def loadFigImage(im):
"""
Return a matplotlib `Figure` with the given raster image spanning the plot extents
and with data coordinates equal to pixel coordinates. All axis and labels are
hidden.
:param im: either path to image file, or RGB image array in uint8 or uint16 type
:rtype: tuple(Figure,Axes)
"""
if isinstance(im, string_types):
im = loadImage(im)
im = image2mpl(im)
h, w = im.shape[0], im.shape[1]
dpi = 80
fig = plt.figure(figsize=(w / dpi, h / dpi), dpi=dpi)
ax = plt.Axes(fig, [0, 0, 1, 1])
ax.set_xlim(0, w)
ax.set_ylim(0, h)
ax.invert_yaxis()
ax.set_axis_off()
fig.add_axes(ax)
if im.ndim == 2:
fig.figimage(im, cmap=cm.gray)
else:
fig.figimage(im)
fig._dontSetColors = True
return fig, ax
def maskAllInFolder(folderPath, outputFolderPath, ext='jpg', maskFn=maskStarfield, preserveExif=True):
"""
Masks the starfield of all images in `folderPath` and stores the masked images
in `outputFolderPath`.
:param str ext: image extension
:param function maskFn: the masking function to use,
by default the standard algorithm from :mod:`auromat.solving.masking`
:param bool preserveExif: whether to copy EXIF data (exiftool must be installed)
"""
if preserveExif:
et = exiftool.ExifTool()
et.start()
for imageFilename in os.listdir(folderPath):
imagePath = os.path.join(folderPath, imageFilename)
maskedPath = os.path.join(outputFolderPath, os.path.splitext(imageFilename)[0] + '.' + ext)
mask, _ = maskFn(imagePath)
im = loadImage(imagePath)
im[~mask] = 0
saveImage(maskedPath, im)
if preserveExif:
et.copy_tags(imagePath, maskedPath)
if preserveExif:
et.terminate()
def maskAllInFolder(folderPath,
outputFolderPath,
ext='jpg',
maskFn=maskStarfield,
preserveExif=True):
"""
Masks the starfield of all images in `folderPath` and stores the masked images
in `outputFolderPath`.
:param str ext: image extension
:param function maskFn: the masking function to use,
by default the standard algorithm from :mod:`auromat.solving.masking`
:param bool preserveExif: whether to copy EXIF data (exiftool must be installed)
"""
if preserveExif:
et = exiftool.ExifTool()
et.start()
for imageFilename in os.listdir(folderPath):
imagePath = os.path.join(folderPath, imageFilename)
maskedPath = os.path.join(
outputFolderPath,
os.path.splitext(imageFilename)[0] + '.' + ext)
mask, _ = maskFn(imagePath)
im = loadImage(imagePath)
im[~mask] = 0
saveImage(maskedPath, im)
if preserveExif:
et.copy_tags(imagePath, maskedPath)
if preserveExif:
et.terminate()
def img_unmasked(self):
if self._img_unmasked is None:
rgb = loadImage(self._imagePath)
if rgb.shape[0] != rgb.shape[1]:
# contains caption below image, cut it off
rgb = rgb[:rgb.shape[1],:]
assert rgb.shape == (rgb.shape[1],rgb.shape[1],3)
self._img_unmasked = rgb
return self._img_unmasked
def estimateArcSecRange(imagePath, imageSize=None):
focal35mm = readFocalLength35mm(imagePath)
if focal35mm is None:
return None
focal35mmLow = focal35mm * 0.9
focal35mmHigh = focal35mm * 1.1
if imageSize is None:
_, w, = loadImage(imagePath).shape
else:
_, w = imageSize
# see http://cbellh47.blogspot.nl/2010/01/astrometry-101-pixel-scale.html
pixelSizeMm = 35 / w
arcsecLow = (pixelSizeMm / focal35mmHigh * u.rad).to(u.arcsec).value
arcsecHigh = (pixelSizeMm / focal35mmLow * u.rad).to(u.arcsec).value
return (arcsecLow, arcsecHigh)
def _copyTempFiles(fitsWcsHeader, name):
if not keepTempFiles:
return
if os.path.exists(objsPath):
p = os.path.join(debugOutputFolder,
objsBaseOutput + '_' + name + '.jpg')
saveImage(p, loadImage(objsPath)) # convert png to jpg
if not fitsWcsHeader and os.path.exists(axyPath):
p = os.path.join(debugOutputFolder, axyBaseOutput + name + '.axy')
shutil.copy(axyPath, p)
if not fitsWcsHeader and os.path.exists(logPath):
p = os.path.join(debugOutputFolder, logBaseOutput + name + '.log')
shutil.copy(logPath, p)
def correctLensDistortion(imagePath,
undistImagePath,
lensfunDbObj=None,
mod=None,
exiftoolObj=None,
preserveExif=True,
minAcceptedScore=MIN_ACCEPTED_SCORE,
**saveImageKws):
"""
Correct lens distortion of an image using its EXIF headers and the lensfun library.
