Stable Diffusion Realistic AI Consistent Character (Instant Method Without Training)

27 Sept 202306:47

TLDRThis video script introduces a method for achieving consistent facial imagery using stable diffusion and the epic realism checkpoint model. It guides viewers on setting up essential tools, using extensions like ultimate SD upscale and ROOPE, and replacing faces in images with high-quality results. The process involves painting over the face, adjusting settings for realism, and upscaling with skin enhancement for a seamless blend. The tutorial aims to help users create an AI modeling account on Instagram with impressive outcomes, emphasizing the potential for variation in results based on original image characteristics.


  • 🎨 The script introduces a method for achieving consistent facial imagery using stable diffusion and generative AI.
  • πŸ–ΌοΈ The goal is to blend a generated face with a real-life photograph seamlessly, without additional editing tools.
  • 🌐 The method is suggested as a potential technique for starting an AI modeling account on Instagram.
  • πŸ† The 'epic realism checkpoint' model is highlighted as a crucial tool for this process.
  • πŸ“š Users are directed to a previous video for more information on the 'epic realism checkpoint' model.
  • πŸ”§ The setup involves downloading and installing specific models and extensions for stable diffusion.
  • πŸ–ŒοΈ The painting process is detailed, with emphasis on settings like mask padding pixels and sampling method.
  • πŸ“ The script provides guidance on image resolution and aspect ratio for optimal results.
  • πŸ” 'Control net' is introduced as a feature of Automatic 1111, with a focus on 'face only' preprocessing.
  • πŸ‘€ The 'Group' extension is mentioned as a tool for face replacement in images without the need for extensive training.
  • πŸ”Ž The importance of using high-quality portrait pictures for target faces is stressed for better outcomes.

Q & A

  • What is the main challenge discussed in the video script related to generative AI and image?

    -The main challenge discussed is maintaining a consistent face using generative AI, specifically when working with stable diffusion.

  • What is the purpose of using the epic realism checkpoint model in this context?

    -The epic realism checkpoint model is used to achieve high-quality, realistic results when generating or replacing faces in images, ensuring that the generated face seamlessly blends with the rest of the image.

  • How does the video script suggest enhancing skin details and imperfections in the generated images?

    -The script suggests using an extension called 'epic realism helper Laura' to enhance skin details and add more imperfections to the generated images, making them look more realistic.

  • What are the two extensions needed for the automatic 1111 to perform the face replacement and upscaling process?

    -The two required extensions are 'Ultimate SD Upscale' for upscaling the images and 'Roop' for face replacement in images.

  • What is the recommended aspect ratio and dimensions for the images when using the epic realism checkpoint model?

    -The recommended aspect ratio is 1024 in width and 1536 in height, which is achieved by using the aspect ratio calculator in the automatic 1111 interface.

  • How does the video script guide users to ensure the generated face blends seamlessly with the original image?

    -The script guides users to use the 'Group' extension for face replacement, adjust settings such as mask padding pixels, sampling method, and sampling steps, and utilize the 'Ultimate SD Upscale' extension for upscaling the image to ensure a seamless blend.

  • What is the significance of the control net in the process described in the video script?

    -The control net, when using the 'open pose' and 'face only' options, helps in achieving a more accurate and realistic face replacement by controlling the generation process based on the input image and the chosen parameters.

  • What is the role of the 'pixel perfect' option in the control net process?

    -The 'pixel perfect' option ensures that the generated face closely matches the details and quality of the original image, maintaining the integrity of the face replacement.

  • How does the script suggest users evaluate the results of the face replacement?

    -Users should evaluate the results by checking if the replaced face looks familiar yet not 100% identical to the target, considering factors like original face shape, pose, and lighting conditions.

  • What is the final recommendation made in the video script for users interested in this method?

    -The final recommendation is to experiment with different checkpoint models and settings to achieve consistent and realistic face replacements, and to apply the method to other images to test its effectiveness.

  • How can users stay updated with future episodes and tutorials?

    -Users are encouraged to subscribe to the channel and hit the like button on the video to support the content and receive notifications for future episodes and tutorials.



🎨 Introducing Stable Diffusion for Consistent AI Modeling

This paragraph introduces the challenge of maintaining a consistent face in the realm of generative AI and image creation. It highlights the use of Stable Diffusion, specifically the epic realism checkpoint model, to achieve this goal. The video's objective is to test the method using stock photos and to demonstrate if the generated face can blend seamlessly with a real-life photograph without additional editing tools. The paragraph also provides instructions on setting up the necessary tools, including downloading the model and extensions, and outlines the initial steps for the AI modeling process, emphasizing the use of the epic realism checkpoint and helper models for enhanced skin details and imperfections.


