Depth Anything V3 Video API Documentation
Playground
Try it on WaveSpeedAI!Depth Anything V3 Video turns any video into a temporally consistent depth map video with no flicker, ideal for replicating camera moves and motion with depth-controlled video generation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
Depth Anything V3 Video converts an input video into a temporally consistent depth-map video using Depth Anything V3. Depth is normalized across the full clip rather than independently frame by frame, helping maintain stable depth values as subjects move, the camera changes position, and the scene evolves.
The generated depth video preserves the input resolution, duration and audio track, with output frame rate preserved up to 30 fps, making it suitable for depth-conditioned video generation, compositing, relighting, parallax, and other motion-aware workflows.
Why Choose This?
-
Temporally consistent depth
Depth is normalized across the entire video to reduce frame-to-frame brightness shifts and depth flicker. -
Stable through fast motion
Depth is estimated with temporal context across neighboring frames, so structure holds up through fast camera moves and motion blur instead of changing from frame to frame. -
Stable subject depth
Subjects can maintain more consistent depth values as the camera moves or the scene changes. -
Clear subject separation
Preserve silhouettes, thin structures, people, hands, and background geometry for downstream control workflows. -
Control-workflow ready
Use the default grayscale output directly in depth-conditioned video generation and ControlNet-style pipelines. -
Multiple colormaps
Choosegrayscalefor depth workflows orinfernoandturbofor visualized depth output. -
Long-video support
Process up to600seconds of video in a single request. -
Original resolution and frame rate
Output follows the input video resolution and preserves frame rate up to30 fps.
Parameters
| Parameter | Required | Description |
|---|---|---|
| video | Yes | Input video provided as a URL or upload. Up to 600 seconds are processed; longer inputs are processed up to the 10-minute mark. |
| colormap | No | Depth-map visualization: grayscale, inferno, or turbo. Default: grayscale. In grayscale mode, near surfaces are white and far surfaces are black. |
How to Use
- Provide an input video — Upload a video or provide its URL.
- Choose a colormap optional — Use
grayscalefor generation and compositing workflows, orinferno/turbofor visual visualization. - Submit — Generate the depth-map video.
- Use the result — Feed the output into depth-controlled generation, relighting, compositing, parallax, or other depth-aware workflows.
Pricing
Pricing is based on input video duration.
The rate is $0.005 per billed second.
Billed duration is rounded up to the next whole second, with a minimum billed duration of 3 seconds and a maximum billed duration of 600 seconds.
| Input Duration | Billed Duration | Cost |
|---|---|---|
| 3s | 3s | $0.015 |
| 10s | 10s | $0.05 |
| 60s | 60s | $0.30 |
| 600s | 600s | $3.00 |
colormap does not add a separate charge.
Best Use Cases
- Depth-conditioned video generation — Use the depth video as structural guidance for recreating motion and camera behavior with new visual content.
- Motion and camera replication — Extract depth from a reference clip and use it to guide another video-generation workflow.
- VFX and compositing — Apply depth-based masking, grading, fog, volumetric effects, and layering.
- Relighting — Use a temporally stable depth pass for depth-aware lighting adjustments.
- Depth of field — Create foreground and background separation for focus and blur effects.
- 2.5D and parallax effects — Use depth information to create spatial movement from existing footage.
- 3D-aware editing — Apply depth-driven transformations while preserving scene structure over time.
- AR occlusion — Use scene depth to help virtual objects pass in front of or behind real-world subjects.
Pro Tips
- Use
grayscalewhen the depth video will be passed into another model or compositing workflow. - Use
infernoorturbowhen the output is primarily for visualization or inspection. - In grayscale mode, white represents surfaces closer to the camera and black represents surfaces farther away.
- Treat the result as relative depth, not real-world metric distance.
- Depth consistency across the full clip makes the output more suitable for motion-aware control workflows than independently processed frame-by-frame depth maps.
- Videos above
30 fpsare returned at30 fpswhile preserving the same duration. - The output keeps the source audio, so the depth video stays in sync when you lay it back over the original edit.
Notes
videois required.colormapdefaults tograyscale.- Supported colormaps are
grayscale,inferno, andturbo. - Up to
600seconds of input video are processed. - Longer videos are processed only up to the first
600seconds. - Output resolution matches the input video resolution.
- Output frame rate matches the source up to
30 fps. - Inputs above
30 fpsare returned at30 fpswith the same duration. - The source audio track is kept in the output video.
- Depth is relative rather than metric.
- In grayscale mode, near surfaces are white and far surfaces are black.
Related Models
- Depth Anything Image — Generate grayscale depth maps from individual images.
- Depth Anything Video — Generate depth maps from video input.
- Depth Anything V3 Image — Generate detailed image depth maps with Depth Anything V3.
- Depth Anything V3 Video — Generate temporally consistent depth-map videos with Depth Anything V3.
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'
{
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"colormap": "grayscale"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/depth-anything-v3/video" \
-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
doneParameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| video | string | Yes | - | The URL of the input video to estimate depth for. Up to 10 minutes; longer videos are processed up to the 10-minute mark. | |
| colormap | string | No | grayscale | grayscale, inferno, turbo | How depth is rendered. grayscale is the standard depth map (near = white, far = black) used by depth-conditioned generation and ControlNet-style workflows; inferno and turbo are color visualizations. |
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 | Output values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.status | string | Task status. completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses. |
| 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 |
| data.model | string | Model ID used for the prediction |
| data.outputs | array<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.urls | object | Object containing related API endpoints |
| data.status | string | Status: completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses |
| data.created_at | string | ISO timestamp of when the request was created |
| 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 |