Evidence row 124187

What was observed

{
  "endpoints": [
    [
      "x402",
      "https://workbot1.oddsys.org/detect"
    ]
  ],
  "name": "Busker Object Detection",
  "owner_address": "0x15459498e1191d8787c83177809bd54022fa18c4",
  "raw": {
    "accepts": [
      {
        "amount": "10000",
        "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
        "extra": {
          "name": "USD Coin",
          "version": "2"
        },
        "maxTimeoutSeconds": 300,
        "network": "eip155:8453",
        "payTo": "0x15459498e1191d8787c83177809bd54022fA18c4",
        "scheme": "exact"
      }
    ],
    "description": "Detect and locate objects in an image (YOLOX-nano, COCO classes): people, pets (dog/cat/horse), vehicles, and 70+ more. Returns per-class counts and pixel bounding boxes. Detection only — no identification. Best on clear, medium-to-large objects.",
    "extensions": {
      "bazaar": {
        "info": {
          "input": {
            "body": {
              "classes": [
                "person"
              ],
              "imageBase64": "iVBORw0KGgoAAAANSUhEUgAAAAgAAAAICAAAAADhZOFXAAAADklEQVR42mNogAIGyhgAgIQgARDoahcAAAAASUVORK5CYII=",
              "minConfidence": 0.4
            },
            "bodyType": "json",
            "method": "POST",
            "type": "http"
          },
          "output": {
            "body": {
              "counts": "object (class -> count)",
              "meta": {
                "height": "number",
                "inferenceMs": "number",
                "model": "string",
                "width": "number"
              },
              "objects": "array of { class, confidence, box: {x, y, width, height} } in source pixels"
            },
            "bodyType": "json",
            "example": {
              "counts": {
                "dog": 1,
                "person": 2
              },
              "meta": {
                "classesFilter": null,
                "height": 1080,
                "inferenceMs": 1450,
                "inputBytes": 348211,
                "minConfidence": 0.4,
                "model": "yolox-nano",
                "width": 1920
              },
              "objects": [
                {
                  "box": {
                    "height": 388,
                    "width": 143,
                    "x": 412,
                    "y": 108
                  },
                  "class": "person",
                  "confidence": 0.87
                },
                {
                  "box": {
                    "height": 371,
                    "width": 130,
                    "x": 655,
                    "y": 121
                  },
                  "class": "person",
                  "confidence": 0.81
                },
                {
                  "box": {
                    "height": 160,
                    "width": 180,
                    "x": 220,
                    "y": 340
                  },
                  "class": "dog",
                  "confidence": 0.63
                }
              ]
            }
          }
        },
        "routeTemplate": "/detect",
        "schema": {
          "properties": {
            "input": {
              "additionalProperties": false,
              "properties": {
                "body": {
                  "additionalProperties": false,
                  "properties": {
                    "classes": {
                      "description": "Restrict results to these COCO class names (e.g. person, dog, cat, horse, car, bus, truck, motorcycle, bicycle). Omit for all 80 classes.",
                      "items": {
                        "type": "string"
                      },
                      "type": "array"
                    },
                    "imageBase64": {
                      "description": "Base64-encoded image (png/jpeg/webp).",
                      "type": "string"
                    },
                    "minConfidence": {
                      "description": "Score threshold 0.05-0.95 (default 0.4).",
                      "type": "number"
                    }
                  },
                  "required": [
                    "imageBase64"
                  ],
                  "type": "object"
                },
                "bodyType": {
                  "enum": [
                    "json"
                  ],
                  "type": "string"
                },
                "method": {
                  "enum": [
                    "POST"
                  ],
                  "type": "string"
                },
                "type": {
                  "const": "http",
                  "type": "string"
                }
              },
              "required": [
                "type",
                "method",
                "bodyType",
                "body"
              ],
              "type": "object"
            }
          }
        }
      }
    },
    "lastUpdated": "2026-10-11T17:25:36.152Z",
    "quality": {
      "l30DaysTotalCalls": 2,
      "l30DaysUniquePayers": 2,
      "lastCalledAt": "2026-10-11T17:25:34.095Z"
    },
    "resource": "https://workbot1.oddsys.org/detect",
    "serviceName": "Busker Object Detection",
    "tags": [
      "detection",
      "vision",
      "image",
      "people",
      "vehicles"
    ],
    "type": "http",
    "x402Version": 2
  },
  "source": "x402_bazaar",
  "summary": "Detect and locate objects in an image (YOLOX-nano, COCO classes): people, pets (dog/cat/horse), vehicles, and 70+ more. Returns per-class counts and pixel bounding boxes. Detection only — no identification. Best on clear, medium-to-large objects."
}

What the leaf hashes

{"body":"9a06b34a5d2fece6294a1a99945632e18babd0a3bdb37b34cfe6483b6a4386d1","id":124187,"kind":"listing","method":"baseline/1","observed_us":1793025624324412,"prev":null,"subject":"x402_bazaar:https://workbot1.oddsys.org/detect","subject_kind":"source_record"}

Proof

Its day has not closed yet. A day closes ten minutes after midnight UTC; the proof appears here then.