fix requirements

app.py

@@ -1,28 +1,23 @@
-import gradio as gr
-from datetime import datetime
-import pytz
-import torch
-import torch.nn as nn
-import torch.optim as optim
-from torch.utils.data import DataLoader
-import pandas as pd
-from tqdm import tqdm
-from collections import defaultdict
-import os
-from PIL import Image
-import shutil
 import copy
-import numpy as np
+import os
+import sys
+sys.path.append('src')
+from collections import defaultdict
+from functools import lru_cache
+
+import gradio as gr
 import matplotlib.pyplot as plt
-from util import transform, train_transform, AnimalDataset
-from Nets import CustomResNet18
+import numpy as np
+import pandas as pd
+import torch
 from deep_translator import GoogleTranslator
-from torchcam.methods import SmoothGradCAMpp, XGradCAM, ScoreCAM, GradCAM, GradCAMpp, CAM
-import matplotlib.pyplot as plt
+from Nets import CustomResNet18
+from PIL import Image
+from torchcam.methods import GradCAM, GradCAMpp, SmoothGradCAMpp, XGradCAM
 from torchcam.utils import overlay_mask
 from torchvision.transforms.functional import to_pil_image
-from sklearn.preprocessing import LabelEncoder
-from functools import lru_cache
+from tqdm import tqdm
+from util import transform
 
 IMAGE_PATH = 'src/examples'
 RANDOM_IMAGES_TO_SHOW = 20