Inject Yourself into the AI and Make Any Image With Your Face! (100% FREE Method)

Matt Wolfe
17 Nov 202217:22

TLDRIn this video, Matt Wolf, also known as e, introduces viewers to the world of AI art and demonstrates how to generate personalized images using AI. The process involves collecting around 20 images of oneself from various angles and backgrounds, resizing them to 512x512 pixels, and renaming them to match the desired prompt. The tutorial guides viewers through setting up an account with Hugging Face, obtaining an API token, and using a specific URL to upload images and train the AI model. The AI is then trained with a set number of steps, and the user can adjust parameters to refine the output. The final step involves generating images using a prompt, which can be customized to include specific scenarios or styles. The video also suggests using Lexica.art to find stylistic prompts and offers tips on how to modify prompts for better results. The result is a fun and creative way to put one's face on various images, suitable for social media profiles, YouTube thumbnails, or NFTs.

Takeaways

  • 📷 **Collect Photos**: Gather around 20 photos of yourself from various angles, backgrounds, and clothing to train the AI.
  • 🖼️ **Image Size**: Ensure all photos are resized and cropped to a 512x512 pixel aspect ratio.
  • 🔄 **Rename Files**: Rename the image files to match the prompt that will be used to generate the AI images.
  • 🔗 **Visit URL**: Visit the provided URL and follow the on-screen instructions to get started.
  • 💻 **System Check**: Check the type of GPU and VRAM available and install the necessary requirements.
  • 🤗 **Hugging Face Account**: Sign up for a free Hugging Face account and accept the terms and conditions.
  • 🔑 **Access Token**: Generate a new access token from Hugging Face and use it in the project.
  • 📁 **Save to Drive**: Save the project to Google Drive for easy future access and reuse.
  • 🧠 **Model Training**: Adjust the number of class images and training steps for optimal AI learning.
  • ⏱️ **Training Time**: Be prepared for a lengthy training process, which may take 30 minutes to an hour.
  • 🚀 **Start Training**: Upload your images and start the training process, keeping the webpage active to prevent timeouts.
  • 🖌️ **Customize Prompts**: Use unique keywords and adjust prompts to control the style and content of the generated images.
  • 🌟 **Stylize Images**: For stylized images, explore prompts from Lexica.art and adapt them to include your unique keyword.
  • 🔄 **Experimentation**: Tweak the random seed number and guidance scale to get different variations of the generated images.
  • 📂 **Save Outputs**: Save the generated images to your desired location for future use.

Q & A

  • What is the purpose of the video by Matt Wolf?

    -The purpose of the video is to guide viewers on how to use AI art to generate images with their own face on various objects or scenes.

  • How many images of oneself are needed to start the AI art generation process?

    -You need about 20 images of yourself, including close-up headshots and waist-up shots from different angles, backgrounds, and clothing.

  • What should be the dimensions of the images used for training the AI?

    -All images should be resized and cropped to exactly 512 by 512 pixels.

  • How does one rename the image files to help with the AI training process?

    -You should rename the files with the prompt that you plan to use, which helps your name or chosen identifier to show up more prominently in the generated images.

  • What is the URL mentioned in the video used for?

    -The URL is used to access the website where the AI art generation process is carried out by following the steps provided on the site.

  • Why is signing up for a Hugging Face account necessary?

    -Signing up for a Hugging Face account is necessary to log in and accept the terms and conditions, which is a step required to use their models and APIs for the AI art generation.

  • What is the role of the access token in the process?

    -The access token is used to connect your Hugging Face account with the project, allowing the AI to access the necessary resources for generating the images.

  • How long does the training process typically take?

    -The training process can take anywhere from 30 minutes to an hour, depending on various factors such as the complexity of the model and the processing power available.

  • What is the significance of the 'instance prompt' in the AI art generation?

    -The 'instance prompt' is a unique keyword that you use to tell the AI to replace a specific face in the generated image with your own. It should be something unique to avoid confusion with common terms.

  • What is the recommended range for 'Max train steps' when training the AI?

    -The recommended range for 'Max train steps' is between 1000 and 2000, as it provides a good balance between training quality and processing time.

  • How can one change the style of the generated images?

    -One can change the style of the generated images by using different prompts, adjusting the guidance scale, changing the seed number, or modifying the dimensions of the output image.

  • Where can one find inspiration for stylized prompts for AI art generation?

    -One can find inspiration for stylized prompts on websites like Lexica dot art, which showcases AI-generated images along with the prompts used to create them.

Outlines

00:00

🎨 Introduction to AI Art and Personalized Image Generation

Matt Wolf, also known as e,flow, introduces the concept of AI art and demonstrates how to generate images with one's own face using AI. He explains the process requires about 20 images of oneself in various angles, backgrounds, and clothing. These images should be 512 by 512 pixels and renamed to the prompt used for generating the AI art. The video provides a step-by-step guide on using a specific URL to access the AI tool, installing necessary requirements, and logging into Hugging Face to accept terms and conditions. It also covers the creation of an access token for the API and setting up the training environment with Google Drive.

