def main_validacao():
"""Versão de validação. Treina com arquivos da pasta treinamento e prediz arquivos da pasta validação"""
random.seed(SEED)
np.random.seed(SEED)
#criação dos datasets a partir dos arquivos de áudio
X_train, y_train = create_set(PATH_TREINAMENTO)
X_val, y_val = create_set(PATH_VALIDACAO)
#X_train = normalize(X_train, axis=0, norm='l2')
#X_val = normalize(X_val, axis=0, norm='l2')
classificador = RandomForestClassifier(n_estimators=75)
classificador.fit(X_train, y_train)
# classificação final e avaliação dos resultados
print("\nAvaliação dos Resultados\n")
y_pred = classificador.predict(X_val)
print("\nPerformance do Modelo para cada classe de Caractér\n")
print(classification_report(y_val, y_pred))
print("\nMatriz de confusão\n")
print(labeled_confusion_matrix(y_val, y_pred))
#reorganização dos labels para formar os captchas
captcha_test = rearrange(y_val, AUDIOS_POR_ARQUIVO)
captcha_pred = rearrange(y_pred, AUDIOS_POR_ARQUIVO)
acerto_captchas = accuracy_score(captcha_test, captcha_pred) * 100
print(
"\nA acurácia obtida com o modelo para a predição dos captchas no conjunto de validação foi de %2.2f%%.\n"
% (acerto_captchas))
import re
import os
import util
# Gets all lines in xls or csv files by given regex and folder
folderName = raw_input('Folder: ')
filePattern = raw_input('Regex: ')
is_csv = filePattern.endswith('.csv')
mails = []
read = 1
for file in os.listdir(folderName):
if re.match(filePattern, file):
if is_csv:
with open(folderName + "/" + file) as csvfile:
for row in csvfile:
mails.extend(re.findall(r'[\w\.-]+@[\w\.-]+', row))
else:
book = xlrd.open_workbook(folderName + "/" + file)
for sheet in book.sheets():
for row in sheet.get_rows():
for cell in row:
if type(cell.value) is unicode:
mails.extend(re.findall(r'[\w\.-]+@[\w\.-]+', cell.value))
print('Files read: ' + repr(read))
read += 1
print('Filtering double mails (total mails ' + repr(len(mails)) + ')')
util.copy_to_clipboard(sorted(util.create_set(mails, lambda s: s.lower()),
key=(str.lower if is_csv else unicode.lower)))
__author__ = 'jens'
import util
# Remove all double entries and entries that have an extension out of the second list
print 'Base set'
base = util.create_set(util.raw_multi_line_input(), lambda s: s.lower())
print 'Extensions to remove from base'
to_del = util.create_set(util.raw_multi_line_input(), lambda s: s.lower())
for to_del_entry in to_del:
base_set = set(base)
for entry in base_set:
if entry.lower().endswith(to_del_entry.lower()):
base.remove(entry)
util.copy_to_clipboard(sorted(base, key=str.lower))
__author__ = 'jens' import util # Read multi line input and copies all unique lines to the clipboard # This will also trim all leading and trailing spaces multiLineInput = util.raw_multi_line_input() uniqueSorted = util.trim(sorted(util.create_set(multiLineInput, lambda s: s.lower()), key=str.lower)) util.copy_to_clipboard(uniqueSorted)
__author__ = 'jens'
import util
# Read multi line input and copies all unique lines to the clipboard
# This will also trim all leading and trailing spaces
multiLineInput = util.raw_multi_line_input()
uniqueSorted = util.trim(
sorted(util.create_set(multiLineInput, lambda s: s.lower()),
key=str.lower))
util.copy_to_clipboard(uniqueSorted)