Topaz Image Lighting API Documentation

Topaz Image Lighting API Documentation

Playground

Topaz Image Lighting adjusts and balances images to improve quality despite sub-optimal lighting. Fix exposure, white balance, and color temperature. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Topaz Image Lighting is a professional-grade image lighting and color adjustment model powered by Topaz Labs’ AI technology. Upload your image and let AI automatically adjust lighting, correct white balance, or even colorize black-and-white photos.

Why Choose This?

• AI-powered lighting adjustment Automatically enhance exposure, shadows, highlights, and overall lighting balance.

• White balance correction Fix color casts and correct inaccurate white balance from any lighting condition.

• Photo colorization Transform black-and-white photos into natural-looking color images.

• Professional quality Powered by Topaz Labs’ AI, trusted by professional photographers worldwide.

• Multiple output formats Export as JPEG or PNG based on your workflow needs.

Parameters

Model Options

Output Format Options

• jpeg — Compressed format, smaller file size
• png — Lossless format, supports transparency

How to Use

1. Upload your image — drag and drop or paste a URL.
2. Select model — choose based on what you want to achieve.
3. Choose output format — select based on your quality and file size needs.
4. Run — submit and download the processed image.

Pricing

The minimum charge is $0.096. Each additional started 24-megapixel block adds $0.096.

Best Use Cases

• Exposure Correction — Fix underexposed or overexposed photos.
• White Balance Fix — Correct color casts from artificial lighting.
• Photo Restoration — Colorize old black-and-white family photos.
• Batch Processing — Consistently adjust lighting across multiple images.
• Professional Editing — Quick lighting fixes in professional workflows.

Pro Tips

• Use Adjust V2 for better results on challenging lighting conditions.
• White Balance model works best on images with obvious color casts.
• Colorize model produces natural results but may need manual tweaking for historical accuracy.
• For archival work, export as PNG to avoid additional compression artifacts.

Notes

• Adjust models work on both color and black-and-white images.
• Colorize model is specifically designed for black-and-white to color conversion.
• Results may vary based on original image quality and lighting conditions.

Related Models

• Topaz Image Sharpen — AI-powered image sharpening.
• Topaz Image Denoise — AI-powered noise reduction.
• Topaz Image Restore — AI-powered dust and scratch removal.

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'
{
  "model": "Adjust V2",
  "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/topaz/image/lighting" \
  -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 "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"

# 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|deleted) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

Response Parameters

Result Request Parameters

Result Response Parameters