Create Video From Image Frames

April 18, 2025 (Jun 19, 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",
  "prompt": "A futuristic city with flying cars and tall buildings",
  "negative_prompt": "people, low quality, distorted",
  "duration": "10",
  "model_name": "kling-v2-1",
  "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. Models 2.x do not support this parameter.
    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. Models 2.x do not support this parameter.
    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, kling-v2-0-master, kling-v2-1-master, kling-v2-1 (default).

  • mode is optional, quality level. Models 2.x master do not support this parameter.
    Supported values: std (standard, default) or pro (higher quality, slower generation).

  • maxJobs is optional, range from 1 to 50.
    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.
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