NextLevel Images with Generative AI and Stable Diffusion GUI

Explore book cover design with generative AI and stable diffusion, choosing portrait or landscape formats and proper dimensions, such as 832 by 1216 in a 13 by 19 proportion.

Conduct the first experiments to generate a book cover by crafting prompts for stable diffusion, featuring a lone explorer in a coat and hat amid a mysterious mountain landscape.

Explore how to improve image quality using prompts, keyword weights, and symmetric composition in generative ai. Learn to apply color constraints, negative prompts, batch variations, and plan for future styles.

Use the style selector to quickly change image style and composition, centralizing elements with the keyword centralized at weight 1.5, while reviewing prompts, negative prompts, and color weights.

Learn to create small variations of images with identical prompts by adjusting the original seed and variation seed, and by using variation strength and batch count for multiple outputs.

Generate a final book-cover image by refining prompts, negative prompts, and a digital art style, then upscale and save using image-to-image workflows, ultimate upscaler, and denoising strength 0.25.

Add the book title to your ai-generated cover in Canva, upload the image, position the text, choose a white decorative font, add the author, and download as pdf.

Learn to generate science fiction book covers with stable diffusion, using style prompts, community prompts, prompt books, and artist references for varied cover concepts.

Generate three science fiction book covers by transforming descriptions into prompts with ChatGPT and a prompt generator. Space station Mars orbit and time travel through a vortex with vibrant colors.

Learn to generate science fiction book covers using ChatGPT prompts, Dream Shaper Excel with Stable Diffusion GUI, and optimize steps, seeds, and prompts for high-quality results.

Generate epic fantasy book covers by crafting prompts for dragon scenes with atmospheric elements like lightning, storm, and a full moon, using stable diffusion and the dream shaper model.

Generate nonfiction book covers with stable diffusion and the Dream Shaper model, using gourmet photo prompts and negative prompts to avoid cartoons, grayscale, and sketches.

Generate horizontal book covers in landscape mode by adjusting width and height to SD XL aspect ratios and resolutions, applying cyberpunk neon colors.

Discover prompts to create fictionary, 3D, architectural, and realistic scenarios using stable diffusion, from living room layouts to a futuristic city and a Norway landscape.

Learn to generate images with text using stable diffusion, download and load a text model, and combine prompts like text logo nebula with Laura and other extensions for better results.

Explore generating images with stable diffusion in Python via Google Colab notebook, install diffusers and transformers, load models, select schedulers, and save and upscale outputs.

Explore realistic image generation with the sd xl base model, compare it to realism-focused custom models, and use keywords like realistic, photo, and hyper detailed.

Learn to generate realistic images from prompts with the base model at 1024 by 1024, seed 777, exploring clean backgrounds and professional photography prompts.

Explore realism-focused diffusion models, including sd xl and 1.5 variants, and master prompts, negative prompts, and model-specific dimensions and schedulers in the Stable Diffusion GUI.

Generate images with realistic models using stable diffusion 1.5 at 512 by 512, apply a negative prompt to reduce blur, and compare results across Realistic Vision and Epic Realism.

Learn to improve face and hand quality using face and hands yolo detection, bounding boxes, and targeted model selection; combine text inversions and embeddings for sharper results.

Learn how to craft prompts to control photography style for people, detailing subject pose, framing, lighting, camera settings, and effects, with styles from candid to street fashion.

Explore prompts to describe age, hair, clothes, facial expressions, accessories, and moods, while guiding eye contact and poses for realistic image generation with stable diffusion.

Master photo framing by learning full shot, close up, eye line, and horizon line concepts, then apply camera angles to prompts for stable diffusion.

Develop an understanding of how backgrounds and environments shape image realism and context, using prompts to explore a green forest, mountains, spaceships, and golden sunset sunlight.

Explore lighting styles for generative AI images, from candlelight and cinematic lighting to ring lighting and low-key shadows, and learn how prompts shape output.

Explore camera angles in generative imaging, including level shots aligned with the eyes, low angles from below, high angles from above, and the Dutch angle for a diagonal, distorted perspective.

Explore camera settings and the shot on technique to simulate cinema and retro looks using diverse cameras, film types, and focal lengths.

Explore filters and effects, including black and white, bokeh, and lens flare. Use color tweaks like purple lights, blue lights, and red lights, and apply long exposure for dynamic images.

Craft complete prompts by combining style, subject details, lighting, and camera angle. Use filters, effects, and camera type with a default negative prompt and default parameters.

Learn to upscale realistic photos by choosing the right algorithms and parameters, doubling image size from 512x512 to 1024x1024 with controlled denoising, while focusing prompts on the environment.

Learn to control stable diffusion using control net and Open Pose key-point extraction to generate pose-consistent images from sketches, with practical steps for selecting control types, prompts, and settings.

Explore character creation with stable diffusion and generative AI, using Cosmo the Adventures Panda astronaut as a hands-on example across literature, games, cinema, education, and marketing in NextLevel images course.

Conduct tests to create a panda astronaut returning to stable diffusion, using green shaper excel, adjusting sampling, steps, resolution, and keywords like 'cute panda astronaut' to achieve a cartoon look.

Experiment with multiple styles—3D model, digital art, fantasy art, anime, and RPG fantasy game—to tailor the character visuals, using prompts and negative prompts for cinematic style.

Highlight the action and location of a panda in a blue astronaut suit at a spacey coffee shop. Use cinematic prompts and test 832 by 1216 dimensions with ChatGPT.

