AI로 실제사진 만들어 내는 방법.너무 쉽고 간단해서 바로 할 수 있습니다. AI 사진, AI 그림
TLDRIn this informative video, the creator, Titan, guides viewers through the process of generating realistic images using AI with Stable Diffusion web UI. The tutorial begins with downloading necessary files, including a checkpoint model, a face-specific model (Lora), a VAE file for image quality enhancement, and a negative prompt file to avoid unwanted features. Titan then explains how to install and set up Stable Diffusion web UI using Google Colab, a cloud-based computing service. The video continues with a detailed walk-through of the configuration process, including setting up the models, adjusting sampling methods, and defining negative prompts. Finally, Titan provides tips on crafting effective prompts to achieve desired image results, emphasizing the importance of balancing the cfg scale for quality and creativity. The video concludes with a reminder of the non-commercial use restrictions for the models and a promise to delve deeper into the topic in future videos.
Takeaways
- 📸 The video provides a tutorial on creating AI-generated images resembling real photos.
- 🔗 The process involves downloading four specific files: a checkpoint file, a lora file, a vae file, and a negative prompt file.
- 🖼️ The checkpoint file (7 Outmix) is a model that generates the overall image, while the lora file focuses on specific parts, typically the face.
- 🎨 The vae file is used for post-image generation adjustments to achieve a more photo-like quality.
- 🚫 The negative prompt file helps to prevent unwanted elements, such as unnecessary fingers or limbs, from appearing in the generated image.
- 💻 The tutorial suggests using Google Colab for a cloud-based computing experience, which can provide high-performance computing capabilities regardless of the user's local hardware.
- 🔗 The video provides links for downloading the necessary files and guides on how to install and use the Stable Diffusion web UI.
- 📝 The user is instructed to upload the downloaded files to Google Drive and set up the Stable Diffusion web UI with these files.
- 📝 The video script includes detailed instructions on how to input prompts and use the Stable Diffusion web UI to generate images.
- 📌 The script emphasizes the importance of following the tutorial step by step and not giving up, even if the process seems complex at first.
- 📝 The video creator plans to release a more in-depth tutorial video later, covering advanced techniques for refining the image generation process.
- ⚠️ The video includes a disclaimer about the use of the AI model, stating that it cannot be used for commercial purposes unless the model name and a link to the model card are clearly stated.
Q & A
What is the main purpose of the video?
-The main purpose of the video is to guide viewers on how to create realistic images using AI, specifically through the Stable Diffusion web UI.
How many files does the user need to download before starting?
-The user needs to download a total of four files: a checkpoint file, a lora file, a vae file, and a negative prompt file.
What is the role of the checkpoint file in the process?
-The checkpoint file, named '7-Aoutmix', serves as the overall model that helps generate the entire image.
What is the purpose of the lora file?
-The lora file is a model that focuses on a specific part of the image, typically the face, to refine and improve its quality.
Why is the vae file important?
-The vae file is used for post-processing the generated images, helping to achieve a higher quality that resembles real photographs.
What does the negative prompt file do?
-The negative prompt file helps to prevent unnecessary elements, such as extra fingers or limbs, from appearing in the generated images.
How does the user access Google Colab?
-The user can access Google Colab by following a link provided in the video, which allows them to use Google's network and computing resources without needing high-end hardware.
What is the significance of the 'cfg scale' setting in the Stable Diffusion web UI?
-The 'cfg scale' setting determines how much the AI will reflect the user's input in the generated image. A lower value gives the AI more autonomy, while a higher value keeps the AI within the boundaries of the prompt.
How does the user ensure the generated images are of high quality?
-The user can ensure high-quality images by adjusting settings like 'sampling steps' and 'cfg scale', as well as using the right combination of positive and negative prompts.
What is the role of the 'seed' in the Stable Diffusion web UI?
-The 'seed' setting allows the user to fix a specific image result, ensuring that the AI generates a consistent outcome each time the same seed is used.
What is the importance of the 'negative prompt' in the process?
