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| import streamlit as st | |
| import pickle | |
| import re | |
| import string | |
| import nltk | |
| from nltk.corpus import stopwords | |
| from nltk.tokenize import word_tokenize | |
| from nltk.stem.porter import PorterStemmer | |
| stemmer = PorterStemmer() | |
| st.set_page_config( | |
| page_title="NLP WEB APP" | |
| ) | |
| st.title("LANGUAGE DETECTOR MODEL") | |
| st.sidebar.success("Select a page above") | |
| nltk.download('stopwords') | |
| nltk.download('punkt') | |
| def preprocess(text): | |
| text = text.lower() | |
| text = re.sub(r'\d+', '', text) | |
| translator = str.maketrans('', '', string.punctuation) | |
| text = text.translate(translator) | |
| stop_words = set(stopwords.words("english")) | |
| word_tokens = word_tokenize(text) | |
| filtered_text = [word for word in word_tokens if word not in stop_words] | |
| stems = [stemmer.stem(word) for word in filtered_text] | |
| preprocessed_text = ' '.join(stems) | |
| return preprocessed_text | |
| cv = pickle.load(open('language-detector-models/vectorizer.pkl','rb')) | |
| model = pickle.load(open('language-detector-models/model.pkl','rb')) | |
| message= st.text_input("ENTER THE MESSAGE") | |
| if st.button("PREDICT"): | |
| # PREPROCESS | |
| transformed_text = preprocess(message) | |
| # VECTORIZE | |
| vector_input = cv.transform([message]) | |
| # PREDICTION | |
| result = model.predict(vector_input)[0] | |
| # DISPLAY | |
| if result==0: | |
| st.header("ARABIC") | |
| elif result==1: | |
| st.header("DANISH") | |
| elif result==2: | |
| st.header("DUTCH") | |
| elif result==3: | |
| st.header("ENGLISH") | |
| elif result==4: | |
| st.header("FRENCH") | |
| elif result==5: | |
| st.header("GERMAN") | |
| elif result==6: | |
| st.header("GREEK") | |
| elif result==7: | |
| st.header("HINDI") | |
| elif result==8: | |
| st.header("ITALIAN") | |
| elif result==9: | |
| st.header("KANNADA") | |
| elif result==10: | |
| st.header("MALYALAM") | |
| elif result==11: | |
| st.header("PORTUGESE") | |
| elif result==12: | |
| st.header("RUSSIAN") | |
| elif result==13: | |
| st.header("SPANISH") | |
| elif result==14: | |
| st.header("SWEDISH") | |
| elif result==15: | |
| st.header("TAMIL") | |
| else: | |
| st.header("TURKISH") |