Kasucast #7 - Using stable diffusion and textual inversion to create stylized character concept art

The speaker begins by greeting the audience and referencing their previous video where they mentioned experimenting with stable diffusion for character artwork. They express their intention to showcase some finished pieces to gauge audience interest in the style. The speaker also notes an update to the automatic 1111 repository, specifically the addition of a textual inversion tab. They recount their experience with textual inversion using a different repository and explain their process of creating a new embedding within the automatic repository. The speaker details their training approach, combining waifu diffusion 1.2 with stable diffusion 1.4, and shares the initialization text used. They also discuss the data set they prepared, which includes art from various artists they admire, such as Krenz Cushart, Choco Fing R, and others, highlighting the diversity and inspiration behind their selection.

The speaker continues by demonstrating the process of setting up a textual inversion embedding. They guide the audience through creating a new embedding, selecting a learning rate, and specifying the data set directory. The speaker emphasizes the importance of the prompt template file in directing the style of the artwork during the training phase. They also discuss their choice to use a combined model of waifu diffusion and stable diffusion, explaining their reasoning and the process of creating this custom model. The speaker provides a real-time update on the training progress, sharing the loss values and their thoughts on the significance of these values. They also touch upon the debate around the number of training steps and images, referencing both academic recommendations and anecdotal evidence from other users.

The speaker moves on to the application of the trained embedding to their artwork. They describe the process of selecting the embedding and entering prompts to guide the style of the generated art. The speaker shares their approach to image editing, including adjustments to sampling steps, denoising, and CFG settings. They also discuss the importance of the prompt structure, particularly the use of arrows and the inclusion of the artist's style in the prompt. The speaker provides examples of prompts they've used, such as 'oil painting of a beautiful female Sage in Alexander McQueen fashion,' and explains the reasoning behind the choice of words. They also mention the use of negative prompts to exclude unwanted elements from the generated images.

The speaker delves into the post-generation editing process using Photoshop. They discuss the use of the Hue/Saturation adjustment layer to correct color saturation and the spot healing brush to remove unwanted elements from the image. The speaker also demonstrates the use of the liquify tool to adjust facial features and the mixer brush for cleaning up areas of the image. They explain their approach to refining the artwork, focusing on details such as the character's ear and the clothing's texture. The speaker also shares their workflow for using the loopback feature, which allows them to iteratively improve the image by feeding the output back into the generation process.

The speaker concludes the video by detailing the final stages of image editing. They discuss the use of the high pass filter to sharpen the image and the Gaussian blur to create atmospheric effects. The speaker also demonstrates the use of the camera raw filter for color adjustments and the curves tool for enhancing the image's lighting and focus. They explain their technique of painting in darkness on non-focal areas to draw attention to the character's face. Lastly, the speaker shares their method of adding painterly effects to the image using a plugin, ensuring that the face remains polished while other areas take on a more traditional art style. The speaker wraps up by expressing hope that the workflow shared will be helpful to the audience.