【神サービス】Stable DiffusionのWEB UIはもう不要！【プログラミング無し】

KEITO【AI&WEB ch】
10 Jun 202309:11

TLDRThe video introduces a web service that allows 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 selection of models, including popular ones from ChitAI's model sharing service. The service is currently free to use, with a system in place to earn coins for generating images, though future use may require coin consumption. The video encourages viewers to try the service, especially those who found setting up their own environment challenging, and suggests learning more about web UI customization for further customization needs.

Takeaways

  • 🌟 Introduction of a service that allows users to output Stable Diffusion images without setting up a WEBUI.
  • 🔍 The service overcomes the technical barriers associated with running Python in a Google Colab environment to set up Stable Diffusion UI.
  • 📸 Users who found it difficult to use Stable Diffusion can now utilize this service to generate images easily.
  • 🎨 The service, referred to as C Art, mimics the experience of using the traditional Stable Diffusion WEBUI but with added functionalities.
  • 🖼️ Users can upload their own models and use control net functionalities within the web application.
  • 🌐 The service offers a wide selection of models, including popular ones like Chit Mix, and allows for aspect ratio adjustments.
  • 🔄 The service supports Japanese prompts and can generate images based on them, showcasing its versatility.
  • 📈 The service is not free indefinitely; it requires a 'coin' for generating images, which is currently available for free on a limited basis.
  • 🎁 Users can earn coins by signing in daily and referring others, enabling them to generate more images.
  • 🚫 Commercial use is not explicitly prohibited, but users are advised to bear the associated risks themselves according to their country's laws.
  • 📚 For those interested in learning more about Stable Diffusion and AI, the speaker recommends joining their specialized community and checking out the materials shared there.

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 output images using Stable Diffusion without setting up a WEBUI.

  • What is the difficulty associated with using Stable Diffusion traditionally?

    -Traditionally, using Stable Diffusion requires a technical barrier such as setting up a programming environment and executing source code, which can be challenging for some users.

  • What is the name of the web service introduced in the video?

    -The name of the web service introduced in the video is C Art.

  • How does C Art differ from other Stable Diffusion web services?

    -C Art differs from other web services by offering a user experience that closely resembles the traditional Stable Diffusion WEBUI, including features like model uploading, control net functionality, and various image generation options.

  • What are some of the features available on C Art that are similar to the traditional Stable Diffusion WEBUI?

    -C Art offers features such as model uploading, control net functionality, image-to-image transformations, mood adjustments, aspect ratio changes, negative prompts, sampling steps, cfg scale, seed values, and the ability to add Lola models.

  • Is it possible to use C Art with Japanese prompts?

    -Yes, C Art can process Japanese prompts and generate images according to the user's request.

  • How does the control net feature work on C Art?

    -The control net feature on C Art allows users to upload an image and use it as a guide for generating new images, ensuring that the output reflects the characteristics of the uploaded image.

  • What are the pricing plans for C Art?

    -C Art has a pricing plan that requires the use of coins to generate images. However, at the time of the video, the service is available for free on a limited-time basis.

  • How can users earn coins on C Art?

    -Users can earn coins by logging in daily, referring new users, and completing various tasks listed on the platform.

  • What is the policy on commercial use of C Art?

    -The official terms of service state that commercial use is prohibited, but users are responsible for adhering to their country's laws and bearing any associated risks.

  • What is the recommendation for users who want to learn more about Stable Diffusion?

    -The video suggests that users who are interested in learning more about Stable Diffusion should try out C Art for free, and if they want to delve deeper, they can explore setting up the traditional WEBUI on their own computers.

Outlines

00:00

🌟 Introducing a Powerful Stable Diffusion Service

The paragraph introduces a service that allows users to generate Stable Diffusion images without the need for a complex web UI setup. The speaker explains that typically, one would need to set up a programming environment using Google Colab and input source code to run the UI for Stable Diffusion. However, this service clears the technical barriers, making it accessible for those who found it challenging to set up. The speaker also mentions their channel, which shares AI-related tools and information, and invites viewers to subscribe and explore their AI-focused community.

05:01

🎨 Exploring C Art: A Feature-Rich Web Service for Stable Diffusion

This paragraph delves into the features of the C Art web service, which enables users to generate Stable Diffusion images online. The service is highlighted for its resemblance to the traditional Stable Diffusion web UI, offering advanced features such as model uploading, control net functionality, and text-to-image capabilities. The speaker notes the variety of models available, including popular ones from the Chibit AI model sharing service. The service also supports Japanese prompts, demonstrating its versatility. The paragraph concludes with a discussion on the service's pricing plans, free usage options, and potential for commercial use, advising users to adhere to their country's rules.

