Diffusion Based Image Generation with Diffuser (Full Course) - Mastering Control-Net: Full Guide to Controlling Diffusion Models in Stable Diffusion

#stablediffusion #controlnet #generativeai #diffusion #pytorch #imageediting I am Dr. Balyogi Mohan Dash, and I welcome you to Intelligent Machines! Unlock full control over your AI-generated images with Control-Net! In this video, we dive deep into how Control-Net enhances standard diffusion models, allowing you to guide image generation using sketches, depth maps, human poses, and more. Learn about architecture, training, conditioning signals, strength adjustment, and practical implementation using the Stable Diffusion pipeline. Perfect for both AI enthusiasts and machine learning engineers looking to understand the mechanics behind controlled image synthesis. 📘 Full playlist on diffusion: https://youtube.com/playlist?list=PLoSULBSCtofearln-pGND44nr69FE9eIM&si=LATKNLGwu0NULoly All code used in this video is available here: https://github.com/mohan696matlab/Diffusion_Gen_AI_Course Subscribe to the channel to follow this complete course and master diffusion models from theory to practical implementation. 🔗Links🔗 LinkedIn: https://www.linkedin.com/in/balyogi-mohan-dash/ GitHub: https://github.com/mohan696matlab Google Scholar: https://scholar.google.com/citations?user=jzcIElIAAAAJ&hl=en WhatsApp inquiries are currently closed. Please reach out via email for any questions: [email protected] Here is the cleaned-up version with only the chapter titles and timestamps: __ Related Videos: Stable Diffusion: Text-to-Image, Image-to-Image & Inpainting Explained https://youtu.be/pucHB7i2IFE Image-to-Image Diffusion Tutorial | Diffusion Course | By Dr Mohan Dash https://youtu.be/-nSAel8dXFo --- 00:00 Introduction to Control Net 00:00:39 What is a Control Net 00:01:04 Types of Guidance: Depth, Canny, Segmentation, Pose 00:01:26 Combining Multiple Control Nets 00:02:00 Basic Operation of Control Net 00:02:42 Zero Convolution and Training 00:03:37 Conditioning Signal and Strength 00:04:16 Coding with Diffusers Library 00:05:29 Preparing Input Images and Canny Edges 00:06:27 Generating Images with Control Net 00:07:27 Controlling Strength of Control Net 00:08:22 Combining Control Net with Inpainting 00:10:53 Manual Denoising Loop Explanation 00:15:57 Final Image Generation Process 00:16:12 Summary and Next Video Preview