An image processing library in Mojo

Overview • Installation • Examples • Documentation • Acknowledgements

Overview

Description

Mosaic is a cross-platform (macOS and linux) image processing library for prototyping and production.

By transparently leveraging hardware acceleration, Mosaic is built specifically for heterogenous compute: CPUs, GPUs, and more in the future.

It can unify image processing workflows into one language that runs on any hardware.

Principles

1. Easy to use
2. Type-safe, memory-safe
3. Performant

Features

• Image representation
  • Image file encoding and decoding
  • Data type specification (at compile time)
  • Color space specification (at compile time)
• Image transformation
  • Filtering
  • Geometric transforms
  • Fourier transforms
• Visualization (currently only macOS)
  • Native image rendering
• Hardware acceleration
  • Parallelization and SIMD on CPUs
  • GPU acceleration when available (coming soon)

Installation

Prerequisites

• Pixi (the Mojo environment and package manager)

Using the pixi cli

pixi add mosaic-mojo

After installation

The pixi.toml file should include the Modular community channel and the Mosaic dependency:

[project]
channels = ["https://repo.prefix.dev/modular-community"]

[dependencies]
mosaic-mojo = "*"

Examples

Prerequisites

Clone the repo and build Mosaic:

git clone git@github.com:brainwave-sh/mosaic.git
cd mosaic
pixi run build

Running an example

After building, run an example file from the examples/ directory like so:

cd examples
pixi run mojo load_image.mojo

Load image

• Loads an image file and displays it in the visualizer
• Source: examples/load_image.mojo

Save image

• Saves an image to a file
• Source: examples/save_image.mojo

Scale image

• Scales an image to half size using bilinear interpolation
• Source: examples/scale_image.mojo

Resize image

• Resizes an image to double its width, stretching it in the process
• Source: examples/resize_image.mojo

Slice image

• Slices the top half of an image
• Image slices are mutable views into the underlying image data
• Source: examples/slice_image.mojo

Rotate image

• Rotates an image by 90° clockwise
• Source: examples/rotate_image.mojo

Flip image

• Flips an image vertically
• Source: examples/flip_image.mojo

Pad image

• Pads an image with zeros
• Source: examples/pad_image.mojo

Convert type

• Starting with a uint8 image, explicitly converts it to float64
• Source: examples/convert_type.mojo

Convert color space

• Converts an RGB image to greyscale
• Source: examples/convert_color_space.mojo

Convert color space as type

• Converts a float64 RGB image to uint8 greyscale in one method
• Source: examples/convert_as_type.mojo

Blur image

• Blurs an image using the built-in Gaussian kernel and reflected border handling
• Source: examples/blur_image.mojo

Detect edges

• Detects edges in an image by smoothing and applying a custom Laplacian kernel
• Source: examples/detect_edges.mojo

Unsharp mask

• Applies unsharp masking and image stacking to visualize the results
• Source: examples/unsharp_mask.mojo

Picture in picture

• Captures a sub-rect of an image and copies it to the top left corner
• Source: examples/picture_in_picture.mojo

Extract channel

• Extracts the green channel of an RGB image
• Source: examples/extract_channel.mojo

Fourier transform

• Calculates the spectrum of an image using the Fourier transform
• Source: examples/fourier_transform.mojo

Inverse Fourier transform

• Recreates an image from a previously calculated spectrum
• Source: examples/inverse_fourier_transform.mojo

High-pass filter

• Applies a high-pass filter by discarding low frequencies in the spectrum
• Source: examples/high_pass_filter.mojo

Documentation

Docs are available at brainwave.sh/mosaic

Acknowledgements

Mosaic makes use of vendored libraries to help with image codecs and FFTs, many thanks to:

• stb_image by Sean Barrett
• pocketfft by Martin Reinecke