Gen AI — Image Generation

DALL-E

response = client.images.generate(
    model="dall-e-3",
    prompt="A futuristic city at sunset, digital art",
    size="1024x1024",
    quality="standard",
    n=1
)

image_url = response.data[0].url

Image editing

response = client.images.edit(
    model="dall-e-2",
    image=open("original.png", "rb"),
    mask=open("mask.png", "rb"),
    prompt="Add a cat sitting on the desk"
)

Variations

response = client.images.create_variation(
    model="dall-e-2",
    image=open("original.png", "rb"),
    n=3,
    size="1024x1024"
)

Prompt tips

# Be specific
"A professional headshot of a woman in a blue blazer, 
 neutral background, studio lighting, 4K"

# Use style references
"Oil painting of a mountain landscape, 
 in the style of Monet, vibrant colors"

# Include composition
"Close-up macro photo of a dewdrop on a leaf,
 shallow depth of field, morning light"

Stable Diffusion

from diffusers import StableDiffusionPipeline

pipe = StableDiffusionPipeline.from_pretrained(
    "runwayml/stable-diffusion-v1-5"
)
pipe = pipe.to("cuda")

image = pipe("A cat wearing sunglasses").images[0]
image.save("cat.png")

Mini Practice

1. Generate an image with DALL-E
2. Create variations
3. Edit an existing image
4. Experiment with prompts

Up Next

Continue with Audio Generation - Text to speech.