-The 'negative prompt' helps to exclude unwanted elements from the generated image, ensuring that the final result aligns more closely with the user's desired outcome.
What is the user's plan for the follow-up video?
-The user plans to create a follow-up video that will provide a more detailed explanation on how to apply the techniques demonstrated in the current video to generate better quality images.
Outlines
📌 Introduction to AI Image Creation Process
The speaker, Titan, apologizes for the delay in explaining the complex process of creating AI-generated images resembling real photos. They plan to provide a simplified method for extracting images and will cover detailed explanations in future videos. The speaker emphasizes that the process is not as complicated as it seems and encourages viewers to follow along without giving up, even if it seems complex at first.
📂 Preparing Files and Installing Stable Diffusion Web UI
The speaker instructs viewers to download four specific files necessary for the image creation process: a checkpoint file named '7 Outmix', a 'Lora' file for facial details, a 'VAE' file for image post-processing, and a 'Negative Prompt' file to prevent unwanted features. They explain the installation of Stable Diffusion Web UI, offering both local and Google Colab cloud options. The speaker guides viewers through the process of setting up Google Colab, which allows users to access high-performance computing resources without needing a powerful local computer.
🔧 Configuring Stable Diffusion Web UI and Prompt Settings
After completing the installation, the speaker explains how to upload and configure the downloaded files within the Stable Diffusion Web UI. They detail the process of setting up the checkpoint, Lora, VAE, and negative prompt files. The speaker then describes the user interface, explaining the purpose of the prompt input fields, sampling methods, and other generation options. They also discuss the importance of maintaining the correct file names for the negative prompt to function properly.
📝 Crafting Prompts and Understanding AI Image Generation
The speaker provides guidance on crafting positive and negative prompts for the AI image generation process. They explain the significance of the 'Lora' and 'Negative Prompt' file names in the prompts and how to adjust the influence of these files on the final image. The speaker also covers the importance of the seed value for generating specific image outcomes and provides a default prompt for beginners. They mention the limitations of using the AI model for commercial purposes and remind viewers to credit the model and include a link to the model card when hosting or using the model outside of personal use.
Mindmap
Keywords
💡AI
💡Stable Diffusion
💡Google Colab
💡Checkpoint
💡LoRA
💡VAE
💡Negative Prompt
💡Text-to-Image
💡Sampling Method
💡CFG Scale
💡Seed
Highlights
The speaker is explaining the process of creating AI-generated images that resemble real-life photographs.
The process is complex, and the speaker has been contemplating how to simplify it for an audience.
The speaker plans to prepare a detailed, in-depth video on the subject, but today will focus on a simplified method.
There are four files that need to be downloaded before starting the process.
The first file, '체크 포인트' (Checkpoint), is a model that provides the overall image.
The second file, '로라' (Lora), is a model that focuses on specific parts, typically the face.
The third file, 'vae', is used for post-generation image adjustments to achieve a more photo-like quality.
The fourth file, '네티티브 프롬프트' (Negative Prompt), helps to prevent unnecessary elements like extra fingers or limbs from appearing in the generated image.
The speaker will guide the audience through the installation of Stable Diffusion Web UI, which can be done locally or using Google Colab.
Google Colab allows users to access Google's network and use Google's computers, providing high performance even on low-spec computers.
The speaker provides a step-by-step guide on how to access and use Google Colab for the image generation process.
The speaker emphasizes the importance of following the tutorial closely and not giving up, even if it seems complex at first.
The speaker explains how to upload the downloaded files to Google Drive and use them in the Stable Diffusion Web UI.
The speaker provides detailed instructions on how to set up the Stable Diffusion Web UI with the downloaded files.
The speaker discusses the various settings and options available in the Stable Diffusion Web UI, such as sampling methods and generation options.
The speaker explains the use of positive and negative prompts to guide the AI in generating the desired image.
The speaker warns about the commercial use of the models and their derivatives, emphasizing the need to credit the model and include a link to the model card.
The speaker plans to create a follow-up video with more detailed instructions on how to improve the quality and accuracy of the generated images.
