def get(self, index): ra = None try: # Read cell origin and dimensions for cell at index cellMin = zeros(3, 'l') # long, 3 dimensions cellDims = zeros(3, 'i') # integer, 3 dimensions grid.getCellDimensions(index, cellMin, cellDims) # Unpack Cell origin (in pixel coordinates) x, y, z = cellMin # Unpack Cell dimensions: at margins, may be smaller than cell_width, cell_height width, height, _ = cellDims # ignore depth: it's 1 # Read cell from file into a byte array ra = RandomAccessFile(filepaths[z], 'r') read_width = width * bytesPerPixel bytes = zeros(read_width * height, 'b') # Initial offset to the Cell origin offset = (section_width * y + x) * bytesPerPixel n_read = 0 n_pixels = width * height # Read line by line while n_read < n_pixels: ra.seek(offset) ra.read(bytes, n_read, read_width) n_read += read_width offset += section_width * bytesPerPixel # Create a new Cell of the right pixel type return Cell(cellDims, cellMin, createAccess(bytes, bytesPerPixel)) except: print sys.exc_info() finally: if ra: ra.close()
def parse_TIFF_IFDs(filepath): """ Returns a generator of dictionaries of tags for each IFD in the TIFF file, as defined by the 'parseIFD' function above. """ ra = RandomAccessFile(filepath, 'r') try: # TIFF file format can have metadata at the end after the images, so the above approach can fail # TIFF file header is 8-bytes long: # (See: http://paulbourke.net/dataformats/tiff/tiff_summary.pdf ) # # Bytes 1 and 2: identifier. Either the value 4949h (II) or 4D4Dh (MM), # meaning little-endian and big-endian, respectively. # All data encountered past the first two bytes in the file obey # the byte-ordering scheme indicated by the identifier field. b1, b2 = ra.read(), ra.read() # as two java int, each one byte sized bigEndian = chr(b1) == 'M' parseNextInt = parseNextIntBigEndian if bigEndian else parseNextIntLittleEndian # Bytes 3 and 4: Version: Always 42 ra.skipBytes(2) # Bytes 5,6,7,8: IFDOffset: offset to first image file directory (IFD), the metadata entry for the first image. nextIFDoffset = parseNextInt(ra, 4) # offset to first IFD while nextIFDoffset != 0: ra.seek(nextIFDoffset) tags, nextIFDoffset = parseIFD(ra, parseNextInt) tags["bigEndian"] = bigEndian yield tags finally: ra.close()
def updateCmdForDeltaScanning(commandLine, Framework): originalScanFileFolderPath = CollectorsParameters.PROBE_MGR_INVENTORY_XMLENRICHER_FILES_FOLDER + XmlEnricherConstants.ORIGINAL_FOLDER_NAME originalScanFile = File(originalScanFileFolderPath, InventoryUtils.generateScanFileName(Framework)) if originalScanFile.exists(): scan = None try: try: buffer = jarray.zeros(0x24, 'b') fileSize = originalScanFile.length() if fileSize > 0x24: scan = RandomAccessFile(originalScanFile, "r") scan.readFully(buffer) if (buffer[0] == 0x1F) and ((buffer[1] & 0xFF) == 0x8B) and (buffer[2] == 0x08): scan.seek(fileSize - 8) scan.readFully(buffer, 0, 8) crc32 = getInt(buffer, 0) size = getInt(buffer, 4) deltaParams = ' -oldscanid:' + str(crc32) + ' -oldscansize:' + str(size) + ' ' index = String(commandLine).indexOf(ENTERPRISE_MODE) + String(ENTERPRISE_MODE).length() commandLine = commandLine[0:index] + deltaParams + commandLine[index + 1:] logger.debug('Scanner execution command updated to ', commandLine) except: logger.debugException("Failed to calculate CRC32 and size of zipped scan file " + originalScanFile.getAbsolutePath()) finally: if scan is not None: try: scan.close() except: pass return commandLine
