【神サービス】Stable DiffusionのWEB UIはもう不要！【プログラミング無し】
TLDRThe video introduces a web service that enables users to generate Stable Diffusion images without the need for a complex web UI setup. The service offers features such as model uploading, control net functionality, and text-to-image capabilities, closely mimicking the traditional Stable Diffusion web UI. It provides a wide range of models, including popular ones from ChitLoutMix, and allows for detailed customization of generated images. The service is currently free to use, with a system in place for earning coins to generate more images. It cautions users about commercial use, advising adherence to local laws and self-assumption of related risks.
Takeaways
- 🌐 Introduction of a web service that enables users to generate Stable Diffusion images without setting up a WEBUI.
- 🛠️ Overcoming technical barriers associated with running Python in a Google Colab environment to set up Stable Diffusion UI.
- 🎨 The service allows users to upload their own models and use features like control nets, similar to traditional Stable Diffusion WEBUI.
- 🖼️ A wide variety of models available for use, including popular ones like Chit Mix, and the ability to manipulate aspects like aspect ratio and sampling steps.
- 🔍 The service supports Japanese prompts and can generate images based on them, showcasing its language versatility.
- 📈 The option to upscale the quality of the generated images and adjust variations with a simple button press.
- 🎨 Advanced features like control nets and tile functions are available for more detailed image generation.
- 🆓 Currently, the service is available for free, but it is hinted that a coin system will be introduced for future use.
- 🤝 Users can earn coins by signing in daily and referring others, allowing for continued free use of the service.
- 📝 Commercial use is not explicitly prohibited but users are responsible for adhering to their local laws and assuming the associated risks.
- 📚 The presenter encourages users to try the service for its ease of use and potential to spark further interest in exploring Stable Diffusion.
Q & A
What is the main topic of the video?
-The main topic of the video is the introduction of a web service that allows users to generate Stable Diffusion images without setting up a WEBUI, making the process more accessible.
What is the significance of the service mentioned in the video?
-The service is significant because it overcomes the technical barriers associated with setting up and running Stable Diffusion UI, allowing users who find the process too difficult to easily generate images using Stable Diffusion.
How does the web service differ from traditional Stable Diffusion WEBUI?
-The web service offers a user experience that closely resembles the traditional Stable Diffusion WEBUI but without the need for programming knowledge or environment setup. It also allows users to upload their own models and use control net functions, which are not typically available on other web-based image generation services.
What are some of the features available on the web service?
-The web service includes features such as model uploading, control net functionality, image-to-image and text-to-image functions, aspect ratio adjustments, negative prompts, sampling steps, cfg scale, and seed values.
How many models can users choose from on this web service?
-Users have access to a large number of models, including popular ones like the Chillout Mix, and the service pulls most of its models from the Stable Diffusion model sharing service, CivitAI.
Is it possible to use the service for free?
-Currently, the service is available for free on a limited-time basis, but it is expected that users will need to consume 'coins' for image generation in the future.
How can users obtain coins for the web service?
-Users can obtain coins by signing in daily to the service, which allows them to earn coins for free. They can also earn coins by referring other users to the platform.
What is the policy regarding commercial use of the generated images?
-The service's terms of use do not explicitly prohibit commercial use, but users are responsible for complying with the laws and regulations of their respective countries and for bearing any associated risks.
How does the service handle Japanese prompts?
-The service supports Japanese prompts and can generate images based on them, as demonstrated in the video with the prompt about a 'metal cute kitten.'
What is the recommendation for users who want to learn more about Stable Diffusion and related technologies?
-The video suggests that users who want to explore more can join the presenter's AI-focused community, where various materials and tutorials related to Stable Diffusion and other AI technologies are shared.
What is the final recommendation for users interested in the web service?
-The presenter encourages users to try the web service while it's free and to learn more about setting up the traditional WEBUI for more customization and detailed control over the image generation process.
Outlines
🌟 Introduction to a New Stable Diffusion Web Service
This paragraph introduces a new web service that simplifies the process of using Stable Diffusion for image generation. The speaker explains that typically, setting up a UI for Stable Diffusion requires technical knowledge and can be a barrier for many. However, this new service allows users to generate images without the need for a complex UI, making it accessible to a wider audience. The speaker also mentions their channel, which shares AI-related tools and information, and invites viewers to subscribe and join their AI-focused community for more insights.
🎨 Features and Capabilities of the C Art Web Service
The second paragraph delves into the features of the C Art web service, which is highlighted as a representative example of a Stable Diffusion image generation web service. It is noted for its user-friendly interface, resembling the traditional Stable Diffusion WEB UI. The service allows users to upload their models, use control nets, and includes image-to-image and text-to-image functionalities. The variety of models available is substantial, with many sourced from the Chibit AI model sharing service. The speaker also touches on the ability to adjust image aspect ratios, negative prompts, sampling steps, and other parameters, making it a comprehensive tool for image generation. Additionally, the service supports Japanese prompts and offers a free trial, with a coin-based system for future use.
Mindmap
Keywords
💡Stable Diffusion
💡Web UI
💡AI
💡Control Net
💡Dream Studio
💡Model Upload
💡Image-to-Image
💡Aspect Ratio
💡Negative Prompt
💡Sampling Steps
💡CFG Scale
💡Seed Value
Highlights
Introduction of a service that allows users to output images from Stable Diffusion without launching a full-fledged UI.
The service is built on Google Colab and allows for the execution of programming source code to run Stable Diffusion.
Overcoming the technical barrier of launching UI for Stable Diffusion using Python in a Google Colab environment.
The presenter's channel shares convenient tools and information related to AI, with an emphasis on community building.
The service, referred to as C Art, is a web service that outputs Stable Diffusion images online.
The service offers a user experience similar to the traditional Stable Diffusion web UI, but without the need for technical setup.
C Art allows users to upload their own models and use a control net feature, which is not available in other web services.
The service provides a wide variety of models, including popular ones from the Chillout Mix, and allows for customization.
Users can change the aspect ratio of images, use negative prompts, and adjust sampling steps, cfg scale, and seed values.
The service supports the addition of the Lola model, enhancing its capabilities further.
Japanese prompts are also supported, demonstrating the service's versatility in language handling.
The UI is user-friendly, allowing for easy navigation and adjustments to image quality and variations.
The service includes a control net feature that can utilize tiles for more precise image generation.
The service is currently free to use, but will eventually require the use of in-service currency called 'coins'.
Users can earn coins by logging in daily and referring other users, allowing for continued free use of the service.
The service's terms of use indicate that commercial use is not prohibited, but users must bear the associated risks.
The presenter encourages users who were previously discouraged by the setup of Stable Diffusion to try this service.
The presenter suggests learning to set up the traditional web UI for more customization options in the future.
The video ends with a call to action for viewers to like, subscribe, and join the AI-focused community for more shared resources.