Create Video From Image Frames

April 18, 2025

Table of contents

  1. Request Headers
  2. Request Body
  3. Responses
  4. Model
  5. Examples
  6. Try It

This endpoint generates a video from one or two images (start and end frames).

https://api.useapi.net/v1/kling/videos/image2video-frames

Request Headers 
Authorization: Bearer {API token}
Content-Type: application/json
# Alternatively you can use multipart/form-data
# Content-Type: multipart/form-data
Request Body 
{
  "email": "[email protected]",
  "image": "https://example.com/start-image.jpg",
  "image_tail": "https://example.com/end-image.jpg",
  "prompt": "A futuristic city with flying cars and tall buildings",
  "negative_prompt": "people, low quality, distorted",
  "cfg_scale": 0.5,
  "duration": "5",
  "model_name": "kling-v1-6",
  "mode": "pro",
  "replyUrl": "https://your-callback-url.com/webhook",
  "replyRef": "your-reference-id"
}

  • email is optional when only one account configured.
    However, if you have multiple accounts configured, this parameter becomes required.

  • image is required if image_tail is not provided. URL to the start frame image.
    Image can be uploaded using POST /assets and the returned URLs can be used here.

  • image_tail is required if image is not provided. URL to the end frame image.
    Image can be uploaded using POST /assets and the returned URLs can be used here.

  • prompt is optional, text description to guide the video generation.
    Maximum length: 2500 characters.

  • negative_prompt is optional, what not to include in the generated video.
    Maximum length: 2500 characters.

  • cfg_scale is optional, guidance scale for image-to-video generation.
    Range: 0 to 1. Default: 0.5.

  • duration is optional, length of the video in seconds.
    Supported values: 5 (default) or 10.

  • model_name is optional, the AI model version to use.
    Supported values: kling-v1-5, kling-v1-6 (default), kling-v2-0.

  • mode is optional, quality level.
    Supported values: std (standard, default) or pro (higher quality, slower generation).

  • maxJobs is optional, range from 1 to 10.
    Specifies the maximum number of concurrent jobs.

  • replyUrl is optional, a callback URL to receive generation progress and result.
    See GET /tasks/task_id for response model.

  • replyRef is optional, a reference identifier for the callback.

Notes:

  • At least one of image or image_tail must be provided.
  • If both image and image_tail are provided, the mode is automatically set to pro.
  • When using model_name kling-v2-0, the parameters cfg_scale, image_tail, and mode are not supported.
Responses

  • 200 OK

    {
  "task": {
    "id": 123456789,
    "userId": 12345,
    "type": "m2v_img2video_hq",
    "scene": "NORMAL_CREATION",
    "status": 5,
    "status_name": "submitted",
    "status_final": false,
    "taskInfo": {
      "type": "m2v_img2video_hq",
      "inputs": [
        {
          "name": "input",
          "inputType": "URL",
          "token": null,
          "blobStorage": null,
          "url": "https://example.com/start-image.jpg",
          "cover": null,
          "fromWorkId": null
        },
        {
          "name": "tail_image",
          "inputType": "URL",
          "token": null,
          "blobStorage": null,
          "url": "https://example.com/end-image.jpg",
          "cover": null,
          "fromWorkId": null
        }
      ],
      "arguments": [
        {
          "name": "prompt",
          "value": "A futuristic city with flying cars and tall buildings"
        },
        {
          "name": "negative_prompt",
          "value": "people, low quality, distorted"
        },
        {
          "name": "cfg",
          "value": "0.5"
        },
        {
          "name": "duration",
          "value": "5"
        },
        {
          "name": "kling_version",
          "value": "1.6"
        },
        {
          "name": "tail_image_enabled",
          "value": "true"
        }
      ],
      "extraArgs": {},
      "callbackPayloads": [],
      "scene": "NORMAL_CREATION"
    },
    "favored": false,
    "deleted": false,
    "viewed": false,
    "createTime": 1745376611075,
    "updateTime": 1745376611075
  },
  "works": [],
  "status": 5,
  "status_name": "submitted",
  "status_final": false,
  "message": "",
  "limitation": {
    "type": "m2v_img2video_hq",
    "remaining": 10000,
    "limit": 10000
  },
  "userPoints": {
    "points": [],
    "total": 0
  },
  "userTickets": {
    "ticket": []
  },
  "editProject": null
}

  • 400 Bad Request

    {
  "error": "image or image_tail is required"
}

  • 401 Unauthorized

    {
  "error": "Unauthorized",
  "code": 401
}

When successful, the response includes a task ID which can be used to check the status using GET /tasks/task_id.

Model 
{ // TypeScript, all fields are optional
    task: {
        id: number
        userId: number
        type: string
        scene: string
        status: number
        status_name: 'submitted' | 'failed' | 'processing' | 'succeed'
        status_final: boolean
        taskInfo: {
            type: string
            inputs: Array<{
                name: string
                inputType: string
                token: string | null
                blobStorage: any | null
                url: string
                cover: string | null
                fromWorkId: number | null
            }>
            arguments: Array<{
                name: string
                value: string
            }>
            extraArgs: Record<string, any>
            callbackPayloads: any[]
            scene: string
        }
        favored: boolean
        deleted: boolean
        viewed: boolean
        createTime: number
        updateTime: number
        viewTime: number
    }
    works: Array<any>
    status: number
    status_name: 'submitted' | 'failed' | 'processing' | 'succeed'
    status_final: boolean
    message: string
    limitation: {
        type: string
        remaining: number
        limit: number
    }
    userPoints: {
        points: Array<{
            orderId: string
            type: string
            amount: number
            balance: number
            startTime: number
            endTime: number
        }>
        total: number
    }
    userTickets: {
        ticket: Array<{
            orderId: string
            type: string
            packageType: string
            amount: number
            balance: number
            startTime: number
            endTime: number
        }>
    }
    editProject: any | null
}
Examples 
  • curl -X POST "https://api.useapi.net/v1/kling/videos/image2video-frames" \
   -H "Content-Type: application/json" \
   -H "Authorization: Bearer …" \
   -d '{
     "email": "[email protected]",
     "image": "https://example.com/start-image.jpg",
     "image_tail": "https://example.com/end-image.jpg",
     "prompt": "A futuristic city with flying cars and tall buildings",
     "negative_prompt": "people, low quality, distorted"
   }'

  • const token = "API token";
const email = "Previously configured account email";
const apiUrl = "https://api.useapi.net/v1/kling/videos/image2video-frames"; 
const response = await fetch(apiUrl, {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "Authorization": `Bearer ${token}`,
  },
  body: JSON.stringify({
    email: email,
    image: "https://example.com/start-image.jpg",
    image_tail: "https://example.com/end-image.jpg",
    prompt: "A futuristic city with flying cars and tall buildings",
    negative_prompt: "people, low quality, distorted"
  })
});
const result = await response.json();
console.log("response", {response, result});

  • import requests
token = "API token"
email = "Previously configured account email"
apiUrl = "https://api.useapi.net/v1/kling/videos/image2video-frames"
headers = {
    "Content-Type": "application/json", 
    "Authorization" : f"Bearer {token}"
}
data = {
    "email": email,
    "image": "https://example.com/start-image.jpg",
    "image_tail": "https://example.com/end-image.jpg",
    "prompt": "A futuristic city with flying cars and tall buildings",
    "negative_prompt": "people, low quality, distorted"
}
response = requests.post(apiUrl, headers=headers, json=data)
print(response, response.json())
Try It