def readFIBSEMdat(path, channel_index=-1, header=1024, magic_number=3555587570, asImagePlus=False, toUnsigned=True): """ Read a file from Shan Xu's FIBSEM software, where two or more channels are interleaved. Assumes channels are stored in 16-bit. path: the file path to the .dat file. channel_index: the 0-based index of the channel to parse, or -1 (default) for all. header: defaults to a length of 1024 bytes magic_number: defaults to that for version 8 of Shan Xu's .dat image file format. isSigned: defaults to True, will subtract the min value when negative. asImagePlus: return a list of ImagePlus instead of ArrayImg which is the default. """ ra = RandomAccessFile(path, 'r') try: # Check the magic number ra.seek(0) magic = ra.readInt() & 0xffffffff if magic != magic_number: msg = "magic number mismatch: v8 magic " + str(magic_number) + " != " + str(magic) + " for path:\n" + path System.out.println(msg) print msg # Continue: attempt to parse the file anyway # Read the number of channels ra.seek(32) numChannels = ra.readByte() & 0xff # a single byte as unsigned integer # Parse width and height ra.seek(100) width = ra.readInt() ra.seek(104) height = ra.readInt() # Read the whole interleaved pixel array ra.seek(header) bytes = zeros(width * height * 2 * numChannels, 'b') # 2 for 16-bit ra.read(bytes) # Parse as 16-bit array sb = ByteBuffer.wrap(bytes).order(ByteOrder.BIG_ENDIAN).asShortBuffer() bytes = None finally: ra.close() # shorts = zeros(width * height * numChannels, 'h') sb.get(shorts) sb = None # Deinterleave channels and convert to unsigned short # Shockingly, these values are signed shorts, not unsigned! (for first popeye2 squid volume, December 2021) # With ASM: fast channels = DAT_handler.deinterleave(shorts, numChannels, channel_index) shorts = None # if toUnsigned: for s in channels: DAT_handler.toUnsigned(s) # With python array sampling: very slow, and not just from iterating whole array once per channel #seq = xrange(numChannels) if -1 == channel_index else [channel_index] #channels = [shorts[i::numChannels] for i in seq] if asImagePlus: return [ImagePlus(str(i), ShortProcessor(width, height, s, None)) for i, s in enumerate(channels)] else: return [ArrayImgs.unsignedShorts(s, [width, height]) for s in channels]
def readBinaryMaskImg(filepath, width, height, depth, header_size): ra = RandomAccessFile(filepath, 'r') try: ra.skipBytes(header_size) bytes = zeros(width * height * depth, 'b') ra.read(bytes) return ArrayImgs.unsignedBytes(bytes, [width, height, depth]) finally: ra.close()
def get(self, index): IFD = self.IFDs[index] ra = RandomAccessFile(self.filepath, 'r') try: cell_position = [0, 0, index] pixels = read_TIFF_plane(ra, IFD) # a native array access = self.types[IFD["bitDepth"]][0] # e.g. ByteArray, FloatArray ... return Cell(self.cell_dimensions, cell_position, access(pixels)) finally: ra.close()
def read2DImageROI(path, dimensions, interval, pixelType=UnsignedShortType, header=0, byte_order=ByteOrder.LITTLE_ENDIAN): """ Read a region of interest (the interval) of an image in a file. Assumes the image is written with the first dimension moving slowest. path: the file path to the image file. dimensions: a sequence of integer values e.g. [512, 512, 512] interval: two sequences of integer values defining the min and max coordinates, e.g. [[20, 0], [400, 550]] pixeltype: e.g. UnsignedShortType, FloatType header: defaults to zero, the number of bytes between the start of the file and the start of the image data. Supports only these types: UnsignedByteType, UnsignedShortType, FloatType. Returns an ArrayImg of the given type. """ ra = RandomAccessFile(path, 'r') try: width, height = dimensions minX, minY = interval[0] maxX, maxY = interval[1] roi_width, roi_height = maxX - minX + 1, maxY - minY + 1 tailX = width - roi_width - minX #print minX, minY #print maxX, maxY #print roi_width, roi_height size = roi_width * roi_height n_bytes_per_pixel = pixelType().getBitsPerPixel() / 8 #print n_bytes_per_pixel bytes = zeros(size * n_bytes_per_pixel, 'b') # Read only the 2D ROI ra.seek(header + (minY * width + minX) * n_bytes_per_pixel) for h in xrange(roi_height): ra.readFully(bytes, h * roi_width * n_bytes_per_pixel, roi_width * n_bytes_per_pixel) ra.skipBytes((tailX + minX) * n_bytes_per_pixel) # Make an image roiDims = [roi_width, roi_height] if UnsignedByteType == pixelType: return ArrayImgs.unsignedBytes(bytes, roiDims) if UnsignedShortType == pixelType: shorts = zeros(size, 'h') ByteBuffer.wrap(bytes).order(byte_order).asShortBuffer().get(shorts) return ArrayImgs.shorts(shorts, roiDims) if FloatType == pixelType: floats = zeros(size, 'f') ByteBuffer.wrap(bytes).order(byte_order).asFloatBuffer().get(floats) return ArrayImgs.floats(floats, roiDims) finally: ra.close()
def readUnsignedBytes(path, dimensions, header=0): """ Read a file as an ArrayImg of UnsignedShortType """ ra = RandomAccessFile(path, 'r') try: if header < 0: # Interpret from the end: useful for files with variable header lengths # such as some types of uncompressed TIFF formats header = ra.length() + header ra.skipBytes(header) bytes = zeros(reduce(operator.mul, dimensions), 'b') ra.read(bytes) return ArrayImgs.unsignedBytes(bytes, dimensions) finally: ra.close()
def get(self, index): """ Assumes: - uncompressed image - one sample per pixel (one channel only) """ IFD = self.IFDs[index] ra = RandomAccessFile(self.filepath, 'r') try: cell_dimensions = [IFD["width"], IFD["height"], 1] cell_position = [0, 0, index] pixels = read_TIFF_plane(ra, IFD) return Cell(cell_dimensions, cell_position, self.types[pixels.typecode](pixels)) finally: ra.close()
def readFIBSEMdat(path, channel_index=-1, header=1024, magic_number=3555587570): """ Read a file from Shan Xu's FIBSEM software, where two channels are interleaved. Assumes channels are stored in 16-bit. path: the file path to the .dat file. channel_index: the 0-based index of the channel to parse, or -1 (default) for all. header: defaults to a length of 1024 bytes magic_number: defaults to that for version 8 of Shan Xu's .dat image file format. """ ra = RandomAccessFile(path, 'r') try: # Check the magic number ra.seek(0) if ra.readInt() & 0xffffffff != magic_number: print "Magic number mismatch" return None # Read the number of channels ra.seek(32) numChannels = ra.readByte() & 0xff # a single byte as unsigned integer # Parse width and height ra.seek(100) width = ra.readInt() ra.seek(104) height = ra.readInt() print numChannels, width, height # Read the whole interleaved pixel array ra.seek(header) bytes = zeros(width * height * 2 * numChannels, 'b') # 2 for 16-bit ra.read(bytes) print "read", len(bytes), "bytes" # takes ~2 seconds # Parse as 16-bit array sb = ByteBuffer.wrap(bytes).order(ByteOrder.BIG_ENDIAN).asShortBuffer() shorts = zeros(width * height * numChannels, 'h') sb.get(shorts) # Deinterleave channels # With Weaver: fast channels = w.deinterleave(shorts, numChannels, channel_index) # With python array sampling: very slow, and not just from iterating whole array once per channel # seq = xrange(numChannels) if -1 == channel_index else [channel_index] #channels = [shorts[i::numChannels] for i in seq] # With clojure: extremely slow, may be using reflection unexpectedly #channels = deinterleave.invoke(shorts, numChannels) print len(channels) # Shockingly, these values are signed shorts, not unsigned! return [ArrayImgs.shorts(s, [width, height]) for s in channels] finally: ra.close()
