Wan 2.2 Image To Image

Wan 2.2 Image To Image

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WAN 2.2 (14B) is an image-to-image model for high-resolution photorealistic image editing with exceptional precision and fidelity. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Wan 2.2 Image-to-Image is a versatile image transformation model that modifies existing images based on text prompts. Convert photos to different styles, apply artistic effects, or reimagine scenes while preserving the original composition and structure.


Why It Stands Out

  • Style transformation: Convert images to different artistic styles like anime, oil painting, or photorealistic renders.
  • Prompt-guided editing: Describe the changes you want and watch the image transform.
  • Prompt Enhancer: Built-in AI-powered prompt optimization for better transformation results.
  • Strength control: Fine-tune how much the original image is preserved versus transformed.
  • Flexible resolution: Customize width and height for your desired output size.
  • Multiple output formats: Export as JPEG, PNG, or other formats.
  • Reproducibility: Use the seed parameter to recreate exact results.

Parameters

ParameterRequiredDescription
promptYesText description of the transformation you want.
imageYesSource image (upload or public URL).
strengthNoHow much to transform the image (0.0–1.0, default: 0.6).
widthNoOutput width in pixels (default: 1024).
heightNoOutput height in pixels (default: 1024).
seedNoSet for reproducibility; -1 for random.
output_formatNoOutput format: jpeg, png, etc. (default: jpeg).
enable_base64_outputNoReturn base64 string instead of URL (API only).
enable_sync_modeNoWait for result before returning response (API only).

How to Use

  1. Upload your source image — drag and drop a file or paste a public URL.
  2. Write a prompt describing the transformation you want. Use the Prompt Enhancer for AI-assisted optimization.
  3. Adjust strength — lower values (0.2–0.4) preserve more of the original; higher values (0.6–0.9) allow more dramatic changes.
  4. Set dimensions — adjust width and height as needed.
  5. Click Run and download your transformed image.

Best Use Cases

  • Style Transfer — Convert photos to anime, watercolor, sketch, or other artistic styles.
  • Photo Enhancement — Apply cinematic lighting, color grading, or atmospheric effects.
  • Creative Reimagining — Transform scenes into different seasons, times of day, or moods.
  • Content Creation — Generate stylized versions of images for social media and marketing.
  • Concept Art — Quickly explore visual variations of reference images.

Pricing

OutputPrice
Per image$0.02

Pro Tips for Best Quality

  • Use lower strength (0.3–0.5) to preserve more details from the original image.
  • Use higher strength (0.6–0.8) for dramatic style changes like photo-to-anime conversion.
  • Be specific in your prompt — describe the style, lighting, colors, and mood you want.
  • Start with default strength and adjust based on results.
  • Fix the seed when iterating to compare different prompt variations.

Notes

  • Ensure uploaded image URLs are publicly accessible.
  • Processing time varies based on resolution and current queue load.
  • Please ensure your prompts comply with content guidelines.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "strength": 0.6,
  "size": "1024*1024",
  "seed": -1,
  "output_format": "jpeg"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.2/image-to-image" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(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' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  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

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-The positive prompt for the generation.
imagestringYes-The image to generate an image from (optional).
strengthnumberNo0.60 ~ 1Strength indicates extent to transform the reference image.
sizestringNo1024*1024-The size of the generated media in pixels (width*height).
seedintegerNo-1-The random seed to use for the generation. -1 means a random seed will be used.
output_formatstringNojpegjpeg, png, webpThe format of the output image.
enable_base64_outputbooleanNofalse-If set to `true`, the prediction's `output` strings are returned as **naked base64** (no `data:<mime>;base64,` prefix). When `false` (default), outputs are returned as URLs pointing to our CDN.
enable_sync_modebooleanNofalse-If set to `true`, the request attempts to wait for the generated result and return outputs in the same response. If the result is not ready within the sync wait window, the API can return a timeout body while the task continues processing. This option is only available via the API and is supported only by some models.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to poll for the prediction result
data.statusstringStatus: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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