added a function to remove lighting non uniformity
This commit is contained in:
Guillaume Raffy
parent
0b4bb9b608
commit
f7ad17f9e8
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@ -1,5 +1,6 @@
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import json
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from imageengine import IHyperStack, IImageEngine, PixelType
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class DacMetadata(object):
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@ -74,15 +75,15 @@ class Sequence(object):
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def get_root_path(self):
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return '/'.join(self.micro_manager_metadata_file_path.split('/')[:-1])
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def get_image_file_path(self, channel_index, frame_index, z_index=0):
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def get_image_file_path(self, channel_index, frame_index, slice_index=0):
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'''
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:param int channel_index:
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:param int frame_index:
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:param int z_index:
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:param int slice_index:
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'''
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assert frame_index < self.num_frames
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assert channel_index < self.num_channels
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frame_info = self.mmm['FrameKey-%d-%d-%d' % (frame_index, channel_index, z_index)]
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frame_info = self.mmm['FrameKey-%d-%d-%d' % (frame_index, channel_index, slice_index)]
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rel_file_path = frame_info['FileName']
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return self.get_root_path() + '/' + rel_file_path
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@ -127,6 +128,33 @@ class Sequence(object):
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white_sequence = seqid_to_white[self.sequence_id]
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return self.catalog.sequences[white_sequence]
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def as_hyperstack(self, selected_channel_ids=None, selected_frames=None, selected_slices=None):
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""" returns a subset of the sequence as an hyperstack
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:param list(str) selected_channel_ids:
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:return IHyperStack: the resulting hyperstack
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"""
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if selected_frames is None:
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selected_frames = range(self.num_frames)
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if selected_slices is None:
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selected_slices = range(self.num_slices)
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if selected_channel_ids is None:
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selected_channel_indices = range(self.num_channels)
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else:
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selected_channel_indices = [self.get_channel_index(channel_id) for channel_id in selected_channel_ids]
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pixel_type = {8: PixelType.U8, 16: PixelType.U16}[self.num_bits_per_pixels]
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stack = IImageEngine.get_instance().create_hyperstack(width=self.width, height=self.height, num_slices=len(selected_slices), num_frames=len(selected_frames), num_channels=len(selected_channel_indices), pixel_type=pixel_type)
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for frame_index in selected_frames:
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for slice_index in selected_slices:
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for channel_index in selected_channel_indices:
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image = IImageEngine.get_instance().load_image(self.get_image_file_path(channel_index=channel_index, frame_index=frame_index, slice_index=slice_index))
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stack.set_image(image=image, channel_index=channel_index, frame_index=frame_index, slice_index=slice_index)
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return stack
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class ImageCatalog(object):
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def __init__(self, raw_images_root):
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@ -7,6 +7,28 @@ import abc
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ABC = abc.ABCMeta('ABC', (object,), {})
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class Aabb(object):
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"""Axis-Aligned bounding box"""
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def __init__(self, x_min, y_min, x_max, y_max):
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self.x_min = x_min
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self.y_min = y_min
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self.x_max = x_max
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self.y_max = y_max
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class PixelType:
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U8 = 1
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U16 = 2
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F32 = 3
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PIXEL_TYPE_TO_NUM_BITS = {U8: 8,
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U16: 16,
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F32:32}
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@staticmethod
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def get_num_bits(pixel_type):
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return PixelType.PIXEL_TYPE_TO_NUM_BITS[ pixel_type ]
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class IImage(ABC):
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@ -19,6 +41,25 @@ class IImage(ABC):
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pass
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class IHyperStack(ABC):
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@abc.abstractmethod
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def width(self):
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pass
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@abc.abstractmethod
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def height(self):
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pass
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@abc.abstractmethod
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def set_image(self, image, frame_index=0, slice_index=0, channel_index=0):
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"""
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:param IImage image:
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"""
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pass
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class IImageEngine(ABC):
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"""
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The active image processor.
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@ -46,6 +87,18 @@ class IImageEngine(ABC):
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assert IImageEngine.__instance is not None
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return IImageEngine.__instance
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@abc.abstractmethod
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def create_hyperstack(self, width, height, num_channels, num_slices, num_frames, pixel_type):
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"""
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"""
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@abc.abstractmethod
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def load_image(self, src_image_file_path):
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"""
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:param str src_image_file_path: eg './white_estimate.tiff'
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:return IImage:
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"""
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@abc.abstractmethod
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def save_as_tiff(self, image, out_file_path):
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"""
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@ -1,7 +1,7 @@
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"""Image processing using imagej.
