"""
Image classes
"""
import base64
import io
import json
import logging
import math
import struct
from collections.abc import Iterator
from typing import (
Any,
Literal,
Optional,
Union,
)
import mrcfile
import numpy as np
import png
import pydicom
import tifffile
try:
import PIL
import PIL.Image
except ImportError:
PIL = None # type: ignore[assignment, unused-ignore]
from galaxy.datatypes.binary import Binary
from galaxy.datatypes.metadata import (
FileParameter,
MetadataElement,
)
from galaxy.datatypes.protocols import (
DatasetProtocol,
HasExtraFilesAndMetadata,
)
from galaxy.datatypes.sniff import (
build_sniff_from_prefix,
FilePrefix,
)
from galaxy.datatypes.text import Html as HtmlFromText
from galaxy.util import nice_size
from galaxy.util.image_util import check_image_type
from . import data
from .xml import GenericXml
log = logging.getLogger(__name__)
# TODO: Uploading image files of various types is supported in Galaxy, but on
# the main public instance, the display_in_upload is not set for these data
# types in datatypes_conf.xml because we do not allow image files to be uploaded
# there. There is currently no API feature that allows uploading files outside
# of a data library ( where it requires either the upload_paths or upload_directory
# option to be enabled, which is not the case on the main public instance ). Because
# of this, we're currently safe, but when the api is enhanced to allow other uploads,
# we need to ensure that the implementation is such that image files cannot be uploaded
# to our main public instance.
[docs]
class Image(data.Data):
"""Class describing an image"""
edam_data = "data_2968"
edam_format = "format_3547"
file_ext = ""
display_behavior: Literal["inline", "download"] = "inline" # Most image formats can be displayed inline in browsers
MetadataElement(
name="axes",
desc="Axes of the image data",
readonly=True,
visible=True,
optional=True,
)
MetadataElement(
name="dtype",
desc="Data type of the image pixels or voxels",
readonly=True,
visible=True,
optional=True,
)
MetadataElement(
name="num_unique_values",
desc="Number of unique values in the image data (e.g., should be 2 for binary images)",
readonly=True,
visible=True,
optional=True,
)
MetadataElement(
name="width",
desc="Width of the image (in pixels)",
readonly=True,
visible=True,
optional=True,
)
MetadataElement(
name="height",
desc="Height of the image (in pixels)",
readonly=True,
visible=True,
optional=True,
)
MetadataElement(
name="channels",
desc="Number of channels of the image",
readonly=True,
visible=True,
optional=True,
)
MetadataElement(
name="depth",
desc="Depth of the image (number of slices)",
readonly=True,
visible=True,
optional=True,
)
MetadataElement(
name="frames",
desc="Number of frames in the image sequence (number of time steps)",
readonly=True,
visible=True,
optional=True,
)
[docs]
def __init__(self, **kwd):
super().__init__(**kwd)
self.image_formats = [self.file_ext.upper()]
[docs]
def set_peek(self, dataset: DatasetProtocol, **kwd) -> None:
if not dataset.dataset.purged:
dataset.peek = f"Image in {dataset.extension} format"
dataset.blurb = nice_size(dataset.get_size())
else:
dataset.peek = "file does not exist"
dataset.blurb = "file purged from disk"
[docs]
def sniff(self, filename: str) -> bool:
"""Determine if the file is in this format"""
return check_image_type(filename, self.image_formats)
[docs]
def handle_dataset_as_image(self, hda: DatasetProtocol) -> str:
dataset = hda.dataset
name = hda.name or ""
with open(dataset.get_file_name(), "rb") as f:
base64_image_data = base64.b64encode(f.read()).decode("utf-8")
return f""
[docs]
class Jpg(Image):
edam_format = "format_3579"
file_ext = "jpg"
[docs]
def __init__(self, **kwd):
super().__init__(**kwd)
self.image_formats = ["JPEG"]
[docs]
class Png(Image):
edam_format = "format_3603"
file_ext = "png"
[docs]
@build_sniff_from_prefix
class Tiff(Image):
edam_format = "format_3591"
file_ext = "tiff"
display_behavior = "download" # TIFF files trigger browser downloads
MetadataElement(
name="offsets",
desc="Offsets File",
param=FileParameter,
file_ext="json",
readonly=True,
visible=False,
optional=True,
)
[docs]
def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
"""
Determine if the file is in TIFF format by checking the file header.
