Add 3D body scanning to your product with one API call.

const SNAPMEASURE_ENDPOINT = "https://…";   // issued at onboarding
const PARTNER_CODE = "your-partner-code";

// Shrink a photo (File or Blob) to 800 px and return it as base64 text
async function toBase64(file, maxSide = 800) {
  const img = await createImageBitmap(file);
  const scale = Math.min(1, maxSide / Math.max(img.width, img.height));
  const canvas = Object.assign(document.createElement("canvas"), {
    width: Math.round(img.width * scale), height: Math.round(img.height * scale),
  });
  canvas.getContext("2d").drawImage(img, 0, 0, canvas.width, canvas.height);
  return canvas.toDataURL("image/jpeg", 0.94).split(",")[1];
}

// frontFile, sideFile: File or Blob objects from your own capture or upload UI,
// e.g. document.querySelector("#front-photo").files[0]
const res = await fetch(SNAPMEASURE_ENDPOINT, {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    height: "174cm",                       // or "68in"
    company: PARTNER_CODE,
    images: [
      { fileName: "front.jpg", data: await toBase64(frontFile) },
      { fileName: "side.jpg",  data: await toBase64(sideFile) },
    ],
  }),
});
if (!res.ok) throw new Error(await res.text());
const result = await res.json();
console.log(result.measurements["waist circumference"]);   // 88.6 (cm)

import base64, requests

SNAPMEASURE_ENDPOINT = "https://…"   # issued at onboarding
PARTNER_CODE = "your-partner-code"

def to_base64(image_bytes):
    # The raw bytes of a JPEG or PNG, as base64 text
    return base64.b64encode(image_bytes).decode("ascii")

# Photo bytes can come from anywhere: your upload handler, S3, a database, or disk
with open("front.jpg", "rb") as f:
    front = f.read()
with open("side.jpg", "rb") as f:
    side = f.read()

payload = {
    "height": "174cm",                  # or "68in"
    "company": PARTNER_CODE,
    "images": [
        {"fileName": "front.jpg", "data": to_base64(front)},
        {"fileName": "side.jpg",  "data": to_base64(side)},
    ],
}

res = requests.post(SNAPMEASURE_ENDPOINT, json=payload, timeout=60)
res.raise_for_status()
result = res.json()
print(result["measurements"]["waist circumference"])   # 88.6 (cm)

# Base64-encode each photo onto one line, then build the JSON body
FRONT=$(base64 < front.jpg | tr -d '\n')
SIDE=$(base64 < side.jpg | tr -d '\n')
printf '{"height":"174cm","company":"%s","images":[{"fileName":"front.jpg","data":"%s"},{"fileName":"side.jpg","data":"%s"}]}' \
  "$PARTNER_CODE" "$FRONT" "$SIDE" > scan.json

curl -X POST "$SNAPMEASURE_ENDPOINT" \
  -H "Content-Type: application/json" \
  --max-time 60 \
  -d @scan.json