Per-pixel depthfrom a single image — no stereo camera needed.

import os, base64, requests
from pathlib import Path

resp = requests.post(
    "https://api.msightflow.ai/v1/depth",
    headers={"Authorization": f"Bearer {os.environ['MSF_API_KEY']}"},
    files={"image": Path("scene.jpg").read_bytes()},
)
result = resp.json()

# Save the colourised depth map
Path("depth.png").write_bytes(base64.b64decode(result["depth_map"]))

# On Pro tier, raw float32 depth is also returned
# import numpy as np
# arr = np.frombuffer(base64.b64decode(result["raw_depth"]), dtype=np.float32)

import fetch from "node-fetch";
import FormData from "form-data";
import fs from "fs";

const form = new FormData();
form.append("image", fs.createReadStream("scene.jpg"));

const resp = await fetch("https://api.msightflow.ai/v1/depth", {
  method: "POST",
  headers: { Authorization: `Bearer ${process.env.MSF_API_KEY}` },
  body: form,
});
const { depth_map } = await resp.json();
fs.writeFileSync("depth.png", Buffer.from(depth_map, "base64"));

curl -X POST https://api.msightflow.ai/v1/depth \
  -H "Authorization: Bearer $MSF_API_KEY" \
  -F "image=@scene.jpg" \
  --output depth-response.json

# Depth + SAM = per-object depth statistics.
import json, base64, numpy as np
from PIL import Image
import io

# 1. Get depth map
depth_resp = requests.post(api + "/depth", headers=hdr, files={"image": img}).json()
depth = np.array(Image.open(io.BytesIO(base64.b64decode(depth_resp["depth_map"]))).convert("L"))

# 2. Get object mask via SAM
seg_resp = requests.post(api + "/interactive_segment", headers=hdr,
    files={"image": img}, data={"points": '[{"x":320,"y":240,"label":1}]'}).json()
mask = np.array(Image.open(io.BytesIO(base64.b64decode(seg_resp["mask"]))).convert("L")) > 127

# 3. Object depth statistics
obj_depth = depth[mask]
print(f"object median depth: {np.median(obj_depth)}, std: {np.std(obj_depth):.1f}")