Image to video

Popular Models

Image-to-video generation combines your input image with motion generation. The output maintains visual consistency with your source image while adding realistic motion.

Step 1: Prepare Your Image

First, you need to provide the source image. You can either upload a file, reference a URL or provide a base64 data URI.

// npm install @krea-ai/sdk
import { openAsBlob } from "node:fs";
import { Krea } from "@krea-ai/sdk";

const krea = new Krea({ apiKey: process.env.KREA_API_KEY });

// Option 1: Upload a local file and use the hosted asset URL
const file = await openAsBlob("./input-image.jpg", { type: "image/jpeg" });
const asset = await krea.assets.upload(file, {
  description: "Input image",
});
const imageUrl = asset.image_url;

// Option 2: Using image URL
// const imageUrl = "https://example.com/input-image.jpg";

import requests

API_BASE = "https://api.krea.ai"
API_TOKEN = "YOUR_API_TOKEN"

# Option 1: Upload a local file and use the hosted asset URL
with open("input-image.jpg", "rb") as image_file:
    upload = requests.post(
        f"{API_BASE}/assets",
        headers={"Authorization": f"Bearer {API_TOKEN}"},
        files={"file": ("input-image.jpg", image_file, "image/jpeg")},
        data={"description": "Input image"},
    )
upload.raise_for_status()
image_url = upload.json()["image_url"]

# Option 2: Using image URL
# image_url = "https://example.com/input-image.jpg"

Replace with your API TokenTo replace the YOUR_API_TOKEN placeholder in the above examples, you’ll need to generate an API token in krea.ai/settings/api-tokens. Follow the instructions on the API Keys & Billing page if you need help.

Step 2: Generate the Video

Make a POST request to /generate/video/kling/kling-2.5 with your image and motion parameters.

// npm install @krea-ai/sdk
import { Krea } from "@krea-ai/sdk";

const krea = new Krea({ apiKey: process.env.KREA_API_KEY });

const job = await krea.video("kling/kling-2.5", {
  start_image: imageUrl,
  prompt: "gentle camera pan from left to right, subtle depth",
  duration: 5,
  aspect_ratio: "16:9"
});

console.log(`Job ID: ${job.job_id}`);

curl -X POST https://api.krea.ai/generate/video/kling/kling-2.5 \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "start_image": "https://example.com/input-image.jpg",
    "prompt": "gentle camera pan from left to right, subtle depth",
    "duration": 5,
    "aspect_ratio": "16:9"
  }'

response = requests.post(
    f"{API_BASE}/generate/video/kling/kling-2.5",
    headers={
        "Authorization": f"Bearer {API_TOKEN}",
        "Content-Type": "application/json"
    },
    json={
        "start_image": image_url,
        "prompt": "gentle camera pan from left to right, subtle depth",
        "duration": 5,
        "aspect_ratio": "16:9"
    }
)

job = response.json()
print(f"Job ID: {job['job_id']}")

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "net/http"
)

func main() {
    apiBase := "https://api.krea.ai"
    apiToken := "YOUR_API_TOKEN"

    payload := map[string]interface{}{
        "start_image": "https://example.com/input-image.jpg",
        "prompt": "gentle camera pan from left to right, subtle depth",
        "duration": 5,
        "aspect_ratio": "16:9",
    }

    jsonData, _ := json.Marshal(payload)
    req, _ := http.NewRequest("POST", apiBase+"/generate/video/kling/kling-2.5", bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer "+apiToken)
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, _ := client.Do(req)
    defer resp.Body.Close()

    var job map[string]interface{}
    json.NewDecoder(resp.Body).Decode(&job)
    fmt.Printf("Job ID: %s\n", job["job_id"])
}

Example Response

{
  "job_id": "550e8400-e29b-41d4-a716-446655440000",
  "status": "queued",
  "created_at": "2025-01-15T10:30:00.000Z",
  "estimated_time": "60-120 seconds"
}

Step 3: Poll for Results

Poll /jobs/{job_id} every 5 seconds to check the video generation progress.