If the camera or lens are not found in the lensfun database, an exception is raised.
:param undistImagePath: path to output image; folders must already exist!
:param exiftoolObj: if not None, use the given exiftool object (must have nums=False)
:param lensfunDbObj: if not None, use the given lensfun.Database object
:param mod: if not None, use this Modifier instead of calling getLensfunModifier()
Note: lensfunDbObj is not used in this case.
:raise ValueError: when lens wasn't found in EXIF data
:raise CameraNotFoundInDBError: when the camera wasn't found in lensfun database
:raise LensNotFoundInDBError: when the lens wasn't found in lensfun database
"""
im = loadImage(imagePath)
if mod is None:
height, width = im.shape[0], im.shape[1]
mod, _, _ = getLensfunModifier(imagePath,
width,
height,
lensfunDbObj,
exiftoolObj,
minAcceptedScore=minAcceptedScore)
undistCoords = mod.apply_geometry_distortion()
imUndistorted = lensfunpy.util.remap(im, undistCoords)
saveImage(undistImagePath, imUndistorted, **saveImageKws)
# TODO set a flag indicating that lens correction has been done
# there is no standard flag for that
# the closest one is Xmp.digiKam.LensCorrectionSettings
# see http://api.kde.org/extragear-api/graphics-apidocs/digikam/html/classDigikam_1_1LensFunFilter.html
# adding custom XMP tags requires to change some exiftool config file...
if preserveExif:
if exiftoolObj:
exiftoolObj.copy_tags(imagePath, undistImagePath)
else:
with exiftool.ExifTool() as et:
et.copy_tags(imagePath, undistImagePath)
def correctLensDistortion(imagePath, undistImagePath,
lensfunDbObj=None, mod=None,
exiftoolObj=None, preserveExif=True,
**saveImageKws):
"""
Correct lens distortion of an image using its EXIF headers and the lensfun library.
If the camera or lens are not found in the lensfun database, an exception is raised.
:param undistImagePath: path to output image; folders must already exist!
:param exiftoolObj: if not None, use the given exiftool object (must have nums=False)
:param lensfunDbObj: if not None, use the given lensfun.Database object
:param mod: if not None, use this Modifier instead of calling getLensfunModifier()
Note: lensfunDbObj is not used in this case.
