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.
Idle
$0.02per run·~50 / $1
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.
| 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). |
Official BRIA pricing:
Current endpoint limit:
Reference prices (USD):
| Duration | Total Price |
|---|---|
| 1 s | $0.02 |
| 5 s | $0.10 |
| > 5 s | Not supported in one official request |
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.
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bria/video-eraser/mask with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Video Eraser Mask below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/bria/video-eraser/mask" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"video": "https://example.com/your-input.mp4",
"copy_audio": true
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("bria/video-eraser/mask", {
"video": "https://example.com/your-input.mp4",
"copy_audio": true
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"bria/video-eraser/mask",
{
"video": "https://example.com/your-input.mp4",
"copy_audio": true
}
)
print(output["outputs"][0]) # → URL of the generated outputVideo Eraser Mask is a Bria model for object / watermark removal, exposed as a REST API 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. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/bria/bria-video-eraser-mask.
Video Eraser Mask starts at $0.020 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `video`, `copy_audio`, `mask_video`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/bria/bria-video-eraser-mask.
Average end-to-end generation time on WaveSpeedAI is around 50 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Bria). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.