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Content Moderator Image

wavespeed-ai /

Image Content Moderator provides automated image moderation to detect and flag policy-violating or inappropriate images for automation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

content-moderation
इनपुट

निष्क्रिय

$0.001प्रति रन·~1000 / $1

संबंधित मॉडल

README

Content Moderator — Image

Ensure your images meet safety and compliance standards with WaveSpeed AI's Content Moderator. This fast, affordable moderation tool analyzes images for policy violations, inappropriate content, and safety concerns — essential for platforms, applications, and workflows that handle user-generated content.

Why It Works Well

  • Fast analysis: Quick moderation results for high-volume workflows.
  • Comprehensive detection: Identifies various types of inappropriate or unsafe content.
  • Text context support: Optionally include associated text for more accurate moderation decisions.
  • Ultra-affordable: At just $0.001 per image, scale moderation without breaking the budget.
  • Simple integration: Minimal parameters make it easy to add to any pipeline.

Parameters

ParameterRequiredDescription
imageYesImage to moderate (upload or public URL).
textNoOptional associated text for additional context in moderation.

How to Use

  1. Upload your image — drag and drop or paste a public URL.
  2. Add text context (optional) — include any associated text that should be considered.
  3. Run — click the button to analyze.
  4. Review results — check the moderation output for any flagged content.

Pricing

Flat rate per moderation request.

OutputCost
Per image$0.001

Best Use Cases

  • User-Generated Content — Screen uploads before publishing to your platform.
  • Social Media & Communities — Maintain safe spaces by filtering inappropriate images.
  • E-commerce — Ensure product listings meet marketplace content policies.
  • Content Pipelines — Add automated safety checks to media processing workflows.
  • AI Output Screening — Verify generated images comply with safety guidelines before delivery.

Pro Tips for Best Results

  • Include associated text when available — it helps provide context for more accurate moderation.
  • Use in automated pipelines for consistent, scalable content screening.
  • Combine with human review for edge cases or appeals.
  • Set up batch processing for high-volume moderation needs.
  • If using URLs, ensure they are publicly accessible for successful analysis.

Notes

  • If using a URL for the image, ensure it is publicly accessible.
  • Moderation results should be used as guidance — consider human review for borderline cases.
  • Processing is typically very fast, suitable for real-time moderation workflows.
  • The text field can provide valuable context for images with ambiguous content.
नोट:यह वेबसाइट तृतीय पक्षों द्वारा प्रदान किए गए AI मॉडलों का उपयोग करती है।

Content Moderator Image API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/content-moderator/image 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 Content Moderator Image below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "text": "A clear example input"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/content-moderator/image" \
  -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/content-moderator/image";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "text": "A clear example input"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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 = {
    "text": "A clear example input"
}

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/content-moderator/image", 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)

Content Moderator Image API — Frequently asked questions

What is the Content Moderator Image API?

Content Moderator Image is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. Image Content Moderator provides automated image moderation to detect and flag policy-violating or inappropriate images for automation. 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 Content Moderator Image 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/content-moderator-image.

How much does Content Moderator Image cost per run?

Content Moderator Image 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 Content Moderator Image accept?

Key inputs: `image`, `enable_sync_mode`, `text`. 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/content-moderator-image.

How long does Content Moderator Image take to generate?

Median end-to-end generation time on WaveSpeedAI is around 2 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 Content Moderator Image 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.

Content Moderator Image | AI Content Moderation API | WaveSpeedAI