:raise ValueError: when lens wasn't found in EXIF data
:raise CameraNotFoundInDBError: when the camera wasn't found in lensfun database
:raise LensNotFoundInDBError: when the lens wasn't found in lensfun database
"""
im = loadImage(imagePath)
if mod is None:
height, width = im.shape[0], im.shape[1]
mod, _, _ = getLensfunModifier(imagePath, width, height, lensfunDbObj, exiftoolObj)
undistCoords = mod.apply_geometry_distortion()
imUndistorted = lensfunpy.util.remap(im, undistCoords)
saveImage(undistImagePath, imUndistorted, **saveImageKws)
# TODO set a flag indicating that lens correction has been done
# there is no standard flag for that
# the closest one is Xmp.digiKam.LensCorrectionSettings
# see http://api.kde.org/extragear-api/graphics-apidocs/digikam/html/classDigikam_1_1LensFunFilter.html
# adding custom XMP tags requires to change some exiftool config file...
if preserveExif:
if exiftoolObj:
exiftoolObj.copy_tags(imagePath, undistImagePath)
else:
with exiftool.ExifTool() as et:
et.copy_tags(imagePath, undistImagePath)
def solveImage(imagePath,
channel=None,
maskingFn=maskStarfield,
sigma=None,
solveTimeout=60 * 5,
debugOutputFolder=None,
noAstrometryPlots=False,
arcsecRange=None,
astrometryBinPath=None,
useModifiedPath=False,
parameters=['xy', 'xy2', 'xy4', 's'],
pixelError=10,
oddsToSolve=None,
verbose=False):
"""
Tries different combinations to solve the image using astrometry.net.
:param imagePath:
:param channel: the channel to use for source extraction
'R','G','B', or None for combining all channels into a grayscale image
:param maskingFn: function to use for masking the given image,
if None, masking is skipped
:param sigma: noise level of the image (optional)
:param solveTimeout: maximum time in seconds after which astrometry.net is killed
:param debugOutputFolder: if given, the path to which debug files are written
:param noAstrometryPlots: whether to let astrometry.net generate plots,
if True, then debugOutputFolder must be given
:param arcsecRange: tuple(low,high), if not given, then it is guessed from
the image file if possible
:param astrometryBinPath: path to the bin/ folder of astrometry.net;
if not given, then whatever is in PATH will be used
:param bool useModifiedPath: invokes astrometry.net with /usr/bin/env PATH=os.environ['PATH']
This may be useful when the PATH was modified after launching Python.
:param int pixelError: size of pixel positional error, use higher values (e.g. 10)
if image contains star trails (ISS images)
:param oddsToSolve: default 1e9, see astrometry.net docs
:rtype: dictionary containing FITS WCS header, or None if solving failed
"""
imageBase = os.path.splitext(os.path.basename(imagePath))[0]
tmpDir = tempfile.mkdtemp()
tmpDirAstrometry = os.path.join(tmpDir, 'astrometry')
# TODO we need to return which solving strategy (downsampling, extractor) was used
# -> this should probably be added to the .axy header
# as astrometry.net repeatedly downsamples in certain cases it
# is hard to determine the correct downsampling that was used
# -> see also http://trac.astrometry.net/ticket/1117
if maskingFn is None:
imageMaskedPath = imagePath
maskedSuffix = ''
imageSize = None
if channel is not None:
raise NotImplementedError
else:
maskedSuffix = '_masked'
imageMaskedPath = os.path.join(tmpDir,
imageBase + maskedSuffix + ".png")
# step 1: create starfield-masked image
t0 = time.time()
if not debugOutputFolder:
debugPathPrefix = None
else:
debugPathPrefix = os.path.join(debugOutputFolder, imageBase) + '_'
mask, sigma_ = maskingFn(imagePath, debugPathPrefix=debugPathPrefix)
if sigma is None:
sigma = sigma_
im = loadImage(imagePath)
im[~mask] = 0
if channel is None:
pass
elif channel.lower() == 'r':
im = im[:, :, 0]
elif channel.lower() == 'g':
im = im[:, :, 1]
elif channel.lower() == 'b':
im = im[:, :, 2]
else:
raise ValueError(
'channel is "{}" but must be R,G,B or None'.format(channel))
saveImage(imageMaskedPath, im)
imageSize = (im.shape[0], im.shape[1])
print('masking:', time.time() - t0, 's')
if debugOutputFolder is not None:
shutil.copy(imageMaskedPath, debugOutputFolder)
