Update app.py

app.py

@@ -74,7 +74,6 @@ def bansum(text):
 st.title("NLP APPLICATION")
 #@st.cache_resource(experimental_allow_widgets=True)
 def main():
-    s=0
     #global tokenizer, model
     #tokenizer = AutoTokenizer.from_pretrained('t5-base')
     #model = AutoModelWithLMHead.from_pretrained('t5-base', return_dict=True)
@@ -89,7 +88,7 @@ def main():
     st.subheader("Please, feed your pdf/images/text, features/services will appear automatically!")
     message = st.text_input("Type your text here!")
     uploaded_photo = st.sidebar.file_uploader("Upload your Images/PDF",type=['jpg','png','jpeg','pdf'], on_change=change_photo_state)
-    camera_photo = st.camera_input("Take a photo, Containing English texts", on_change=change_photo_state)
+    camera_photo = st.sidebar.camera_input("Take a photo, Containing English texts", on_change=change_photo_state)
     if "photo" not in st.session_state:
         st.session_state["photo"]="not done"
     if st.session_state["photo"]=="done" or message:
@@ -102,7 +101,7 @@ def main():
             #tet = pytesseract.image_to_string(img, lang="ben") if st.checkbox("Mark to see Bangla Image's Text") else pytesseract.image_to_string(img)
             values = st.slider('Select a approximate number of lines to see and summarize',value=[0, len(tet)//(7*100)])
             text = tet[values[0]*7*10:values[1]*7*10] if values[0]!=len(tet)//(7*10) else tet[len(tet)//(7*100):]
-            st.success(text)
+            engsum(text)
         elif uploaded_photo:
             img = Image.open(uploaded_photo)
             img = img.save("img.png")
@@ -110,33 +109,29 @@ def main():
             st.text("Press the content type:")
             if st.button("Content Type: Bangla"):
                 text =  pytesseract.image_to_string(img, lang="ben")
-                s=1
+                bansum(text)
             if st.button("Content Type: English"): 
                 text=pytesseract.image_to_string(img)
-                s=0
+                engsum(text)
             #st.success(text)
         elif camera_photo:
             img = Image.open(camera_photo)
             img = img.save("img.png")
             img = cv2.imread("img.png")
             #text = pytesseract.image_to_string(img) if st.checkbox("Bangla") else pytesseract.image_to_string(img, lang="ben")
-            st.text("Please select the content type:")
+            st.text("Please select the content type for summarization:")
             if st.button("Content Type: Bangla"):
                 text =  pytesseract.image_to_string(img, lang="ben")
-                s=1
+                bansum(text)
             if st.button("Content Type: English"): 
                 text=pytesseract.image_to_string(img)
-                s=0
-            st.success(text)
+                engsum(text)
         elif uploaded_photo==None and camera_photo==None:
             text = message
-                
-        if st.checkbox("Mark for Text Summarization"):
-            if s==1:
+            if st.button("Content Type: Bangla"):
                 bansum(text)
-            else:
-                engsum(text)
-                
+            if st.button("Content Type: English"): 
+                engsum(text)  
         if st.checkbox("English Text Generation"): 
             def query(payload):
             	response = requests.post(API_URL2, headers=headers2, json=payload)
@@ -148,8 +143,7 @@ def main():
             if isinstance(out, list) and out[0].get("generated_text"):
                 text_output = out[0]["generated_text"]
                 st.success(text_output)
-        if st.button("Refresh"):
-            text=None
-            s=0
+                #text=text_output
+
 if __name__ == '__main__':
     main()