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import pandas as pd
import numpy as np
import tensorflow as tf
import string
import re
import gradio as gr
tr_stop_words = pd.read_csv("tr-stop-words.txt",header=None)
@tf.keras.utils.register_keras_serializable()
def standart_custom(input_text):
lower = tf.strings.lower(input_text, encoding='utf-8')
no_stars = tf.strings.regex_replace(lower, "\*", " ")
stripped_html = tf.strings.regex_replace(no_stars, "<br />", "")
no_numbers = tf.strings.regex_replace(stripped_html, "\w*\d\w*","")
no_punctuation = tf.strings.regex_replace(no_numbers,'[%s]' % re.escape(string.punctuation),'')
#remove stopwords
no_stop_words =' '+no_punctuation+ ' '
for each in tr_stop_words.values:
no_stop_words = tf.strings.regex_replace(no_stop_words, ' '+each[0]+' ', r" ")
no_space = tf.strings.regex_replace(no_stop_words, " +", " ")
no_turkish_character = tf.strings.regex_replace(no_space, "ç", "c")
no_turkish_character = tf.strings.regex_replace(no_turkish_character, "ğ", "g")
no_turkish_character = tf.strings.regex_replace(no_turkish_character, "ı", "i")
no_turkish_character = tf.strings.regex_replace(no_turkish_character, "ö", "o")
no_turkish_character = tf.strings.regex_replace(no_turkish_character, "ş", "s")
no_turkish_character = tf.strings.regex_replace(no_turkish_character, "ü", "u")
return no_turkish_character
loaded_end_to_end_model = tf.keras.models.load_model("end_to_end_model")
def gradio_comment(comment):
result = loaded_end_to_end_model.predict([comment])
result = np.round(result,1)
result = (result > 0.5).astype(int)
if result[0][0] == 1:
if result[0][1] == 1:
text = "OFFENSİVE/INSULT"
elif result[0][3] == 1:
text = 'OFFENSİVE/SEXIST'
elif result[0][4] == 1:
text = 'OFFENSİVE/RACIST'
elif result[0][5] == 1:
text = 'OFFENSİVE/PROFANITY'
else:
text = "NOT OFFENSİVE/OTHER"
return text
GradioGUI = gr.Interface(
fn=gradio_comment,
inputs='text',
outputs='text',
title='Aşağılayıcı Yorum Tespiti',
css='''span{text-transform: uppercase} p{text-align: center}''')
GradioGUI.launch() |