Merge pull request #1894 from TaranSinghania/master

Added Data Augmentation Support

deepchem/trans/tests/test_transformers.py

@@ -587,6 +587,35 @@ def test_blurring(self):
     check_blur = scipy.ndimage.gaussian_filter(self.d, 1.5)
     assert np.allclose(check_blur, blurred)
 
+  def test_center_crop(self):
+    # Check center crop
+    dt = DataTransforms(self.d)
+    x_crop = 50
+    y_crop = 50
+    crop = dt.center_crop(x_crop, y_crop)
+    y = self.d.shape[0]
+    x = self.d.shape[1]
+    x_start = x // 2 - (x_crop // 2)
+    y_start = y // 2 - (y_crop // 2)
+    check_crop = self.d[y_start:y_start + y_crop, x_start:x_start + x_crop]
+    assert np.allclose(check_crop, crop)
+
+  def test_crop(self):
+    #Check crop
+    dt = DataTransforms(self.d)
+    crop = dt.crop(0, 10, 0, 10)
+    y = self.d.shape[0]
+    x = self.d.shape[1]
+    check_crop = self.d[10:y - 10, 0:x - 0]
+    assert np.allclose(crop, check_crop)
+
+  def test_convert2gray(self):
+    # Check convert2gray
+    dt = DataTransforms(self.d)
+    gray = dt.convert2gray()
+    check_gray = np.dot(self.d[..., :3], [0.2989, 0.5870, 0.1140])
+    assert np.allclose(check_gray, gray)
+
   def test_rotation(self):
     # Check rotation
     dt = DataTransforms(self.d)
@@ -677,3 +706,13 @@ def test_DAG_transformer(self):
     # atoms. These are denoted the "parents"
     for idm, mol in enumerate(dataset.X):
       assert dataset.X[idm].get_num_atoms() == len(dataset.X[idm].parents)
+
+  def test_median_filter(self):
+    #Check median filter
+    from PIL import Image, ImageFilter
+    dt = DataTransforms(self.d)
+    filtered = dt.median_filter(size=3)
+    image = Image.fromarray(self.d)
+    image = image.filter(ImageFilter.MedianFilter(size=3))
+    check_filtered = np.array(image)
+    assert np.allclose(check_filtered, filtered)

deepchem/trans/transformers.py

@@ -1306,8 +1306,15 @@ def flip(self, direction="lr"):
 
   def rotate(self, angle=0):
     """ Rotates the image
-          Parameters:
-              angle (default = 0 i.e no rotation) - Denotes angle by which the image should be rotated (in Degrees)
+
+    Parameters
+    ----------
+    angle: float (default = 0 i.e no rotation)
+	Denotes angle by which the image should be rotated (in Degrees)
+
+    Returns
+    ----------
+    The rotated imput array
     """
     return scipy.ndimage.rotate(self.Image, angle)
 
@@ -1318,6 +1325,59 @@ def gaussian_blur(self, sigma=0.2):
     """
     return scipy.ndimage.gaussian_filter(self.Image, sigma)
 
+  def center_crop(self, x_crop, y_crop):
+    """ Crops the image from the center
+
+    Parameters
+    ----------
+    x_crop: int
+	the total number of pixels to remove in the horizontal direction, evenly split between the left and right sides
+    y_crop: int
+        the total number of pixels to remove in the vertical direction, evenly split between the top and bottom sides
+
+    Returns
+    ----------
+    The center cropped input array
+
+    """
+    y = self.Image.shape[0]
+    x = self.Image.shape[1]
+    x_start = x // 2 - (x_crop // 2)
+    y_start = y // 2 - (y_crop // 2)
+    return self.Image[y_start:y_start + y_crop, x_start:x_start + x_crop]
+
+  def crop(self, left, top, right, bottom):
+    """ Crops the image and returns the specified rectangular region from an image
+
+    Parameters
+    ----------
+    left: int
+	the number of pixels to exclude from the left of the image
+    top: int
+	the number of pixels to exclude from the top of the image
+    right: int
+	the number of pixels to exclude from the right of the image    
+    bottom: int
+	the number of pixels to exclude from the bottom of the image
+
+    Returns
+    ----------
+    The cropped input array
+    """
+    y = self.Image.shape[0]
+    x = self.Image.shape[1]
+    return self.Image[top:y - bottom, left:x - right]
+
+  def convert2gray(self):
+    """ Converts the image to grayscale. The coefficients correspond to the Y' component of the Y'UV color system.
+    
+    Returns
+    ----------
+    The grayscale image.
+
+    """
+    return np.dot(self.Image[..., :3], [0.2989, 0.5870, 0.1140])
+
   def shift(self, width, height, mode='constant', order=3):
     """Shifts the image
         Parameters:
@@ -1358,3 +1418,20 @@ def salt_pepper_noise(self, prob=0.05, salt=255, pepper=0):
     x[noise < (prob / 2)] = pepper
     x[noise > (1 - prob / 2)] = salt
     return x
+
+  def median_filter(self, size):
+    """ Calculates a multidimensional median filter
+
+    Parameters
+    ----------
+    size: int
+	The kernel size in pixels.
+
+    Returns
+    ----------
+    The median filtered image.
+    """
+    from PIL import Image, ImageFilter
+    image = Image.fromarray(self.Image)
+    image = image.filter(ImageFilter.MedianFilter(size=size))
+    return np.array(image)