QuickThumb

QuickThumb is a Python library for programmatic thumbnail, social card, and promo image generation. It is designed for code-first and JSON-first workflows, with a layer-based API that works well for human-authored scripts and AI-generated specs.

Gallery

YouTube Thumbnail	Burnout Thumbnail	Instagram News Card

Talking Head	Reaction / Commentary	Tutorial / Explainer

Why QuickThumb

• Built for thumbnails and social graphics, not just generic image composition
• Works with Python method chaining and JSON serialization/deserialization
• Handles gradients, remote images, rich text, shapes, blend modes, and export helpers
• Good fit for AI-assisted workflows that need deterministic image specs

Installation

uv pip install quickthumb

Optional background removal support:

uv pip install "quickthumb[rembg]"

Quick Start

from quickthumb import Background, Canvas, Filter, Shadow, Stroke, TextPart

canvas = (
    Canvas.from_aspect_ratio("16:9", base_width=1280)
    .background(
        image="https://images.unsplash.com/photo-1516321318423-f06f85e504b3",
        effects=[Filter(brightness=0.65)],
    )
    .background(color="#000000", opacity=0.45)
    .text(
        content=[
            TextPart(
                text="BUILD THUMBNAILS\nFAST\n",
                color="#B8FF00",
                effects=[Stroke(width=8, color="#000000")],
            ),
            TextPart(
                text="With Python or JSON specs",
                color="#F5F5F5",
                size=44,
                effects=[Shadow(offset_x=2, offset_y=2, color="#000000", blur_radius=4)],
            ),
        ],
        size=112,
        position=("8%", "50%"),
        align=("left", "middle"),
        weight=900,
    )
    .outline(width=14, color="#B8FF00")
)

canvas.render("thumbnail.png")

Core API

Create a canvas

from quickthumb import Canvas

canvas = Canvas(1280, 720)
square = Canvas.from_aspect_ratio("1:1", base_width=1080)
vertical = Canvas.from_aspect_ratio("9:16", base_width=1080)

Background layers

from quickthumb import Canvas, Filter, FitMode, LinearGradient

canvas = (
    Canvas(1280, 720)
    .background(color="#101828")
    .background(
        gradient=LinearGradient(
            angle=120,
            stops=[("#0F172A", 0.0), ("#0F172A00", 1.0)],
        ),
    )
    .background(
        image="hero.jpg",
        fit=FitMode.COVER,
        blend_mode="multiply",
        effects=[Filter(blur=4, brightness=0.75, contrast=1.1, saturation=0.9)],
    )
)

Text layers and rich text

from quickthumb import Background, Canvas, Glow, Shadow, Stroke, TextPart

canvas = Canvas(1280, 720).text(
    content=[
        TextPart(text="5 ", color="#FBBF24", weight=900),
        TextPart(text="WARNING SIGNS", color="#FFFFFF", weight=900),
    ],
    size=72,
    position=(80, 540),
    effects=[
        Background(color="#111827CC", padding=(16, 22), border_radius=12),
        Stroke(width=2, color="#000000"),
        Shadow(offset_x=4, offset_y=4, color="#000000", blur_radius=8),
        Glow(color="#F59E0B", radius=14, opacity=0.35),
    ],
)

Image layers

from quickthumb import Canvas, Filter

canvas = Canvas(1280, 720).image(
    path="portrait.png",
    position=("73%", "52%"),
    width=420,
    height=520,
    fit="cover",
    align=("center", "middle"),
    border_radius=24,
    remove_background=True,
    blend_mode="normal",
    effects=[Filter(contrast=1.1, saturation=1.05)],
)

Shape layers

from quickthumb import Canvas, Shadow, Stroke

canvas = Canvas(1280, 720).shape(
    shape="rectangle",
    position=(64, 60),
    width=320,
    height=88,
    color="#CC0000",
    border_radius=10,
    effects=[
        Stroke(width=2, color="#FFFFFF"),
        Shadow(offset_x=0, offset_y=6, color="#000000", blur_radius=12),
    ],
)

