modifying image_posterior

app.py

@@ -38,9 +38,9 @@ def get_image_data(image_name):
 def segmentation_generation(image_name, c_width, n_top, n_gif_imgs):
     print("Inputs Received:", image_name, c_width, n_top, n_gif_imgs)
 
-    cred_width = c_width
-    n_top_segs = n_top
-    n_gif_images = n_gif_imgs
+    # cred_width = c_width
+    # n_top_segs = n_top
+    # n_gif_images = n_gif_imgs
     image, model_and_data = get_image_data(image_name)
     print("model_and_data", model_and_data)
     # Unpack datax
@@ -78,12 +78,12 @@ def segmentation_generation(image_name, c_width, n_top, n_gif_imgs):
     rout = exp_init.explain(classifier_f=cur_model,
                             data=np.ones_like(xtrain[0]),
                             label=label,
-                            cred_width=cred_width,
+                            cred_width=c_width,
                             focus_sample=False,
                             l2=False)
 
     # Create the gif of the explanation
-    return create_gif(rout['blr'], image_name, segments, instance, n_gif_images, n_top_segs)
+    return create_gif(rout['blr'], image_name, segments, instance, n_gif_imgs, n_top)
 
 def image_mod(image):
     return image.rotate(45)

image_posterior.py

@@ -69,6 +69,9 @@ def create_gif(explanation_blr, img_name, segments, image, n_images=20, n_max=5)
         # https://stackoverflow.com/questions/61716066/creating-an-animation-out-of-matplotlib-pngs
         print(f"Saving gif to {img_name}_explanation.gif")
 
+        if(os.path.exists(f'file/{img_name}_explanation.gif')):
+            os.remove(f'file/{img_name}_explanation.gif')
+
         ims = [imageio.imread(f) for f in paths]
         imageio.mimwrite(f'{img_name}_explanation.gif', ims)