AI로 실제사진 만들어 내는 방법.너무 쉽고 간단해서 바로 할 수 있습니다. AI 사진, AI 그림
TLDRThe video script outlines a step-by-step guide on creating realistic images using AI through Stable Diffusion's web UI. It emphasizes the importance of downloading necessary files, setting up the environment with Google Colab, and fine-tuning the AI with specific prompts and parameters. The guide aims to simplify the process, making it accessible for anyone to follow, and promises a future in-depth video on enhancing the quality and precision of the generated images.
Takeaways
- 🌟 The speaker is introducing a method to create AI-generated images that resemble real photographs.
- 📂 The process involves downloading four specific files: a checkpoint file called '7-a-umix', a 'Lora' file for facial details, a 'VAE' file for image enhancement, and a 'Negative Prompt' file to avoid unwanted features.
- 🔗 The speaker provides links to download these files and emphasizes the importance of following the instructions carefully to achieve the desired results.
- 💻 The tutorial requires the installation of Stable Diffusion Web UI, which can be done locally or through Google Colab, depending on the user's computer specifications.
- 🔄 The speaker guides through the process of setting up the downloaded files in Google Drive and accessing them through Stable Diffusion Web UI.
- 🎨 The user interface of Stable Diffusion Web UI is explained, including the sections for prompts, negative prompts, sampling methods, and additional generation options.
- ⚙️ The speaker discusses the importance of adjusting parameters such as sampling steps, batch count, and size to balance quality and processing time.
- 📏 Aspect ratio, width, and height settings in the generation options are crucial for producing images with the desired dimensions.
- 🔢 The 'cfg scale' parameter determines how closely the AI adheres to the input prompts, with mid-range values offering a balance between creativity and adherence to the original request.
- 🛠️ The speaker provides a basic template for positive and negative prompts, emphasizing the need to match file names and adjust values according to the downloaded models.
- 🚫 A cautionary note is included regarding the use of the models for commercial purposes, advising users to credit the model names and include links to the model cards when hosting or using them outside of personal projects.
Q & A
What is the main topic of the video?
-The main topic of the video is about creating realistic images using AI, specifically through the use of Stable Diffusion web UI.
What are the four files that the viewer needs to download before starting?
-The four files are: 1) Checkpoint file, named '7 Outmix', 2) Lola file, which focuses on specific parts like faces, 3) VAE file for image post-processing to achieve a more photo-like quality, and 4) Negative Prompt file to prevent unwanted elements from appearing in the generated images.
How can one access the Stable Diffusion web UI?
-The viewer can access the Stable Diffusion web UI by visiting the official website, which is linked in the video description or can be found through a search engine.
What is the purpose of using Google Colab?
-Google Colab is used to utilize Google's network and computing resources, allowing users to perform tasks that require high computational power without needing a high-end computer.
What is the significance of tuning the settings in the Stable Diffusion web UI?
-Tuning the settings helps to refine the output of the generated images, adjusting factors like the influence of specific models, the quality, and the number of images produced in a batch.
How does the 'cfg scale' option affect the generated images?
-The 'cfg scale' option determines how much the AI will be influenced by the user's prompt. Lower values give more freedom to the AI, while higher values constrain the AI to stay within the boundaries of the prompt more strictly.
What is the role of the 'negative prompt' in the AI image generation process?
-The 'negative prompt' is used to specify elements that the user does not want to appear in the generated images, helping to avoid unwanted features or objects.
What is the recommended 'sampling method' for most users?
-For most users, the recommended sampling method is 'DPN+' or 'SDE Karas', as they provide a good balance between quality and processing time.
How can users ensure that they are using the AI models responsibly?
-Users should ensure that they do not use the models for commercial or non-commercial purposes without permission, and always credit the model's name and include links to the model's card or source when hosting or using the models.
What is the purpose of the 'seed' value in the generation options?
