Results for “avatar-generation”

Casting personas: rapid generation from diverse inputs, registry-based persistence and lifecycle, data-driven evolution, inter-agent sync. Not for UI walkthroughs (Echo) or user research (Field).

[DEPRECATED] Use `create-video` for prompt-based video generation or `avatar-video` for precise avatar/scene control. This legacy skill combines both workflows — the newer focused skills provide clearer guidance.

Generate a viral-style talking baby video with custom costumes and dialogue using AI image and video generation.

Turns a person's photo into a custom 3D action figure with collectible toy packaging.

Generate images, videos, 3D assets, and audio via the Higgsfield AI CLI, including Marketing Studio ads and Virality Predictor analysis.

Generates a humorous, ultra-realistic video of an anthropomorphic animal vlogger in a real-world setting using AI image and video generation.

Generate AI avatar and talking head videos using inference.sh CLI with models like P-Video-Avatar, OmniHuman, Fabric, and PixVerse.

Generate images using AI from OpenAI or Google Gemini, with support for textures, icons, sprites, and visual assets.

Generates images with Google Gemini's image generation API for UI mockups, icons, illustrations, and visual assets.

Generates a multi-part animated story video by establishing a consistent character, creating sequential scenes, and animating them using image generation and image-to-video models.

Generates short AI videos from text or images across Runway, Kling, Sora, Pika, Seedance, Grok Imagine, and Veo, with provider-specific APIs and prompt guidance.

Generates a Pixar-style 3D cartoon character from a photo and animates it with a reference dance video using the MuAPI platform.

Generates images using multiple AI providers including OpenAI, Google, Azure, and others. Supports text-to-image, reference images, aspect ratios, and batch generation from prompt files.

Generates complete AI videos through a 6-stage pipeline (script, character/scene design, storyboard, reference images, video generation, post-production) or one-shot pipelines for short videos, action transfer, and digital human dubbing, all running on local servers.

Generates images from text prompts using Google Gemini's image generation model, saving them as PNG files for use in UI, documentation, and design projects.

Generate short videos from a text prompt or from still images using ByteDance Seedance on Volcengine Ark. Use this skill whenever the user wants to create, generate, render, or animate a video, clip, animation, motion graphic, or product demo — including text-to-video ("a drone shot over a forest at sunrise") and image-to-video, where a still becomes the first frame, or two stills are morphed start-to-end. Prefer this skill over describing a video in text.

Generates images using Google Gemini's image generation model for UI placeholders, documentation, and design assets.

Generates images from text prompts using Google Gemini's image generation model, saving them as PNG files for use in UI, documentation, and design assets.

Generates or edits images for projects using the OpenAI Image API, with support for batch runs and structured prompt augmentation.

Generates, edits, and transforms images via the Bria API, including text-to-image, background removal, product photography, and batch processing for e-commerce catalogs.

Generates images from text prompts using diffusion models, covering prompt engineering, inpainting/outpainting, ControlNet, and API integration for production workflows.

Generates images via OpenAI, Google, DashScope, and Replicate APIs, supporting text prompts, reference images, aspect ratios, and quality presets.

Create AI avatar, talking-head, and lip-sync videos on RunComfy via the `runcomfy` CLI. Routes across ByteDance OmniHuman (audio-driven full-body avatar), Wan-AI Wan 2-7 (audio-driven mouth sync via `audio_url` on a portrait), HappyHorse 1.0 (Arena #1 t2v / i2v with in-pass audio), and Seedance v2 Pro (multi-modal cinematic with reference audio + reference subject). Picks the right model for the user's actual intent — UGC voiceover, virtual presenter, dubbed product demo, lip-synced character, dialog scene — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "talking head", "lip sync", "avatar video", "make X speak", "audio to video", "audio driven avatar", "virtual presenter", "AI spokesperson", "dubbed video", "UGC avatar", "HeyGen alternative", "Synthesia alternative", "digital human", "make this portrait talk", "video from voiceover", or any explicit ask to put words in a face.

Train a personalized identity model on a person's face for use in Higgsfield's image and video generation.

Generate videos from text, images, or references using 40+ AI models via the inference.sh CLI.