diff --git a/python/dllib/src/bigdl/dllib/feature/common.py b/python/dllib/src/bigdl/dllib/feature/common.py
index 068f29542ee..e25fce0b018 100644
--- a/python/dllib/src/bigdl/dllib/feature/common.py
+++ b/python/dllib/src/bigdl/dllib/feature/common.py
@@ -246,10 +246,14 @@ def image_frame(cls, image_frame, memory_type="DRAM", bigdl_type="float"):
     def image_set(cls, imageset, memory_type="DRAM", bigdl_type="float"):
         """
         Create FeatureSet from ImageFrame.
-        :param image_frame: ImageFrame
+        :param imageset: ImageSet
         :param memory_type: string, DRAM or PMEM
                             If it's DRAM, will cache dataset into dynamic random-access memory
                             If it's PMEM, will cache dataset into Intel Optane DC Persistent Memory
+                            If it's a Int number n, will cache dataset into disk, and only hold 1/n
+                              of the data into memory during the training. After going through the
+                              1/n, we will release the current cache, and load another 1/n into
+                              memory.
         :param bigdl_type: numeric type
         :return: A feature set
         """
@@ -257,6 +261,24 @@ def image_set(cls, imageset, memory_type="DRAM", bigdl_type="float"):
                                imageset.to_image_frame(), memory_type)
         return cls(jvalue=jvalue)
 
+    @classmethod
+    def sample_rdd(cls, rdd, memory_type="DRAM", bigdl_type="float"):
+        """
+        Create FeatureSet from RDD[Sample].
+        :param rdd: A RDD[Sample]
+        :param memory_type: string, DRAM or PMEM
+                            If it's DRAM, will cache dataset into dynamic random-access memory
+                            If it's PMEM, will cache dataset into Intel Optane DC Persistent Memory
+                            If it's a Int number n, will cache dataset into disk, and only hold 1/n
+                              of the data into memory during the training. After going through the
+                              1/n, we will release the current cache, and load another 1/n into
+                              memory.
+        :param bigdl_type:numeric type
+        :return: A feature set
+        """
+        jvalue = callBigDlFunc(bigdl_type, "createSampleFeatureSetFromRDD", rdd, memory_type)
+        return cls(jvalue=jvalue)
+
     @classmethod
     def rdd(cls, rdd, memory_type="DRAM", bigdl_type="float"):
         """
diff --git a/python/dllib/src/bigdl/dllib/feature/image/imagePreprocessing.py b/python/dllib/src/bigdl/dllib/feature/image/imagePreprocessing.py
index c0762546807..4dcf16c992c 100644
--- a/python/dllib/src/bigdl/dllib/feature/image/imagePreprocessing.py
+++ b/python/dllib/src/bigdl/dllib/feature/image/imagePreprocessing.py
@@ -41,6 +41,15 @@ def __init__(self, byte_key="bytes", image_codec=-1, bigdl_type="float"):
         super(ImageBytesToMat, self).__init__(bigdl_type, byte_key, image_codec)
 
 
+class ImagePixelBytesToMat(ImagePreprocessing):
+    """
+    Transform byte array(pixels in byte) to OpenCVMat
+    :param byte_key key that maps byte array
+    """
+    def __init__(self, byte_key="bytes", bigdl_type="float"):
+        super(ImagePixelBytesToMat, self).__init__(bigdl_type, byte_key)
+
+
 class ImageResize(ImagePreprocessing):
     """
     Resize image
@@ -331,6 +340,14 @@ def __init__(self, bigdl_type="float"):
         super(ImageHFlip, self).__init__(bigdl_type)
 
 
+class ImageMirror(ImagePreprocessing):
+    """
+    Flip the image horizontally and vertically
+    """
+    def __init__(self, bigdl_type="float"):
+        super(ImageMirror, self).__init__(bigdl_type)
+
+
 class ImageFeatureToTensor(Preprocessing):
     """
     a Transformer that convert ImageFeature to a Tensor.
@@ -339,6 +356,14 @@ def __init__(self, bigdl_type="float"):
         super(ImageFeatureToTensor, self).__init__(bigdl_type)
 
 
+class ImageFeatureToSample(Preprocessing):
+    """
+    A transformer that get Sample from ImageFeature.
+    """
+    def __init__(self, bigdl_type="float"):
+        super(ImageFeatureToSample, self).__init__(bigdl_type)
+
+
 class RowToImageFeature(Preprocessing):
     """
     a Transformer that converts a Spark Row to a BigDL ImageFeature.