Mindmap

Keywords

💡Stable Diffusion

Stable Diffusion is an AI model that generates images from textual descriptions. It is a type of deep learning model that has gained popularity for its ability to create high-quality, realistic images. In the video, the speaker discusses a service that allows users to utilize Stable Diffusion without the need to set up a complex web UI, making it more accessible for image generation.

💡Web UI

Web UI refers to the user interface that is presented through the web, allowing users to interact with applications or services via a web browser. In the context of the video, the speaker talks about the traditional method of using Stable Diffusion, which involves setting up a Web UI, but the service they introduce aims to simplify this process.

💡Control Net

A Control Net is a feature within image generation AI models like Stable Diffusion that allows users to guide the generation process by providing additional input or constraints. It serves as a tool to fine-tune the output based on specific requirements or styles. In the video, the speaker highlights that the new service includes a Control Net feature, enabling users to have more control over the generated images.

💡Dream Studio

Dream Studio is an official web application developed by Stability AI that utilizes the Stable Diffusion model for image generation. It is known for its user-friendly interface and is mentioned in the video as a comparison to the new service being introduced, which offers more features and flexibility.

💡Model Upload

Model Upload refers to the ability to load custom AI models into a service or application. In the video, the speaker discusses a web service that allows users to upload their own models for image generation, which is a significant feature not commonly found in other similar web services.

💡Aspect Ratio

Aspect Ratio is the proportion of the width and height of an image or video. It is a critical parameter in image generation services as it determines the shape and layout of the output. In the video, the speaker mentions that users can change the aspect ratio of the generated images, offering flexibility in the final product's appearance.

💡Negative Prompt

Negative Prompt is a technique used in AI image generation where the user provides additional instructions to the model to avoid certain elements or styles in the generated image. It helps guide the AI to produce more precise results by specifying what not to include. In the video, the speaker includes negative prompts as one of the many adjustable parameters in the new service.

💡Sampling Steps

Sampling Steps refer to the number of iterations or stages an AI model goes through to generate an image from a prompt. More steps often result in higher quality or more detailed images, but can also increase the computational cost. In the context of the video, the speaker discusses the ability to adjust sampling steps as part of the image generation process in the new service.

💡CFG Scale

CFG Scale, or Control Flow Graph Scale, is a parameter related to the control mechanisms within AI models that affects the granularity of control over the image generation process. Adjusting the CFG Scale can influence the model's ability to follow instructions and generate images that closely match the user's prompt. In the video, the speaker includes CFG Scale as one of the many customizable settings available in the service.

💡Seed Value

Seed Value is a starting point or initial value used by a random number generator in AI models to produce a sequence of random numbers. In image generation, changing the seed value can result in different variations of the same image based on the same prompt. The speaker in the video notes that users can alter the seed value to explore different outcomes from the image generation process.

💡Tile Function

Tile Function is a feature that allows users to input an image and use it as a pattern or template for generating new images. It can be used to create variations or to apply specific styles to the generated content. In the video, the speaker describes a scenario where the tile function is used to incorporate an existing image into the control process of generating a new image.

💡Commercial Use

Commercial Use refers to the application of a product, service, or technology for monetary gain or business purposes. In the context of the video, the speaker discusses the service's terms of use, noting that while commercial use is not explicitly prohibited, users are responsible for adhering to the laws and regulations of their respective countries.

Highlights

Introduction of a service that allows users to output Stable Diffusion images without launching a traditional UI.

The service clears the technical barriers associated with running Stable Diffusion on platforms like Google Colab.

The service is particularly useful for those who find the process of setting up Stable Diffusion UI too challenging.

The presenter's channel shares AI-related tools and information, and encourages viewers to subscribe.

The service, referred to as 'Cアート', mimics the experience of using the traditional Stable Diffusion web UI.

The service allows users to upload their own models and use control net functionality within the web application.

Users can select from a wide variety of models, including famous ones like the Chillout Mix.

The service supports Japanese prompts, showcasing its versatility in language support.

The service offers the ability to adjust image aspect ratio, negative prompts, sampling steps, cfg scale, and seed values.

The service includes the tile function for control net usage, allowing users to input specific images for style guidance.

The service is currently free to use, but will likely require a 'coin' system for image generation in the future.

Users can earn coins by logging in daily and referring users, allowing for continued free usage of the service.

The service's terms of use do not prohibit commercial use, but users are responsible for adhering to their country's laws.

The presenter encourages users who were previously discouraged by setting up Stable Diffusion to try this service.

The service provides a platform for users to generate images based on their prompts, with the potential for high-quality outputs.

The presenter suggests that users who wish to customize their UI further may still need to set up the traditional web UI on their computers.

The service's main features are comparable to the traditional Stable Diffusion web UI, making it a comprehensive tool for image generation.

The presenter concludes by encouraging viewers to try the service, especially since it is currently free, and to explore further learning resources.