def saveImages(self): for index in range(self.length): image = self.getImageFromName(self.namesObservations[index]) imageWorker = RGBImageWorker(image, self.rows, self.columns) patch = imageWorker.getPatch(self.coordinates[index], self.patchSize) reducedFileName = "%s_%d.tif" % (Utils.getFolderName(self.namesObservations[index]), index) if self.targetVector is None: fileName = os.path.join(data_io.get_testing_folder(), data_io.get_test_folder(), reducedFileName) elif self.targetVector[index] == 1: fileName = os.path.join(data_io.get_training_folder(), data_io.get_positive_folder(), reducedFileName) else: fileName = os.path.join(data_io.get_training_folder(), data_io.get_negative_folder(), reducedFileName) io.imsave(fileName, patch.image)
def prepareEnvironment(self): # People want to save time trainingPathPositive = os.path.join(data_io.get_training_folder(), data_io.get_positive_folder()) trainingPathOldPositive = os.path.join(data_io.get_training_old_folder(), data_io.get_positive_folder()) Utils.shift(data_io.get_training_old_folder(), trainingPathOldPositive, data_io.get_positive_folder(), trainingPathPositive) trainingPathNegative = os.path.join(data_io.get_training_folder(), data_io.get_negative_folder()) trainingPathOldNegative = os.path.join(data_io.get_training_old_folder(), data_io.get_negative_folder()) Utils.shift(data_io.get_training_old_folder(), trainingPathOldNegative, data_io.get_negative_folder(), trainingPathNegative) os.mkdir(trainingPathPositive) os.mkdir(trainingPathNegative) if not self.load: Utils.shift('.', data_io.get_savez_name(), data_io.get_savez_name(), data_io.get_savez_name()) if not self.loadWndchrm: Utils.shift('.', data_io.get_wndchrm_dataset(), data_io.get_wndchrm_dataset(), data_io.get_wndchrm_dataset())
def executeWndchrm(self): command = ["wndchrm", "train", data_io.get_training_folder(), data_io.get_wndchrm_datafit()] subprocess.call(" ".join(command), shell=True) (train, target) = self.parseWndchrmOutput() outfile = open(data_io.get_wndchrm_dataset(), "wb") np.savez(outfile, train=train, target=target) return (train, target)
def saveImages(self): for index in range(self.length): image = self.getImageFromName(self.namesObservations[index]) imageWorker = RGBImageWorker(image, self.rows, self.columns) patch = imageWorker.getPatch(self.coordinates[index], self.patchSize) reducedFileName = "%s_%d.tif" % (Utils.getFolderName( self.namesObservations[index]), index) if self.targetVector is None: fileName = os.path.join(data_io.get_testing_folder(), data_io.get_test_folder(), reducedFileName) elif self.targetVector[index] == 1: fileName = os.path.join(data_io.get_training_folder(), data_io.get_positive_folder(), reducedFileName) else: fileName = os.path.join(data_io.get_training_folder(), data_io.get_negative_folder(), reducedFileName) io.imsave(fileName, patch.image)
def prepareEnvironment(self): # People want to save time trainingPathPositive = os.path.join(data_io.get_training_folder(), data_io.get_positive_folder()) trainingPathOldPositive = os.path.join( data_io.get_training_old_folder(), data_io.get_positive_folder()) Utils.shift(data_io.get_training_old_folder(), trainingPathOldPositive, data_io.get_positive_folder(), trainingPathPositive) trainingPathNegative = os.path.join(data_io.get_training_folder(), data_io.get_negative_folder()) trainingPathOldNegative = os.path.join( data_io.get_training_old_folder(), data_io.get_negative_folder()) Utils.shift(data_io.get_training_old_folder(), trainingPathOldNegative, data_io.get_negative_folder(), trainingPathNegative) os.mkdir(trainingPathPositive) os.mkdir(trainingPathNegative) if not self.load: Utils.shift('.', data_io.get_savez_name(), data_io.get_savez_name(), data_io.get_savez_name()) if not self.loadWndchrm: Utils.shift('.', data_io.get_wndchrm_dataset(), data_io.get_wndchrm_dataset(), data_io.get_wndchrm_dataset())