Update app.py

app.py

@@ -61,21 +61,21 @@ def upload_image_inference(input_img, n_top_classes, transparency):
   return([confidences, [org_img, grayscale_cam, visualization]])
 
 
-def misclass_gr(num_images, layer_val, transparency):
+def misclass_gr(num_images, layer_val, transparency, isview):
   images_list = misclassified_data[:num_images]
 
-  images_list = [image_to_array(img, layer_val, transparency) for img in images_list]
+  images_list = [image_to_array(img, layer_val, isview, transparency) for img in images_list]
   return(images_list)
 
 
-def class_gr(num_images, layer_val, transparency):
+def class_gr(num_images, layer_val, transparency, isview):
   images_list = classified_data[:num_images]
 
-  images_list = [image_to_array(img, layer_val, transparency) for img in images_list]
+  images_list = [image_to_array(img, layer_val, isview, transparency) for img in images_list]
   return(images_list)
 
 
-def image_to_array(input_img, layer_val, transparency=0.6):
+def image_to_array(input_img, layer_val, isview, transparency=0.6):
   input_tensor = input_img[0]
 
   cam = GradCAM(model=model, target_layers=[model.res_block2.conv[-layer_val]])
@@ -90,7 +90,11 @@ def image_to_array(input_img, layer_val, transparency=0.6):
   visualization = show_cam_on_image(rgb_img, grayscale_cam, use_rgb=True,
                                     image_weight=transparency)
 
-  plt.imshow(visualization)
+  if isview:
+      plt.imshow(visualization)
+  else:
+      plt.imshow(rgb_img)
+
   plt.title(r"Correct: " + classes[input_img[1].item()] + '\n' + 'Output: ' + classes[input_img[2].item()])
 
   with io.BytesIO() as buffer:
@@ -174,8 +178,9 @@ with gr.Blocks() as gradcam:
       with gr.Row():
           with gr.Column():
             cam_input21 = [gr.Number(minimum=1, maximum=20, precision=0, value=3, label='View Correctly Classified CAM | Num Images'),
-                          gr.Number(minimum=1, maximum=3, precision=0, value=1, label='(-) Target Layer'),
-                          gr.Slider(0, 1, value=0.6, label='Transparency')]
+                           gr.Number(minimum=1, maximum=3, precision=0, value=1, label='(-) Target Layer'),
+                           gr.Slider(0, 1, value=0.6, label='Transparency'), 
+                           gr.Checkbox(label="GradCAM", value=True, info="View GradCAM ?")]
 
             image_output21 = gr.Gallery(label="Images - Grad-CAM (correct)",
                                       show_label=True, min_width=80)
@@ -183,8 +188,9 @@ with gr.Blocks() as gradcam:
 
           with gr.Column():
             cam_input22 = [gr.Number(minimum=1, maximum=20, precision=0, value=3, label='View Misclassified CAM | Num Images'),
-                          gr.Number(minimum=1, maximum=3,  precision=0, value=1, label='(-) Target Layer'),
-                          gr.Slider(0, 1, value=0.6, label='Transparency')]
+                           gr.Number(minimum=1, maximum=3,  precision=0, value=1, label='(-) Target Layer'),
+                           gr.Slider(0, 1, value=0.6, label='Transparency'), 
+                           gr.Checkbox(label="GradCAM", value=True, info="View GradCAM ?")]
 
             image_output22 = gr.Gallery(label="Images - Grad-CAM (Misclassified)",
                                         show_label=True, min_width=80)