Update app.py

app.py

@@ -61,7 +61,7 @@ _, row1_col1, _ = st.columns([2,3,2])
 _, row2_col1, _ = st.columns([2,3,2])
 _, row3_col1, row3_col2, row3_col3, row3_col4, _ = st.columns([8,3,3,3,3,8])
 _, row4_col1, row4_col2, row4_col3, row4_col4, _ = st.columns([8,3,3,3,3,8])
-_, row5_col2, row5_col3, _ = st.columns([1,4,4,1], gap="medium")
+_, row5_col2, row5_col3, row5_col4, _ = st.columns([1,4,4,2,1], gap="medium")
 
 # heading
 with row0_col1:
@@ -239,49 +239,30 @@ if st.session_state.screen == 2:
             st.session_state.results = st.session_state.model.predict(st.session_state.tiles, conf=st.session_state.confidence) # predict     
             st.rerun()
 
-        # show character locations
-        class_names = {0: "Waldo", 1: "Wenda", 2: "Odlaw", 3: "Wizard", 4: "Woof"}
-        character_dict = {
-            "Waldo": [],
-            "Wenda": [],
-            "Odlaw": [],
-            "Wizard": [],
-            "Woof": [],
-        }
-        for idx, pred in enumerate(st.session_state.results):
-            try:
-                for boxes in pred.boxes:
-                    if boxes.conf >= 0.5:
-                        character_dict[class_names[int(boxes.cls.item())]].append(idx + 1)
-            except:
-                pass
-                
-        st.session_state.output = ""
-        for key, value in character_dict.items():
-            if value != []:
-                st.session_state.output += str(key) + " tiles: "+ str(value) + "\n"
-
-        st.write(st.session_state.output)
-            #extract detected character names and their confidence scores
-            # st.session_state.detected_characters = {}
-            # st.write(str(idx) + str(pred.cls) + str(pred.conf))
-
-            # if pred.conf >= 0.5:
-            #     st.write(str(int(pred.cls.item())))
-                
-
-            # 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)
+        with row5_col4:
+            # show character locations
+            class_names = {0: "Waldo", 1: "Wenda", 2: "Odlaw", 3: "Wizard", 4: "Woof"}
+            character_dict = {
+                "Waldo": [],
+                "Wenda": [],
+                "Odlaw": [],
+                "Wizard": [],
+                "Woof": [],
+            }
+            for idx, pred in enumerate(st.session_state.results):
+                try:
+                    for boxes in pred.boxes:
+                        if boxes.conf >= 0.5:
+                            character_dict[class_names[int(boxes.cls.item())]].append(idx + 1)
+                except:
+                    pass
+                    
+            st.session_state.output = ""
+            for key, value in character_dict.items():
+                if value != []:
+                    st.session_state.output += str(key) + " tiles: "+ str(value) + "  \n"
+    
+            st.write(st.session_state.output)
             
         # 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)