# step 2: invoke astrometry.net
# Note that astrometry.net assumes that images are taken from earth.
# As the ISS is very near to earth, the error is most likely below the
# accuracy that astrometry.net provides and also below the common pixel
# resolution of images and can therefore be ignored.
keepTempFiles = False if debugOutputFolder is None else True
if debugOutputFolder is None:
noAstrometryPlots = True
logFilename = imageBase + maskedSuffix + '.log'
logFilenameOutput = imageBase + '.log'
logPath = os.path.join(tmpDirAstrometry, logFilename)
logBaseOutput = imageBase + '_'
objsBase = imageBase + maskedSuffix + '_objs'
objsBaseOutput = imageBase + '_objs'
objsPath = os.path.join(tmpDirAstrometry, objsBase + '.png')
indxBase = imageBase + maskedSuffix + '_indx'
indxBaseOutput = imageBase + '_indx'
indxFilename = indxBase + '.png'
indxFilenameOutput = indxBaseOutput + '.png'
indxPath = os.path.join(tmpDirAstrometry, indxFilename)
matchFilename = imageBase + maskedSuffix + '.match'
matchFilenameOutput = imageBase + '.match'
matchPath = os.path.join(tmpDirAstrometry, matchFilename)
indxXyFilename = imageBase + maskedSuffix + '.xyls'
indxXyFilenameOutput = imageBase + '.xyls'
indxXyPath = os.path.join(tmpDirAstrometry, indxXyFilename)
axyFilename = imageBase + maskedSuffix + '.axy'
axyFilenameOutput = imageBase + '.axy'
axyPath = os.path.join(tmpDirAstrometry, axyFilename)
axyBaseOutput = imageBase + '_'
corrFilename = imageBase + maskedSuffix + '.corr'
corrFilenameOutput = imageBase + '.corr'
corrPath = os.path.join(tmpDirAstrometry, corrFilename)
# remove old debug files first
if keepTempFiles:
for filename in [
matchFilenameOutput, indxFilenameOutput, indxXyFilenameOutput,
corrFilenameOutput, axyFilenameOutput, logFilenameOutput,
objsBaseOutput + '_xy2.jpg', objsBaseOutput + '_xy4.jpg',
objsBaseOutput + '_xy.jpg', objsBaseOutput + '_s.jpg',
axyBaseOutput + 'xy2.axy', axyBaseOutput + 'xy4.axy',
axyBaseOutput + 'xy.axy', axyBaseOutput + 's.axy',
logBaseOutput + 'xy2.log', logBaseOutput + 'xy4.log',
logBaseOutput + 'xy.log', logBaseOutput + 's.log'
]:
path = os.path.join(debugOutputFolder, filename)
if os.path.exists(path):
os.remove(path)
t0 = time.time()
def _copyTempFiles(fitsWcsHeader, name):
if not keepTempFiles:
return
if os.path.exists(objsPath):
p = os.path.join(debugOutputFolder,
objsBaseOutput + '_' + name + '.jpg')
saveImage(p, loadImage(objsPath)) # convert png to jpg
if not fitsWcsHeader and os.path.exists(axyPath):
p = os.path.join(debugOutputFolder, axyBaseOutput + name + '.axy')
shutil.copy(axyPath, p)
if not fitsWcsHeader and os.path.exists(logPath):
p = os.path.join(debugOutputFolder, logBaseOutput + name + '.log')
shutil.copy(logPath, p)
# first try astrometry.net's own star extraction (simplexy) with different downsampling options
if arcsecRange:
if len(arcsecRange) != 2:
raise ValueError('arcsecRange must be a pair (low,high)')
arcsecLowHigh = arcsecRange
else:
arcsecLowHigh = estimateArcSecRange(imagePath, imageSize)
_solve = partial(_solveStarfield,
imageMaskedPath,
tmpDirAstrometry,
keepTempFiles=keepTempFiles,
timeout=solveTimeout,
sigma=sigma,
plotsBgImagePath=imagePath,
noPlots=noAstrometryPlots,
arcsecPerPxLowHigh=arcsecLowHigh,
pixelError=pixelError,
oddsToSolve=oddsToSolve,
astrometryBinPath=astrometryBinPath,
useModifiedPath=useModifiedPath,
verbose=verbose)
# "The downsampling just seems to generally do a better job of source detection on
# most of the images we get, at least at about 2-4. I think it has to do with either
# the PSF size (default is too narrow) or saturation (downsampling smears out
# saturated pixels, making them not so saturated)." (Dustin Lang)
# (https://groups.google.com/d/msg/astrometry/Pp_MZD6s4w8/muuH-1T_zpAJ)
fitsWcsHeader = None
if 'xy2' in parameters:
fitsWcsHeader = _solve(useSextractor=False, downsample=2)
_copyTempFiles(fitsWcsHeader, 'xy2')
