Bria Video Eraser Mask
Playground
Try it on WavespeedAI!Bria Video Eraser (Mask) removes unwanted objects from videos using a user-provided mask video. Mark regions frame-by-frame (black/white or alpha), and the model performs AI video inpainting to reconstruct clean, temporally consistent backgrounds for people, logos, text, and props. Ready-to-use REST API with fast response, best performance, no cold starts, and affordable pricing.
Features
Bria Video Eraser (Mask-Based)
Bria Video Eraser (Mask-Based) is a precision video inpainting tool that removes objects using a mask video. Provide the original video plus a matching mask video (white = erase, black = keep), and the model removes the masked regions frame-by-frame while reconstructing the background for clean, production-ready results.
This mode is ideal for creators and post-production teams who need pixel-accurate control over what gets removed—without manual frame-by-frame painting.
Why it stands out
- Mask-based control for precise, frame-consistent object removal.
- Clean inpainting to reconstruct backgrounds after erasing masked regions.
- Works well for VFX cleanup, unwanted object removal, and scene polishing.
- copy_audio toggle to preserve or remove the original audio track.
- Transparent, duration-based pricing with a clear minimum charge and 10-minute cap.
Capabilities
- Mask-video guided object removal (white regions removed, black regions preserved)
- Background reconstruction (video inpainting) across frames
- Frame-by-frame precision for moving objects and tracked masks
- Optional original audio preservation via copy_audio
Parameters
| Parameter | Description |
|---|---|
| video* | Input video file or public URL. |
| mask_video* | Mask video defining erase vs keep (white = remove, black = keep). Must align with the input video. |
| copy_audio | Whether to keep the original audio in the output video (true = preserve, false = remove). |
How to use
-
Upload the video you want to edit (or paste a public URL).
-
Upload a matching mask_video:
- White areas = regions to erase
- Black areas = regions to keep
-
Make sure the mask video matches the input video’s resolution, duration, and timing for best results.
-
Choose copy_audio:
- true to preserve the original audio track
- false to output a silent video
-
Run the model, preview the output, and refine the mask if needed.
Mask tips (best practices)
- Use pure white for removal and pure black for preservation whenever possible.
- Slight edge feathering can reduce hard seams and improve blending.
- If the mask “misses” parts of the object during motion, expand the mask slightly and re-run.
- For complex motion, generate masks with rotoscoping tools or segmentation models, then export as a mask video.
Pricing
Billing rules (plain English):
- Minimum charge: $0.07 for any clip up to 5 seconds
- After 5 seconds: billed by duration in 5-second units at $0.07 per 5s
- Billing cap: durations over 600 seconds (10 minutes) are billed as 600 seconds
Effective rate:
- Standard rate: $0.014 per second
Reference prices (USD):
| Duration | Total Price |
|---|---|
| 5 s | $0.07 |
| 10 s | $0.14 |
| 20 s | $0.28 |
| 60 s | $0.84 |
| 600 s | $8.40 |
Notes
- The mask video must be properly aligned; misaligned masks can cause jittery edges or incomplete removals.
- Fast motion blur and heavy occlusion may reduce inpainting quality—use tighter masks and short test clips first.
- If you need quick removal without mask prep, use the prompt-based variant instead.
- If you want to generate a mask video. Please use the SAM-3 Video to build one!
Related Models
-
Bria Video Eraser (Prompt) — Prompt-based video object removal for quick, text-driven cleanup without mask preparation.
-
bria/remove-background — Fast image background removal for product photos, portraits, and design cutouts.
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/bria/video-eraser/mask" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"copy_audio": true
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| video | string | Yes | - | The input video to erase objects from. Provide a URL to a publicly accessible video file. | |
| mask_video | string | Yes | - | - | The mask video that defines areas to erase (white regions = remove, black regions = keep). Provide a URL to a publicly accessible video file. |
| copy_audio | boolean | No | true | - | Whether to keep the original audio in the output video (true = preserve audio, false = remove audio) |
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 |