# f.write("\n")
# with open("data/test_data.txt", "w") as f:
# f.write("-DOCSTART- -X- -X- -X- O\n\n")
# for i in range(len(test)):
# for j in range(len(test[i])):
# f.write("{} {}\n".format(test[i][j][0], test[i][j][1]))
# f.write("\n")
from ui import Ui_MainWindow
if __name__ == '__main__':
app = QtWidgets.QApplication(sys.argv)
with open("qdarkstyle/style.qss") as f:
app.setStyleSheet(f.read())
MainWindow = QtWidgets.QMainWindow()
ui = Ui_MainWindow()
ui.setWindowTitle("Arabic Ner")
ui.setupUi(MainWindow)
MainWindow.show()
sys.exit(app.exec_())
# def spacy_train():
# iterations = 20
# nlp = spacy.blank("xx")
# print("Begin Training")
# other_pipes = [pipe for pipe in nlp.pipe_names if pipe != 'ner']
# with nlp.disable_pipes(*other_pipes): # only train NER
# optimizer = nlp.begin_training()
# for itn in range(iterations):
# random.shuffle(train_data)
# losses = {}
# for text, annotations in train_data:
