def load_classifier(self):
utils.clear_screen()
if not MODEL_CONTROLLER.load_model():
self.start_menue()
else:
self.main_menue()
def show_setting_SURF(self):
utils.clear_screen()
# print current settings
print "SURF SETTINGS"
print "Cross Val. k:\t\t", Settings.SU_CROSS_VALIDATION_K
print "Test Segments:\t\t", Settings.SU_TESTDATA_SEGMENTS
print "SVM Props:\t\t", Settings.SU_SVM_PARAMS
print "BOW Dimension:\t\t", Settings.SU_BOW_DIMENSION
options = ["change cross validation number", "change BOW Dimension"]
input = utils.menue("OPTIONS:", options, False, True)
if input == 1:
Settings.SU_CROSS_VALIDATION_K = utils.value_setting(
"Cross validation runs", "i", "1 means no cross validation.")
self.save_settings()
self.show_setting_SURF()
elif input == 2:
Settings.SU_BOW_DIMENSION = utils.value_setting(
"Change BOW Dimension", "i", "default: 1000")
self.save_settings()
self.show_setting_SURF()
else:
self.show_settings()
def start_menue(self):
"""Starting point of program."""
utils.clear_screen()
options = [
"create NEW classifier", "load EXISTING classifier",
"test parameters", "show high scores", "segment image",
"test data manipulation", "settings"
]
input = utils.menue("START MENUE:", options, True, False)
if input == 1:
self.create_classifier()
elif input == 2:
self.load_classifier()
elif input == 3:
self.test_parameters()
elif input == 4:
self.show_highscores()
elif input == 5:
self.segment_image()
elif input == 6:
self.test_data_menue()
elif input == 7:
self.show_settings()
elif input == 8:
return
self.start_menue()
def show_setting_histogram(self):
utils.clear_screen()
# print current settings
print "Histogram SETTINGS"
print "Cross Val. k:\t\t", Settings.H_CROSS_VALIDATION_K
print "Test Segments:\t\t", Settings.H_TESTDATA_SEGMENTS
print "Image Segments:\t\t", Settings.H_IMAGE_SEGMENTS
print "Bins per Color\t\t", Settings.H_BINS
print "Range:\t\t\t", Settings.H_COLOR_RANGE
print "Color Space:\t\t", Settings.H_COLOR_SPACE
print "SVM Props:\t\t", Settings.H_SVM_PARAMS
options = [
"change cross validation number", "change image segmentation",
"change number of bins", "change color range", "change color space"
]
input = utils.menue("OPTIONS:", options, False, True)
if input == 1:
Settings.H_CROSS_VALIDATION_K = utils.value_setting(
"Cross validation runs", "i", "1 means no cross validation.")
self.save_settings()
self.show_setting_histogram()
elif input == 2:
Settings.H_IMAGE_SEGMENTS = utils.radio_setting(
"Number of Image Segments", Settings.H_IMAGE_SEGMENTS,
["1", "2", "4", "9", "16", "25"], [1, 2, 4, 9, 16, 25])
self.save_settings()
self.show_setting_histogram()
elif input == 3:
Settings.H_BINS = utils.value_setting(
"Number of histogram bins per color", "i", "default: 64 bins")
self.save_settings()
self.show_setting_histogram()
elif input == 4:
lower = utils.value_setting("Lower range for color values", "i",
"default: 0")
upper = utils.value_setting("Upper range for color values", "i",
"default: 256")
Settings.H_COLOR_RANGE = [lower, upper]
self.save_settings()
self.show_setting_histogram()
elif input == 5:
Settings.H_COLOR_SPACE = utils.radio_setting(
"Color Space", Settings.H_COLOR_SPACE, ["HSV", "RGB", "BGR"],
[ColorSpace.HSV, ColorSpace.RGB, ColorSpace.BGR])
self.save_settings()
self.show_setting_histogram()
else:
self.show_settings()
def show_model_screen(self):
"""
Prints a model selection screen to the console window.
Returns:
ModelId
"""
utils.clear_screen()
options = ["SIFT kp/dp + BoW + SVM", "Histogram & SVM", "SURF kp/dp + BoW + SVM", "ORB kp/dp + BoW + SVM", "DAISY [deprecated]", "CenSurE kp, SIFT dp + BoW + SVM", "Late Fusion - SVM-Vectors", "LBP + SVM", "Neural Nets", "Late Fusion Majority Vote", "Random Keypoint Sampling"]
modelId = utils.menue("Choose model:", options, False)
if modelId == len(options):
return -1
return modelId
def show_settings(self):
utils.clear_screen()
# print current settings
print "SETTINGS"
print "DataSet:\t\t", self.show_default_dataset()
print "High Eval Detail:\t", Settings.G_EVALUATION_DETAIL_HIGH
print "Detailed output:\t", Settings.G_DETAILED_CONSOLE_OUTPUT
print "Mail Notifications:\t", MailServer.are_mails_enabled()
print "Auto report mailing:\t", Settings.G_AUTOMATIC_REPORT_MAILING
options = [
"change default data set", "change evaluation detail level",
"change console output level", "SIFT Settings",
"Histogram Settings", "SURF Settings", "Configure Mail Settings"
]
input = utils.menue("OPTIONS:", options, False, True)
if input == 1:
self.change_default_dataset()
self.show_settings()
elif input == 2:
Settings.G_EVALUATION_DETAIL_HIGH = utils.radio_setting(
"Detail Level", Settings.G_EVALUATION_DETAIL_HIGH,
["High", "Low"], [True, False])
self.save_settings()
self.show_settings()
elif input == 3:
Settings.G_DETAILED_CONSOLE_OUTPUT = utils.radio_setting(
"Console Output Detail", Settings.G_DETAILED_CONSOLE_OUTPUT,
["High", "Low"], [True, False])
self.save_settings()
self.show_settings()
elif input == 4:
self.show_setting_SIFT()
self.show_settings()
elif input == 5:
self.show_setting_histogram()
self.show_settings()
elif input == 6:
self.show_setting_SURF()
self.show_settings()
elif input == 7:
self.show_setting_Mail()
self.show_settings()
elif input == 8:
self.start_menue()
def test_data_menue(self):
utils.clear_screen()
options = [
"equalize test data image size", "add prefix to test data",
"crop bounding boxes", "crop to square", "augment test data size",
"cherry pick 'test data augmentation' iteration"
]
input = utils.menue("Test data menue", options, False, True)
if input == 1:
self.normalize_testdata()
elif input == 2:
self.rename_prefix()
elif input == 3:
self.crop_bounding_boxes()
elif input == 4:
self.crop_test_data_to_square()
elif input == 5:
self.augment_test_data()
elif input == 6:
self.augment_test_data(True)
else:
return
self.test_data_menue()