Explore token-based image generation, adjusting tokens, resolution, and models to balance quality and resources, including pixel art options and native resolution considerations.

Generate an image by entering text or using prompts, illustrated with futuristic cars in New York during rain and night, at 512 by 512 resolution, with edits and new variations.

Explore creating multiple image variations from the same text by applying different styles—Leonardo, vintage photography, isometric—yielding diverse perspective shots of a futuristic car.

Save generated images by downloading from the interface, saving as named JPEG files in an images folder, and adjusting resolution for future use.

Discover how guidance scale weights the text prompt in AI art generation, using default seven, adjusting to five or nine, and avoiding extremes for clearer images.

Learn how image prompts and reference images guide text-to-image generation, using image-for-image workflows, strength controls, tiling for backgrounds, and negative prompts to avoid undesired features.

Explore how to load and edit canvases in Leonardo Eye, apply masks and generate variations like platinum blonde hair, then download results and manage tokens to avoid losing work.

Increase image resolution by using creative, upscale, upscale image, and hd upscale beta options to download higher quality images for printing, noting original vs upscale and token costs.

Explore how canvas resolution and image loading affect token usage and rendering in AI art generation, including masking, editing parts, and upscaling for higher detail.

Explore how gallery resources, seeds, prompts, and negative prompts guide image generation across models like Leonardo Diffusion and Dream Shaper, including remixing and stylistic choices.

Explore prompt magic in ai art generation, balancing image prompts with magic strength and image weight to shape rendering outcomes, using multiple images and Leonardo style.

Explore control net in stable diffusion 1.5, activated by uploading an image, and adjust poses, depth to image, and control weight to guide image-to-image generation with a seed.

Learn to create and manage training data sets, add or remove images, and edit elements and text. Queue processing jobs with file uploads and gallery selections, noting subscription limits.

Craft a training dataset by selecting images with aligned framing and graphic styles, manage backgrounds for clarity, limit to 5–15 images (max 30), and train the model to diversify representations.

Train a model using a training set and upscale resolution from 512 to 768. Choose stable diffusion 1.5, build characters and environments for illustration, then start training and monitor progress.

Explore training and datasets concepts in ai art generation through prompts in an image generator, testing Buddha, bear, and cow subjects, and applying Leonardo style with backgrounds.

Understand how training and datasets subscription plans drive item launches every 11 days on the free plan, with five jobs, image generation, and saving 512x512 Buddha and cow images.

Increase image resolution to 300 dpi in Krita, adjust levels and contrast, apply unsharp mask and noise reduction, and save a print-ready, sRGB file.

Publish ai-generated art on the ArtStation marketplace, where printing, shipping, and selling are handled, and choose formats, prices, and categories for posters, canvases, and prints.

navigate price management for art prints and upgrades, adjust posters, frames, and hd metals, and learn how subscriptions and platform rules shape earnings.

Explore ai art generation workflows by image-to-image transformations with platform models, adjusting icon typologies, and fine-tuning size, framing, lighting, and camera-like settings to create photorealistic or portrait outputs.

Master masking to edit interior scenes, generate multiple variations, adjust lamps and plants, and download artwork after upscaling for improved resolution.

Experiment with canvas objects, masking and references to place toys on the floor, adjust size, avoid carpet areas, render with illumination, then download the artwork as a png.

Explore interior rendering with image prompts, image-to-image references, and image weight in Leonardo diffusion and V-Ray, shaping composition and lighting.

Master AI art generation for interiors by adjusting image weight, image to image prompts, and prompt strength to create variations and upscale renders.

Conclude the interiors portion and invite further experimentation with quickly generated images using artificial intelligence, exploring the new frontier of graphic, photographic, and other representations.

train ai with images from the network using leonardo diffusion and prompt magic edition. adjust image weight, choose horizontal or vertical prompts, and use negative prompts for cleaner results.

Experiment with prompts to place a character near a swimming pool, use image prompts and front camera positioning, and test variations—including Italian prompts—to achieve consistent, near-front full-figure results.

Explore Chicago exteriors by generating Millennium Park scenes with exterior prompts. Adjust aspect ratio 16/9, image weight, and magic strength to study prompt effects in ai art generation.

Explore how image prompts inform ai and how public internet resources can train an artificial intelligence. Understand copyright considerations, public profile visibility, and the shift toward three-dimensional representations.

Discover the new HD smooth upscaler that increases image resolution and yields softer details on in-focus objects. Compare it with other upscaling modes in the gallery to apply smoother results.

Navigate generation history and the personal feed to view, edit, or delete images; apply upscaling, HD, clear, and filter edits, then refresh to see updates.

