Improve image quality with auto-enhance, denoise, sharpening, white balance, and basic upscaling.
auto_enhance
denoise
deblur_basic
sharpen
upscale_basic
fix_dark_photo
fix_overexposed_photo
white_balance
Low-quality image cleanup
Commerce photo polishing
Import pipeline normalization
All ImageHQ processing endpoints are asynchronous. Upon a successful POST, you receive a 202 Acceptedresponse with a job_id. Poll the status endpoint until the state reaches succeeded.
Request Example
import requests
url = "https://api.imagehq.io/v1/enhance"
payload = {
"tool_slug": "auto-enhance",
"operation": "auto_enhance",
"options": {
"strength": 0.7,
"preserve_natural_tones": True
}
}
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({
"tool_slug": "auto-enhance",
"operation": "auto_enhance",
"options": {
"strength": 0.7,
"preserve_natural_tones": true
}
}));
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({
"tool_slug": "auto-enhance",
"operation": "auto_enhance",
"options": {
"strength": 0.7,
"preserve_natural_tones": true
}
}));
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: $(uuidgen)" \
-F "files[]=@image.png" \
-F 'request={"tool_slug":"auto-enhance","operation":"auto_enhance","options":{"strength":0.7,"preserve_natural_tones":true}}'$client = new GuzzleHttp\Client();
$response = $client->post("https://api.imagehq.io/v1/enhance", [
"multipart" => [
["name" => "files[]", "contents" => fopen("image.png", "r")],
["name" => "request", "contents" => '{"tool_slug":"auto-enhance","operation":"auto_enhance","options":{"strength":0.7,"preserve_natural_tones":true}}']
]
]);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" => '{"tool_slug":"auto-enhance","operation":"auto_enhance","options":{"strength":0.7,"preserve_natural_tones":true}}' }
endbody := &bytes.Buffer{}
writer := multipart.NewWriter(body)
writer.WriteField("request", `{"tool_slug":"auto-enhance","operation":"auto_enhance","options":{"strength":0.7,"preserve_natural_tones":true}}`)
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('{"tool_slug":"auto-enhance","operation":"auto_enhance","options":{"strength":0.7,"preserve_natural_tones":true}}'), "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.
{
"queued": {
"id": "job_123",
"status": "queued",
"operation": "enhance",
"tool_slug": "png-to-jpg",
"client_reference_id": "example-123",
"progress": 0,
"current_stage": "queued",
"poll_url": "/v1/jobs/job_123",
"created_at": "2026-05-02T00:00:00Z",
"expires_at": "2026-05-03T00:00:00Z"
},
"completed": {
"id": "job_123",
"status": "succeeded",
"progress": 100,
"inputs": [
{
"filename": "input.png",
"format": "png",
"mime_type": "image/png",
"size_bytes": 420122
}
],
"outputs": [
{
"id": "0",
"filename": "output.jpg",
"format": "jpg",
"mime_type": "image/jpeg",
"size_bytes": 161002
}
],
"warnings": [],
"stages": [
{
"name": "queued",
"status": "succeeded",
"progress": 100
},
{
"name": "processing",
"status": "succeeded",
"progress": 100
}
],
"download_url": "/v1/jobs/job_123/download",
"retention_policy": {
"ttl_hours": 24,
"clamp": true
},
"expires_at": "2026-05-03T00:00:00Z"
}
}This iteration focuses on classic enhancement operations without AI dependencies.
Yes. Enhance operations can be configured per request and combined in pipelines.
Use output options to control metadata preservation or stripping.