Image Techniques
12 frameworks, Visual understanding and generation techniques for AI image interaction.
*These are learning tools, not prompts. They teach you to write your own, think of them as training wheels that guide you while you learn, then fall away once you can ride on your own.
Overview
Image modality frameworks span two key areas: visual understanding (analyzing and reasoning about images) and visual generation (creating and editing images). Understanding techniques like Multimodal CoT and Visual QA help AI interpret what it sees, while generation techniques like Negative Prompting and ControlNet give you precise creative control over AI-generated imagery.
Image Techniques 12
Image Prompting
Foundational techniques for interacting with AI using visual inputs.
Multimodal CoT
Chain-of-thought reasoning that combines visual and textual information.
Visual CoT
Step-by-step visual reasoning for complex image analysis tasks.
Image-as-Text
Converting visual content into textual descriptions for processing.
Visual QA
Question-answering systems that reason about image content.
Image Generation
Crafting prompts for AI image generation models like DALL-E and Midjourney.
Negative Prompting
Specifying what to exclude from generated images for better results.
ControlNet
Precise control over image generation using structural guides.
Inpainting
Selectively editing or filling in regions of existing images.
Style Transfer
Applying artistic styles and visual aesthetics across images.
Image-to-Image
Transforming existing images based on textual instructions.
Composition
Controlling layout, arrangement, and spatial relationships in images.
Related Categories
Explore other modality categories that complement Image Techniques.