05:01

📂 Setting Up the AI Training Environment and Uploading Images

The paragraph details the process of setting up the AI training environment. It involves navigating to the instance prompt, class prompt, and data directories, renaming them appropriately, and uploading 20 pre-cropped images of oneself into the designated folder. The video also explains how to start the training process by adjusting specific settings, such as the number of class images and the maximum training steps, to optimize the AI model. It emphasizes the importance of staying active on the website during the training process to prevent timeouts and provides a practical approach to multitasking during the training period.

10:01

🖼️ Generating Preview Images and Converting Weights

After the training process, which may take around 37 minutes, the video moves on to generating a grid of preview images to ensure the AI has learned the user's likeness accurately. It then guides on converting the trained weights into a format that can be reused in the future, which is saved to Google Drive. The process also includes running an inference script and setting a random seed for image generation, allowing for different outcomes with each generation by changing the seed number.

15:04

🎭 Customizing and Stylizing AI Generated Images

The final paragraph focuses on customizing the AI-generated images by using a prompt with a keyword unique to the user, followed by descriptors like 'person,' 'man,' or 'woman.' It discusses the importance of the guidance scale and the number of samples for generating images with the desired level of detail. The video also reveals a trick for achieving stylized images by using prompts from Lexica dot art, a site that showcases AI-generated images. By replacing a celebrity's name in a prompt with the user's keyword, unique and stylized images can be created. The video concludes with tips on saving the generated images and potential uses for them, such as YouTube thumbnails or profile pictures.

Mindmap

Keywords

💡AI art

AI art refers to the use of artificial intelligence in the creation of art. In the context of the video, AI art involves generating images with the user's face on them, which can be applied to various scenarios and styles. The process is showcased as a creative and innovative way to produce personalized artwork.

💡Image generation

Image generation is the process of creating visual content using algorithms and computational models. In this video, the term is used to describe how AI can generate a wide array of images with the user's face, demonstrating the flexibility and potential of AI in artistic creation.

💡512 by 512 pixels

This term refers to the resolution of the images used for training the AI. Each image must be resized and cropped to measure exactly 512 pixels by 512 pixels to maintain a consistent aspect ratio, which is crucial for the AI to effectively learn and replicate the user's face.

💡Hugging Face

Hugging Face is a company that provides tools and services for natural language processing and AI. In the video, the presenter instructs viewers to sign up for a Hugging Face account and use their platform to facilitate the AI image generation process, highlighting its role in the contemporary AI landscape.

💡API

API stands for Application Programming Interface, which is a set of rules and protocols that allows different software applications to communicate with each other. In the context of the video, the presenter connects to the Hugging Face API to utilize their services for the AI image generation.

💡Training data

Training data is the set of information used to teach a machine learning model. In the video, the user's collection of 20 images is the training data that helps the AI learn to recognize and replicate the user's face across different images.

💡Instance prompt

An instance prompt is a specific keyword or phrase used to guide the AI in generating images. The video describes using a unique instance prompt, such as 'Mr e flow,' to ensure that the AI replaces another person's face with the user's face in the generated images.

💡Max train steps

Max train steps refers to the maximum number of iterations the AI will perform during the training process. The video suggests that a range of 1000 to 2000 steps is optimal for training the AI without overfitting, which could result in a less accurate representation of the user's face.

💡Google Drive

Google Drive is a cloud storage service that allows users to store and share files online. In the video, it is used as a storage solution to save the trained model and generated images, making it easier for the user to access and reuse their AI-generated content.

💡Negative prompt

A negative prompt is a keyword or phrase that instructs the AI to exclude certain elements from the generated images. The video mentions using negative prompts to ensure that unwanted elements do not appear in the final AI-generated images.

💡Guidance scale

The guidance scale is a parameter that controls the level of detail and style in the AI-generated images. The video suggests adjusting the guidance scale between 5 and 15 to achieve the best image quality, avoiding overly dull or overly detailed results.

Highlights

AI art allows you to generate images with your face on them.

You can create any image you can imagine with your face on it.

20 images of yourself are required, with varying angles, backgrounds, and clothing.

Images should be resized and cropped to 512 by 512 pixels.

Rename image files to match the prompt for better AI training.

A long URL is provided for the process, which will be available in the comments or blog post.

Sign up for a Hugging Face account to use their AI model.

Accept terms and conditions on the model card page while logged into Hugging Face.

Create an access token in Hugging Face for the project.

Install Xformers from pre-compiled Wheel.

Save your trained images to Google Drive for future use.

Use a unique keyword as an instance prompt for your face in the AI.

Upload 20 images of your face into the designated directory.

Set the number of training steps between 1000 and 2000 for optimal results.

Keep the site active to prevent timeout during the 30-40 minute processing time.

After training, generate a grid of preview images to check the AI's work.

Convert weights tockpt for future use of the trained model.

Use a random seed to generate images, which can be changed for different results.

Adjust the guidance scale and the number of samples for varying image styles.

Explore Lexica art for stylistic prompts and adapt them for your own use.

Replace celebrity names in prompts with your unique keyword for personalized AI images.

Save generated images for use in thumbnails, profile pictures, NFTs, and more.