/usr/lib/python2.7/dist-packages/ginga/util/io_rgb.py is in python-ginga 2.6.1-2.
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# io_rgb.py -- RGB image file handling.
#
# This is open-source software licensed under a BSD license.
# Please see the file LICENSE.txt for details.
#
from __future__ import print_function
import sys, time
import os, glob
import numpy
import mimetypes
import hashlib
from io import BytesIO
from ginga.util import paths
from ginga.util.six.moves import map, zip
try:
# do we have Python Imaging Library available?
import PIL.Image as PILimage
from PIL.ExifTags import TAGS
have_pil = True
except ImportError:
have_pil = False
# We only need one of { have_pilutil, have_qtimage }, but both have
# their strengths
have_pilutil = False
have_qtimage = False
try:
from scipy.misc import imresize, imsave, toimage, fromimage
have_pilutil = True
except ImportError:
pass
# Qt can be used as a replacement for PIL
if not have_pilutil:
try:
from ginga.qtw.QtHelp import QImage, QColor, QtCore
have_qtimage = True
except ImportError as e:
pass
# EXIF library for getting metadata, in the case that we don't have PIL
try:
import EXIF
have_exif = True
except ImportError:
have_exif = False
# How about color management (ICC profile) support?
try:
import PIL.ImageCms as ImageCms
have_cms = True
except ImportError:
have_cms = False
# For testing...
#have_qtimage = False
#have_pilutil = False
#have_pil = False
#have_cms = False
class RGBFileHandler(object):
def __init__(self, logger):
self.logger = logger
def load_file(self, filepath, header):
return self._imload(filepath, header)
def save_file_as(self, filepath, data_np, header):
if not have_pil:
raise ImageError("Install PIL to be able to save images")
# TODO: save keyword metadata!
imsave(filepath, data_np)
def _imload(self, filepath, kwds):
"""Load an image file, guessing the format, and return a numpy
array containing an RGB image. If EXIF keywords can be read
they are returned in the dict _kwds_.
"""
start_time = time.time()
typ, enc = mimetypes.guess_type(filepath)
if not typ:
typ = 'image/jpeg'
typ, subtyp = typ.split('/')
self.logger.debug("MIME type is %s/%s" % (typ, subtyp))
if (typ == 'image') and (subtyp in ('x-portable-pixmap',
'x-portable-greymap')):
# Special opener for PPM files, preserves high bit depth
means = 'built-in'
data_np = open_ppm(filepath)
elif have_pil:
# PIL seems to be the faster loader than QImage, and can
# return EXIF info, where QImage will not.
means = 'PIL'
image = PILimage.open(filepath)
try:
info = image._getexif()
for tag, value in info.items():
kwd = TAGS.get(tag, tag)
kwds[kwd] = value
except Exception as e:
self.logger.warning("Failed to get image metadata: %s" % (str(e)))
# If we have a working color profile then handle any embedded
# profile or color space information, if possible
if have_cms and os.path.exists(profile['working']):
# Assume sRGB image, unless we learn to the contrary
in_profile = 'sRGB'
try:
if 'icc_profile' in image.info:
self.logger.debug("image has embedded color profile")
buf_profile = image.info['icc_profile']
# Write out embedded profile (if needed)
prof_md5 = hashlib.md5(buf_profile).hexdigest()
in_profile = "/tmp/_image_%d_%s.icc" % (
os.getpid(), prof_md5)
if not os.path.exists(in_profile):
with open(in_profile, 'w') as icc_f:
icc_f.write(buf_profile)
# see if there is any EXIF tag about the colorspace
elif 'ColorSpace' in kwds:
csp = kwds['ColorSpace']
iop = kwds.get('InteroperabilityIndex', None)
if (csp == 0x2) or (csp == 0xffff):
# NOTE: 0xffff is really "undefined" and should be
# combined with a test of EXIF tag 0x0001
# ('InteropIndex') == 'R03', but PIL _getexif()
# does not return the InteropIndex
in_profile = 'AdobeRGB'
self.logger.debug("hmm..this looks like an AdobeRGB image")
elif csp == 0x1:
self.logger.debug("hmm..this looks like a sRGB image")
in_profile = 'sRGB'
else:
self.logger.debug("no color space metadata, assuming this is an sRGB image")
# if we have a valid profile, try the conversion
tr_key = (in_profile, 'working', rendering_intent)
if tr_key in icc_transform:
# We have am in-core transform already for this (faster)
image = convert_profile_pil_transform(image, icc_transform[tr_key],
inPlace=True)
else:
# Convert using profiles on disk (slower)
if in_profile in profile:
in_profile = profile[in_profile]
image = convert_profile_pil(image, in_profile,
profile['working'],
rendering_intent)
self.logger.info("converted from profile (%s) to profile (%s)" % (
in_profile, profile['working']))
except Exception as e:
self.logger.error("Error converting from embedded color profile: %s" % (str(e)))
self.logger.warning("Leaving image unprofiled.")
