iiq2img 0.6.0

Fast IIQ converter for Phase One iXM-GS120 (120MP) raw images

iiq2img

Fast converter for Phase One iXM-GS120 (120 MP) IIQ raw files. Outputs JPEG, PNG, or TIFF with full EXIF/GPS/XMP metadata and optional georeferencing.

Quick start

# Install from PyPI
pip install iiq2img

# Or install the latest dev version from git
uv pip install git+https://github.com/DPIRD-DMA/iiq2img.git

# Or clone and install locally
git clone https://github.com/DPIRD-DMA/iiq2img.git && cd iiq2img
uv sync

# Convert (uses fast pipeline by default)
iiq2img photo.IIQ                     # single file
iiq2img batch ./raw ./out             # batch directory
iiq2img photo.IIQ --libraw            # use LibRaw PPG instead

Pipelines

Pipeline	End-to-end	Speedup	Quality
default (fast)	~1.0 s	3.6x	Mean diff ~7/255 vs reference
--libraw (LibRaw PPG)	~3.3 s	baseline	Reference

The fast pipeline uses cv2 edge-aware demosaic + numba parallel LUTs with BT.709 gamma, matched to LibRaw's output. See FINDINGS.md for how.

Python API

from iiq2img import convert_iiq, read_iiq, batch_convert

# Single file (fast pipeline is the default)
out_path = convert_iiq("photo.IIQ", "output.jpg")

# Read as NumPy array (no file written)
rgb = read_iiq("photo.IIQ")

# Batch (parallel)
results = batch_convert("./raw", "./out", workers=8)

# Georeferenced output (requires `pip install iiq2img[geo]`)
# TIFF: CRS embedded in the GeoTIFF itself.
# JPEG/PNG: sidecars written next to the image (.jgw/.pgw + .prj + .aux.xml)
# so QGIS/ArcGIS recognise the projection.
convert_iiq("photo.IIQ", "output.tif", output_format="tiff", georef=True)
convert_iiq("photo.IIQ", "output.jpg", georef=True)

Option	Default	Description
thumbnail	False	Extract embedded JPEG thumbnail instead of converting
output_format	"jpg"	Output format: jpg, png, or tiff
compress_quality	90	JPEG/PNG compression quality (1-100)
max_dimension	None	Downscale longest edge to this size
rotate	0	Rotate output: 0, 90, 180, 270
georef	False	World file + .prj + .aux.xml sidecars for JPEG/PNG, embedded CRS for TIFF (requires [geo] extra)
extract_meta	True	Copy EXIF/GPS/XMP metadata to output
pipeline	"fast"	Demosaic pipeline: fast or libraw

CLI

# Single file (outputs photo.jpg next to the original)
iiq2img photo.IIQ
iiq2img photo.IIQ --libraw            # use LibRaw PPG instead of fast

# Batch convert a directory (parallel)
iiq2img batch ./raw ./out                           # defaults: jpg, q=90, fast
iiq2img batch ./raw ./out --format tiff --workers 8 # tiff, q=90, 8 workers
iiq2img batch ./raw ./out --format jpg --quality 75 --workers 4 --libraw
iiq2img batch ./raw ./out --georef                  # write georef sidecars for every output
iiq2img batch ./raw ./out --rotate 180 --no-meta    # 180° flip, skip EXIF copy

# Benchmark all pipelines on a sample file
iiq2img benchmark photo.IIQ

Changelog

See CHANGELOG.md for version history.

Contributing

git clone https://github.com/DPIRD-DMA/iiq2img.git && cd iiq2img
uv sync --dev
pre-commit install

Pre-commit hooks run ruff (lint + format) and pytest on every commit. To run them manually:

uv run ruff check .                  # lint
uv run ruff format .                 # format
uv run pytest                        # tests
uv run iiq2img benchmark photo.IIQ   # timing comparison