POST /v1/enhance

Image Enhance API

Improve image quality with auto-enhance, denoise, sharpening, white balance, and basic upscaling.

Opérations clés

auto_enhance

denoise

deblur_basic

sharpen

upscale_basic

fix_dark_photo

fix_overexposed_photo

white_balance

Cas d’utilisation

Low-quality image cleanup
Commerce photo polishing
Import pipeline normalization

Cycle de vie de la tâche async

Tous les endpoints de traitement ImageHQ sont asynchrones. Après un POST réussi, vous recevez une réponse 202 Acceptedavec un job_id. Interrogez l’endpoint de statut jusqu’à ce que l’état atteigne succeeded.

Exemple de requête

import requests

url = "https://api.imagehq.io/v1/enhance"
payload = {
  "operation": "auto_enhance",
  "options": {
    "preserve_natural_tones": True,
    "strength": 0.7
  },
  "tool_slug": "auto-enhance"
}
files = [("files[]", open("image.png", "rb"))]
data = {"request": json.dumps(payload)}

response = requests.post(url, files=files, data=data)
print(response.json())

const form = new FormData();
form.append("files[]", file);
form.append("request", JSON.stringify({
  "operation": "auto_enhance",
  "options": {
    "preserve_natural_tones": true,
    "strength": 0.7
  },
  "tool_slug": "auto-enhance"
}));

const response = await fetch("https://api.imagehq.io/v1/enhance", {
  method: "POST",
  headers: { "Idempotency-Key": crypto.randomUUID() },
  body: form
});

const data = await response.json();
console.log(data);

const form = new FormData();
form.append("files[]", file);
form.append("request", JSON.stringify({
  "operation": "auto_enhance",
  "options": {
    "preserve_natural_tones": true,
    "strength": 0.7
  },
  "tool_slug": "auto-enhance"
}));

const response = await fetch("https://api.imagehq.io/v1/enhance", {
  method: "POST",
  headers: { "Idempotency-Key": crypto.randomUUID() },
  body: form
});

const data = await response.json();
console.log(data);

curl -X POST "https://api.imagehq.io/v1/enhance" \
  -H "Idempotency-Key: $(uuidgen)" \
  -F "files[]=@image.png" \
  -F 'request={"operation":"auto_enhance","options":{"preserve_natural_tones":true,"strength":0.7},"tool_slug":"auto-enhance"}'

$client = new GuzzleHttp\Client();
$response = $client->post("https://api.imagehq.io/v1/enhance", [
  "multipart" => [
    ["name" => "files[]", "contents" => fopen("image.png", "r")],
    ["name" => "request", "contents" => '{"operation":"auto_enhance","options":{"preserve_natural_tones":true,"strength":0.7},"tool_slug":"auto-enhance"}']
  ]
]);

require "faraday"

response = Faraday.post("https://api.imagehq.io/v1/enhance") do |req|
  req.headers["Idempotency-Key"] = SecureRandom.uuid
  req.body = { "files[]" => Faraday::UploadIO.new("image.png", "image/png"), "request" => '{"operation":"auto_enhance","options":{"preserve_natural_tones":true,"strength":0.7},"tool_slug":"auto-enhance"}' }
end

body := &bytes.Buffer{}
writer := multipart.NewWriter(body)
writer.WriteField("request", `{"operation":"auto_enhance","options":{"preserve_natural_tones":true,"strength":0.7},"tool_slug":"auto-enhance"}`)
file, _ := writer.CreateFormFile("files[]", "image.png")
_ = file
writer.Close()
http.Post("https://api.imagehq.io/v1/enhance", writer.FormDataContentType(), body)

HttpRequest request = HttpRequest.newBuilder()
  .uri(URI.create("https://api.imagehq.io/v1/enhance"))
  .header("Idempotency-Key", UUID.randomUUID().toString())
  .POST(HttpRequest.BodyPublishers.ofString("multipart form data"))
  .build();

using var form = new MultipartFormDataContent();
form.Add(new StringContent('{"operation":"auto_enhance","options":{"preserve_natural_tones":true,"strength":0.7},"tool_slug":"auto-enhance"}'), "request");
form.Add(new StreamContent(File.OpenRead("image.png")), "files[]", "image.png");
await httpClient.PostAsync("https://api.imagehq.io/v1/enhance", form);

var request = URLRequest(url: URL(string: "https://api.imagehq.io/v1/enhance")!)
request.httpMethod = "POST"
request.setValue(UUID().uuidString, forHTTPHeaderField: "Idempotency-Key")
// Attach multipart files[] and request fields before sending.

Réponse réussie

{
  "completed": {
    "download_url": "/v1/jobs/job_123/download",
    "expires_at": "2026-05-03T00:00:00Z",
    "id": "job_123",
    "inputs": [
      {
        "filename": "input.png",
        "format": "png",
        "mime_type": "image/png",
        "size_bytes": 420122
      }
    ],
    "outputs": [
      {
        "filename": "output.jpg",
        "format": "jpg",
        "id": "0",
        "mime_type": "image/jpeg",
        "size_bytes": 161002
      }
    ],
    "progress": 100,
    "retention_policy": {
      "clamp": true,
      "ttl_hours": 24
    },
    "stages": [
      {
        "name": "queued",
        "progress": 100,
        "status": "succeeded"
      },
      {
        "name": "processing",
        "progress": 100,
        "status": "succeeded"
      }
    ],
    "status": "succeeded",
    "warnings": []
  },
  "queued": {
    "client_reference_id": "example-123",
    "created_at": "2026-05-02T00:00:00Z",
    "current_stage": "queued",
    "expires_at": "2026-05-03T00:00:00Z",
    "id": "job_123",
    "operation": "enhance",
    "poll_url": "/v1/jobs/job_123",
    "progress": 0,
    "status": "queued",
    "tool_slug": "png-to-jpg"
  }
}

Questions fréquentes

Does enhance use AI models?

This iteration focuses on classic enhancement operations without AI dependencies.

Can I sharpen and denoise together?

Yes. Enhance operations can be configured per request and combined in pipelines.

Does enhance preserve metadata?

Use output options to control metadata preservation or stripping.

API associées

API filter API optimize API pipeline API batch