Update app.py

app.py

@@ -11,10 +11,10 @@ import sys
 import os
 
 sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
-from segmentation_model import load_model,transform_image, run_inference, save_input_image, save_objects_and_metadata, extract_object
-from identification_model import load_yolov8_model, run_object_detection
-from text_extraction_model import extract_text
-from summarization_model import generate_summary
+from models.segmentation_model import load_model,transform_image, run_inference, save_input_image, save_objects_and_metadata, extract_object
+from models.identification_model import load_yolov8_model, run_object_detection
+from models.text_extraction_model import extract_text
+# from models.summarization_model import generate_summary
 # from utils.data_mapping import create_summary_table
 
 
@@ -61,6 +61,11 @@ if uploaded_file is not None:
     image = Image.open(uploaded_file).convert('RGB')
     # Generate a unique master ID for the image
     master_id = str(uuid.uuid4())
+    extracted_text = extract_text(image)
+    if extracted_text:
+        st.write(extracted_text)
+    else:
+        st.write("No text was detected")
     
     # Save the input image
     save_input_image(image, master_id)
@@ -89,16 +94,16 @@ if uploaded_file is not None:
          st.write(f"Detection results for Object {i+1}:")
          st.json(detection_results)
 
-         text_data = extract_text(obj_img)
+         extracted_text = extract_text(obj_img)
          
-         if text_data:
+         if extracted_text:
             st.write(f"Extracted Text for Object {i+1}:")
-            st.json(text_data)
-        else:
+            st.json(extracted_text)
+         else:
             st.write("No text was detected")
 
-        summary = generate_summary(obj_img,text_data)
-        st.write(f"Object Summary:\n{summary}")
+        # summary = generate_summary(obj_img,text_data)
+        # st.write(f"Object Summary:\n{summary}")
 
     else:
         st.write("No objects were detected")