Export helpers

png_base64 = canvas.to_base64(format="PNG")
jpeg_data_url = canvas.to_data_url(format="JPEG", quality=90)
canvas.render("output.webp", format="WEBP", quality=90)

JSON-First Workflow

QuickThumb can round-trip most canvases through JSON:

from quickthumb import Canvas

config = """
{
  "width": 1280,
  "height": 720,
  "layers": [
    {
      "type": "background",
      "color": "#111827"
    },
    {
      "type": "text",
      "content": "Hello QuickThumb",
      "size": 72,
      "color": "#FFFFFF",
      "align": "center",
      "position": ["50%", "50%"]
    },
    {
      "type": "outline",
      "width": 10,
      "color": "#22C55E"
    }
  ]
}
"""

canvas = Canvas.from_json(config)
canvas.render("hello.png")

serialized = canvas.to_json()

Notes:

• JSON uses top-level width, height, and layers
• Named custom layers added with canvas.custom(fn, name="...", kwargs={...}) are JSON-serializable via the registry; unnamed custom layers are not
• Enum-like values such as blend_mode, fit, and align can be passed as strings

AI-Friendly Workflows

QuickThumb is a good target when you want an LLM to generate image specs that are deterministic and easy to validate.

Prompt pattern for Python generation:

Generate QuickThumb Python code for a 1280x720 YouTube thumbnail.
Use layered composition only.
Keep text on the left, subject image on the right, and use high-contrast typography.
Return runnable code that ends with canvas.render("thumbnail.png").

Prompt pattern for JSON generation:

Generate a QuickThumb JSON config with top-level width, height, and layers.
Use one background image layer, one dark overlay background layer, two text layers, and one outline layer.
Only use valid QuickThumb layer types and effect names.

Recommended workflow:

1. Have the model produce QuickThumb Python or JSON.
2. Validate or render it locally.
3. Adjust only the content, colors, and assets instead of rewriting layout logic from scratch.

Environment Variables

QuickThumb looks for fonts using these environment variables:

• QUICKTHUMB_FONT_DIR: directory that contains font files
• QUICKTHUMB_DEFAULT_FONT: default font family/name to use when font is omitted

Example:

import os

os.environ["QUICKTHUMB_FONT_DIR"] = "assets/fonts"
os.environ["QUICKTHUMB_DEFAULT_FONT"] = "Roboto"

Feature Matrix

Area	Supported
Canvas sizing	Explicit width/height, from_aspect_ratio()
Backgrounds	Solid colors, linear gradients, radial gradients, local/remote images
Background controls	Opacity, blend modes, fit modes, blur, brightness, contrast, saturation
Text	Positioning, alignment, wrapping, letter spacing, line height, rotation, auto-scale
Rich text	Per-segment TextPart styling
Text effects	Stroke, shadow, glow, background fill
Fonts	Local fonts, CSS-style weights, italic/bold flags, webfont URLs, fallback mapping
Images	Local/remote images, sizing, fit modes, alignment, opacity, rotation
Image effects	Stroke, shadow, glow, filter effects, border radius, background removal
Shapes	Rectangle and ellipse primitives with stroke/shadow/glow support
Export	PNG, JPEG, WebP, file output, base64, data URLs
Serialization	to_json() / from_json() for built-in layer types and named custom layers

Real Example Scripts

See the shipped examples in examples/README.md:

• examples/youtube_thumbnail_01.py
• examples/youtube_thumbnail_02.py
• examples/instagram_news_card.py

Gotchas

• weight and bold=True are mutually exclusive on text layers and TextPart
• auto_scale=True requires max_width
• position percentage values must be strings like "50%"
• canvas.custom(fn) without a name runs during render order but cannot be serialized to JSON; pass name= and register the function with Canvas.register_layer_fn() to enable serialization

Development

uv sync
uv run pytest
uv run ruff check .
uv run ty quickthumb/

Reference

• Design notes: DESIGN.md
• License: LICENSE