diff --git a/hapi/datasets/flowers.py b/hapi/datasets/flowers.py
index 1f4f707888d460260d598826ba15ca3c69455f7b..aaae6107163d12b23a62366587f10c43d3579fab 100644
--- a/hapi/datasets/flowers.py
+++ b/hapi/datasets/flowers.py
@@ -121,7 +121,7 @@ class Flowers(Dataset):
         image = np.array(Image.open(io.BytesIO(image)))
 
         if self.transform is not None:
-            image, label = self.transform(image, label)
+            image = self.transform(image)
 
         return image, label
 
diff --git a/hapi/datasets/mnist.py b/hapi/datasets/mnist.py
index 18c62901edb95fd573334a4f3fe2201be7447711..e45aea711d8c4b8db2df5a558668939740bbc6bf 100644
--- a/hapi/datasets/mnist.py
+++ b/hapi/datasets/mnist.py
@@ -149,7 +149,7 @@ class MNIST(Dataset):
     def __getitem__(self, idx):
         image, label = self.images[idx], self.labels[idx]
         if self.transform is not None:
-            image, label = self.transform(image, label)
+            image = self.transform(image)
         return image, label
 
     def __len__(self):
diff --git a/hapi/vision/transforms/transforms.py b/hapi/vision/transforms/transforms.py
index 14bcd00221caf0f33d645d89478a9cf55d81c4ca..90b43b8d410aecd9fedbae3434c5d16c9351a411 100644
--- a/hapi/vision/transforms/transforms.py
+++ b/hapi/vision/transforms/transforms.py
@@ -61,6 +61,24 @@ class Compose(object):
     Args:
         transforms (list of ``Transform`` objects): list of transforms to compose.
 
+    Returns:
+        A compose object which is callable, __call__ for this Compose
+        object will call each given :attr:`transforms` sequencely.
+
+    Examples:
+    
+        .. code-block:: python
+
+            from hapi.datasets import Flowers
+            from hapi.vision.transforms import Compose, ColorJitter, Resize
+
+            transform = Compose([ColorJitter(), Resize(size=608)])
+            flowers = Flowers(mode='test', transform=transform)
+
+            for i in range(10):
+                sample = flowers[i]
+                print(sample[0].shape, sample[1])
+
     """
 
     def __init__(self, transforms):