Update Experiments/Resnet50_classification.py

Experiments/Resnet50_classification.py

@@ -51,11 +51,11 @@ class HiddenLayer(nn.Module):
 
 def predict(features_path,image):
     batch1 = unpickle(r"Model/data/data_batch_1")
-    batch2 = unpickle(r"Model\data\data_batch_2")
-    batch3 = unpickle(r"Model\data\data_batch_3")
-    batch4 = unpickle(r"Model\data\data_batch_4")
-    batch5 = unpickle(r"Model\data\data_batch_5")
-    test_batch = unpickle(r"Model\data\test_batch")
+    batch2 = unpickle(r"Model/data/data_batch_2")
+    batch3 = unpickle(r"Model/data/data_batch_3")
+    batch4 = unpickle(r"Model/data/data_batch_4")
+    batch5 = unpickle(r"Model/data/data_batch_5")
+    test_batch = unpickle(r"Model/data/test_batch")
     train_batch = [batch1,batch2,batch3,batch4,batch5]
     train_y = []
     train_x = []
@@ -102,7 +102,7 @@ def predict(features_path,image):
     
     
 
-def retrieve(image,k,feature_path=r"Model\Resnet50_train_features.pt"):
+def retrieve(image,k,feature_path=r"Model/Resnet50_train_features.pt"):
     print(image.shape)
     test_label,z,features,class_images_dict,train_x = predict(feature_path,image)
     class_indices = class_images_dict[test_label.item()]