now a clean trap image is computed as the median value of all traps
This commit is contained in:
Guillaume Raffy
parent
dcf5d61f3d
commit
1702d97965
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@ -113,11 +113,35 @@ class IImageFeeder(ABC):
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@abc.abstractmethod
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def next(self):
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"""returns the nex image in the collection
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"""returns the next image in the collection
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for iterator
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"""
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pass
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@abc.abstractmethod
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def get_num_images(self):
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pass
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def create_hyperstack(self):
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"""
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creates an hyperstack from this image feeder
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:rtype IHyperStack
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"""
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it = iter(self)
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image = it.next()
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ie = IImageEngine.get_instance()
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hyperstack = ie.create_hyperstack(width=image.width(), height=image.height(), num_channels=1, num_slices=1, num_frames=self.get_num_images(), pixel_type=image.get_pixel_type())
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frame_index = 0
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for image in it:
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hyperstack.set_image(image, frame_index=frame_index)
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frame_index += 1
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print(frame_index)
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print(self.get_num_images())
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assert frame_index == self.get_num_images()
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return hyperstack
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class FileImageFeeder(IImageFeeder):
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@ -137,6 +161,9 @@ class FileImageFeeder(IImageFeeder):
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return image
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raise StopIteration
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def get_num_images(self):
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return len(self.image_filepaths)
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def add_image(self, image_filepath):
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self.image_filepaths.append(image_filepath)
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@ -160,29 +187,42 @@ class StackImageFeeder(IImageFeeder):
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return self
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def next(self):
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print(self.next_channel_index, self.next_frame_index, self.next_slice_index)
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print(self.hyperstack.num_channels, self.hyperstack.num_frames, self.hyperstack.num_slices)
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print("channel %d/%d frame %d/%d slice %d/%d" % (self.next_channel_index, self.hyperstack.num_channels(), self.next_frame_index, self.hyperstack.num_frames(), self.next_slice_index, self.hyperstack.num_slices()))
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if self.end_is_reached:
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raise StopIteration
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else:
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image = self.hyperstack.get_image(frame_index=self.next_frame_index, slice_index=self.next_slice_index, channel_index=self.next_channel_index)
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# compute next image index
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if self.next_slice_index < self.hyperstack.num_slices():
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self.next_slice_index += 1
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else:
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self.next_slice_index += 1
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if self.next_slice_index == self.hyperstack.num_slices():
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self.next_slice_index = 0
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if self.next_frame_index < self.hyperstack.num_frames():
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self.next_frame_index += 1
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else:
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self.next_frame_index += 1
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if self.next_frame_index == self.hyperstack.num_frames():
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self.next_frame_index = 0
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if self.next_channel_index < self.hyperstack.num_channels():
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self.next_channel_index += 1
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else:
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self.next_channel_index += 1
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if self.next_channel_index == self.hyperstack.num_channels():
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self.end_is_reached = True
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# if self.next_slice_index < self.hyperstack.num_slices() - 1:
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# self.next_slice_index += 1
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# else:
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# self.next_slice_index = 0
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# if self.next_frame_index < self.hyperstack.num_frames() - 1:
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# self.next_frame_index += 1
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# else:
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# self.next_frame_index = 0
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# if self.next_channel_index < self.hyperstack.num_channels():
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# self.next_channel_index += 1
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# else:
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# self.end_is_reached = True
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print("after : channel %d/%d frame %d/%d slice %d/%d" % (self.next_channel_index, self.hyperstack.num_channels(), self.next_frame_index, self.hyperstack.num_frames(), self.next_slice_index, self.hyperstack.num_slices()))
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return image
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def get_num_images(self):
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return self.hyperstack.num_frames()
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class IImageEngine(ABC):
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"""
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@ -245,6 +285,14 @@ class IImageEngine(ABC):
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:rtype IImage:
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"""
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@abc.abstractmethod
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def compute_median(self, image_feeder):
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"""Compute for each pixel position the median value at this position in all input images.
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:param IImageFeeder image_feeder:
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:rtype IImage:
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"""
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@abc.abstractmethod
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def mean_filter(self, image, radius):
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"""Each pixel becomes an average of its neighbours within the given radius
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@ -7,6 +7,7 @@ from ij import IJ, ImagePlus # pylint: disable=import-error
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from ij.measure import ResultsTable # pylint: disable=import-error
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from ij.plugin import ImageCalculator # pylint: disable=import-error
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from ij.plugin.filter import MaximumFinder # pylint: disable=import-error
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from ij.plugin import ZProjector # pylint: disable=import-error
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from ijopencv.ij import ImagePlusMatConverter # pylint: disable=import-error
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from ijopencv.opencv import MatImagePlusConverter # pylint: disable=import-error
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import org.bytedeco.javacpp.opencv_core as opencv_core # pylint: disable=import-error
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@ -239,6 +240,21 @@ class IJImageEngine(IImageEngine):
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print('max_image', max_image)
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return IJImage(self, max_image)
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def compute_median(self, image_feeder):
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"""Computes for each pixel position the median value at this position in all input images.
