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Moondream3 Preview Point

wavespeed-ai /

Moondream3 Point finds objects in images and returns precise coordinate points for computer vision tasks, enabling accurate point localization. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-text
Eingabe

Bereit

{
  "answer": "The woman is wearing a pink baseball cap with a strap across her forehead. She is also wearing large silver hoop earrings and a pink fuzzy sweater. Her blonde hair is styled in loose waves, and she has her tongue sticking out slightly while looking directly at the camera. Behind her, there are several posters visible, including one with a pink background and an image of a cup."
}

$0.001pro Durchlauf·~1000 / $1

Weiter:

BeispieleAlle anzeigen

hat

person

wall

picture

mirror

person

castle

ice-cream

flower

Ähnliche Modelle

README

Moondream 3 — Point (Locate & Describe)

Moondream 3 Point is a vision-language model designed to identify and describe specific objects within an image using natural language. Instead of returning coordinates, it provides a concise textual description of the detected object, making it ideal for lightweight interactive queries and content understanding.

✨ Key Features

  • Locate and Describe Objects Enter a short text query (e.g., “hat”, “watch”, “phone”) and receive a natural-language description of that item in context.

  • Fast Single-Object Queries Optimized for fast, low-latency inference — perfect for real-time applications.

  • Readable Natural Output The model outputs a fluent English sentence describing the object’s appearance, position, and context.

  • Multilingual Understanding Capable of recognizing and describing objects in a wide range of visual scenarios.

⚙️ Example Usage

Locate & Describe “Hat”

{
 "image": "https://example.com/photo.jpg",
 "prompt": "hat"
}

Example Response

{
 "answer": "The woman is wearing a pink baseball cap with a strap across her forehead. She is also wearing large silver hoop earrings and a pink fuzzy sweater."
}

💡 Best Practices

  • Use concise object names (e.g., “hat”, “car”, “tree”) for more accurate detection.

  • For precise bounding boxes or coordinates, use:

  • Moondream 3 Detect — returns x_min, y_min, x_max, y_max bounding boxes.

  • A coordinate-enabled version of Moondream 3 Point (coming soon).

  • Supported formats: JPEG, PNG, WebP

  • Maximum image size: 10 MB

💰 Pricing

  • $0.001 per request
  • Volume and enterprise pricing available upon request.

📝 Notes

  • The current endpoint returns descriptive text in JSON format:
{"answer": "..."}

— it does not output coordinates.

  • For small or occluded objects, use higher-resolution input or switch to the Detect model for better spatial precision.
Hinweis:Diese Website nutzt KI-Modelle von Drittanbietern.

Moondream3 Preview Point API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/moondream3-preview/point with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Moondream3 Preview Point below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/moondream3-preview/point" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/moondream3-preview/point";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/moondream3-preview/point", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Moondream3 Preview Point API — Frequently asked questions

What is the Moondream3 Preview Point API?

Moondream3 Preview Point is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. Moondream3 Point finds objects in images and returns precise coordinate points for computer vision tasks, enabling accurate point localization. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Moondream3 Preview Point API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/moondream3-preview-point.

How much does Moondream3 Preview Point cost per run?

Moondream3 Preview Point starts at $0.001 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Moondream3 Preview Point accept?

Key inputs: `prompt`, `image`, `enable_sync_mode`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/moondream3-preview-point.

How long does Moondream3 Preview Point take to generate?

Median end-to-end generation time on WaveSpeedAI is around 4 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Moondream3 Preview Point outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Moondream3 Preview Point | AI Image Understanding API | WaveSpeedAI