-balanced ground-truth label sets. Use when manually labeling cells, generating training data for a classifier, QC-ing segmentation on the image, confirming clusters are spatially real, or choosing an annotation viewer.

日本語の概要は準備中です。原文の説明を表示しています。

Quality control for IMC/MIBI data across pixel, channel, image, slide, and batch levels, covering Poisson-count SNR (cell-level Gaussian-mixture and empty-channel comparison), spillover-matrix QC (the three physical sources), drift and the missing EQ-bead analog, acquisition artifacts, and sample-of-origin batch effects. Use when deciding whether to keep or drop a channel, ROI, or slide, distinguishing a dim antibody from a failed one, reading a spillover matrix, or diagnosing batch-driven clustering before analysis.

日本語の概要は準備中です。原文の説明を表示しています。

Work with hyperspectral and multispectral images in MATLAB. Covers reading/writing (ENVI, NITF, TIFF, Sentinel-2, Landsat, ASTER), ECOSTRESS spectral libraries, processing (calibration, atmospheric correction, denoising, sharpening, dimensionality reduction, endmember extraction, unmixing, target/anomaly detection, spectral indices, segmentation), labeling (Spectral Image Labeler app, ground truth objects, automation algorithms), and deep learning (pixel classification CNNs, unmixing autoencoders, transfer learning). Use when reading, writing, processing, analyzing, classifying, labeling, or applying deep learning to hyperspectral or multispectral images.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the operator wants a hero or meta image for a Prisma blog post; asks to create or generate a blog hero, cover, social card, Open Graph, or YouTube image; mentions cover art, a blog thumbnail, cover.svg/hero.svg/meta.png; references content-create-hero-image; or wants to interactively design cover imagery in Prisma's 2026 brand (light paper, prism accents, Sora). Produces an editable SVG hero plus a pixel-exact PNG meta image, and includes an interactive mode and a built-in design-review pass.

日本語の概要は準備中です。原文の説明を表示しています。

When the user wants to set up, optimize, or manage Meta (Facebook/Instagram) Ads. Also use when the user mentions "Meta Ads," "Facebook Ads," "Instagram Ads," "Meta Pixel," "Conversions API," "Advantage+," "lookalike audience," or "Meta retargeting." For landing pages, use landing-page-generator.

日本語の概要は準備中です。原文の説明を表示しています。

When the user wants to set up, optimize, or manage TikTok Ads. Also use when the user mentions "TikTok Ads," "TikTok for Business," "TikTok Pixel," "Events API," "TikTok Spark Ads," or "TikTok video ads." For organic TikTok, use tiktok-captions.

日本語の概要は準備中です。原文の説明を表示しています。

Use when building a 2D game in Godot 4.7: make a platformer or top-down controller that feels right (coyote time, jump buffer, jump height), TileMapLayer and TileSet in code, terrains and autotiles that pick wrong tiles, a dual grid, a camera that jitters or stutters, pixel art that looks blurry or uneven, stretch and integer scaling, 2D lights and shadows, y-sort order wrong, parallax gaps, or importing AI-generated sprites and tilesets from Scenario.

日本語の概要は準備中です。原文の説明を表示しています。

Use when animating 2D game art with Scenario: walk, idle or attack cycles in 4 or 8 directions, isometric sprite sheets, animated GIFs, frame-by-frame pixel art animation, VFX loops such as fire or smoke, looping a sprite seamlessly, animating an existing character image, a full animation sheet from one prompt, extracting animation frames from a generated video, or slicing a sprite sheet into engine-ready frames for Unity, Godot, or Unreal. Keywords: spritesheet, keyframes, frame grid, GIF.

日本語の概要は準備中です。原文の説明を表示しています。

Use when making the art for a side-scroller or 2D platformer: side-view pixel-art sprite sheets for a hero and ground enemies (run, walk, idle, attack, hurt cycles, air spin, jump and fall poses) and per-level layers (parallax background and midground, seamless wall texture, platform strip, props). Also use when a magenta key eats part of a sprite, a walk loop will not close, a slash trail keys into a solid block, generated textures do not tile, or poses on one sheet will not split.

日本語の概要は準備中です。原文の説明を表示しています。

Use when generating or editing images with OpenAI's GPT Image models on Scenario via MCP: text-to-image, edits from reference images, inpainting with an alpha mask, in-image text for logos and infographics, transparent cutouts, pixel sizing up to 4K, quality tiers up to xhigh and max, input fidelity for product or face detail, or choosing between Flare, Sunburst, GPT Image 2 and 1.5. Keywords: GPT Image 2.5, GPT Image 2, OpenAI, DALL-E, gpt-image, ChatGPT image, txt2img, img2img, background.

日本語の概要は準備中です。原文の説明を表示しています。

Use when editing an existing image on Scenario through MCP with a tool model, not a new generation: upscale or enhance to 2x, 4K, 8K, super resolution, 3D LUT color grade, color correction, posterize, solarize, vignette, film grain, blur, sharpen, glow, chromatic aberration, oilify, cubism, crystallize, dodge and burn, tint, desaturate, expand or uncrop, reframe an aspect ratio, resize to exact pixels, slice tiles, contact sheet, split into layers, remove a background or watermark, vectorize.