πŸ–ΌοΈ Enhancing and Upscaling AI-Generated Images

The second paragraph delves into the process of enhancing and upscaling AI-generated images. It discusses the use of extensions like Ultimate SD Upscale and ROOPE for face replacement in images. The paragraph provides a detailed walkthrough of the painting process, focusing on settings such as mask padding pixels, sampling method, and dimensions for optimal results. It also explains how to use the aspect ratio calculator and control net for better image generation. The paragraph concludes with a demonstration of the seamless face replacement and the application of skin enhancement and upscaling techniques, showcasing the realistic outcomes possible with the described method.



πŸ’‘Generative AI

Generative AI refers to the branch of artificial intelligence that focuses on creating new content, such as images, music, or text, through machine learning algorithms. In the context of the video, generative AI is used to maintain a consistent face in images, which is crucial for creating an AI modeling account on platforms like Instagram.

πŸ’‘Stable Diffusion

Stable Diffusion is a type of generative AI model that specializes in image synthesis and manipulation. It allows users to generate, edit, and transform images by understanding and applying the content of the images. In the video, Stable Diffusion is the platform used to achieve the goal of creating a consistent face across different images.

πŸ’‘Realism Checkpoint Model

The Realism Checkpoint Model is a specific type of AI model designed to enhance the realism of generated images. It focuses on improving the quality and believability of the images by adding realistic details and textures. In the video, this model is used to ensure that the generated face appears lifelike and seamlessly integrates with the rest of the image.


Extensions, in the context of the video, refer to additional software components or plugins that enhance the functionality of the primary AI model. They provide specialized features or improvements to the base model, such as upscaling images or enhancing skin details.

πŸ’‘Epic Realism Helper

Epic Realism Helper is an extension that focuses on enhancing the skin details and adding more imperfections to the generated images. This extension aims to make the images appear more realistic by simulating the natural variations and textures found in human skin.

πŸ’‘Control Net

Control Net is a feature within the AI modeling software that allows users to have more control over the generation process by specifying certain aspects of the image, such as the pose or facial features. It helps to guide the AI to produce results that align more closely with the desired outcome.


Upscaling refers to the process of increasing the resolution or size of an image while maintaining or improving its quality. This is particularly important in the context of the video, as it allows the generated images to be enlarged without losing detail or clarity.

πŸ’‘DPM++ Karras

DPM++ Karras is a sampling method used in the generative AI models to refine the image generation process. It is an advanced technique that helps to produce higher quality images by optimizing the sampling steps and improving the transitions between different parts of the image.

πŸ’‘Noise Strength

Noise strength is a parameter in AI image generation that controls the level of random variation or 'noise' introduced into the generated image. Adjusting noise strength can affect the overall texture and detail of the image, with higher values potentially adding more detail but also more randomness.

πŸ’‘Aspect Ratio

Aspect ratio refers to the proportional relationship between the width and height of an image. Maintaining a consistent aspect ratio is important for ensuring that the image looks balanced and undistorted when displayed on various platforms or devices.

πŸ’‘Pixel Perfect

Pixel Perfect is a term used to describe an image or design that is optimized at the pixel level, ensuring that it looks crisp and clear without any distortion or blurriness, especially when viewed on digital screens. In the context of the video, Pixel Perfect is a setting that helps to enhance the quality of the generated images.


Maintaining a consistent face in generative AI imagery can be challenging, but the video presents a method to achieve this using stable diffusion.

The method is suitable for starting an AI modeling account on Instagram, offering incredible results.

The test involves using stock photos and a realism checkpoint model to blend a generated face with a real-life photograph without additional editing tools.

The essential tool for this method is the epic realism checkpoint model, which can be downloaded and installed in the stable diffusion folder.

Enhancing skin details and imperfections is achieved by using the epic realism helper, Laura.

Two extensions, Ultimate SD Upscale and ROOPE, are required for the process and can be installed through automatic 1111.

The epic realism checkpoint is used to replace a face in an image by focusing on the face and neck during the painting process.

Settings for the process include mask padding pixels, sampling method, dimensions, CFG scale, and noise strength.

Control net is used for face replacement, with the open pose and face-only preprocessor settings.

The Group extension for stable fusion's automatic 1111 enables face replacement based on a single image without Laura training.

A high-quality portrait picture is used as the target face, with simple positive and negative prompts for the generation process.

Upscaling and skin enhancement are applied simultaneously using the Laura and Ultimate SD Upscale extensions.

The 4X NMKD Superscale is selected for upscaling, which works well with the epic realism helper.

The outcome shows a seamless blend of the replaced face with the original image, demonstrating realistic skin texture.

The method can yield consistent results when applied to other images, though variations may occur based on factors like face shape, pose, and lighting.

The tutorial encourages the use of this method with other checkpoint models for diverse applications.