// npm install @krea-ai/sdk
import { Krea } from "@krea-ai/sdk";

const krea = new Krea({ apiKey: process.env.KREA_API_KEY });

async function waitForVideo(jobId) {
  const completed = await krea.jobs.wait(jobId, { intervalMs: 5000 });
  return completed.result.urls[0];
}

const videoUrl = await waitForVideo(job.job_id);
console.log(`Video ready: ${videoUrl}`);

curl -X GET https://api.krea.ai/jobs/YOUR_JOB_ID \
  -H "Authorization: Bearer YOUR_API_TOKEN"

import time

def wait_for_video(job_id):
    while True:
        response = requests.get(
            f"{API_BASE}/jobs/{job_id}",
            headers={"Authorization": f"Bearer {API_TOKEN}"}
        )
        job = response.json()

        if job["status"] == "completed":
            return job["result"]["urls"][0]
        if job["status"] in ("failed", "cancelled"):
            raise Exception(f"Job failed: {job['status']}")

        # Show progress if available
        if "progress" in job:
            print(f"Progress: {job['progress']}%")
        else:
            print(f"Status: {job['status']}")

        time.sleep(5)

video_url = wait_for_video(job["job_id"])
print(f"Video ready: {video_url}")

func waitForVideo(jobID string) (string, error) {
    for {
        req, _ := http.NewRequest("GET", apiBase+"/jobs/"+jobID, nil)
        req.Header.Set("Authorization", "Bearer "+apiToken)

        resp, _ := client.Do(req)
        var job map[string]interface{}
        json.NewDecoder(resp.Body).Decode(&job)
        resp.Body.Close()

        switch job["status"] {
        case "completed":
            result := job["result"].(map[string]interface{})
            urls := result["urls"].([]interface{})
            return urls[0].(string), nil
        case "failed", "cancelled":
            return "", fmt.Errorf("job failed: %s", job["status"])
        }

        // Show progress if available
        if progress, ok := job["progress"]; ok {
            fmt.Printf("Progress: %.0f%%\n", progress)
        } else {
            fmt.Printf("Status: %s\n", job["status"])
        }

        time.Sleep(5 * time.Second)
    }
}

Example Completed Response

{
  "job_id": "550e8400-e29b-41d4-a716-446655440000",
  "status": "completed",
  "created_at": "2025-01-15T10:30:00.000Z",
  "completed_at": "2025-01-15T10:31:45.000Z",
  "result": {
    "urls": ["https://gen.krea.ai/videos/your-video.mp4"]
  }
}

Webhooks available!Set up webhooks to receive notifications when jobs complete. See the Webhooks guide to get started.

Common Parameters

For a list of detailed parameters for all models, see the Model APIs page.

Parameter	Type	Description
`start_image`	string	URL of the source image
`prompt`	string	Description of desired motion and camera movement
`duration`	number	Video length in seconds. Supported values depend on the model.
`aspect_ratio`	string	Video aspect ratio, such as `16:9`, `9:16`, or `1:1`
`end_image`	string	Optional ending frame URL for supported models
`mode`	string	Optional quality mode for models that expose one

Motion Prompt Tips:

Describe camera movement (pan, zoom, dolly, tilt)
Specify motion direction and speed
Mention depth and parallax effects
Use restrained camera language for subtle animations
Use stronger action verbs for dramatic effects

Getting Started

Krea 2

Core Concepts

Code Examples

Tutorials

Image to video

Popular Models

Step 1: Prepare Your Image

Step 2: Generate the Video

Step 3: Poll for Results

Common Parameters

​Popular Models

​Step 1: Prepare Your Image

​Step 2: Generate the Video

​Step 3: Poll for Results

​Common Parameters

Popular Models

Step 1: Prepare Your Image

Step 2: Generate the Video

Step 3: Poll for Results

Common Parameters