-The 'seed' value is used to fix the result of a specific image generation. If a user wants to reproduce the same image or result, they can input the same seed value.
What additional advice does the creator provide for users who find the process challenging?
-The creator advises users not to give up, to follow along with the video carefully, and to revisit the tutorial if they do not understand certain steps. They also suggest using AIprm from ChatGPT or Google Translate to help with prompt creation if needed.
Outlines
📝 Introduction to AI Image Creation Process
The speaker introduces themselves as Titan and explains the complex process of creating AI-generated images. They acknowledge the delay in explaining the process due to its complexity and promise to provide a straightforward method for creating photo-like images. The speaker emphasizes that despite the complexity, they will guide the audience step by step, ensuring that everyone can follow along. They mention the need to download four specific files before starting and provide links for these files, which are essential for the image creation process. The speaker also introduces the concept of using Google Colab for those with lower computer specifications, allowing them to utilize Google's network and computers for the task.
🔧 Setting Up Google Drive and Stable Diffusion Web UI
The speaker guides the audience through the process of setting up Google Drive and installing the Stable Diffusion Web UI. They detail the steps of downloading and installing the necessary files, such as the checkpoint, Lola, VAE, and negative prompt files. The speaker explains how to upload these files to Google Drive and use Google Colab for the image generation process. They also provide instructions on how to access and use the Stable Diffusion Web UI, including setting up the model and applying the files for image generation. The speaker emphasizes the importance of following the steps carefully to ensure successful installation and use of the system.
🎨 Customizing AI Image Generation with Prompts and Settings
The speaker discusses the customization of AI image generation through the use of positive and negative prompts. They explain how to use the Lola file to influence the generation of facial features and how to mix different Lola files to create a desired look. The speaker also covers the use of the VAE file for image refinement and the negative prompt file to exclude unwanted elements from the generated images. They provide a detailed explanation of the settings within the Stable Diffusion Web UI, such as sampling methods, steps, and other generation options. The speaker advises on the appropriate values for these settings to balance quality and processing time. They also mention the importance of adhering to the terms of use for the models and files, emphasizing that the content should be for non-commercial use and should include proper attribution.
Mindmap
Keywords
💡AI
💡Photograph-like images
💡Checkpoint file
💡LoRA file
💡VAE file
💡Negative prompt file
💡Stable Diffusion web UI
💡Google Colab
💡Prompt
💡Sampling method
💡Seed
Highlights
The video introduces a method for creating AI-generated images that resemble real-life photographs.
The process of creating these images is complex, but the video aims to simplify it for viewers.
There are four files that need to be downloaded beforehand for the process: a checkpoint file, a lora file, a vae file, and a negative prompt file.
The checkpoint file, named '7 Outmix', provides the overall structure of the generated image.
The lora file focuses on specific parts of the image, typically the face, and is used to concentrate on learning that area.
The vae file is responsible for post-generation image adjustments to achieve a more photo-like quality.
The negative prompt file prevents unnecessary elements, such as extra fingers or limbs, from appearing in the generated images.
The video provides a link to Google Colab for those who do not have high-end graphics cards on their personal computers.
Google Colab allows users to access Google's network and utilize Google's computers, enabling high-performance capabilities regardless of the user's computer specifications.
The video provides a step-by-step guide on how to install and use the Stable Diffusion web UI for generating images.
The process involves uploading the four downloaded files to Google Drive and setting them up within the Stable Diffusion web UI.
The video explains the importance of the 'seed' in generating consistent and replicable results.
The video emphasizes the need to adjust the 'cfg scale' to reflect the desired level of influence of the user's prompt on the AI-generated image.
The 'batch count' and 'batch size' options allow users to control the number of images generated per session.
The video provides a default prompt for users to start with, which includes the name of the lora file used.
The video discusses the limitations and guidelines for using the checkpoint file, especially regarding commercial use and hosting.
The video promises a follow-up video with more in-depth explanations and tips on improving the quality of AI-generated images.