fix requirements

app.py

@@ -19,7 +19,7 @@ from torchvision.transforms.functional import to_pil_image
 from tqdm import tqdm
 from util import transform
 
-IMAGE_PATH = 'src/examples'
+IMAGE_PATH = 'src\\examples'
 RANDOM_IMAGES_TO_SHOW = 20
 IMAGES_PER_ROW = 5
 
@@ -41,7 +41,8 @@ def load_random_images():
         idx = np.random.randint(0, len(data_df))
         p = os.path.join(IMAGE_PATH, data_df.iloc[idx]['path'])
         animal = data_df.iloc[idx]['target']
-        random_images.append((animal, Image.open(p)))
+        if os.path.exists(p):
+            random_images.append((animal, Image.open(p)))
     return random_images
 
 def get_class_name(idx):