Topaz Image Restore
Playground
Try it on WavespeedAI!Topaz Image Restore enhances older and poorer quality photos through restoration. Remove dust, scratches, and damage from vintage photos. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
Topaz Image Restore
Topaz Image Restore is a professional-grade image restoration model powered by Topaz Labs’ AI technology. Upload your image and let AI automatically detect and remove dust, scratches, and other imperfections — perfect for restoring old photos and scanned images.
Why Choose This?
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Dust and scratch removal AI automatically detects and removes dust particles, scratches, and other surface imperfections.
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Old photo restoration Ideal for restoring scanned photos, film negatives, and vintage images.
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Professional quality Powered by Topaz Labs’ AI, trusted by professional photographers and archivists.
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Multiple output formats Export as JPEG, PNG, or TIFF based on your workflow needs.
Parameters
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Source image to restore (upload or URL) |
| model | No | Restoration model to use (default: Dust-Scratch) |
| output_format | No | Output format: jpeg, jpg, png, tiff, or tif |
Model Options
| Model | Description |
|---|---|
| Dust-Scratch | Standard dust and scratch removal (default) |
| Dust-Scratch V2 | Improved version with better detection and removal |
Output Format Options
- jpeg / jpg — Compressed format, smaller file size
- png — Lossless format, supports transparency
- tiff / tif — Professional format, highest quality preservation
How to Use
- Upload your image — drag and drop or paste a URL.
- Select model — choose Dust-Scratch or Dust-Scratch V2.
- Choose output format — select based on your quality and file size needs.
- Run — submit and download the restored image.
Pricing
| Item | Cost |
|---|---|
| Per image | $0.07 |
Simple flat-rate pricing regardless of image size or model selected.
Best Use Cases
- Old Photo Restoration — Remove dust and scratches from vintage photographs.
- Film Scanning — Clean up scanned film negatives and slides.
- Archive Digitization — Restore historical images for digital archives.
- Family Photos — Bring old family photos back to life.
- Print Restoration — Clean up scanned prints with surface damage.
Pro Tips
- Use Dust-Scratch V2 for better results on heavily damaged images.
- For archival work, export as TIFF to preserve maximum quality.
- Combine with other Topaz tools (Sharpen, Upscale) for complete restoration workflow.
- Best results come from high-resolution scans of the original photos.
Notes
- This model is optimized for dust and scratch removal, not for colorization or major damage repair.
- For best results, scan original photos at high resolution before processing.
- V2 model generally produces better results but may take slightly longer.
Related Models
- Topaz Image Sharpen — AI-powered image sharpening.
- Topaz Image Enhance — AI-powered image upscaling.
- Topaz Image Denoise — AI-powered noise reduction.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/topaz/image/restore" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"model": "Dust-Scratch",
"output_format": "jpeg",
"enable_base64_output": false
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| image | string | No | - | The image file to be processed. Supported formats (png jpg jpeg tiff tif) | |
| model | string | No | Dust-Scratch | Dust-Scratch, Dust-Scratch V2 | The restore model to use. Dust-Scratch: Remove dust and scratches from old photos. Dust-Scratch V2: Enhanced dust and scratch removal with better detail preservation. |
| output_format | string | No | jpeg | jpeg, jpg, png, tiff, tif | The format of the output image. |
| enable_base64_output | boolean | No | false | - | If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API. |
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Array of URLs to the generated content (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction, the ID of the prediction to get |
| data.model | string | Model ID used for the prediction |
| data.outputs | string | Array of URLs to the generated content (empty when status is not completed). |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |