classes package¶

Submodules¶

classes.auxiliary module¶

class classes.auxiliary.Auxiliary(sizeX=100, sizeY=100, interpolation=2)[source]¶

Class that provides some auxiliary functions.

calcAccuracy(recognizedImages, totalFaceImages)[source]¶: Calculates the accuracy (percentage) using the formula: acc = recognizedImages / totalFaceImages * 100 :param recognizedImages: The number of recognized face images. :param totalFaceImages: The number of total face images. :return: The accuracy.

concatenateImages(leftImage, rightImage)[source]¶: Concatenate two images side by side (horizontally) and returns a new one. :param leftImage: The image that should be put to the left. :param rightImage: The image that should be put to the right. :return: The new concatenated image.

extractFilesPaths(path)[source]¶: Extract all paths for all files type. :param path: The directory path. :return: A list with all paths for all files.

extractImagesPaths(path)[source]¶: Extract all paths for each image in a directory. :param path: The directory path. :return: A list with all file paths.

getDefaultSize()[source]¶: Get the default image size defined (default is 100x100).

getInterpolationMethodName()[source]¶: Get the selected interpolation method name. :return: A string containing the interpolation method name.

isGrayscale(image)[source]¶: Check if an image is in grayscale. :param image: The image. :return: True if the image is in grayscale.

loadAllImagesForTest(testPath)[source]¶: Load all images for test. :param testPath: The test path. :return: Three lists with the images, labels and file names.

loadAllImagesForTrain(trainPath)[source]¶: Load all images for training. :param trainPath: The train path. :return: Three lists with the images, labels and file names.

loadImage(path)[source]¶: Load an image based on the path passed by parameter. :param path: The path to the image file. :return: The image object.

preprocessImage(path)[source]¶: Preprocess an image. Load an image, convert to grayscale and resize it. :param path: The image path. :return: The preprocessed image.

resizeImage(image, sizeX, sizeY, interpolationMethod)[source]¶: Resize an image. :param image: The image object. :param sizeX: The image width. :param sizeY: The image height. :param interpolationMethod: The interpolation method. :return: The resized image.

saveImage(fileName, image)[source]¶: Save an image based on the fileName passed by parameter. :param fileName: The file name. :param image: The image.

setDefaultSize(sizeX, sizeY)[source]¶: Set the default size. :param sizeX: Image width. :param sizeY: Image height.

toGrayscale(image)[source]¶: Convert an image to grayscale :param image: The image. :return: The image in grayscale.

writeTextFile(content, fileName)[source]¶: Write the content to a text file based on the file name. :param content: The content as a string. :param fileName: The file name (e.g. home/user/test.txt)

classes.ensemble module¶

class classes.ensemble.Ensemble(fralgorithms=[], auxiliary=<classes.auxiliary.Auxiliary instance>, voting=<classes.voting.Voting instance>)[source]¶

Class that provides an interface for the Ensemble

recognizeFaces(testPath)[source]¶: Function that tries to recognize each face (path passed by parameter).

reset()[source]¶: Reset all lists and results. It is used to reset all values to re-train the algorithm

resetResults()[source]¶: Reset results (including the test lists and the predictions) It is used to reset only the results of the tests

train(trainPath)[source]¶: Function responsible for train the face recognition algorithm based on the image files from the trainPath.

classes.face_recognition module¶

class classes.face_recognition.FaceRecognition(algorithm, auxiliary=<classes.auxiliary.Auxiliary instance>, threshold=-1)[source]¶

Class that provides an interface to the face recognition algorithms

recognizeFaces(testPath)[source]¶: Function that tries to recognize each face (path passed by parameter).

reset()[source]¶: Reset all values, including train and test paths

resetResults()[source]¶: Reset all results

train(trainPath)[source]¶: Function responsible for train the face recognition algorithm based on the image files from the trainPath.

classes.report module¶

class classes.report.Report(object)[source]¶

Class that provides an interface to generate reports

generateFullReport()[source]¶: Generate the full report. Return the content containing the information about each predicted image.

generateReportSummary()[source]¶: Generate a report summary with informations about the test. Return the content as a string.

printResults()[source]¶: Function used to show the results

saveAllResults(path=”)[source]¶: Function used to automatically save the report in a defined folder. Save the entire results, including the summary report, full report and all images.

saveReport(path=”)[source]¶: Function used to automatically save the report in a defined folder. Save only the text report not the images.

classes.voting module¶

class classes.voting.Voting(votingScheme=0, weights=[])[source]¶

Class the provides voting methods for the ensemble.

MAJORITY = 0¶

WEIGHTED = 1¶

getVotingSchemeName()[source]¶: Get the name of the selected voting scheme to be used in the report.

majorityVoting(subjects)[source]¶: Majority voting. Return -1 for empty list

vote(subjects, weights=[])[source]¶: Call the selected voting scheme

weightedVoting(subjects, weights)[source]¶: Weighted voting.