Veo2 (Image-to-Video)

This documentation is valid for the following list of our models:

veo2/image-to-video

Overview

An advanced AI model that transforms static images into high-quality, dynamic video content. It builds upon the success of Google's model, offering unprecedented control and realism in video generation from still images.

Key Features:

Faithful content preservation from source images.
Intuitive motion generation with physics-aware movement.
High-resolution output up to 4K.
Multimodal input processing (image + text).

Setup your API Key

If you don’t have an API key for the AI/ML API yet, feel free to use our .

How to Make a Call

Generating a video using this model involves sequentially calling two endpoints:

The first one is for creating and sending a video generation task to the server (returns a generation ID).
The second one is for requesting the generated video from the server using the generation ID received from the first endpoint.

Below, you can find two corresponding API schemas and examples for both endpoint calls.

API Schemas

Video Generation

You can generate a video using this API.

Fetch the video

Examples

Video generation

import requests


def main():
    url = "https://api.aimlapi.com/v2/generate/video/google/generation"
    payload = {
        "model": "veo2/image-to-video",
        "prompt": "Mona Lisa puts on glasses with her hands.",
        "image_url": "https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg",
        "aspect_ratio": "16:9",
        "duration": "5",
    }
    headers = {"Authorization": "Bearer <YOUR_API_KEY>", "Content-Type": "application/json"}

    response = requests.post(url, json=payload, headers=headers)
    print("Generation:", response.json())


if __name__ == "__main__":
    main()

Fetch the video

import requests


def main():
    url = "https://api.aimlapi.com/v2/generate/video/google/generation"
    params = {
        "generation_id": "<YOUR_GENERATION_ID>",
    }
    headers = {"Authorization": "Bearer <YOUR_API_KEY>", "Content-Type": "application/json"}

    response = requests.get(url, params=params, headers=headers)
    print("Generation:", response.json())


if __name__ == "__main__":
    main()

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Overview

Key Features:

Faithful content preservation from source images.

Intuitive motion generation with physics-aware movement.

High-resolution output up to 4K.

Multimodal input processing (image + text).

How to Make a Call

Generating a video using this model involves sequentially calling two endpoints:

The first one is for creating and sending a video generation task to the server (returns a generation ID).

The second one is for requesting the generated video from the server using the generation ID received from the first endpoint.

Below, you can find two corresponding API schemas and examples for both endpoint calls.

Examples

Video generation

import requests


def main():
    url = "https://api.aimlapi.com/v2/generate/video/google/generation"
    payload = {
        "model": "veo2/image-to-video",
        "prompt": "Mona Lisa puts on glasses with her hands.",
        "image_url": "https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg",
        "aspect_ratio": "16:9",
        "duration": "5",
    }
    headers = {"Authorization": "Bearer <YOUR_API_KEY>", "Content-Type": "application/json"}

    response = requests.post(url, json=payload, headers=headers)
    print("Generation:", response.json())


if __name__ == "__main__":
    main()

Fetch the video

import requests


def main():
    url = "https://api.aimlapi.com/v2/generate/video/google/generation"
    params = {
        "generation_id": "<YOUR_GENERATION_ID>",
    }
    headers = {"Authorization": "Bearer <YOUR_API_KEY>", "Content-Type": "application/json"}

    response = requests.get(url, params=params, headers=headers)
    print("Generation:", response.json())


if __name__ == "__main__":
    main()