Explore prompts and keywords to shape diverse styles for a panda in a blue space suit, using concept art, expression sheets, and logo-ready designs for engaging non-human characters.

Generate Amberlynn the sorceress using stable diffusion prompts and an initial prompt. Experiment with realism by adding photo keywords, dramatic lighting, and celestial, magical fantasy art, adjusting seeds and styles.

Create options for a wise gray-haired wizard named Gray Leaf from the ancient forests. Use ChatGPT prompts and stable diffusion to test variations and adjust prompts for different visual results.

Explore prompt comprehension across models, including sd xl and open dall-e, and learn to choose stable diffusion options for game characters, realistic and fantasy images.

Explore testing custom modules with stable diffusion GUI, using the gallery to copy keywords and prompts, and fine-tune results with textual inversion and parameters like guidance scale and steps.

Learn to keep the same character face across diverse scenes using reactor in Stable Diffusion, saving a high-quality face and applying image-to-image with denoising strength control.

Generate image variations with image-to-image prompts and negative prompts, adjusting denoising strength and seeds to control face consistency. Adjust batch size and environments to produce multiple outputs.

Learn to edit images with AI using inpainting to add, modify, or delete elements and outpainting to extend regions. Use denoising strength and ControlNet modules to control edits and reconstruction.

Learn inpainting with stable diffusion using Dream Shaper inpainting, image to image, and brush-driven masking to replace or remove people, and add objects in beach scenes.

Add, modify, and delete objects using stable diffusion GUI and inpaint. Explore image-to-image workflows, prompts, and parameter options to influence outcomes.

Master editing realistic images with stable diffusion inpainting, using prompts, negative prompts, seeds, and masks to add glasses, necklaces, and earrings while testing models and denoising settings.

outpainting extends the image by generating the background outside the original frame with stable diffusion, using prompts and the img2img workflow to create background variants.

Use IP adapter to transfer features from an input image to a target image, enabling face changes in stable diffusion with inpaint and control net.

Learn to use the inpaint sketch tool in the img to img tab with Stable Diffusion and the Shaper XL model, drawing apples on a wooden table to generate results.

Embed the Photopea extension in stable diffusion to edit images with layers, brushes, and a seamless image to image workflow, using prompts like painting of apples on a wooden table.

Explore image-to-image generation with a stable diffusion gui by uploading a base image and applying prompts to create fantasy landscapes while adjusting denoising strength.

Explore two algorithms for turning sketches into complex images: scribe and line art, using stable diffusion in a gui. Learn inputs for each model and how to enable both tools.

Use control net with stable diffusion to turn sketches into complex images, applying scribe and color-inversion preprocessing, and experiment with prompts and control weight for targeted results.

Convert sketches into realistic architecture images using stable diffusion and control net, applying keywords for interior and exterior moods like modern house and sunny architecture.

Convert sketches into characters using dream shaper prompts and control net to position the staff, invert colors, and place the mage in varied environments with stable diffusion gui.

Turn simple product sketches into realistic shoe and boot photos using the dream shaper model and stable diffusion, with control net, pre-processing, and dimension checks.

Master controlnet with scribble and line art to convert simple sketches into photorealistic images, using 512 by 512 canvases, prompts, negative prompts, and stable diffusion for Batman images.

Learn to increase realism of images by using image-to-image with a realism-focused model like epic realism, adjust sampling with pm++ sd cards, set denoising to 0.4, and generate realistic results.

Learn to extract image edges to feed control net for image generation. Experiment with Open Pose and canny edge detection, adjusting thresholds and control weight for different results.

Create vector logos and logo marks for brands using stable diffusion, with a Mars Coffee case study, exploring minimalist vector designs, prompts, color controls, backgrounds, and logo variations.

Generate coffee shop logos with Stable Diffusion GUI by starting from a generic prompt, then iteratively add keywords, adjust seeds, batch counts, and sampling steps to customize the design.

Generate and refine logos using stable diffusion GUI by adjusting sampling steps, background colors, and prompts, and compare results from logo-specific models like Logo Redmond v2.

Learn logo post-processing workflow: upsample to 2048 with low denoising, apply Ultimate SD upscale and Resr upscaler, then remove backgrounds and create a design in Canva for Mars Coffee.

Learn to generate stickers with prompts and color or composition keywords, including die-cut styles. Explore examples like panda sticker and astronaut playing guitar.

Explore how to craft a t-shirt print design using prompts, keywords, and a base prompt in Stable Diffusion GUI, experimenting with color splash, vintage, and comic styles.

Discover how to use stable diffusion creatively, control image composition with prompts, logos, faces, shapes, and text for surreal visuals inspired by Salvador Dali.

Explore generative image creation with a realistic vision model and control net to shape a mountain landscape and play button symbols through prompts, upscaling, and adjustable controls.

Learn to place brand logos in diverse scenes using generative AI and Stable Diffusion, then compile the images into a video while exploring prompts and logo inversion with a preprocessor.

Explore generating images with logos using control net in a stable diffusion gui, adjusting control weight to improve logo clarity and testing prompts for landscapes, aqueducts, and food scenes.

Wrap up this course with insights on image generation using generative AI and stable diffusion, reviewing book covers, character creation, inpainting, outpainting, logos, and composition control for realistic images.

Explore next level images with generative AI and stable diffusion GUI through AI Expert Academy's online courses on artificial intelligence and data science, with monthly new content and certificates.