Create Your Own AI Art Model with Open Art's Photobooth! (NO CODE BEST DREAMBOOTH)

The video begins with a greeting to viewers and a reference to a previous video about Google's DreamBooth, an open-source AI research project. The host explains that DreamBooth enables the creation of new images based on a series of input photos, which can include people, pets, objects, or styles. The technology is particularly useful for text-to-image generators like Stable Diffusion. The host then introduces a collaboration with OpenArt, a company that has released its own version of DreamBooth called Photo Booth, which offers distinct capabilities. The video promises to explore these features and provides a sneak peek at AI-generated images of the host, including a realistic self-portrait, a depiction as Napoleon Bonaparte, an action hero, and a terrifying evil demon clown. The host also navigates to the OpenArt website to demonstrate the simplicity of starting with Photo Booth and highlights the variety of example images available.

The host delves into the different categories available in OpenArt's Photo Booth, such as person, pet, character, art style, and object. Each category is tailored to specific types of image generation, with the character category being noted for its potential in creating fan art and bringing online community characters to life. The art style category is particularly interesting as it allows users to teach the AI a specific art style, which has significant implications for personalized and consistent image generation. The host also discusses the preset packages available in the OpenArt store, which can be applied to models for a fee, with the first package being free. The process of training a model is outlined, including the need for consent when using images of people or pets, and the guidelines for the number and type of images required for different categories. The host demonstrates how to upload images and fill out necessary fields for model training.

The host proceeds to train an AI model using a folder of lemon-themed images, aiming to create a 'lemon character.' The process involves selecting an identifier and class for the model, with the host choosing 'Lem' as the identifier and 'lemon character' as the class, along with additional descriptors like 'wearing sunglasses.' The host explains that training takes between 30 to 90 minutes and that users receive an email notification upon completion. While waiting, the host explores other models previously created, such as self-portraits and images of the host's dog, showcasing the variety of presets and upscaling options available. The host also demonstrates the upscaling and enhancement features, which improve the resolution and facial details of the generated images.

The host concludes by expressing satisfaction with the lemon character model's ability to generate coherent and varied images of the lemon character in different scenarios. The video emphasizes the potential of custom pre-trained models to produce high-quality, specific imagery that may not be achievable with base stable diffusion models. The host thanks viewers for watching, encourages them to explore OpenArt's Photo Booth through the provided link, and invites them to join the community on Discord for additional resources. The host also reminds viewers to subscribe to the channel for more content.