Update app.py

app.py

@@ -11,20 +11,20 @@ import torch.nn as nn
 #model = torch.hub.load('pytorch/vision:v0.9.0', 'mobilenet_v2', pretrained=False)
 #checkpoint = 'https://github.com/liuxiaoyuyuyu/vanGogh-and-Other-Artist/blob/main/model_weights_mobilenet_v2_valp1trainp2.pth'
 #model.load_state_dict(torch.hub.load_state_dict_from_url(checkpoint, progress=False))
-model = models.efficientnet_b0()
-num_ftrs = model.classifier[1].in_features
-model.classifier[1] = nn.Linear(num_ftrs, 6)
-device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
+#model = models.efficientnet_b0()
+#num_ftrs = model.classifier[1].in_features
+#model.classifier[1] = nn.Linear(num_ftrs, 6)
+#device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
 #model = model.to(device)
-model.load_state_dict(torch.load('model_weights_EfficientNetB0_final.pth',map_location=device))
+#model.load_state_dict(torch.load('model_weights_EfficientNetB0_final.pth',map_location=device))
 
 
-#model = models.vgg16()
-#num_ftrs = model.classifier[6].in_features
-#model.classifier[6] = nn.Linear(num_ftrs, 6)
-#device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
-#model = model.to(device)
-#model.load_state_dict(torch.load('VGG16_weights_May28.pth',map_location=device))
+model = models.vgg16()
+num_ftrs = model.classifier[6].in_features
+model.classifier[6] = nn.Linear(num_ftrs, 6)
+device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
+model = model.to(device)
+model.load_state_dict(torch.load('VGG16_weights_May28.pth',map_location=device))
 #torch.hub.download_url_to_file("https://github.com/pytorch/hub/raw/master/images/dog.jpg", "dog.jpg")