Speed up Leonardo registration by requesting access, joining Discord, selecting your language (such as Italian), and using priority links to gain access within one day to several days.

The lecture tests how Leonardo understands Italian prompts in art generation, comparing Italian and English inputs, using prompts, seeds, negative prompts, and image prompts to explore stylistic results.

Explore how Leonardo's AI art models alter a reference image and reveal stylistic differences across basic models. Use the built-in library to save files and compare results quickly.

Explore platform portrait models like dreamscapes, RPG 4.0, deliberate, and vintage photography to see how prompts and image influence shape youth, armor, and realism in AI art.

Explore how AI art generation models modify a character’s armor, age, hair, and facial features across photorealistic, isometric fantasy, and cartoon styles.

Explore how generated styles influence image elements across various model typologies, lighting, and shots, from dreamscape and Leonardo to pixel art and isometric outputs for food photography.

Explore AI-driven jewelry imagery by crafting prompts, selecting stylistic models, and iterating with crystals, diamonds, rubies, and gemstones to generate ring visuals.

Engage in a Canva exercise that mirrors Photoshop-style masking to replace backgrounds, edit faces, and generate new elements with stable diffusion 1.5 and 2. Download high-resolution artwork of your creations.

Explore Krita post-production techniques, applying precise brush and clone tools, masking, selections, and patches to refine images, adjust real-pixel resolution, and manage masking without overreliance on filters.

Explore the remix function in AI art generation. Copy prompts and model text to create new versions like RPG studio photography in Leonardo Diffusion.

Explore the Santa muerte project created in Leonardo, highlighting differences and typologies. The next lesson covers image generation and related insights.

Explore how prompts shape AI-generated portraits, using kiss Santa Muerte and close-up female faces, while negative prompts control skull or skeleton effects.

Compare default and alternate resolutions to see different details, textures, and dimensions in AI art generation, then layer and align elements in a photo editor.

Explore seed analysis in AI art generation: fixed seeds with the same prompt reproduce images of Santa muerte; changing seeds or prompts yields varied shots while keeping color and framing.

Learn to replicate a photorealistic close‑up portrait of a Cuban girl using precise prompts, negative prompting, seeds, and RPG 4.0 on the Leonardo platform, with studio lighting and ultra-realistic skin.

Learn how ai renders age progression by varying prompts, seeds, and reference images, showing a character aging from ten to ninety years old while appearance changes.

Explore upscaling beyond Leonardo, compare with Krita and programs using a non-Krita tool, and download Joanna upscaling, Krita upscaling, and Santa Muerte upscaling folders while noting one gigabyte platform limits.

install topa gigapixel hi test version, download 2.89 gigabytes of machine-learning models, and launch the program to explore its interface for advanced upscaling.

Prepare Krita 9k files from Leonardo AI outputs, set 9000-pixel targets at 300 ppi, compare Krita and Gigapixel scaling, and apply unsharp mask to enhance detail before saving as JPEG.

Upload or drag an image into the upscaling tool, view the original size (2368 by 3088), and adjust output with preset scales up to 600%.

Master advanced size and crop upscaling by adjusting width and height across pixels, inches, and centimeters, applying upscaling filters, and cropping while managing image queues to preserve sharpness.

Manage a two-image queue to control size, updates, and AI rendering with the linear model, updating Ebony and Santa muerte simultaneously, while using zoom, movement tools, and queue deletion.

Navigate comparison windows to compare original and processed AI art across four models using single view, split view, and side-by-side layouts, observing the contrast and detail differences.

Explore AI-driven upscaling with model-based options that tailor enhancement to image type: photographs, architecture, or art and CG, optimizing resolution, contrast, and detail while avoiding artifacts.

Learn to manage model settings in AI art generation, switching between automatic and manual modes to tailor art and cg presets, adjust noise suppression, compression, and contrast for optimal images.

Explore how to manage automatic and manual AI art generation settings, adjusting noise suppression, blur, and compression to compare results and tailor image output.

Explore advanced settings for AI art generation, including face recovery, gamma correction, and color space adjustments, to affect blur, delineations, and recognition on various image resolutions.

Master saving generated art: set save options, prefixes, color profiles, and formats; manage queues and directories; compare models (standard, line, high resolution) and remove watermarks with a license.

Compare image variants—original, unsharp mask, linear rendering, and multiple scaling modes (standard, line, Rcg, HQ)—to show how fixed compression and blur settings alter results.

Explore how to improve ai generated human anatomy by using control net, depth to image, and negative prompts, while adjusting resolution, weights, and reference images for coherent, ultra realistic figures.

Learn mask creation and post production workflows to generate alternate upscale versions, download images with transparency, and refine edges using erasers, selections, feathering, and gradient shading.