data_np = numpy.array(image)
elif have_qtimage:
# QImage doesn't give EXIF info, so use 3rd-party lib if available
if have_exif:
with open(filepath, 'rb') as in_f:
d = EXIF.process_file(in_f)
kwds.update(d)
means = 'QImage'
qimage = QImage()
qimage.load(filepath)
data_np = qimage2numpy(qimage)
else:
raise ImageError("No way to load image format '%s/%s'" % (
typ, subtyp))
end_time = time.time()
self.logger.debug("loading (%s) time %.4f sec" % (
means, end_time - start_time))
return data_np
def imload(self, filepath, kwds):
return self._imload(filepath, kwds)
def get_thumb(self, filepath):
if not have_pil:
raise Exception("Install PIL to use this method")
if not have_exif:
raise Exception("Install EXIF to use this method")
with open(filepath, 'rb') as in_f:
try:
d = EXIF.process_file(in_f)
except Exception as e:
return None
if 'JPEGThumbnail' in d:
buf = d['JPEGThumbnail']
# TODO: other possible encodings?
else:
return None
image = PILimage.open(BytesIO.BytesIO(buf))
data_np = numpy.array(image)
return data_np
def get_buffer(self, data_np, header, format, output=None):
"""Get image as a buffer in (format).
Format should be 'jpeg', 'png', etc.
"""
if not have_pil:
raise Exception("Install PIL to use this method")
image = PILimage.fromarray(data_np)
buf = output
if buf is None:
buf = BytesIO()
image.save(buf, format)
return buf
def imresize(self, data, new_wd, new_ht, method='bilinear'):
"""Scale an image in numpy array _data_ to the specified width and
height. A smooth scaling is preferred.
"""
old_ht, old_wd = data.shape[:2]
start_time = time.time()
if have_qtimage:
# QImage method is slightly faster and gives a smoother looking
# result than PIL
means = 'QImage'
qimage = numpy2qimage(data)
if (old_wd != new_wd) or (old_ht != new_ht):
# NOTE: there is a strange bug in qimage.scaled if the new
# dimensions are exactly the same--so we check and only
# scale if there is some difference
qimage = qimage.scaled(new_wd, new_ht,
transformMode=QtCore.Qt.SmoothTransformation)
newdata = qimage2numpy(qimage)
else:
newdata = data
elif have_pilutil:
means = 'PIL'
zoom_x = float(new_wd) / float(old_wd)
zoom_y = float(new_ht) / float(old_ht)
if (old_wd >= new_wd) or (old_ht >= new_ht):
# data size is bigger, skip pixels
zoom = max(zoom_x, zoom_y)
else:
zoom = min(zoom_x, zoom_y)
newdata = imresize(data, zoom, interp=method)
else:
raise ImageError("No way to scale image smoothly")
end_time = time.time()
self.logger.debug("scaling (%s) time %.4f sec" % (
means, end_time - start_time))
return newdata
# UTILITY FUNCTIONS
def open_ppm(filepath):
infile = open(filepath,'rb')
# Get type: PPM or PGM
header = infile.readline()
ptype = header.strip().upper()
if ptype == b'P5':
depth = 1
elif ptype == b'P6':
depth = 3
#print header
# Get image dimensions
header = infile.readline().strip()
while header.startswith(b'#') or len(header) == 0:
header = infile.readline().strip()
#print(header)
width, height = tuple(map(int, header.split()))
header = infile.readline()
# Get unit size
maxval = int(header)
if maxval <= 255:
dtype = numpy.uint8
elif maxval <= 65535:
dtype = numpy.uint16
#print width, height, maxval
# read image
if depth > 1:
arr = numpy.fromfile(infile, dtype=dtype).reshape((height, width,
depth))
else:
arr = numpy.fromfile(infile, dtype=dtype).reshape((height, width))
if sys.byteorder == 'little':
arr = arr.byteswap()
return arr
# --- Credit ---
# the following function set by Hans Meine was found here:
# http://kogs-www.informatik.uni-hamburg.de/~meine/software/vigraqt/qimage2ndarray.py
#
# see also a newer version at
# http://kogs-www.informatik.uni-hamburg.de/~meine/software/qimage2ndarray/
#
def qimage2numpy(qimage):
"""Convert QImage to numpy.ndarray."""
