Satellite Land Cover

import { readFile } from "node:fs/promises";
import { DecisionMachine } from "@cloudraker/milliseconds";

// Run on your server; reads MS_API_KEY from the environment.
// The image carries the input; the leading text is optional context.
const dm = new DecisionMachine();

const { result, usage } = await dm.classify(
  await readFile("image.jpg"),
  {
    "Annual crop": "Satellite view of cultivated annual-crop fields: geometric agricultural parcels, often bare brown or muted green, with field boundaries.",
    "Forest": "Satellite view dominated by dense continuous tree canopy, with mottled dark green texture and few large open fields or buildings.",
    "Herbaceous vegetation": "Satellite view of natural low-growing grasses and shrubs, with irregular vegetation texture rather than uniform planted rows or dense forest.",
    "Highway": "Satellite view containing a prominent wide road or highway corridor, often with parallel lanes, interchanges or long straight pavement.",
    "Industrial": "Satellite view of large industrial roofs, warehouses, paved yards and broad roads, with larger buildings than a residential neighborhood.",
    "Pasture": "Satellite view of grassy grazing land: green open fields separated by hedges or boundaries, without dense tree cover or strong crop-row texture.",
    "Permanent crop": "Satellite view of orchards, vineyards or other long-lived crops: repeated planted rows or regular patterns within agricultural parcels.",
    "Residential": "Satellite view of a neighborhood with many small building roofs and streets, often interspersed with trees and gardens.",
    "River": "Satellite view of a long narrow or winding water channel with visible land along its banks.",
    "Sea or lake": "Satellite view dominated by a broad expanse of open water, generally smooth dark blue or blue-green, with few visible land features."
  },
  { detail: "low" }
).withUsage();

console.log(result);
console.log({ inputTokens: usage.inputTokens, modelMs: usage.inferenceMs });

from pathlib import Path
from milliseconds import DecisionMachine

# Reads MS_API_KEY from the environment.
# The image carries the input; the leading text is optional context.
dm = DecisionMachine()

result = dm.classify(
    Path("image.jpg").read_bytes(),
    {
      "Annual crop": "Satellite view of cultivated annual-crop fields: geometric agricultural parcels, often bare brown or muted green, with field boundaries.",
      "Forest": "Satellite view dominated by dense continuous tree canopy, with mottled dark green texture and few large open fields or buildings.",
      "Herbaceous vegetation": "Satellite view of natural low-growing grasses and shrubs, with irregular vegetation texture rather than uniform planted rows or dense forest.",
      "Highway": "Satellite view containing a prominent wide road or highway corridor, often with parallel lanes, interchanges or long straight pavement.",
      "Industrial": "Satellite view of large industrial roofs, warehouses, paved yards and broad roads, with larger buildings than a residential neighborhood.",
      "Pasture": "Satellite view of grassy grazing land: green open fields separated by hedges or boundaries, without dense tree cover or strong crop-row texture.",
      "Permanent crop": "Satellite view of orchards, vineyards or other long-lived crops: repeated planted rows or regular patterns within agricultural parcels.",
      "Residential": "Satellite view of a neighborhood with many small building roofs and streets, often interspersed with trees and gardens.",
      "River": "Satellite view of a long narrow or winding water channel with visible land along its banks.",
      "Sea or lake": "Satellite view dominated by a broad expanse of open water, generally smooth dark blue or blue-green, with few visible land features."
    },
    detail="low"
)

print(result)

# Reads MS_API_KEY. The image and the other fields are read from disk.
cat > classify-labels.json <<'DM1_LABELS'
{
  "Annual crop": "Satellite view of cultivated annual-crop fields: geometric agricultural parcels, often bare brown or muted green, with field boundaries.",
  "Forest": "Satellite view dominated by dense continuous tree canopy, with mottled dark green texture and few large open fields or buildings.",
  "Herbaceous vegetation": "Satellite view of natural low-growing grasses and shrubs, with irregular vegetation texture rather than uniform planted rows or dense forest.",
  "Highway": "Satellite view containing a prominent wide road or highway corridor, often with parallel lanes, interchanges or long straight pavement.",
  "Industrial": "Satellite view of large industrial roofs, warehouses, paved yards and broad roads, with larger buildings than a residential neighborhood.",
  "Pasture": "Satellite view of grassy grazing land: green open fields separated by hedges or boundaries, without dense tree cover or strong crop-row texture.",
  "Permanent crop": "Satellite view of orchards, vineyards or other long-lived crops: repeated planted rows or regular patterns within agricultural parcels.",
  "Residential": "Satellite view of a neighborhood with many small building roofs and streets, often interspersed with trees and gardens.",
  "River": "Satellite view of a long narrow or winding water channel with visible land along its banks.",
  "Sea or lake": "Satellite view dominated by a broad expanse of open water, generally smooth dark blue or blue-green, with few visible land features."
}
DM1_LABELS

dm1 classify --image image.jpg --detail low --labels @classify-labels.json --json --usage