qwencloud-image-generation

To generate images from text prompts using Wan and Qwen, provide a descriptive text prompt and optional image references to the script. The models will process your inputs to create diverse art and product visuals like posters and illustrations.

Yes, you can perform style transfer and maintain subject consistency during image editing. The Qwen image models support these specific editing features, allowing you to modify existing visuals while preserving the original subject and applying new artistic styles.

Yes, you need Python 3.9 or higher and curl installed in your environment to run the text-to-image generation script. These dependencies are required to manage prompts, references, and optional parameters for the Wan and Qwen models.

Interleaved text-image output combines generated images with text in a single sequence. You need this format when creating tutorials or step-by-step guides, allowing the models to generate instructional content with accompanying visual aids.

You can use reference images alongside text prompts to compose complex scenes. By providing these optional image references to the script, the Wan and Qwen models integrate the visual context into the final generated artwork or product visuals.