For a successful check, the first 4 bytes must be the TIFF magic number. See [1] for a list of magic numbers.
Manual checking of the file header, as opposed to trying to read the file with tifffile, is required due to an
ambiguity with DICOM files. This is because the DICOM standard allows *any content* for the first 128 bytes of
the file, followed by the DICOM prefix (see §7.1 in [2] for details).
[1] https://gist.github.com/leommoore/f9e57ba2aa4bf197ebc5
[2] https://dicom.nema.org/medical/dicom/current/output/html/part10.html
"""
return file_prefix.contents_header_bytes[:4] in (
b"\x4d\x4d\x00\x2a", # TIFF format (Motorola - big endian)
b"\x49\x49\x2a\x00", # TIFF format (Intel - little endian)
) and (
len(file_prefix.contents_header_bytes) < 132 # file is too short to be a DICOM
or file_prefix.contents_header_bytes[128:132] != b"DICM" # file does not contain the DICOM prefix
)
@staticmethod
def _get_axis_size(shape: tuple[int, ...], axes: str, axis: str) -> int:
idx = axes.find(axis)
return shape[idx] if idx >= 0 else 0
@staticmethod
def _get_num_unique_values(series: tifffile.TiffPageSeries) -> Optional[int]:
"""
Determines the number of unique values in a TIFF series of pages.
"""
unique_values: list[Any] = []
try:
for page in series.pages:
if page is None:
continue # No idea how this might occur, but mypy demands that we check it, just to be sure
for chunk in Tiff._read_chunks(page):
unique_values = list(np.unique(unique_values + list(chunk)))
return len(unique_values)
except ValueError:
return None # Occurs if the compression of the TIFF file is unsupported
@staticmethod
def _read_chunks(
page: Union[tifffile.TiffPage, tifffile.TiffFrame], mmap_chunk_size: int = 2**14
) -> Iterator["np.typing.NDArray"]:
"""
Generator that reads all chunks of values from a TIFF page.
"""
if len(page.dataoffsets) > 1:
# There are multiple segments that can be processed consecutively
for segment in Tiff._read_segments(page):
yield segment.reshape(-1)
else:
# The page can be memory-mapped and processed chunk-wise
arr = page.asarray(out="memmap") # No considerable amounts of memory should be allocated here
arr_flat = arr.reshape(-1) # This should only produce a view without any new allocations
if mmap_chunk_size > len(arr_flat):
yield arr_flat
else:
chunks_count = math.ceil(len(arr_flat) / mmap_chunk_size)
yield from np.array_split(arr_flat, chunks_count)
@staticmethod
def _read_segments(page: Union[tifffile.TiffPage, tifffile.TiffFrame]) -> Iterator["np.typing.NDArray"]:
"""
Generator that reads all segments of a TIFF page.
"""
reader = page.parent.filehandle
for segment_idx, (segment_offset, segment_size) in enumerate(zip(page.dataoffsets, page.databytecounts)):
reader.seek(segment_offset)
segment_data = reader.read(segment_size)
segment = page.decode(segment_data, segment_idx)[0]
if segment is None:
continue # No idea how this might occur, but mypy demands that we check it, just to be sure
yield segment
[docs]
class OMETiff(Tiff):
file_ext = "ome.tiff"
[docs]
def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
buf = io.BytesIO(file_prefix.contents_header_bytes)
with tifffile.TiffFile(buf) as tif:
return tif.is_ome
[docs]
class OMEZarr(data.ZarrDirectory):
"""OME-Zarr is a format for storing multi-dimensional image data in Zarr format.
It is technically a Zarr directory with custom metadata but stores image information
so it is an Image datatype.
