Update app.py

app.py

@@ -232,7 +232,7 @@ def grad_cam(input_model, img_array, cls, layer_name):
 
 
 # Compute Grad-CAM
-def compute_gradcam(model, img_path, layer_name='bn'):
+def compute_gradcam(model_gradcam, img_path, layer_name='bn'):
     # base_model  = keras.applications.DenseNet121(weights = './densenet.hdf5', include_top = False)
     # x = base_model.output
     # x = keras.layers.GlobalAveragePooling2D()(x)
@@ -255,7 +255,7 @@ def compute_gradcam(model, img_path, layer_name='bn'):
     
     for i in range(len(labels)):
         st.write(f"Generating gradcam for class {labels[i]}")
-        gradcam = grad_cam(model, preprocessed_input, i, layer_name)
+        gradcam = grad_cam(model_gradcam, preprocessed_input, i, layer_name)
         gradcam = (gradcam * 255).astype(np.uint8)
         gradcam = cv2.applyColorMap(gradcam, cv2.COLORMAP_JET)
         gradcam = cv2.addWeighted(gradcam, 0.5, original_image.squeeze().astype(np.uint8), 0.5, 0)