Video Colorizer restores natural color to black-and-white, monochrome or faded footage while keeping every subject, the framing and the motion exactly as they are. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.2per run·~50 / $10
Video Colorizer restores natural, believable color to grayscale, monochrome, or heavily faded video while preserving the original subjects, framing, and motion. Colors are inferred from the footage automatically, and you can optionally use a prompt to guide specific color choices.
Video colorization workflow
Add natural color to black-and-white, monochrome, or desaturated footage.
Content-preserving enhancement
Preserve the original subject identity, framing, background geometry, and motion while adding color.
Automatic color inference
Let the model infer realistic colors for skin tones, clothing, foliage, sky, water, buildings, and lighting.
Prompt-guided color control
Use prompt to specify colors for important objects, clothing, environments, or lighting.
Multiple output resolutions
Choose 480p, 720p, or 1080p while preserving the original aspect ratio.
Seed support
Set a seed when reproducible colorization results are needed.
| Parameter | Required | Description |
|---|---|---|
| video | Yes | Grayscale, monochrome, faded, or desaturated input video URL or uploaded video. Up to 120 seconds is processed. |
| prompt | No | Optional color guidance. Name objects and their desired colors, such as green grass, blue sky, or red jacket. Leave empty to infer colors automatically. |
| target_resolution | No | Output resolution: 480p, 720p, or 1080p. Default: 720p. Aspect ratio is preserved. |
| seed | No | Random seed for reproducible results. |
480p, 720p, or 1080p.Pricing is based on input video duration and selected target_resolution.
Billed duration is rounded up to the next whole second, with a minimum billed duration of 3 seconds and a maximum billed duration of 120 seconds.
| Output Resolution | Per 5s | Per second |
|---|---|---|
| 480p | $0.10 | $0.02 |
| 720p | $0.20 | $0.04 |
| 1080p | $0.50 | $0.10 |
| Input Duration | Billed Duration | 480p | 720p | 1080p |
|---|---|---|---|---|
| 1s | 3s | $0.06 | $0.12 | $0.30 |
| 3s | 3s | $0.06 | $0.12 | $0.30 |
| 5s | 5s | $0.10 | $0.20 | $0.50 |
| 10s | 10s | $0.20 | $0.40 | $1.00 |
| 60s | 60s | $1.20 | $2.40 | $6.00 |
| 120s | 120s | $2.40 | $4.80 | $12.00 |
prompt and seed do not add separate charges.
prompt when specific colors matter, such as red jacket, blue sky, or warm golden street lights.prompt empty when you want the model to infer natural colors automatically.seed when you want to reproduce a colorization result.480p for quick tests and 1080p when higher-resolution output is needed.120 seconds.120 seconds is not processed or billed.video is required.target_resolution defaults to 720p.3–120 seconds.3 seconds.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/video-colorizer with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Video Colorizer below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"target_resolution": "720p"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/video-colorizer" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d "$REQUEST_BODY")
TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; 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' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/video-colorizer";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
async function requestJson(url, options = {}) {
const response = await fetch(url, options);
if (!response.ok) throw new Error(await response.text());
return response.json();
}
// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"target_resolution": "720p"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;
// 2. Poll until the prediction finishes.
while (true) {
const resultBody = await requestJson(resultUrl, {
headers: { "Authorization": `Bearer ${apiKey}` },
});
const result = resultBody.data ?? resultBody;
if (result.status === "completed") {
console.log(result.outputs);
break;
}
if (["failed", "cancelled", "timeout", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
await new Promise(resolve => setTimeout(resolve, 2000));
}import json
import os
import time
from urllib.request import Request, urlopen
api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"target_resolution": "720p"
}
def request_json(url, data=None):
request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
with urlopen(request) as response:
return json.load(response)
# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/video-colorizer", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
raise RuntimeError("Submission response did not contain a prediction id")
result_url = f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"
# 2. Poll until the prediction finishes.
while True:
result_body = request_json(result_url)
result = result_body.get("data", result_body)
status = result.get("status")
if status == "completed":
print(result.get("outputs", []))
break
if status in {"failed", "cancelled", "timeout", "deleted"}:
raise RuntimeError(result)
time.sleep(2)Video Colorizer is a WaveSpeedAI model for video editing, exposed as a REST API on WaveSpeedAI. Video Colorizer restores natural color to black-and-white, monochrome or faded footage while keeping every subject, the framing and the motion exactly as they are. Ready-to-use REST inference API, best performance, no coldstarts, 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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/video-colorizer.
Video Colorizer starts at $0.2 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: `prompt`, `video`, `seed`, `target_resolution`. 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/wavespeed-ai/video-colorizer.
Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.