"""
file_ext = "ome_zarr"
[docs]
def set_peek(self, dataset: DatasetProtocol, **kwd) -> None:
if not dataset.dataset.purged:
dataset.peek = "OME-Zarr directory"
dataset.blurb = f"Zarr Format v{dataset.metadata.zarr_format}"
else:
dataset.peek = "file does not exist"
dataset.blurb = "file purged from disk"
[docs]
class Hamamatsu(Image):
file_ext = "vms"
display_behavior = "download" # Proprietary microscopy format, not browser-displayable
[docs]
class Mirax(Image):
file_ext = "mrxs"
display_behavior = "download" # Proprietary microscopy format, not browser-displayable
[docs]
class Sakura(Image):
file_ext = "svslide"
display_behavior = "download" # Proprietary microscopy format, not browser-displayable
[docs]
class Nrrd(Image):
file_ext = "nrrd"
display_behavior = "download" # Medical imaging format, not browser-displayable
[docs]
class Bmp(Image):
edam_format = "format_3592"
file_ext = "bmp"
[docs]
class Gif(Image):
edam_format = "format_3467"
file_ext = "gif"
[docs]
class Im(Image):
edam_format = "format_3593"
file_ext = "im"
[docs]
class Pcd(Image):
edam_format = "format_3594"
file_ext = "pcd"
[docs]
class Pcx(Image):
edam_format = "format_3595"
file_ext = "pcx"
[docs]
class Ppm(Image):
edam_format = "format_3596"
file_ext = "ppm"
[docs]
class Psd(Image):
edam_format = "format_3597"
file_ext = "psd"
[docs]
class Xbm(Image):
edam_format = "format_3598"
file_ext = "xbm"
[docs]
class Xpm(Image):
edam_format = "format_3599"
file_ext = "xpm"
[docs]
class Rgb(Image):
edam_format = "format_3600"
file_ext = "rgb"
[docs]
class Pbm(Image):
edam_format = "format_3601"
file_ext = "pbm"
[docs]
class Pgm(Image):
edam_format = "format_3602"
file_ext = "pgm"
[docs]
class Eps(Image):
edam_format = "format_3466"
file_ext = "eps"
[docs]
class Rast(Image):
edam_format = "format_3605"
file_ext = "rast"
[docs]
class Pdf(Image):
edam_format = "format_3508"
file_ext = "pdf"
display_behavior = "download" # PDFs often trigger downloads depending on browser settings
[docs]
def sniff(self, filename: str) -> bool:
"""Determine if the file is in pdf format."""
with open(filename, "rb") as fh:
return fh.read(4) == b"%PDF"
[docs]
@build_sniff_from_prefix
class Dicom(Image):
"""
DICOM medical imaging format (.dcm)
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('ct_image.dcm')
>>> Dicom().sniff(fname)
True
"""
MetadataElement(
name="is_tiled",
desc="Is this a WSI DICOM?",
readonly=True,
visible=True,
optional=True,
)
edam_format = "format_3548"
file_ext = "dcm"
[docs]
def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
"""
Determine if the file is in DICOM format according to §7.1 in [1].
[1] https://dicom.nema.org/medical/dicom/current/output/html/part10.html
"""
return len(file_prefix.contents_header_bytes) >= 132 and file_prefix.contents_header_bytes[128:132] == b"DICM"
[docs]
def get_mime(self) -> str:
"""
Returns the mime type of the datatype.
"""
return "application/dicom"
[docs]
@build_sniff_from_prefix
class Tck(Binary):
"""
Tracks file format (.tck) format
https://mrtrix.readthedocs.io/en/latest/getting_started/image_data.html#tracks-file-format-tck
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('fibers_sparse_top_6_lines.tck')
>>> Tck().sniff( fname )
True
>>> fname = get_test_fname('2.txt')
>>> Tck().sniff( fname )
False
"""
file_ext = "tck"
[docs]
def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
format_def = [
[b"mrtrix tracks"],
[b"datatype: Float32LE", b"datatype: Float32BE", b"datatype: Float64BE", b"datatype: Float64LE"],
[b"count: "],
[b"file: ."],
[b"END"],
]
matches = 0
for elem in format_def:
for identifier in elem:
if identifier in file_prefix.contents_header_bytes:
matches += 1
if matches == 5:
return True
return False
[docs]
@build_sniff_from_prefix
class Trk(Binary):
"""
Track File format (.trk) is the tractography file format.
