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Creative AI - Mastering Image Generation with Python Diffusion Networks
Reshape image data for NN
01 Preprocess image data with Python (3:08)
02 Load flower image dataset in Colab (4:34)
03 Reshape image data with Python (4:48)
Source Files
Calculate Kernel Inception Distance
01 Calculate Kernel Inception Distance in Python (6:34)
02 Update Kernel State with Keras (8:49)
Source Files
Build downsampling and upsampling with Keras
01 Build residual block with Python (3:24)
02 Build down and up blocks with Keras (3:29)
Source files
Build a CNN with Keras
01 Build sinusoidal embedding with TensorFlow (3:35)
02 Build a CNN for image generation (5:30)
CNN Source Files
Build a diffusion model for image generation
01 Build a diffusion schedule with TensorFlow (3:00)
02 Denoise images in Python (2:09)
03 Build a diffusion model for image generation (4:02)
04 Build reverse diffusion algorithm (4:45)
Diffusion Source Files
Generate images with diffusion
01 Generate images with diffusion (3:07)
02 Build training step for model (7:49)
03 Build Keras model test step (3:58)
Source Files
Train and visualize image generation model
01 Run model training for diffusion image generation (5:51)
02 Visualize image generation results (4:59)
Source files
What are diffusion models
01 What are diffusion models (2:40)
02 What is the diffusers library (8:36)
03 What is stable diffusion (3:09)
Source files
Image generation with Stable Diffusion Python
01 Load Stable Diffusion model in Colab (7:54)
Image to image translation with Stable Diffusion Python
01 Load pretrained image translation model (3:05)
02 Preprocess original image for translation with Python (4:31)
03 Generate image variant with prompt (3:50)
Image translation files
Inpainting with Stable Diffusion Python
01 Load images for inpainting (2:43)
02 Generate inpainted image with prompt (4:48)
Inpainting files
01 Run model training for diffusion image generation
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