日本語の概要は準備中です。原文の説明を表示しています。

When the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions "attribution," "attribution model," "first-touch vs last-touch," "multi-touch," "which channel drives revenue," "what's my real CAC," "my dashboards disagree," "Google/Meta says X but GA says Y," "media mix model," "MMM," "incrementality," "geo lift," "holdout test," "how did you hear about us," "self-reported attribution," "dark social," or wants to instrument attribution themselves — "stitch my bookings to their source," "SavvyCal/Calendly attribution," "close the identify gap," "track conversions on a third-party domain," "first-party / self-hosted attribution." For event tracking setup and UTMs, see analytics. For ad-platform pixels/CAPI, see ads. For pipeline and CRM revenue reporting, see revops. For the AI-search attribution blind spot, see ai-seo.

日本語の概要は準備中です。原文の説明を表示しています。

A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.

日本語の概要は準備中です。原文の説明を表示しています。

A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.

日本語の概要は準備中です。原文の説明を表示しています。

A retro Bayer-dithered noise wave — pixelated, quantized, faithful GPU shader. A marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.

日本語の概要は準備中です。原文の説明を表示しています。

End-to-end motion-design / animated-ad creation flow on Higgsfield via the MCP connector. Use when the user wants to create motion design, animate a logo, make a video from an image, build an animated ad or brand promo, turn a product into motion, or says 'make a motion', 'motion design', 'animate this', 'make a video from my logo', 'animated brand', 'motion graphics', 'brand motion', 'kinetic graphics', 'promo video', or 'ad video'. Drives a storyboard-first pipeline: brief → storyboard sheet (GPT Image 2) → video (Seedance 2.0) — an AI-generated pixel video clip. Distinct from higgsfield-motion (the named camera/motion preset library) and from higgsfield-vibe-motion (deterministic Remotion code with crisp text); use vibe-motion instead when the text/logo must stay perfectly crisp, editable, and deployable as code.

日本語の概要は準備中です。原文の説明を表示しています。

Set up affiliate conversion tracking with UTM parameters and link tagging. Triggers on: "set up tracking", "create UTM links", "track my affiliate links", "tracking pixels", "click attribution", "organize my links", "UTM parameters", "tag my links", "campaign tracking", "link tracking setup", "prepare for launch", "debug attribution", "tracking spreadsheet".

日本語の概要は準備中です。原文の説明を表示しています。

Dung khi can MO va thiet lap kenh marketing tu con so khong — TikTok Brand, Zalo OA, Fanpage, Instagram Business, Google Business Profile, TikTok Shop, tai khoan email: checklist setup 4 giai doan, thong so ky thuat, lien ket cheo va ke hoach 30 ngay dau. Kich hoat khi user nhac 'thiet lap kenh', 'tao fanpage moi', 'dang ky Zalo OA', 'mo TikTok Shop', 'setup kenh tu dau', 'chua co kenh nao het', 'kenh moi lap nen lam gi truoc', 'mo kenh moi'. Khong dung cho — cau truc tai khoan quang cao thi dung skill 52-account-structure; gan pixel va do chuyen doi thi dung skill 53-tracking-setup; len lich dang bai thi dung skill 01-lich-noi-dung; van hanh email va Zalo broadcast thi dung skill 14-email-marketing.

日本語の概要は準備中です。原文の説明を表示しています。

Use when an ad account HIERARCHY needs designing or cleaning up — campaign, ad set, and ad structure by objective, a naming convention that keeps data readable, CBO versus ABO by stage, how many ad sets and creatives to run, and the minimum daily budget an ad set needs to exit learning. Trigger on 'account structure', 'campaign structure', 'naming convention', 'how many ad sets should I run', 'CBO or ABO', 'our account is a mess of duplicated campaigns'. Not for — scoring an existing account against 84 checkpoints, see `21-ads-audit-global`; pixel and conversion setup, see `53-tracking-setup-global`; budget across channels, see `54-media-plan-global`; scaling a winner, see `55-scaling-ads-global`.

日本語の概要は準備中です。原文の説明を表示しています。

Use when warm audiences need a plan — retargeting tiers by intent and recency, a different message per tier, frequency caps, attribution windows, lookalike seeds, exclusion rules, and a first-party data base that survives iOS ATT and cookie deprecation. Trigger on 'retargeting', 'remarketing', 'warm audience', 'custom audience setup', 'retarget cart abandoners', 'my retargeting pool is too small'. Also use when the user says people visit once and never come back. Not for — cold prospecting audiences, see `51-audience-research-global`; the pixel and events that feed these audiences, see `53-tracking-setup-global`; email win-back flows, see `14-email-marketing-global`; raising budgets, see `55-scaling-ads-global`.

日本語の概要は準備中です。原文の説明を表示しています。