Name: Veo 2 Image-to-Video API
Brand: Google

Overview

OpenAI Assistants Description

Overview:

Veo2 Image-to-Video is an advanced AI model that transforms static images into high-quality, dynamic video content. It builds upon the success of Google's Veo2 text-to-video 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).

Intended Use:

Veo2 Image-to-Video is designed for various applications, including:

Enhancing photography with motion.
Creating engaging marketing and e-commerce content.
Bringing historical photographs to life.
Expanding creative possibilities in digital art and design.

Language Support:

While primarily focused on visual processing, the model likely supports multilingual text inputs for additional context and control.

Technical Details

Architecture:

Veo2 Image-to-Video likely employs a hybrid architecture combining:

Convolutional Neural Networks (CNNs) for image encoding.
Transformer-based models for temporal reasoning.
Generative Adversarial Networks (GANs) or diffusion models for video synthesis.

The model builds on the groundbreaking physics understanding and cinematographic capabilities of its text-to-video predecessor

Training Data:

The model was trained on a massive dataset derived from YouTube’s video library and other proprietary sources, ensuring diversity in motion patterns, visual styles, and real-world physics.

Diversity and Bias:

Google has likely implemented measures to ensure diversity in the training data, minimizing biases in generated content. However, as with all AI models, some biases may persist.

Performance Metrics:

Usage

Code Samples

The model is available on the AI/ML API platform as "Veo2 Image-to-Video" .

Params:

prompt [str]: The text prompt describing how the image should be animated
image_url [str]: URL of the input image to animate. Should be 720p or higher resolution
aspect_ratio [auto, 9:16, 16:9]: Aspect ratio of the generated video
duration [5, 6, 7, 8]: The duration of the generated video in seconds

To get the generated video

API Documentation

Detailed API Documentation is available here.

Ethical Guidelines

Google has integrated safety filters into Veo2 to prevent the generation of harmful or inappropriate content. Developers are encouraged to use the model responsibly in alignment with ethical guidelines for AI-generated media.

Licensing

Veo2 is currently available through Google Labs’ VideoFX platform under a commercial license

‍

Get Veo2 Text-to-Video API here.

Use cases

Social media video content creation and marketing
Digital advertising and promotional video generation
Animated presentations and explainer videos
Creative storytelling and artistic video production
E-commerce and product visualization through dynamic videos
Rapid prototyping of visual content for various industries

How to use Veo 2 Image-to-Video API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to google/veo2-image-to-video.

import requests, time

headers = {"Authorization": "Bearer " + AIMLAPI_KEY}
job = requests.post(
    "https://api.aimlapi.com/v2/video/generations",
    headers=headers,
    json={
      "model": "google/veo2-image-to-video",
      "prompt": "A serene timelapse of clouds over a mountain range"
    },
).json()
gid = job["id"]

while True:
    res = requests.get(f"https://api.aimlapi.com/v2/video/generations?generation_id={gid}", headers=headers).json()
    if res.get("status") in ("completed", "error"):
        break
    time.sleep(5)
print(res["video"]["url"])

const headers = {
  Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
  "Content-Type": "application/json",
};
const job = await (await fetch("https://api.aimlapi.com/v2/video/generations", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "model": "google/veo2-image-to-video",
    "prompt": "A serene timelapse of clouds over a mountain range"
  }),
})).json();

let res;
do {
  await new Promise((r) => setTimeout(r, 5000));
  res = await (await fetch(`https://api.aimlapi.com/v2/video/generations?generation_id=${job.id}`, { headers })).json();
} while (!["completed", "error"].includes(res.status));
console.log(res.video.url);

# submit the generation — the response contains the job "id"
curl -X POST https://api.aimlapi.com/v2/video/generations \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"google/veo2-image-to-video","prompt":"A serene timelapse of clouds over a mountain range"}'

# then poll until status is "completed" — video.url holds the result
curl "https://api.aimlapi.com/v2/video/generations?generation_id={id}" -H "Authorization: Bearer $AIMLAPI_KEY"

OpenAI-compatible — swap the base URL and it works with your existing SDK.