Update app.py

app.py

@@ -35,14 +35,15 @@ from PIL import Image
 from PyPDF2 import PdfFileReader
 from pdf2image import convert_from_bytes
 import pdfplumber
-#from line_cor import mark_region
+from line_cor import mark_region
 import pdf2image
 
 
 # NLP Pkgs
 from textblob import TextBlob 
 import spacy
-#from gensim.summarization import summarize
+import gensim
+from gensim.summarization import summarize
 import requests
 import cv2
 import numpy as np
@@ -180,13 +181,13 @@ def main():
             st.text("Using Hugging Face Transformer, Contrastive Search ..")
             output = model.generate(input_ids, max_length=128)
             st.success(tokenizer.decode(output[0], skip_special_tokens=True))
-        #if st.checkbox("Mark here, Text Summarization for English or Bangla!"):
-			#st.subheader("Summarize Your Text for English and Bangla Texts!")
-			#message = st.text_area("Enter the Text","Type please ..")
-			#st.text("Using Gensim Summarizer ..")
-			#st.success(mess)
-            #summary_result = summarize(text)
-            #st.success(summary_result)
+        if st.checkbox("Mark here, Text Summarization for English or Bangla!"):
+			st.subheader("Summarize Your Text for English and Bangla Texts!")
+			message = st.text_area("Enter the Text","Type please ..")
+			st.text("Using Gensim Summarizer ..")
+			st.success(mess)
+            summary_result = summarize(text)
+            st.success(summary_result)
         if st.checkbox("Mark to better English Text Summarization!"):
 			#st.title("Summarize Your Text for English only!")
             tokenizer = AutoTokenizer.from_pretrained('t5-base')