{"uid":"cap_EjO1K6ZF1lF8jS52eJ2_E","slug":"sar-image-connected-component-extractor-c47fd272","name":"SAR Image Connected Component Extractor","description":"Treats cells at or above a caller threshold as foreground, labels four-neighbor connected components, and reports area, bounding box, peak, and mean value. It does not ingest imagery, calibrate backscatter, remove speckle, geolocate pixels, classify objects, or infer real-world meaning.","url":"https://space.halowerk.com/v1/sar-image-extract","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"grid":{"type":"array","items":{"type":"array","items":{"type":"number","maximum":1000000000000,"minimum":-1000000000000,"description":"Numeric cell value in a caller-defined unit."},"maxItems":128,"minItems":1},"maxItems":128,"minItems":1},"threshold":{"type":"number","maximum":1000000000000,"minimum":-1000000000000},"pixel_area_m2":{"type":"number","maximum":1000000000000,"minimum":0.000001},"minimum_component_pixels":{"type":"integer","maximum":16384,"minimum":1}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.004","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.004/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.004","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.004","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_D2gMolNfzxyq8sVXz_jWr","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.004","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Labels four-neighbor connected components in a 2-D numeric grid above a caller-defined threshold, returning area, bounding box, peak, and mean value for each component.","exampleAgentPrompt":"Take this 64×64 SAR backscatter grid and find all connected foreground regions above a threshold of 150, using a pixel area of 100 square meters and ignoring any components smaller than 5 pixels — give me the area, bounding box, peak, and mean for each one.","exampleUseCases":[{"title":"Detect ship-sized objects in SAR scene","prompt":"I have a 128×128 SAR intensity grid and want to find all connected clusters of pixels above a backscatter threshold of 200, with each pixel covering 25 square meters — only keep components of at least 10 pixels and tell me the bounding box and area of each detected object."},{"title":"Measure flood extent from radar grid","prompt":"Here's a 100×100 numeric grid of radar return values from a flood mapping pass. Set the foreground threshold to 80, pixel area to 400 square meters, and a minimum size of 3 pixels — I need the area and mean value of each flooded region."},{"title":"Extract bright anomaly clusters for change detection","prompt":"Run connected component analysis on this 64×64 backscatter difference grid with a threshold of 50 and pixel area of 900 square meters, ignoring blobs smaller than 2 pixels, so I can see where significant changes occurred and how large each anomaly cluster is."}],"resultDescription":"A list of detected foreground connected components, each with: pixel count (area), bounding box coordinates, peak cell value, and mean cell value across the component. Components below the minimum pixel threshold are excluded.","failureModes":["Grid dimensions exceed 128×128 limit — request rejected","Threshold set so high no foreground pixels exist — empty component list returned","Minimum component pixel size filters out all detected regions — empty result","Grid contains non-numeric or out-of-range values — validation error","Malformed grid (ragged rows, non-array types) — schema validation failure"],"whenToPreferThis":"Use this endpoint when you have a raw 2-D numeric grid (e.g. SAR backscatter, difference images, or any raster) and need fast connected-component labeling with per-component statistics. It is ideal for detecting and measuring discrete foreground blobs by threshold without needing image ingestion, geolocation, speckle filtering, or object classification — those must be handled upstream or downstream.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T12:32:57.879Z","isFirstParty":false}