- Installing the libraries (xformers library to memory optimization)
- Pipeline for image generation: Creating the prompt -> Generating the image -> Saving the result
- Generating multiple images
- Parameters: Seed, Inference steps, Guidance scale (CFG), Image size (dimensions), Negative prompt
- Other models: SD v1.5, SD v2.x, Fine-tuned models with specific styles
- Changing the scheduler: PNDM (default), DDIM Scheduler, K-LMS Scheduler, Euler Ancestral Discrete Scheduler (Euler A), DPM Scheduler
- Exploring the prompts: Subject / object, Action and location, Type, Style, Colors, Artist, Resolution, Site. And Other attributes: Ilumination, Negative prompts
- Use cases: Generating arts, Generating photographs, Generating landscapes, Generating 3D images, Generating drawings, Generating architectures
- Improving the results using custom models: Anything (cag/anything-v3-1), DreamShaper (Lykon/DreamShaper), Realistic Vision (SG161222/Realistic_Vision_V1.4), Analog Diffusion (wavymulder/Analog-Diffusion), Protogen (darkstorm2150/Protogen_x3.4_Official_Release), Mitsua Diffusion One (Mitsua/mitsua-diffusion-one)
- Installing the libraries (accelerate transformers ftfy bitsandbytes==0.35.0 gradio natsort safetensors xformers)
- Loading the model
- Training: Three components are needed: unique identifier, class name, images
- Convert the weights into (checkpoint)
- Inference (tests)
- Generating images: Testing multiple prompts, More prompt examples: in the forest, in cairo, in cairo desert, in a western scene, in star wars, in mountain fuji, in the snow, etc.
- Saving the results
- Installing the libraries (accelerate transformers ftfy bitsandbytes==0.35.0 gradio natsort safetensors xformers)
- Generating the image
- Strength parameter (intensity)
- Testing different styles
- Changing the input image
- Changing the scheduler
- Image to image "editing" (InstructPix2pix)
- Installing the libraries (accelerate transformers ftfy bitsandbytes==0.35.0 gradio natsort safetensors xformers)
- Creating the prompt
- Exchanging the objects
- Comparing the results (Other image, Generating multiple images)
- Installing the libraries (accelerate transformers xformers)
- Generating images using edges (ControlNet model + Canny Edge, Detecting edges using Canny Edge, fine-tuned model)
- Generating images using poses