#print "FORMAT IS %s" % str(qimage.format())
result_shape = (qimage.height(), qimage.width())
temp_shape = (qimage.height(),
qimage.bytesPerLine() * 8 / qimage.depth())
if qimage.format() in (QImage.Format_ARGB32_Premultiplied,
QImage.Format_ARGB32,
QImage.Format_RGB32):
dtype = numpy.uint8
result_shape += (4, )
temp_shape += (4, )
else:
raise ValueError("qimage2numpy only supports 32bit and 8bit images")
# FIXME: raise error if alignment does not match
buf = qimage.bits()
if hasattr(buf, 'asstring'):
# Qt4
buf = bytes(buf.asstring(qimage.numBytes()))
else:
# PySide
buf = bytes(buf)
result = numpy.frombuffer(buf, dtype).reshape(temp_shape)
if result_shape != temp_shape:
result = result[:,:result_shape[1]]
# QImage loads the image as BGRA, we want RGB
#res = numpy.dstack((result[:, :, 2], result[:, :, 1], result[:, :, 0]))
res = numpy.empty((qimage.height(), qimage.width(), 3))
res[:, :, 0] = result[:, :, 2]
res[:, :, 1] = result[:, :, 1]
res[:, :, 2] = result[:, :, 0]
return res
def numpy2qimage(array):
if numpy.ndim(array) == 2:
return gray2qimage(array)
elif numpy.ndim(array) == 3:
return rgb2qimage(array)
raise ValueError("can only convert 2D or 3D arrays")
def gray2qimage(gray):
"""Convert the 2D numpy array `gray` into a 8-bit QImage with a gray
colormap. The first dimension represents the vertical image axis.
ATTENTION: This QImage carries an attribute `ndarray` with a
reference to the underlying numpy array that holds the data. On
Windows, the conversion into a QPixmap does not copy the data, so
that you have to take care that the QImage does not get garbage
collected (otherwise PyQt will throw away the wrapper, effectively
freeing the underlying memory - boom!)."""
if len(gray.shape) != 2:
raise ValueError("gray2QImage can only convert 2D arrays")
h, w = gray.shape
bgra = numpy.empty((h, w, 4), numpy.uint8, 'C')
bgra[...,0] = gray
bgra[...,1] = gray
bgra[...,2] = gray
bgra[...,3].fill(255)
fmt = QImage.Format_RGB32
result = QImage(bgra.data, w, h, fmt)
result.ndarray = bgra
return result
def rgb2qimage(rgb):
"""Convert the 3D numpy array `rgb` into a 32-bit QImage. `rgb` must
have three dimensions with the vertical, horizontal and RGB image axes.
ATTENTION: This QImage carries an attribute `ndarray` with a
reference to the underlying numpy array that holds the data. On
Windows, the conversion into a QPixmap does not copy the data, so
that you have to take care that the QImage does not get garbage
collected (otherwise PyQt will throw away the wrapper, effectively
freeing the underlying memory - boom!)."""
if len(rgb.shape) != 3:
raise ValueError("rgb2QImage can only convert 3D arrays")
if rgb.shape[2] not in (3, 4):
raise ValueError("rgb2QImage can expects the last dimension to contain exactly three (R,G,B) or four (R,G,B,A) channels")
h, w, channels = rgb.shape
# Qt expects 32bit BGRA data for color images:
bgra = numpy.empty((h, w, 4), numpy.uint8, 'C')
bgra[...,0] = rgb[...,2]
bgra[...,1] = rgb[...,1]
bgra[...,2] = rgb[...,0]
if rgb.shape[2] == 3:
bgra[...,3].fill(255)
fmt = QImage.Format_RGB32
else:
bgra[...,3] = rgb[...,3]
fmt = QImage.Format_ARGB32
result = QImage(bgra.data, w, h, fmt)
result.ndarray = bgra
return result
# --- end QImage to numpy conversion functions ---
# --- Color Management conversion functions ---
def convert_profile_pil(image_pil, inprof_path, outprof_path, intent_name,
inPlace=False):
if not have_cms:
return image_pil
image_out = ImageCms.profileToProfile(image_pil, inprof_path,
outprof_path,
renderingIntent=intents[intent_name],
outputMode='RGB', inPlace=inPlace,
flags=0)
if inPlace:
return image_pil
return image_out
def convert_profile_pil_transform(image_pil, transform, inPlace=False):
if not have_cms:
return image_pil
image_out = ImageCms.applyTransform(image_pil, transform, inPlace)
if inPlace:
return image_pil
return image_out
def convert_profile_numpy(image_np, inprof_path, outprof_path, intent_name):
