Wan: Open and Advanced Large-Scale Video Generative Models
Generate video animations from image trajectories
Wan: Open and Advanced Large-Scale Video Generative Models
https://imagetovideoaifree.com/wanx21
Create a video by combining an image and audio
Generate a video from an image and text prompt
Image Generator with Stable Diffusion
Convert images to videos
Wan: Open and Advanced Large-Scale Video Generative Models
Generate animated videos from images and motion
Generate a video from a prompt and an image
Create videos from text and images using EasyAnimate
Wan: Open and Advanced Large-Scale Video Generative Models
Wan2.1 is an open and advanced large-scale video generative model designed to create videos from text or images. It is part of the Wan family of models, which are known for their flexibility and efficiency in generating high-quality video content. Wan2.1 is specifically tailored for users who want to transform static images or text descriptions into dynamic video outputs.
• Text-to-Video Generation: Convert textual descriptions into video content with high precision and creativity.
• Image-to-Video Generation: Transform static images into engaging videos, adding motion and depth to your visuals.
• Customizable Settings: Adjust parameters like resolution, frame rate, and duration to tailor videos to your needs.
• Efficient Processing: Built with advanced algorithms to ensure fast rendering times without compromising quality.
• Integration Capabilities: Easily incorporate into existing workflows or applications for seamless video production.
What formats does Wan2.1 support for image input?
Wan2.1 supports JPEG, PNG, and BMP formats for image input. For best results, use high-quality images with clear details.
Can I use Wan2.1 for commercial purposes?
Yes, Wan2.1 is licensed for both personal and commercial use, making it a versatile tool for creators and businesses alike.
How consistent are the results when generating videos from the same input?
Wan2.1 uses deterministic algorithms, ensuring that videos generated from the same input will be consistent and identical.