Update main.py

main.py

@@ -1,24 +1,29 @@
-import streamlit as st
+import zipfile
+import random
 
 import pandas as pd
+import numpy as np
+import streamlit as st
 
 import clip
-import torchvision.transforms as transforms
-import torchvision.datasets as datasets
 import torch
-import numpy as np
-import random
-from get_similiarty import get_similiarity
+import torchvision.transforms as transforms
 
-device = "cuda" if torch.cuda.is_available() else "cpu"
-#load model -resnet50
+from get_similiarty import get_similiarity
 
 
-model_resnet = torch.load("model.pt", device )
+device = "cuda" if torch.cuda.is_available() else "cpu"
 
+#load model -resnet50
+model_resnet = torch.load("model.pt", device)
 #load model - ViT-B/32
-model_vit = torch.load("model_vit.pt", device )
+model_vit = torch.load("model_vit.pt", device)
 
+#Распаковка ZIP-файла с фотографиями
+zip_file_path = "sample.zip"
+target_folder = "sample/"
+with zipfile.ZipFile(zip_file_path, 'r') as zip_ref:
+    zip_ref.extractall(target_folder)
 
 st.title('Find my pic!')
 
@@ -53,4 +58,4 @@ if txt is not None:
                 st.write(img_desc[ind])
             with col2:
                 st.image(pic[1])
-                st.write(img_desc[ind])
+                st.write(img_desc[ind])