'image generation' 검색 결과

Generate video clips from text descriptions or reference images through multiple API services. Compare available providers by cost and task needs, choose aspect ratios, track generation progress, and refine existing clips through conversational editing with Gemini Omni.

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• Generating clips from written scene descriptions
• Animating a product photo
• Creating vertical videos for social media

Integrate FLUX image generation and editing into applications through the BFL API. The guide covers authentication, checking asynchronous results, completion notifications through webhooks, request limits, error handling, regional endpoints, and downloading generated images before their URLs expire.

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• Add FLUX image generation and editing to an application
• Implement result checks and completion notifications
• Handle request limits and API errors

Plan image and graphic design workflows by matching tasks to available tools, from AI generation and photo editing to logos, interface mockups, diagrams, and publishing. Compare requirements, costs, and offline options before combining providers.

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• Generate and compose social sharing images
• Create logos and export size variants
• Draft interface wireframes and user flows

Use Hugging Face Transformers to load pretrained models, generate text, and classify text, images, or audio. Prepare model inputs, control generation settings, and fine-tune models on custom datasets with the Trainer API.

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• Prototype text, image, or audio classification
• Configure text generation and conversational responses
• Fine-tune a model on a custom dataset

Generate images and videos through Atlas Cloud by checking each model’s input requirements before submission. Guides the agent through sending a request, checking progress within a time limit, and downloading and validating the resulting media.

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• Generate an image from a text prompt with Atlas Cloud
• Generate a short video from a scene description
• Check model-specific inputs before submitting a request

Create presentation drafts from text, outlines, or documents through the 2slides API. Match a reference image's style, choose themes, add AI voice narration, and export slide images or audio for review and use.

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• Create a presentation from text or an outline
• Summarize a document into slides
• Match slide styling to a reference image

Use SAM to identify object regions in images from points, boxes, or existing masks. The skill provides implementation examples for transparent cutouts, automatic mask generation, annotation tools, and model selection based on available resources.

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• Extracting objects with transparent backgrounds
• Building annotation tools with point or box selection
• Generating object masks automatically

Turn method notes or figure descriptions into academic architecture and concept illustrations. Claude plans and reviews the layout, while a local Codex bridge generates images, with refinement rounds and final PNG, LaTeX snippet, and review records.

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• Illustrating a model architecture for a paper
• Turning method notes into a workflow diagram
• Creating concept or comparison figures

Create masks that identify object regions in images using points, boxes, or existing masks. The skill guides automatic mask generation, transparent-background extraction, annotation workflows, and deployment, without requiring training for each specific task.

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• Extracting objects with transparent backgrounds
• Building annotation tools with point and box selection
• Generating object masks automatically

Generate and edit transparent PNG ornaments, game sprites, emblems, and interface graphics with built-in Codex image generation. Includes transparency checks, saved prompts, and optional integration into an existing project with verified asset copies.

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• Create transparent PNG decorations for game interfaces
• Generate standalone sprites and emblems
• Check PNG transparency and gaps within artwork

Build chat, image generation, and speech transcription features on 0G Compute Network, a distributed GPU marketplace. This skill guides SDK integration, model fine-tuning, response processing for billing, and account funding through code patterns and CLI commands.

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• Integrating chat and image generation into an application
• Preparing model fine-tuning jobs
• Checking balances and funding provider accounts

Create 2D game art from code, including sprites, icons, tiles and backgrounds. The skill renders written specifications, checks palettes and tile seams, and packages images with review sheets without using an image model.

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• Create pixel sprites with palette variants
• Draw UI elements and icons in SVG
• Build terrain tiles with checked seams

Generate videos from text or images, edit existing clips, and extend scenes with Gemini Omni 1.1 Flash. Includes scripts for preparing source footage, regenerating audio, refining previous results, and processing multiple video jobs.

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• Generate a short video from text or a still image
• Create a transition between two images
• Change a video's style or regenerate its audio

Use pre-trained models with Hugging Face Transformers for text generation, translation, image recognition, and speech tasks. Load models, prepare inputs, run predictions, and fine-tune them, meaning further training with your own data.

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• Prototyping text classification, summarization, or translation
• Building image recognition or speech recognition workflows
• Adjusting text generation settings

Generate or edit images via Nano Banana image models. Triggers on "generate image", "image generation", "nano banana", "edit image", "nano banana pro", "nano banana 2"

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Seedance 2.0 video & image generation via LibTV Gateway - AI text-to-video, image-to-video, video continuation, style transfer, and text-to-image using Seedance 2.0 model. Also supports Kling 3.0, Wan 2.6, Midjourney, Seedream 5.0. Trigger phrases: seedance, generate video, make a video, generate image, make an image, draw, libtv, liblib.

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All-in-one image generation with Gemini models. Supports Nano Banana (3.1 Flash), Nano Banana Pro (3 Pro), and Nano Banana 2 (2.5 Flash). Triggers on "generate image", "image generation", "nano banana", "edit image".

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AI image generation via Fal.ai, gpt-image-2, nano-banana, MiniMax image-01, and xAI Grok Imagine. Use when the user wants to generate or create an image / picture / still.

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Google Gemini media generation: Nano Banana images, Imagen 4 images, Veo video, TTS, model listing. Trigger phrases: gemini image, nano banana, imagen, veo video, google veo, gemini tts.

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Recreate a static graphic ad (Pinterest pin, IG/FB feed image, poster) from a reference image, swapping in a new brand's product and new copy while keeping the reference's layout, composition, and visual energy. ALWAYS generated with GPT Image 2 in edit-the-reference mode (fal-ai/gpt-image-1/edit-image, a billed FAL generation); the HTML/goose-graphics overlay is only an optional text-finishing step, never the generator. The static-graphics counterpart to the video remix-ad skill; this is what the app calls when a user picks a reference ad and wants it for their own product.

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Creates MATLAB interfaces to Python image processing and computer vision models from GitHub repositories or pip-installable packages using MPyReq. Use when asked to interface MATLAB with a Python CV/image model (segmentation, depth estimation, object detection, image generation, super-resolution, etc.), given a GitHub repo URL for an image/vision model, or asked to create an MPyReq demo for a deep-learning vision pipeline. Do NOT use for general-purpose Python-MATLAB interfacing, non-vision models (NLP, tabular, audio), model deployment/serving, or MATLAB-only image processing workflows.

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Generate AI images using Volcengine Seedream model. Supports text-to-image (T2I), image editing (I2I), multi-image fusion, and web-search-based generation. Use this skill when the user wants to create, generate, or edit images.

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Standalone multi-agent image generation skill for Hermes. Includes an internal design compiler, GPT-Image-2 generation via apimart.ai, case library reuse, interactive reference selection, batch workflows, and style-consistent series generation.

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Analyze user-provided reference images and reverse-engineer high-fidelity AI image-generation prompts. Use when the user asks to recreate, imitate, reverse-engineer, or extract prompts from photographs, illustrations, 3D renders, products, characters, landscapes, typography, logos, posters, or other visual references. Do not use for requests that only require OCR or an ordinary image description.

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