Advanced Image Techniques: Inpainting, Outpainting, and ControlNet
Part of the Prompt Engineering course
In the last two lessons you generated whole images from a text prompt and learned to steer them with structure, style, and negative prompts. That approach gives the model wide creative latitude, which is a strength when you are exploring and a problem when you need a specific result.
In lesson eight a generation began from random noise and denoised toward your prompt. Image-to-image (often written img2img) changes the starting point: instead of noise, the model begins from an existing image and denoises from there. The prompt still guides the result, but the source picture pulls it toward a familiar shape. ...
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Start this lessonAdvanced Image Techniques: Inpainting, Outpainting, and ControlNetWhat you'll learn
- Image-to-image generation
- Inpainting with masks
- Outpainting to extend a canvas
- ControlNet for pose, depth, and edge guidance
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All lessons in this course
11 lessons- 1What a Prompt Is20 min
- 2How Large Language Models Generate Text30 min
- 3The Five Principles of Prompting30 min
- 4Standard Practices for Text Generation35 min
- 5Prompt Templates and Function Calling35 min
- 6Vector Databases and Retrieval-Augmented Generation40 min
- 7Autonomous Agents: Memory and Tools40 min
- 8How Diffusion Models Generate Images30 min
- 9Standard Practices for Image Generation35 min
- 10Advanced Image Techniques: Inpainting, Outpainting, and ControlNet35 min
- 11Building AI-Powered Applications40 min