def readFloats(path, dimensions, header=0, byte_order=ByteOrder.LITTLE_ENDIAN): """ Read a file as an ArrayImg of FloatType """ size = reduce(operator.mul, dimensions) ra = RandomAccessFile(path, 'r') try: if header < 0: # Interpret from the end: useful for files with variable header lengths # such as some types of uncompressed TIFF formats header = ra.length() + header ra.skipBytes(header) bytes = zeros(size * 4, 'b') ra.read(bytes) floats = zeros(size, 'f') ByteBuffer.wrap(bytes).order(byte_order).asFloatBuffer().get(floats) return ArrayImgs.floats(floats, dimensions) finally: ra.close()
def readUnsignedShorts(path, dimensions, header=0, return_array=False, byte_order=ByteOrder.LITTLE_ENDIAN): """ Read a file as an ArrayImg of UnsignedShortType """ size = reduce(operator.mul, dimensions) ra = RandomAccessFile(path, 'r') try: if header < 0: # Interpret from the end: useful for files with variable header lengths # such as some types of uncompressed TIFF formats header = ra.length() + header ra.skipBytes(header) bytes = zeros(size * 2, 'b') ra.read(bytes) shorts = zeros(size, 'h') # h is for short ByteBuffer.wrap(bytes).order(byte_order).asShortBuffer().get(shorts) return shorts if return_array else ArrayImgs.unsignedShorts(shorts, dimensions) finally: ra.close()
def updateCmdForDeltaScanning(commandLine, Framework): originalScanFileFolderPath = CollectorsParameters.PROBE_MGR_INVENTORY_XMLENRICHER_FILES_FOLDER + XmlEnricherConstants.ORIGINAL_FOLDER_NAME originalScanFile = File(originalScanFileFolderPath, InventoryUtils.generateScanFileName(Framework)) if originalScanFile.exists(): scan = None try: try: buffer = jarray.zeros(0x24, 'b') fileSize = originalScanFile.length() if fileSize > 0x24: scan = RandomAccessFile(originalScanFile, "r") scan.readFully(buffer) if (buffer[0] == 0x1F) and ( (buffer[1] & 0xFF) == 0x8B) and (buffer[2] == 0x08): scan.seek(fileSize - 8) scan.readFully(buffer, 0, 8) crc32 = getInt(buffer, 0) size = getInt(buffer, 4) deltaParams = ' -oldscanid:' + str( crc32) + ' -oldscansize:' + str(size) + ' ' index = String(commandLine).indexOf( ENTERPRISE_MODE) + String( ENTERPRISE_MODE).length() commandLine = commandLine[ 0:index] + deltaParams + commandLine[index + 1:] logger.debug('Scanner execution command updated to ', commandLine) except: logger.debugException( "Failed to calculate CRC32 and size of zipped scan file " + originalScanFile.getAbsolutePath()) finally: if scan is not None: try: scan.close() except: pass return commandLine
def get(self, index): ra = None try: # Read cell origin and dimensions for cell at index cellMin = zeros(3, 'l') # long[3] cellDims = zeros(3, 'i') # integer[3] grid.getCellDimensions(index, cellMin, cellDims) # Unpack Cell origin (in pixel coordinates) x, y, z = cellMin # Unpack Cell dimensions: at margins, may be smaller than cell_width, cell_height width, height, _ = cellDims # ignore depth: it's 1 # Read cell from file into a byte array ra = RandomAccessFile(filepaths[z], 'r') read_width = width * bytesPerPixel bytes = zeros(read_width * height, 'b') # will contain the entire Cell pixel data # Initial offset to the Cell origin offset = (section_width * y + x) * bytesPerPixel n_pixels = width * height if width == section_width: # Read whole block in one go: cell data is continuous in the file ra.seek(offset) ra.read(bytes, 0, n_pixels * bytesPerPixel) else: # Read line by line n_read = 0 while n_read < n_pixels: ra.seek(offset) ra.read(bytes, n_read, read_width) n_read += read_width # ensure n_read advances in case file is truncated to avoid infinite loop offset += section_width * bytesPerPixel # Create a new Cell of the right pixel type return Cell(cellDims, cellMin, createAccess(bytes, bytesPerPixel)) except: print sys.exc_info() finally: if ra: ra.close()
