Update app.py

app.py

@@ -133,11 +133,11 @@ def load_gradcam_model():
     # and a logistic layer
     predictions = Dense(14, activation="sigmoid")(x)
 
-    model = Model(inputs=base_model.input, outputs=predictions)
-    model.compile(optimizer='adam', loss="categorical_crossentropy")
-    model.load_weights("./model_renamed.h5")
+    model_gradcam = Model(inputs=base_model.input, outputs=predictions)
+    model_gradcam.compile(optimizer='adam', loss="categorical_crossentropy")
+    model_gradcam.load_weights("./model_renamed.h5")
     
-    return model
+    return model_gradcam
 
 
 # Utility Functions
@@ -524,7 +524,7 @@ if uploaded_file is not None:
     with col2:
         # file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
         # image = cv2.imdecode(file_bytes, 1)
-        if st.button('Auto Detect'):
+        # if st.button('Auto Detect'):
             # st.write("Processing...")
             # input_image = preprocess_image(image)
             # pred_bbox, pred_label, pred_label_confidence = predict(model_detection, input_image)