
Miaohua is an AI painting creation platform launched by SenseTime based on its self-developed Artist painting large model with 7 billion parameters. It is simple and easy to use, allowing users to easily customize and generate images. SenseTime Miaohua supports text-to-image and image-to-image prompting methods, and combines precise controls and style models to generate high-quality artwork content anytime, anywhere.
About
Overview
Miaohua is an AI painting creation platform launched by SenseTime, positioned as an image generation tool for individual creators and enterprise users. The product is based on SenseTime's self-developed Artist painting large model, supports quickly generating images through Chinese prompts, and also supports uploading reference images for secondary creation. Overall, the barrier to entry is low, making it suitable for scenarios such as design inspiration exploration, marketing material production, and character and scene concept art generation.
According to information on the official website, Miaohua emphasizes that "if you can type, you can use it," is relatively friendly to Chinese prompts, and provides a variety of common styles such as photography, cute, exquisite, cyberpunk, and cinematic. For users who want to improve image controllability, the platform also provides more detailed parameter and style control capabilities.
Main Features
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Text-to-image
Enter prompts to generate corresponding visuals, suitable for creative needs such as concept art, poster drafts, and illustration inspiration. -
Image-to-image
Upload existing images as references to generate images with similar compositions or different styles, making it convenient for style transfer and secondary design. -
Multi-style image creation
Supports multiple visual styles such as realism, anime, photographic, cinematic, and cyberpunk, adapting to different content directions. -
Precise control capabilities
Supports ControlNet-based pose control, line art coloring, depth detection, and other methods to improve consistency in characters, structure, and image details. -
LoRA model training
Supports uploading local images to train customized LoRA models for generating content that is closer to specific characters, styles, or brand visuals. -
High-resolution output
Official materials mention that it can generate relatively high-resolution images, suitable for display, proposals, and some commercial visual production scenarios. -
API support
Provides interface capabilities for enterprise applications, making it convenient to integrate image generation capabilities into business systems or workflows.
Pricing
In the currently available public information, a unified pricing plan is not clearly displayed. Some functions, quotas, or enterprise API capabilities of Miaohua may require logging in to view or contacting the official team for the latest information. If you plan to use it for commercial projects or team collaboration, it is recommended to confirm the following first:
- Whether a free trial quota is provided
- Whether high-resolution generation is billed separately
- Whether LoRA training has limits on usage count or resources
- API call billing methods and enterprise packages
FAQ
Who is Miaohua suitable for?
It is suitable for designers, content operations staff, marketers, game and animation professionals, as well as ordinary users who need to quickly turn ideas into visual drafts.
What generation methods does Miaohua support?
Current public information shows that Miaohua supports two core methods: text-to-image and image-to-image, and supports creation combined with style models and control functions.
Does Miaohua support Chinese prompts?
Yes. The official website emphasizes good adaptation to Chinese prompts, making it suitable for Chinese users to create directly through descriptive prompts.
Can Miaohua be used for enterprise scenarios?
Yes. The materials show that it provides an API, making it suitable for enterprise-level usage scenarios such as marketing material generation, design assistance, and content production workflow integration.
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