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@ -78,6 +78,38 @@ class Parser(object): |
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else: |
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else: |
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return Frame(image, frame_no=frame_number, metadata=self._get_frame_metadata()) |
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return Frame(image, frame_no=frame_number, metadata=self._get_frame_metadata()) |
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def get_slice_by_attributes(self, xywh, frame_number, field_of_view, channel, z_level, height, width): |
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"""Gets a rectangular slice of an image based on its attributes alone |
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Args: |
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xywh: tuples containing (x, y, w, h) values of the |
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rectangular region to load |
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frame_number: the frame number |
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field_of_view: the field of view |
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channel_name: the color channel name |
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z_level: the z level |
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height: the height of the image |
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width: the width of the image |
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Returns: |
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Frame: the requested image |
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""" |
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frame_number = 0 if frame_number is None else frame_number |
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field_of_view = 0 if field_of_view is None else field_of_view |
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channel = 0 if channel is None else channel |
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z_level = 0 if z_level is None else z_level |
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image_group_number = self._calculate_image_group_number(frame_number, field_of_view, z_level) |
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try: |
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timestamp, raw_image_data = self._get_raw_slice_data( |
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xywh, image_group_number, channel, height, width |
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) |
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except (TypeError): |
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return Frame([], frame_no=frame_number, metadata=self._get_frame_metadata()) |
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else: |
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return Frame(raw_image_data, frame_no=frame_number, metadata=self._get_frame_metadata()) |
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def get_image_by_attributes(self, frame_number, field_of_view, channel, z_level, height, width): |
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def get_image_by_attributes(self, frame_number, field_of_view, channel, z_level, height, width): |
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"""Gets an image based on its attributes alone |
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"""Gets an image based on its attributes alone |
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@ -246,6 +278,79 @@ class Parser(object): |
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""" |
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""" |
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return {channel: n for n, channel in enumerate(self.metadata["channels"])} |
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return {channel: n for n, channel in enumerate(self.metadata["channels"])} |
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def _get_raw_slice_data(self, xywh, image_group_number, channel, height, width): |
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"""Reads the raw bytes and the timestamp of a rectangular slice |
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of an image. |
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Args: |
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xywh: tuples containing (x, y, w, h) values of the |
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rectangular region to load |
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image_group_number: the image group number (see _calculate_image_group_number) |
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channel: the position (int) of the channel to load |
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height: the height of the image |
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width: the width of the image |
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Returns: |
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""" |
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size_c = len(self.metadata["channels"]) |
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x0, y0, w, h = xywh |
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chunk_location = self._label_map.get_image_data_location(image_group_number) |
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fh = self._fh |
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if chunk_location is None or fh is None: |
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return None |
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fh.seek(chunk_location) |
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# The chunk metadata is always 16 bytes long |
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chunk_metadata = fh.read(16) |
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header, relative_offset, data_length = struct.unpack("IIQ", chunk_metadata) |
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if header != 0xabeceda: |
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raise ValueError("The ND2 file seems to be corrupted.") |
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# We start at the location of the chunk metadata, skip over the metadata, and then proceed to the |
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# start of the actual data field, which is at some arbitrary place after the metadata. |
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fh.seek(chunk_location + 16 + relative_offset) |
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# Read timestamp (8 bytes) |
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timestamp = struct.unpack("d", fh.read(8))[0] |
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# Stitched Images: evaluate number of bytes to strip |
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# (with stitched images sometimes after each row we have a regular number of extra bytes) |
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n_unwanted_bytes = (data_length-8) % (height*width) |
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assert 0 == n_unwanted_bytes % height |
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rowskip = n_unwanted_bytes // height |
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# Read ROI: row-by-row |
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image_start_pos = chunk_location + 16 + relative_offset + 8 |
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line_bytemask = np.zeros(size_c, dtype=np.bool) |
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line_bytemask[channel] = True |
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line_bytemask = np.tile(line_bytemask.repeat(2),w) |
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def get_line(y): |
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fh.seek(image_start_pos + size_c*2*((width)*y+x0) + y*rowskip) |
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return np.frombuffer(fh.read(size_c*2*w), np.byte)[line_bytemask] |
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data = [get_line(y) for y in range(y0, y0+h)] |
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data = bytes().join(data) |
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image_group_data = array.array("H", data) |
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true_channels_no = int(len(image_group_data) / (h * w)) |
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image_data = np.reshape(image_group_data, (h, w, true_channels_no)) |
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missing_channels = ~np.any(image_data, axis=(0, 1)) |
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image_data[..., missing_channels] = np.full( |
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(h, w, missing_channels.sum()), np.nan) |
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if np.any(missing_channels): |
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warnings.warn( |
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"ND2 file contains gap frames which are represented by " |
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+ "np.nan-filled arrays; to convert to zeros use e.g. " |
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+ "np.nan_to_num(array)") |
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return timestamp, image_data[...,0] |
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def _get_raw_image_data(self, image_group_number, channel_offset, height, width): |
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def _get_raw_image_data(self, image_group_number, channel_offset, height, width): |
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"""Reads the raw bytes and the timestamp of an image. |
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"""Reads the raw bytes and the timestamp of an image. |
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