# Tanod imagepeek – Perceptual Hash > Tanod imagepeek – Perceptual Hash is a paid API for AI agents from tanod.dev, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-11). Computes perceptual hashes (aHash, dHash, pHash, wHash) for one image and optionally compares them against a second image to return Hamming distances. ## Facts - Endpoint: POST https://tanod.dev/v1/image/hash?utm_source=zero.xyz - Price: $0.002/call - Payment: x402 - Status: unknown - Last checked: 2026-10-11 - Activations on Zero: 0 - Tags: x402 - Canonical page: https://www.zero.xyz/c/tanod-imagepeek-perceptual-hash-d06122e7 - Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_cjy_GWYwxhUtPKpuaLzu_ Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently. ## How to call it through Zero Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`): ```sh zero fetch --capability tanod-imagepeek-perceptual-hash-d06122e7 -d '' ``` Example prompt: Can you compute the perceptual hashes (aHash, dHash, pHash, and wHash) for this image — https://example.com/photo.jpg — and also compare it against https://example.com/photo2.jpg to see how similar they are? ## When to prefer this Use this endpoint when you need fast, lightweight image similarity detection or deduplication without full ML-based embedding models. It is ideal for near-duplicate detection, tamper/crop detection, or building image fingerprint databases. Prefer it over pixel-diff tools when images may be resized, color-shifted, or slightly cropped, since perceptual hashes are robust to those transformations. Choose it over heavy vision APIs when cost and latency matter and exact pixel fidelity is not required. ## Known failure modes - Image URL is unreachable or returns non-200 — endpoint cannot fetch the image - Image exceeds 10 MB size limit — rejected with size error - Invalid or unsupported image format — decoding failure - Base64 payload is malformed or exceeds character limit — parse error - No image provided (both url and image_base64 are null) — validation error - Compare image also fails to load or decode — comparison skipped or error returned ## How this service works One MCP server and HTTP API with 193 pay-per-call tools for AI agents (security checks, chain data, finance, aviation, documents), plus free uptime and MikroTik monitoring and 130+ free browser tools. No signup; free daily tier. Operated by an AI. ## Output Returns one or more perceptual hash values (aHash, dHash, pHash, wHash) as hex strings for the input image. When a second comparison image is provided, also returns pairwise Hamming distances between each hash, indicating the degree of visual similarity (lower distance = more similar). ## Request schema (JSON Schema) ```json { "type": "object", "properties": { "url": { "anyOf": [ { "type": "string", "maxLength": 2048 }, { "type": "null" } ], "default": null, "description": "Public http(s) URL of the image (at most 10 MB; private, internal and IP-literal hosts are refused); or use image_base64." }, "hash_size": { "enum": [ 8, 16 ], "type": "integer", "default": 8, "description": "Hash grid: 8 (64-bit hashes, default) or 16 (256-bit)." }, "algorithms": { "anyOf": [ { "type": "array", "items": { "enum": [ "ahash", "dhash", "phash", "whash" ], "type": "string" }, "maxItems": 4, "minItems": 1 }, { "type": "null" } ], "default": null, "description": "Default: all four." }, "auto_orient": { "type": "boolean", "default": true, "description": "Apply the EXIF orientation first (default true)." }, "compare_url": { "anyOf": [ { "type": "string", "maxLength": 2048 }, { "type": "null" } ], "default": null, "description": "A second image to compare (or compare_base64)." }, "image_base64": { "anyOf": [ { "type": "string", "maxLength": 13333464 }, { "type": "null" } ], "default": null, "description": "The image as standard or url-safe base64 (at most 10 MB decoded; a data:image/...;base64, prefix is fine); or use url." }, "compare_base64": { "anyOf": [ { "type": "string", "maxLength": 13333464 }, { "type": "null" } ], "default": null, "description": "A second image as base64 (at most 10 MB decoded; or compare_url)." } } } ``` ## Response schema (JSON Schema) ```json { "type": "json", "example": { "bits": 64, "input": { "bytes": 161713, "width": 640, "format": "jpeg", "frames": 1, "height": 480, "animated": false, "has_alpha": false }, "notes": [], "hashes": { "ahash": "fcffffb310160040", "dhash": "313c1d66e2e4e595", "phash": "cedbd88c49eaf808", "whash": "fcfffff310340000" }, "source": { "url": "https://python-pillow.org", "library": "Pillow", "license": "MIT-CMU (HPND)" }, "compare": { "input": { "bytes": 159137, "width": 640, "format": "jpeg", "frames": 1, "height": 480, "animated": false, "has_alpha": false }, "hashes": { "ahash": "e4fae8c01e0e0000", "dhash": "0c168a9174dce2be", "phash": "f1f136161a62d393", "whash": "eefaf8d03e1e1202" }, "distance": { "ahash": 19, "dhash": 34, "phash": 34, "whash": 20 }, "final_url": "https://raw.githubusercontent.com/ianare/exif-samples/master/jpg/gps/DSCN0012.jpg", "similarity": { "ahash": 0.7031, "dhash": 0.4688, "phash": 0.4688, "whash": 0.6875 }, "source_url": "https://raw.githubusercontent.com/ianare/exif-samples/master/jpg/gps/DSCN0012.jpg", "likely_same": false }, "final_url": "https://raw.githubusercontent.com/ianare/exif-samples/master/jpg/gps/DSCN0010.jpg", "operation": "hash", "source_url": "https://raw.githubusercontent.com/ianare/exif-samples/master/jpg/gps/DSCN0010.jpg" } } ``` ## More - Live health (JSON, refreshed every minute): https://www.zero.xyz/c/tanod-imagepeek-perceptual-hash-d06122e7/health.json - [Zero catalog index](https://www.zero.xyz/llms.txt) - [Other services from tanod.dev](https://www.zero.xyz/host/tanod.dev/llms.txt)