http://trackvis.org/docs/?subsect=fileformat
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('IIT2mean_top_2000bytes.trk')
>>> Trk().sniff( fname )
True
>>> fname = get_test_fname('2.txt')
>>> Trk().sniff( fname )
False
"""
file_ext = "trk"
[docs]
def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
# quick check
header_raw = None
header_raw = file_prefix.contents_header_bytes[:1000]
if header_raw[:5] != b"TRACK":
return False
# detailed check
header_def = [
("magic", "S6"),
("dim", "h", 3),
("voxel_size", "f4", 3),
("origin", "f4", 3),
("n_scalars", "h"),
("scalar_name", "S20", 10),
("n_properties", "h"),
("property_name", "S20", 10),
("vox_to_ras", "f4", (4, 4)),
("reserved", "S444"),
("voxel_order", "S4"),
("pad2", "S4"),
("image_orientation_patient", "f4", 6),
("pad1", "S2"),
("invert_x", "S1"),
("invert_y", "S1"),
("invert_z", "S1"),
("swap_xy", "S1"),
("swap_yz", "S1"),
("swap_zx", "S1"),
("n_count", "i4"),
("version", "i4"),
("header_size", "i4"),
]
np_dtype = np.dtype(header_def)
header: np.ndarray = np.ndarray(shape=(), dtype=np_dtype, buffer=header_raw)
if (
header["header_size"] == 1000
and b"TRACK" in header["magic"]
and header["version"] == 2
and len(header["dim"]) == 3
):
return True
return False
[docs]
class Mrc2014(Binary):
"""
MRC/CCP4 2014 file format (.mrc).
https://www.ccpem.ac.uk/mrc_format/mrc2014.php
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('1.mrc')
>>> Mrc2014().sniff(fname)
True
>>> fname = get_test_fname('2.txt')
>>> Mrc2014().sniff(fname)
False
"""
file_ext = "mrc"
[docs]
def sniff(self, filename: str) -> bool:
try:
# An exception is thrown
# if the file is not an
# mrc2014 file.
mrcfile.load_functions.open(filename, header_only=True)
return True
except Exception:
return False
[docs]
class Gmaj(data.Data):
"""Deprecated class. Exists for limited backwards compatibility."""
edam_format = "format_3547"
file_ext = "gmaj.zip"
[docs]
def get_mime(self) -> str:
"""Returns the mime type of the datatype"""
return "application/zip"
[docs]
class Analyze75(Binary):
"""
Mayo Analyze 7.5 files
http://www.imzml.org
"""
file_ext = "analyze75"
composite_type = "auto_primary_file"
[docs]
def __init__(self, **kwd):
super().__init__(**kwd)
# The header file provides information about dimensions, identification,
# and processing history.
self.add_composite_file("hdr", description="The Analyze75 header file.", is_binary=True)
# The image file contains the actual data, whose data type and ordering
# are described by the header file.
self.add_composite_file("img", description="The Analyze75 image file.", is_binary=True)
self.add_composite_file("t2m", description="The Analyze75 t2m file.", optional=True, is_binary=True)
[docs]
def generate_primary_file(self, dataset: HasExtraFilesAndMetadata) -> str:
rval = ["<html><head><title>Analyze75 Composite Dataset.</title></head><p/>"]
rval.append("<div>This composite dataset is composed of the following files:<p/><ul>")
for composite_name, composite_file in self.get_composite_files(dataset=dataset).items():
fn = composite_name
opt_text = ""
if composite_file.optional:
opt_text = " (optional)"
if composite_file.get("description"):
rval.append(
f"<li><a href=\"{fn}\" type=\"text/plain\">{fn} ({composite_file.get('description')})</a>{opt_text}</li>"
)
else:
rval.append(f'<li><a href="{fn}" type="text/plain">{fn}</a>{opt_text}</li>')
rval.append("</ul></div></html>")
return "\n".join(rval)
[docs]
@build_sniff_from_prefix
class Nifti1(Binary):
"""
Nifti1 format
https://nifti.nimh.nih.gov/pub/dist/src/niftilib/nifti1.h
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('T1_top_350bytes.nii1')
>>> Nifti1().sniff( fname )
True
>>> fname = get_test_fname('2.txt')
>>> Nifti1().sniff( fname )
False
"""
file_ext = "nii1"
[docs]
def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
magic = file_prefix.contents_header_bytes[344:348]
