Update app.py

app.py

@@ -25,6 +25,7 @@ import torch
 from ultralytics import YOLO
 from src.tiles import *
 from src.image_transform import *
+from time import sleep
 
 
 
@@ -243,17 +244,20 @@ if st.session_state.screen == 2:
         for idx, pred in enumerate(st.session_state.results):
             #extract detected character names and their confidence scores
             st.session_state.detected_characters = {}
-            for x, y, w, h, cls_id, conf in pred:
-                name = class_names[int(cls_id)]  # Convert class ID to character name
-                if name in st.session_state.detected_characters:
-                    if conf >= st.session_state.confidence:
-                        st.session_state.detected_characters[name].append(idx)
+            st.write(str(idx) + str(pred))
+            sleep(1)
+            # for cls_id in pred:
+            #     name = class_names[int(cls_id)]  # Convert class ID to character name
+                
+                # if name in st.session_state.detected_characters:
+                #     if conf >= st.session_state.confidence:
+                #         st.session_state.detected_characters[name].append(idx)
 
         # display locations
-        st.session_state.locations = ""
-        for name, idx in st.session_state.detected_characters.items():
-            st.session_state.locations += f" {name} tiles: {str(idx)}, )"
-        st.write(st.session_state.locations)
+        # st.session_state.locations = ""
+        # for name, idx in st.session_state.detected_characters.items():
+        #     st.session_state.locations += f" {name} tiles: {str(idx)}, )"
+        # st.write(st.session_state.locations)
             
         # plot predicted image
         st.markdown(f"<h4 style='text-align: center; color: black;'>Image Tile {str(st.session_state.image_counter + 1)}</h4>", unsafe_allow_html=True)