# Astrometry.net might have already tried downsample=4 when downsample=2 was requested
# in case no stars could be extracted, so it might happen that we repeat this below.
# We have to try it anyway because with downsample=2 it could have happened that
# only 1 or 2 stars in the corners were detected after which astrometry didn't repeat
# downsampling and just failed.
# There should be an astrometry flag to disable the repeated downsampling,
# see also https://groups.google.com/d/msg/astrometry/qNOgWTL1pVA/BNIbqkXEM-gJ
# Note that with repeated downsampling, astrometry re-uses the sigma (noise level)
# from the original downsampling, so there may be slight differences if
# astrometry is manually called with downsample=4 because it recomputes sigma
# based on downsample=4.
# NOTE: this is the behaviour of the -D flag of image2xy, which cannot be set from solve-field!
if fitsWcsHeader is None and 'xy4' in parameters:
if keepTempFiles and os.path.exists(tmpDirAstrometry):
shutil.rmtree(tmpDirAstrometry)
fitsWcsHeader = _solve(useSextractor=False, downsample=4)
_copyTempFiles(fitsWcsHeader, 'xy4')
# if this didn't work, we try SExtractor for star extraction
if fitsWcsHeader is None and 's' in parameters:
if keepTempFiles and os.path.exists(tmpDirAstrometry):
shutil.rmtree(tmpDirAstrometry)
fitsWcsHeader = _solve(useSextractor=True, downsample=None)
_copyTempFiles(fitsWcsHeader, 's')
# in case the input image has a low resolution (which is not the case for ISS images)
# we also might have luck with downsampling disabled and using simplexy:
if fitsWcsHeader is None and 'xy' in parameters:
if keepTempFiles and os.path.exists(tmpDirAstrometry):
shutil.rmtree(tmpDirAstrometry)
fitsWcsHeader = _solve(useSextractor=False, downsample=None)
_copyTempFiles(fitsWcsHeader, 'xy')
print('solving:', time.time() - t0, 's')
if fitsWcsHeader is not None:
if keepTempFiles and os.path.exists(indxPath):
p = os.path.join(debugOutputFolder, indxBaseOutput + '.jpg')
saveImage(p, loadImage(indxPath)) # convert png to jpg
tempPaths = [matchPath, indxXyPath, axyPath, corrPath, logPath]
outputFilenames = [
matchFilenameOutput, indxXyFilenameOutput, axyFilenameOutput,
corrFilenameOutput, logFilenameOutput
]
if keepTempFiles:
outputPaths = [
os.path.join(debugOutputFolder, f) for f in outputFilenames
]
for tempPath, outputPath in zip(tempPaths, outputPaths):
if os.path.exists(tempPath):
shutil.move(tempPath, outputPath)
else:
print(
'WARNING!! {} does not exist after successfully solving, but it should!'
.format(tempPath),
file=sys.stderr)
shutil.rmtree(tmpDir)
return fitsWcsHeader