# Bytes 3 and 4: Version: Always 42 ra.skipBytes(2) # Bytes 5,6,7,8: IFDOffset: offset to first image file directory (IFD), the metadata entry for the first image. firstIFDoffset = parseNextInt(ra, 4) ra.skipBytes(firstIFDoffset - ra.getFilePointer() ) # minus the current position: all offsets are absolute firstTags, _ = parseIFD(ra, parseNextInt) # Correct headerSize for TIFF files (and then assuming images are contiguous and in order, # which they don't have to be either in TIFF) headerSize = firstTags["offset"] # Sanity check: if width != firstTags["width"] or height != firstTags[ "height"] or bitDepth != firstTags["samples_per_pixel"] * 8: print "TIFF header disagrees with ChannelSeparator's parsing of metadata." finally: ra.close() """ # Try to read the header size using OME as per Curtis Rueden's suggestion from loci.common import RandomAccessInputStream, Location ira = None cs = None try: #rais = RandomAccessInputStream(filepath) #Location.mapFile("my-rais", rais) cs = ChannelSeparator() cs.setId(filepath) Location.mapFile("my-rais", cs) ira = Location.getHandle("my-rais") print "IRA file pointer:", ira.getFilePointer()
def savePointMatches(img_filename1, img_filename2, pointmatches, directory, params, coords_header=["x1", "y1", "x2", "y2"]): filename = basename(img_filename1) + '.' + basename( img_filename2) + ".pointmatches.csv" path = os.path.join(directory, filename) msg = [str(len(pointmatches))] ra = None try: """ with open(path, 'w') as csvfile: w = csv.writer(csvfile, delimiter=',', quotechar='"', quoting=csv.QUOTE_NONNUMERIC) # First two rows: parameter names and values keys = params.keys() msg.append("keys: " + ",".join(map(str, keys))) msg.append("vals: " + ",".join(str(params[key]) for key in keys)) #for pm in pointmatches: # msg.append(", ".join(map(str, PointMatches.asRow(pm)))) w.writerow(keys) w.writerow(tuple(params[key] for key in keys)) # PointMatches header if 0 == len(pointmatches): # Can't know whether there are 2 or 3 dimensions per coordinate w.writerow(coords_header) else: w.writerow(PointMatches.csvHeader(next(iter(pointmatches)))) # support both lists and sets # One PointMatch per row for pm in pointmatches: w.writerow(PointMatches.asRow(pm)) # Ensure it's written csvfile.flush() os.fsync(csvfile.fileno()) """ # DEBUG write differently, the above FAILS for ~20 out of 130,000 files lines = [] keys = params.keys() lines.append(",".join(map(str, keys))) lines.append(",".join(map(str, (params[key] for key in keys)))) header = coords_header if 0 == len(pointmatches) \ else PointMatches.csvHeader(next(iter(pointmatches))) lines.append(",".join(header)) for pm in pointmatches: p1 = pm.getP1().getW() # a double[] array p2 = pm.getP2().getW() # a double[] array lines.append("%f,%f,%f,%f" % (p1[0], p1[1], p2[0], p2[1])) body = "\n".join(lines) ra = RandomAccessFile(path, 'rw') ra.writeBytes(body) ra.getFD().sync() # ensure it's written except: syncPrintQ("Failed to save pointmatches at %s\n%s" % (path, "\n".join(msg))) printException() if os.path.exists(path): os.remove(path) finally: if ra is not None: ra.close()