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"""
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from lipase.imageengine import IImage, IImageEngine
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from ..imageengine import IImage, IHyperStack, IImageEngine, PixelType
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from ij import IJ # pylint: disable=import-error
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from ij.plugin import ImageCalculator # pylint: disable=import-error
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from ijopencv.ij import ImagePlusMatConverter # pylint: disable=import-error
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@ -22,12 +22,31 @@ class IJImage(IImage):
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self.ij_image = ij_image
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def width(self):
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raise NotImplementedError
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return self.ij_image.width
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def height(self):
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raise NotImplementedError
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return self.ij_image.height
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class IJHyperStack(IHyperStack):
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def __init__(self, width, height, num_channels, num_slices, num_frames, pixel_type):
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"""
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"""
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stack_name = ''
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self.hyperstack = IJ.createHyperStack(stack_name, width, height, num_channels, num_slices, num_frames, PixelType.get_num_bits(pixel_type))
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def set_image(self, image, frame_index=0, slice_index=0, channel_index=0):
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self.hyperstack.setPositionWithoutUpdate(channel_index + 1, slice_index + 1, frame_index + 1)
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self.hyperstack.setProcessor(image.ij_image.getProcessor())
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def width(self):
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return self.hyperstack.width
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def height(self):
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return self.hyperstack.height
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def imagej_run_image_command(image, command, options):
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"""performs the given imagej command on the given image
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@ -123,9 +142,21 @@ class IJImageEngine(IImageEngine):
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def missing(self):
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pass
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def create_hyperstack(self, width, height, num_channels, num_slices, num_frames, pixel_type):
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return IJHyperStack(width, height, num_channels, num_slices, num_frames, pixel_type)
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def load_image(self, src_image_file_path):
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image_plus = IJ.openImage(src_image_file_path)
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return IJImage(self, image_plus)
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def save_as_tiff(self, image, out_file_path):
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IJ.saveAsTiff(image.ij_image, out_file_path)
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def divide(self, numerator_image, denominator_image):
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ic = ImageCalculator()
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result_image = ic.run("Divide create float", numerator_image.ij_image, denominator_image.ij_image)
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return IJImage(self, result_image)
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def compute_max(self, images_file_path):
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"""Computes for each pixel position the maximum at this position in all input images.
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@ -1,7 +1,7 @@
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"""preprocessing of synchrotron images based on telemosToolbox."""
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from catalog import ImageCatalog, Sequence
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from imageengine import IImageEngine
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from imageengine import IImageEngine, PixelType
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class WhiteEstimator(object):
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@ -122,8 +122,8 @@ class WhiteEstimator(object):
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for channel_id in channel_ids:
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channel_index = sequence.get_channel_index(channel_id)
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for frame_index in range(sequence.num_frames):
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for z_index in range(sequence.num_slices):
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images_file_path.append(sequence.get_image_file_path(channel_index, frame_index, z_index))
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for slice_index in range(sequence.num_slices):
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images_file_path.append(sequence.get_image_file_path(channel_index, frame_index, slice_index))
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white_estimate = IImageEngine.get_instance().compute_max(images_file_path)
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@ -160,6 +160,64 @@ class InteractiveWhiteEstimator(WhiteEstimator):
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# white_estimator_settings.ask
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def correct_non_uniform_lighting(non_uniform_sequence, channel_id, white_estimator=WhiteEstimator(open_size=75, close_size=75, average_size=75)):
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""" correction of non uniform lighting
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:param Sequence non_uniform_sequence: the input sequence, which is expected to have a non uniform lighting
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:param str channel_id:
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:param WhiteEstimator white_estimator: the method used to estimate the light image
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:return IHyperStack: the hyperstack of images after correction
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"""
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white_estimate = white_estimator.estimate_white([non_uniform_sequence], [channel_id])
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uniform_stack = IImageEngine.get_instance().create_hyperstack(width=white_estimate.width(), height=white_estimate.height(), num_slices=1, num_frames=non_uniform_sequence.num_frames, num_channels=1, pixel_type=PixelType.F32)
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for frame_index in range(non_uniform_sequence.num_frames):
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non_uniform_frame = IImageEngine.get_instance().load_image(non_uniform_sequence.get_image_file_path(channel_index=0, frame_index=frame_index, slice_index=0))
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uniform_frame = IImageEngine.get_instance().divide(non_uniform_frame, white_estimate)
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uniform_stack.set_image(frame_index=frame_index, image=uniform_frame)
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return uniform_stack
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# def get_sequence_as_hyperstack(sequence, selected_channel_ids=None, selected_frames=None, selected_slices=None):
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# """ returns a subset of the sequence as an hyperstack
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# :param IHyperStack non_uniform_sequence: the input sequence
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# :param list(str) selected_channel_ids:
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# :return IHyperStack: the resulting hyperstack
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# """
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# if selected_frames is None:
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# selected_frames = range(sequence.num_frames)
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# if selected_slices is None:
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# selected_slices = range(sequence.num_slices)
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# if selected_channel_ids is None:
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# selected_channel_indices = range(sequence.num_channels)
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# else:
