Nvidia Chrono Edit

Nvidia Chrono Edit

Playground

Try it on WaveSpeedAI!

NVIDIA Chrono Edit is a state-of-the-art image-to-image AI editor that turns photos into stylized edits and retouches with a few clicks. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

ChronoEdit performs edits by reasoning through a short “imagined motion” between the original and the requested change. That temporal reasoning helps keep geometry, lighting, shadows, and contacts consistent in the final image.


Highlights

  • Consistency-first edits: pose, lighting, reflections, and shadows stay believable.
  • Works with one input image plus a natural-language instruction.
  • Reproducible results with seed control; quick iteration for creative teams.
  • Production-friendly outputs in JPEG, PNG, or WEBP; optional BASE64 and sync return.

Parameters

  • prompt: Describe the change you want, not general style fluff. Example: replace the plastic mug with a clear glass half-filled with tea; keep same angle and morning light.

  • image: Source image URL or upload. Use a clean, well-lit photo for best fidelity.

  • seed: Integer for determinism. Same prompt + image + seed gives the same result. Use −1 to randomize.

  • output_format: jpeg for compact distribution, png for lossless editing, webp for web delivery.


How to Use

  1. Upload the source image.
  2. Write a concrete prompt that states the target edit and what must be preserved.
  3. Set seed if you need reproducibility.
  4. Choose output_format.
  5. Run and review. If something drifts, tighten the prompt and fix the seed.

Prompting Tips

  • Be explicit about conservation: keep camera angle, keep morning sunlight, keep the person’s pose.
  • State the edit as a physical change: swap, add, remove, change material, change color.
  • If lighting must change, say it clearly; otherwise the model will preserve the original light.
  • For faces or text areas, crop tighter to the region before editing for crisper results.

Pricing

Per run: $0.02


Quality Notes

  • Input quality sets the ceiling. Soft, noisy, or heavily compressed sources limit realism.
  • For large pose or object changes, iterate with fixed seed and small prompt adjustments.

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",
  "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/nvidia/chrono-edit" \
  -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.
seedintegerNo-1-The random seed to use for the generation. -1 means a random seed will be used.
output_formatstringNojpegjpeg, pngThe 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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