if (not have_pilutil) or (not have_cms):
return image_np
in_image_pil = toimage(image_np)
out_image_pil = convert_profile_pil(in_image_pil,
inprof_path, outprof_path, intent_name)
image_out = fromimage(out_image_pil)
return image_out
def convert_profile_numpy_transform(image_np, transform):
if (not have_pilutil) or (not have_cms):
return image_np
in_image_pil = toimage(image_np)
convert_profile_pil_transform(in_image_pil, transform, inPlace=True)
image_out = fromimage(in_image_pil)
return image_out
def get_transform_key(from_name, to_name, to_intent, proof_name,
proof_intent, flags):
return (from_name, to_name, to_intent, proof_name, proof_intent,
flags)
def get_transform(from_name, to_name, to_intent='perceptual',
proof_name=None, proof_intent=None,
use_black_pt=False):
global icc_transform
flags = 0
if not (proof_name is None):
flags |= ImageCms.SOFTPROOFING
if use_black_pt:
flags |= ImageCms.BLACKPOINTCOMPENSATION
key = get_transform_key(from_name, to_name, to_intent, proof_name,
proof_intent, flags)
try:
output_transform = icc_transform[key]
except KeyError:
# try to build transform on the fly
try:
if not (proof_name is None):
output_transform = ImageCms.buildProofTransform(
profile[from_name],
profile[to_name],
profile[proof_name],
'RGB', 'RGB',
renderingIntent=intents[to_intent],
proofRenderingIntent=intents[proof_intent],
flags=flags)
else:
output_transform = ImageCms.buildTransform(
profile[from_name],
profile[to_name],
'RGB', 'RGB',
renderingIntent=intents[to_intent],
flags=flags)
icc_transform[key] = output_transform
except Exception as e:
raise Exception("Failed to build profile transform: %s" % (str(e)))
return output_transform
def convert_profile_fromto(image_np, from_name, to_name,
to_intent='perceptual',
proof_name=None, proof_intent=None,
use_black_pt=False):
try:
output_transform = get_transform(from_name, to_name,
to_intent=to_intent,
proof_name=proof_name,
proof_intent=proof_intent,
use_black_pt=use_black_pt)
out_np = convert_profile_numpy_transform(image_np, output_transform)
return out_np
except Exception as e:
print("Error converting profile from '%s' to '%s': %s" % (
from_name, to_name, str(e)))
return image_np
def set_rendering_intent(intent):
"""
Sets the color management attribute rendering intent.
Parameters
----------
intent: integer
0: perceptual, 1: relative colorimetric, 2: saturation,
3: absolute colorimetric
"""
global rendering_intent
rendering_intent = intent
basedir = paths.ginga_home
# Color Management configuration
profile = {}
rendering_intent = 'perceptual'
intents = dict(perceptual=0)
# Look up all the profiles the user has available
glob_pat = os.path.join(basedir, "profiles", "*.icc")
for path in glob.glob(glob_pat):
dirname, filename = os.path.split(path)
profname, ext = os.path.splitext(filename)
profile[profname] = os.path.abspath(path)
# These are ones we are particularly interested in
for filename in ('working.icc', 'monitor.icc', 'sRGB.icc', 'AdobeRGB.icc'):
profname, ext = os.path.splitext(filename)
profile[profname] = os.path.join(basedir, "profiles", filename)
# Prepare common transforms
icc_transform = {}
# Build transforms for profile conversions for which we have profiles
if have_cms:
intents = dict(absolute_colorimetric=ImageCms.INTENT_ABSOLUTE_COLORIMETRIC,
perceptual=ImageCms.INTENT_PERCEPTUAL,
relative_colorimetric=ImageCms.INTENT_RELATIVE_COLORIMETRIC,
saturation=ImageCms.INTENT_SATURATION)
# # build input transforms
# for inprof, outprof in [('sRGB', 'working'), ('AdobeRGB', 'working')]:
# for intent_name, intent_value in intents.items():
# if os.path.exists(profile[inprof]) and os.path.exists(profile[outprof]):
# get_transform(profile[inprof], profile[outprof])
def get_profiles():
names = list(profile.keys())
names.sort()
return names
def get_intents():
names = list(intents.keys())
names.sort()
return names
#END
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