Merge branch 'main' of hf.co:spaces/Shchushch/CV

assets/skin.py

@@ -2,14 +2,8 @@
 import torch
 from torchvision import transforms
 from torchvision.models import VGG19_BN_Weights, vgg19_bn
-
-model =torch.load('assets/skin.pth')
-#print(torch.load('assets/weights.pth'))
-# model=vgg19_bn()
-# print(torch.load('assets/model.pth'))
-# model.load_state_dict(torch.load('assets/skin_cancer.pth'))
-# print(model)
-# torch.save(model.state_dict(), 'assets/skin_cancer.pth')
+DEVICE = 'cpu'
+model =torch.load('assets/skin.pth', map_location=DEVICE)
 skin_map={0:'Добро',1:'Зло'}
 def get_evil(img):
     
@@ -20,12 +14,11 @@ def get_evil(img):
     
     input_image = transform(img).unsqueeze(0) # Добавьте размерность пакета (batch dimension)
     
-    device = 'cpu'
+    
     #torch.device("cuda" if torch.cuda.is_available() else 'cpu')
-    model.to(device)
+    model.to(DEVICE)
     model.eval()
-    input_image = input_image.to(device)
-    #model.to(device)
+    input_image = input_image.to(DEVICE)
     with torch.no_grad():
         res=model(input_image).item()
     return f'Степень злобы: {res}\n\n Т.е. опухоль: {skin_map[round(res)]}'

pages/1 📖_Умный_поиск_книг.py

@@ -32,7 +32,7 @@ items_per_page=st.number_input('Количество книг на страни
 # if search_but:
 #     st.session_state.clicked = True
 #st.toast('Уфф')
-#@st.cache_data(experimental_allow_widgets=True)
+@st.cache_data(experimental_allow_widgets=True)
 def books_show(books_idx,sim,n=items_per_page):
     col=[]
     books=df.copy().iloc[books_idx][:n]