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# selected_channel_indices = [sequence.get_channel_index(channel_id) for channel_id in selected_channel_ids]
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# pixel_type = {8: PixelType.U8, 16: PixelType.U16}[sequence.num_bits_per_pixels]
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# stack = IImageEngine.get_instance().create_hyperstack(width=sequence.width, height=sequence.height, num_slices=len(selected_slices), num_frames=len(selected_frames), num_channels=len(selected_channel_indices), pixel_type=pixel_type)
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# for frame_index in selected_frames:
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# for slice_index in selected_slices:
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# for channel_index in selected_channel_indices:
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# image = IImageEngine.get_instance().load_image(sequence.get_image_file_path(channel_index=channel_index, frame_index=frame_index, slice_index=slice_index))
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# stack.set_image(image=image, channel_index=channel_index, frame_index=frame_index, slice_index=slice_index)
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# return stack
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# def correct_non_uniform_lighting(non_uniform_sequence, channel_id, white_estimator=WhiteEstimator(open_size=75, close_size=75, average_size=75)):
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# """ correction of non uniform lighting
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# :param IHyperStack non_uniform_sequence: the input sequence, which is expected to have a non uniform lighting
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# :param WhiteEstimator white_estimator: the method used to estimate the light image
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# :return IHyperStack: the hyperstack of images after correction
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# """
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# white_estimate = white_estimator.estimate_white([non_uniform_sequence], [channel_id])
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# uniform_stack = IImageEngine.get_instance().create_hyperstack(width=white_estimate.width(), height=white_estimate.height(), num_slices=1, num_frames=non_uniform_sequence.num_frames, num_channels=1, pixel_type=PixelType.F32)
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# for frame_index in range(non_uniform_sequence.num_frames):
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# non_uniform_frame = IImageEngine.get_instance().load_image(non_uniform_sequence.get_image_file_path(channel_index=0, frame_index=frame_index, slice_index=0))
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# uniform_frame = IImageEngine.get_instance().divide(non_uniform_frame, white_estimate)
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# uniform_stack.set_image(frame_index=frame_index, image=uniform_frame)
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# return uniform_stack
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def find_white_reference_image(white_estimate, white_z_stack):
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"""Find the white reference Image among a z stack of reference image the most correlated to the white image estimated from a serie of acquisition.
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@ -0,0 +1,32 @@
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from catalog import ImageCatalog, Sequence
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# from imageengine import Toto
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from imageengine import IImageEngine
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from imageengine import PixelType
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from preprocessing import WhiteEstimator
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def remove_traps(sequence, channel_id, trap_aabb):
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"""Remove the traps in the input sequence
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:param Sequence sequence:
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:param str channel_id:
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:param Aabb trap_aabb:
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"""
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white_estimator = WhiteEstimator(open_size=75, close_size=75, average_size=75)
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white_estimate = white_estimator.estimate_white([sequence], [channel_id])
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print(white_estimate)
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uniform_stack = IImageEngine.get_instance().create_hyperstack(width=white_estimate.width(), height=white_estimate.height(), num_slices=1, num_frames=sequence.num_frames, num_channels=1, pixel_type=PixelType.F32)
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for frame_index in range(sequence.num_frames):
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non_uniform_frame = IImageEngine.get_instance().load_image(sequence.get_image_file_path(channel_index=0, frame_index=frame_index, slice_index=0))
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uniform_frame = IImageEngine.get_instance().divide(non_uniform_frame, white_estimate)
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uniform_stack.set_image(frame_index=frame_index, image=uniform_frame)
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#num_expected_traps = 13 # 13 traps are completely visible in the
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#assert num_traps = num_expected_traps
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#non_uniform_stack = sequence.as_stack()
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#uniform_stack = IImageEngine.get_instance().divide(non_uniform_stack, white_estimate)
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# IImageEngine.get_instance().save_as_tiff(white_estimate, './white_estimate.tiff')
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@ -7,10 +7,11 @@
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import unittest # unittest2 doesn't exist in fiji
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import sys
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from lipase.catalog import ImageCatalog, Sequence
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from lipase.imageengine import IImageEngine
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from lipase.imageengine import IImageEngine, PixelType, Aabb
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from lipase.imagej.ijimageengine import IJImageEngine, IJImage
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from lipase.preprocessing import WhiteEstimator
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from lipase.preprocessing import WhiteEstimator, correct_non_uniform_lighting
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from lipase.traps_remover import remove_traps
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from lipase.catalog import ImageCatalog, Sequence
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class TestLipase(unittest.TestCase):
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@ -28,8 +29,6 @@ class TestLipase(unittest.TestCase):
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print("uninitializing TestLipase instance")
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self.catalog = None
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def test_estimate_white(self):
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sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos2']
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white_estimator = WhiteEstimator(open_size=75, close_size=75, average_size=75)
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@ -40,6 +39,18 @@ class TestLipase(unittest.TestCase):
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# assert False, "hellooooo"
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print('end of test_estimate_white')
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def test_uniform_lighting_correction(self):
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non_uniform_sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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uniform_sequence = correct_non_uniform_lighting(non_uniform_sequence, 'DM300_nofilter_vis', white_estimator=WhiteEstimator(open_size=75, close_size=75, average_size=75))
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# def test_traps_removal(self):
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# sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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# x_min = 423
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# x_max = 553
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# y_min = 419
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# y_max = 533
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# trap_aabb = Aabb(x_min, y_min, x_max, y_max)
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# remove_traps(sequence, 'DM300_nofilter_vis', trap_aabb)
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def run_script():
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