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:param IImageFeeder image_feeder:
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:rtype IJmage:
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"""
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hyperstack = image_feeder.create_hyperstack()
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# https://imagej.nih.gov/ij/developer/api/ij/plugin/ZProjector.html
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projector = ZProjector()
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median_image = projector.run(hyperstack.hyperstack, 'median')
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# imagej_run_image_command(image=hyperstack.hyperstack, command="Z Project...", options="projection=Median")
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# # after median computation, the resulting image is expected to be the selected one
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# median_image = IJ.getImage() # get the currently selected image
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return IJImage(self, median_image)
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def mean_filter(self, image, radius):
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"""Implement interface method."""
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IJ.run(image.ij_image, "Mean...", "radius=%d" % radius)
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@ -1,10 +1,10 @@
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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 IImageEngine, Aabb, StackImageFeeder
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from imageengine import PixelType
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from preprocessing import WhiteEstimator, correct_non_uniform_lighting
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from maxima_finder import Match
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from template_matcher import TemplateMatcher
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class TrapsDetector(object):
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@ -15,7 +15,7 @@ class TrapsDetector(object):
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"""
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self.template_matcher = template_matcher
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def compute_traps_mask(self, sequence, channel_id, trap_aabb):
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def compute_traps_mask(self, sequence, channel_id, template_trap_aabb):
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"""Remove the traps in the input sequence
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:param Sequence sequence:
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@ -33,11 +33,32 @@ class TrapsDetector(object):
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uniform_stack = correct_non_uniform_lighting(sequence, channel_id, white_estimator=WhiteEstimator(open_size=75, close_size=75, average_size=75))
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first_image = uniform_stack.get_image(frame_index=0)
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trap_image = first_image.get_subimage(trap_aabb)
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template_trap_image = first_image.get_subimage(template_trap_aabb)
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# ie.save_as_tiff(trap_image, '/home/graffy/Desktop/template.tiff')
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matches = self.template_matcher.match_template(first_image, trap_image)
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matches = self.template_matcher.match_template(first_image, template_trap_image)
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num_traps_per_frame = len(matches)
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num_traps = uniform_stack.num_frames() * num_traps_per_frame
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ie = IImageEngine.get_instance()
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traps_stack = ie.create_hyperstack(width=template_trap_aabb.width, height=template_trap_aabb.height, num_slices=1, num_frames=num_traps, num_channels=1, pixel_type=PixelType.F32)
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trap_index = 0
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for frame_index in range(uniform_stack.num_frames()):
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uniform_frame = uniform_stack.get_image(frame_index=frame_index)
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for frame_trap_index in range(num_traps_per_frame):
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match = matches[frame_trap_index]
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trap_aabb = Aabb(x_min=match.x, y_min=match.y, x_max=match.x + template_trap_aabb.width - 1, y_max=match.y + template_trap_aabb.height - 1)
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assert trap_aabb.width == template_trap_aabb.width
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trap_image = uniform_frame.get_subimage(trap_aabb)
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traps_stack.set_image(frame_index=trap_index, image=trap_image)
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trap_index += 1
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image_feeder = StackImageFeeder(traps_stack)
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clean_trap_image = ie.compute_median(image_feeder)
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ie.save_as_tiff(clean_trap_image, './clean_trap_image.tiff')
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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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@ -7,13 +7,13 @@
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import unittest # unittest2 doesn't exist in fiji
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import sys
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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, correct_non_uniform_lighting
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from lipase.maxima_finder import MaximaFinder
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from lipase.template_matcher import TemplateMatcher
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from lipase.traps_detector import TrapsDetector
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from lipase.catalog import ImageCatalog, Sequence
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from lipase.imageengine import IImageEngine, PixelType, Aabb # pylint: disable=import-error
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from lipase.imagej.ijimageengine import IJImageEngine, IJImage # pylint: disable=import-error
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from lipase.preprocessing import WhiteEstimator, correct_non_uniform_lighting # pylint: disable=import-error
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from lipase.maxima_finder import MaximaFinder # pylint: disable=import-error
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from lipase.template_matcher import TemplateMatcher # pylint: disable=import-error
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from lipase.traps_detector import TrapsDetector # pylint: disable=import-error
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from lipase.catalog import ImageCatalog, Sequence # pylint: disable=import-error
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class TestLipase(unittest.TestCase):
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@ -31,19 +31,19 @@ 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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white_estimate = white_estimator.estimate_white([sequence], ['DM300_327-353_fluo'])
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# find_white_reference_image(white_estimate, sequence.get_white())
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print(white_estimate)
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IImageEngine.get_instance().save_as_tiff(white_estimate, './white_estimate.tiff')
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# assert False, "hellooooo"
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print('end of test_estimate_white')
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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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# white_estimate = white_estimator.estimate_white([sequence], ['DM300_327-353_fluo'])
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# # find_white_reference_image(white_estimate, sequence.get_white())
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# print(white_estimate)
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# IImageEngine.get_instance().save_as_tiff(white_estimate, './white_estimate.tiff')
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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_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_detector(self):
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# the typical value of peaks is -500 and the value between peaks is below -2500
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