if magic == b"n+1\0":
return True
return False
[docs]
@build_sniff_from_prefix
class Nifti2(Binary):
"""
Nifti2 format
https://brainder.org/2015/04/03/the-nifti-2-file-format/
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('avg152T1_LR_nifti2_top_100bytes.nii2')
>>> Nifti2().sniff( fname )
True
>>> fname = get_test_fname('T1_top_350bytes.nii1')
>>> Nifti2().sniff( fname )
False
"""
file_ext = "nii2"
[docs]
def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
magic = file_prefix.contents_header_bytes[4:8]
if magic in [b"n+2\0", b"ni2\0"]:
return True
return False
[docs]
@build_sniff_from_prefix
class Gifti(GenericXml):
"""Class describing a Gifti format"""
file_ext = "gii"
[docs]
def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
"""Determines whether the file is a Gifti file
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('Human.colin.R.activations.label.gii')
>>> Gifti().sniff(fname)
True
>>> fname = get_test_fname('interval.interval')
>>> Gifti().sniff(fname)
False
>>> fname = get_test_fname('megablast_xml_parser_test1.blastxml')
>>> Gifti().sniff(fname)
False
>>> fname = get_test_fname('tblastn_four_human_vs_rhodopsin.blastxml')
>>> Gifti().sniff(fname)
False
"""
handle = file_prefix.string_io()
line = handle.readline()
if not line.strip().startswith('<?xml version="1.0"'):
return False
line = handle.readline()
if line.strip() == '<!DOCTYPE GIFTI SYSTEM "http://www.nitrc.org/frs/download.php/1594/gifti.dtd">':
return True
line = handle.readline()
if line.strip().startswith("<GIFTI"):
return True
return False
[docs]
@build_sniff_from_prefix
class Star(data.Text):
"""Base format class for Relion STAR (Self-defining
Text Archiving and Retrieval) image files.
https://relion.readthedocs.io/en/latest/Reference/Conventions.html"""
file_ext = "star"
[docs]
def set_peek(self, dataset: DatasetProtocol, **kwd) -> None:
"""Set the peek and blurb text"""
if not dataset.dataset.purged:
dataset.peek = data.get_file_peek(dataset.get_file_name())
dataset.blurb = "Relion STAR data"
else:
dataset.peek = "file does not exist"
dataset.blurb = "file purged from disk"
[docs]
def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
"""Each file must have one or more data blocks.
The start of a data block is defined by the keyword
``data_`` followed by an optional string for
identification (e.g., ``data_images``). All text
before the first ``data_`` keyword are comments
>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('1.star')
>>> Star().sniff(fname)
True
>>> fname = get_test_fname('interval.interval')
>>> Star().sniff(fname)
False
"""
in_data_block = False
for line in file_prefix.line_iterator():
# All lines before the first
# data_ block must be comments.
line = line.strip()
if len(line) == 0:
continue
if line.startswith("data_"):
in_data_block = True
continue
if in_data_block:
# Lines within data blocks must
# be blank, start with loop_, or
# start with _.
if len(line) == 0:
continue
if line.startswith("loop_") or line.startswith("_"):
return True
return False
return False
[docs]
class Html(HtmlFromText):
"""Deprecated class. This class should not be used anymore, but the galaxy.datatypes.text:Html one.
This is for backwards compatibilities only."""
[docs]
class Laj(data.Text):
"""Deprecated class. Exists for limited backwards compatibility."""
![[docs]](../../../lib/galaxy.datatypes.html#galaxy.datatypes.images.Jpg){kind=link}
![[docs]](../../../lib/galaxy.datatypes.html#galaxy.datatypes.images.Jpg.__init__){kind=link}
![[docs]](../../../lib/galaxy.datatypes.html#galaxy.datatypes.images.Png){kind=link}
![[docs]](../../../lib/galaxy.datatypes.html#galaxy.datatypes.images.Png.set_meta){kind=link}
![[docs]](../../../lib/galaxy.datatypes.html#galaxy.datatypes.images.Bmp){kind=link}
![[docs]](../../../lib/galaxy.datatypes.html#galaxy.datatypes.images.Gif){kind=link}