Results for “mask-auto-label”

Apply CSS alpha masking with linear-gradient for horizontal or vertical edge fades (mask-image and -webkit-mask-image). Use when asked for alpha masks, fade edges, or CSS mask gradients.

Train, evaluate, export, and run inference for Masked Auto-Encoder (MAE) models for self-supervised pretraining and fine-tuning of visual representations.

Masks a URL behind a custom domain for demos and recordings by setting up an HTTPS reverse proxy with trusted certificates and automatic cleanup.

Mask-driven image inpainting on RunComfy via the `runcomfy` CLI. Routes to Tongyi MAI Z-Image Turbo Inpainting (the dedicated inpainting endpoint with mask, strength, and control-scale) and to identity-preserving edit models (Nano Banana 2 Edit, GPT Image 2 Edit, FLUX Kontext Pro) when a mask isn't available and the region must be described instead. Use for object removal, watermark removal, region replacement, blemish cleanup, and any controlled local edit where a binary mask defines the target area. Triggers on "inpaint", "inpainting", "image inpaint", "remove from image", "fill region", "mask-driven edit", "remove watermark", "remove object", "patch the photo", "fill the hole", or any explicit ask to edit a specific masked region of a still.

Generate a compact PDF shipping label with sender and recipient addresses, barcode, and tracking number.

Mask-driven image inpainting on RunComfy via the `runcomfy` CLI. Routes to Tongyi MAI Z-Image Turbo Inpainting (the dedicated inpainting endpoint with mask, strength, and control-scale) and to identity-preserving edit models (Nano Banana 2 Edit, GPT Image 2 Edit, FLUX Kontext Pro) when a mask isn't available and the region must be described instead. Use for object removal, watermark removal, region replacement, blemish cleanup, and any controlled local edit where a binary mask defines the target area. Triggers on "inpaint", "inpainting", "image inpaint", "remove from image", "fill region", "mask-driven edit", "remove watermark", "remove object", "patch the photo", "fill the hole", or any explicit ask to edit a specific masked region of a still.

Create masked staggered word reveals on scroll with GSAP ScrollTrigger. Use when headings, hero copy, section titles, or editorial text should reveal word-by-word through an overflow mask as they enter the viewport.

Builds reliable browser automation skills by iteratively running a browsing task, reading the trace, and improving the navigation strategy until it passes consistently.

Set up and manage data labeling workflows using manual annotation tools, semi-automated pipelines, active learning, and programmatic weak supervision. Use when the user requests data labeling or provides relevant inputs for this workflow.

Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. Surfaces taste decisions (close approaches, borderline scope, codex disagreements) at a final approval gate. One command, fully reviewed plan out. Use when asked to "auto review", "autoplan", "run all reviews", "review this plan automatically", or "make the decisions for me". Proactively suggest when the user has a plan file and wants to run the full review gauntlet without answering 15-30 intermediate questions. (gstack) Voice triggers (speech-to-text aliases): "auto plan", "automatic review".

Audits and rewrites user-facing copy across web and mobile codebases, improving clarity, tone, and actionability of labels, errors, CTAs, and empty states.

Analyze and replicate xAI's design language: near-black canvas, white pill outlines, Universal Sans display type, and Geist Mono technical labels.

Autonomous run-loop for the blog pipeline. Picks the top unwritten keyword from the vetted queue, dispatches /blog-pipeline in autonomous mode, auto-publishes on success, quarantines persistent failures, and refreshes the keyword queue when empty. Cron-friendly. No human in the loop.

Audit or refresh MarketingClaw maturity scorecard docs from root taxonomy, maturity scores, and QA evidence artifacts without using maintainer discrawl data or committed inventory reports.

Run Karpathy-style autonomous ML search on a real training repo: choose the right mode (setup, program.md, bounded loop, results interpretation, or constrained-hardware adaptation), preserve the immutable prepare.py / 300-second / val_bpb contract, and route prompt/skill eval work away to LangSmith, Promptfoo, Braintrust, or skill-autoresearch.

Mask-driven image inpainting on RunComfy via the `runcomfy` CLI. Routes to Tongyi MAI Z-Image Turbo Inpainting (the dedicated inpainting endpoint with mask, strength, and control-scale) and to identity-preserving edit models (Nano Banana 2 Edit, GPT Image 2 Edit, FLUX Kontext Pro) when a mask isn't available and the region must be described instead. Use for object removal, watermark removal, region replacement, blemish cleanup, and any controlled local edit where a binary mask defines the target area. Triggers on "inpaint", "inpainting", "image inpaint", "remove from image", "fill region", "mask-driven edit", "remove watermark", "remove object", "patch the photo", "fill the hole", or any explicit ask to edit a specific masked region of a still.

Masked Autoencoders Are Scalable Vision Learners

Use when applying seamless infinite marquee loops with duplicated items for logo strips, tickers, or continuous horizontal content.

Use when building cursor-following spotlight reveals that expose a second aligned image through a soft radial mask—hover-to-color, before-and-after, x-ray, material, texture, product-detail, or illustrated heroes where a desaturated or embossed base stays visible while another treatment follows an eased pointer.

Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. (gstack)

Open-Vocabulary Object Detection Using Captions

Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.

Converts human-written CLAUDE.md files into a structured-label format that AI models follow more reliably while using fewer tokens.

Configures AutoML pipelines with algorithm selection, feature engineering, and ensemble methods

Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.

Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.

Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B.

Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.

Converts human-written CLAUDE.md files into a structured-label format that AI models follow more reliably while using fewer tokens.

Builds a custom LWC lookup component with typeahead search via Apex SOSL/SOQL, debounce, keyboard navigation, and pill UI for cases where standard pickers fall short.

ElevenLabs text-to-speech with mac-style say UX.

Applies a battle-tested bilingual web-design system with typography, responsive rules, and performance patterns for Yuval Avidani's projects.

Apply image blur effects and privacy masks using Python PIL processing. Use when you need to blur, redact faces, or mask sensitive regions in images.

Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.

Create a layered CSS progressive blur (top or bottom) using multiple backdrop-filter masks for depth and softness. Use when asked for “progressive blur”, “gradient blur overlay”, or stepped blur masks that fade from an edge of the viewport.