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Analyze images using Gemini's vision capabilities for OCR, UI analysis, and visual understanding. \n \n Supports PNG, JPEG, GIF, and WebP images including screenshots, diagrams, charts, and code snippets \n Built-in analysis templates for common tasks: text extraction, code recovery, UI/UX feedback, error diagnosis, and data extraction from charts \n Handles single and multiple image comparisons in a single request \n Requires Google Generative AI library and valid GEMINI_API_KEY environment var

Enhance image resolution, sharpness, and clarity for professional-quality output. \n \n Analyzes and improves resolution, sharpness, and compression artifacts; intelligently upscales images while reducing noise \n Supports batch processing of entire directories and preserves original files automatically \n Optimizes output based on intended use case: web, print, social media, or presentations \n Works best with screenshots and digital images; accepts PNG and JPG formats with configurable output

Unified access to 8 AI image generation models with automatic model selection and zero API key setup. \n \n Supports Midjourney, Flux (Pro/Dev/Schnell), Ideogram, Recraft, SDXL, and Nano Banana with automatic model routing based on user intent \n Handles Midjourney's async polling transparently; all models return consistent output format with image URLs \n Includes Midjourney actions (upscale, variation, reroll) and reference image support for style consistency \n All requests routed through hos

Generate high-quality images via Gemini models with structured prompts, aspect ratios, and brand validation. \n \n Supports multiple Gemini models (gemini-3-pro-image, gemini-2.5-flash-image, gemini-2.5-pro-image) optimized for different quality and speed tradeoffs \n Enforces structured prompt format covering subject, style, lighting, mood, composition, aspect ratio, and brand colors to ensure consistent outputs \n Includes validation workflows across multiple agents for prompt completeness, st

Fast, optimized image generation with Pruna's P-Image models via inference.sh CLI. \n \n Four model variants: P-Image for text-to-image, P-Image-LoRA with 11 preset styles, P-Image-Edit for image editing, and P-Image-Edit-LoRA for stylized edits \n Supports multiple aspect ratios (1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, custom) and multi-image compositing for collages and combinations \n Requires inference.sh CLI ( infsh ) and login; run models via infsh app run pruna/[model-name] with JSON input p

Generate customizable article cover images across 5 independent dimensions and 3 aspect ratios. \n \n Combines 6 image types (hero, conceptual, typography, metaphor, scene, minimal) with 10 color palettes and 7 rendering styles for fine-grained visual control \n Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects, plus additional ratios (4:3, 3:2, 3:4) \n Auto-analyzes article content to recommend dimensions, or accepts explicit flags for type, palette, rendering, text level

Category: test

Generate images with Alibaba Qwen-Image-2.0-Pro via inference.sh CLI. Best for professional text rendering and complex designs.

Convert ```mermaid code blocks in Markdown (or other text) files into PNG images, and replace the code blocks with image references. Useful for platforms that don't render Mermaid natively (GitHub Pages/Jekyll, Dev.to, etc.).

Create social sharing images (Open Graph) via inference.sh CLI.