Loading deepchem/trans/tests/test_transformers.py +12 −3 Original line number Diff line number Diff line Loading @@ -587,12 +587,12 @@ class TestTransformers(unittest.TestCase): check_blur = scipy.ndimage.gaussian_filter(self.d, 1.5) assert np.allclose(check_blur, blurred) def check_crop(self): # Check crop def check_center_crop(self): # Check center crop dt = DataTransforms(self.d) x_crop = 50 y_crop = 50 crop = dt.crop(x_crop, y_crop) 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) Loading @@ -600,6 +600,15 @@ class TestTransformers(unittest.TestCase): check_crop = self.d[y_start:y_start + y_crop, x_start:x_start + x_crop] assert np.allclose(check_crop, crop) def check_crop(self): #Check crop from PIL import Image dt = DataTransforms(self.d) crop = dt.crop(0, 10, 0, 10) image = Image.fromarray(self.d) check_crop = np.array(image.crop((0, 10, 0, 10))) assert np.allclose(crop, check_crop) def chef_convert2gray(self): # Check convert2gray dt = DataTransforms(self.d) Loading deepchem/trans/transformers.py +37 −16 Original line number Diff line number Diff line Loading @@ -1304,23 +1304,19 @@ class DataTransforms(Transformer): "Invalid flip command : Enter either lr (for left to right flip) or ud (for up to down flip)" ) def rotate(self, angle=0, reshape=True, mode='constant', order=3): 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). reshape (default = True i.e will get reshape) mode - Points outside the boundaries of the input are filled according to the given mode (‘constant’, ‘nearest’, ‘reflect’ or ‘wrap’). Default is ‘constant’. order - The order of the spline interpolation, default is 3. The order has to be in the range 0-5. angle: float (default = 0 i.e no rotation) Denotes angle by which the image should be rotated (in Degrees) Returns ---------- The rotated imput array. The rotated imput array """ return scipy.ndimage.rotate( self.Image, angle, reshape=reshape, mode=mode, order=order) return scipy.ndimage.rotate(self.Image, angle) def gaussian_blur(self, sigma=0.2): """ Adds gaussian noise to the image Loading @@ -1329,17 +1325,19 @@ class DataTransforms(Transformer): """ return scipy.ndimage.gaussian_filter(self.Image, sigma) def crop(self, x_crop, y_crop): def center_crop(self, x_crop, y_crop): """ Crops the image from the center Parameters ---------- x_crop - bound for x. y_crop - bound for y. 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 cropped input array. The center cropped input array """ y = self.Image.shape[0] Loading @@ -1348,9 +1346,31 @@ class DataTransforms(Transformer): 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 """ from PIL import Image image = Image.fromarray(self.Imaage) image = image.crop((left, top, right, bottom)) return np.array(image) def convert2gray(self): """ Converts the image to grayscale. Borrowd from the MATLAB implementation of the "rgb2gray" function. Link to reference: https://in.mathworks.com/help/matlab/ref/rgb2gray.html """ Converts the image to grayscale. The coefficients correspond to the Y' component of the Y'UV color system. Returns ---------- Loading Loading @@ -1405,7 +1425,8 @@ class DataTransforms(Transformer): Parameters ---------- size - The kernel size in pixels. size: int The kernel size in pixels. Returns ---------- Loading Loading
deepchem/trans/tests/test_transformers.py +12 −3 Original line number Diff line number Diff line Loading @@ -587,12 +587,12 @@ class TestTransformers(unittest.TestCase): check_blur = scipy.ndimage.gaussian_filter(self.d, 1.5) assert np.allclose(check_blur, blurred) def check_crop(self): # Check crop def check_center_crop(self): # Check center crop dt = DataTransforms(self.d) x_crop = 50 y_crop = 50 crop = dt.crop(x_crop, y_crop) 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) Loading @@ -600,6 +600,15 @@ class TestTransformers(unittest.TestCase): check_crop = self.d[y_start:y_start + y_crop, x_start:x_start + x_crop] assert np.allclose(check_crop, crop) def check_crop(self): #Check crop from PIL import Image dt = DataTransforms(self.d) crop = dt.crop(0, 10, 0, 10) image = Image.fromarray(self.d) check_crop = np.array(image.crop((0, 10, 0, 10))) assert np.allclose(crop, check_crop) def chef_convert2gray(self): # Check convert2gray dt = DataTransforms(self.d) Loading
deepchem/trans/transformers.py +37 −16 Original line number Diff line number Diff line Loading @@ -1304,23 +1304,19 @@ class DataTransforms(Transformer): "Invalid flip command : Enter either lr (for left to right flip) or ud (for up to down flip)" ) def rotate(self, angle=0, reshape=True, mode='constant', order=3): 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). reshape (default = True i.e will get reshape) mode - Points outside the boundaries of the input are filled according to the given mode (‘constant’, ‘nearest’, ‘reflect’ or ‘wrap’). Default is ‘constant’. order - The order of the spline interpolation, default is 3. The order has to be in the range 0-5. angle: float (default = 0 i.e no rotation) Denotes angle by which the image should be rotated (in Degrees) Returns ---------- The rotated imput array. The rotated imput array """ return scipy.ndimage.rotate( self.Image, angle, reshape=reshape, mode=mode, order=order) return scipy.ndimage.rotate(self.Image, angle) def gaussian_blur(self, sigma=0.2): """ Adds gaussian noise to the image Loading @@ -1329,17 +1325,19 @@ class DataTransforms(Transformer): """ return scipy.ndimage.gaussian_filter(self.Image, sigma) def crop(self, x_crop, y_crop): def center_crop(self, x_crop, y_crop): """ Crops the image from the center Parameters ---------- x_crop - bound for x. y_crop - bound for y. 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 cropped input array. The center cropped input array """ y = self.Image.shape[0] Loading @@ -1348,9 +1346,31 @@ class DataTransforms(Transformer): 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 """ from PIL import Image image = Image.fromarray(self.Imaage) image = image.crop((left, top, right, bottom)) return np.array(image) def convert2gray(self): """ Converts the image to grayscale. Borrowd from the MATLAB implementation of the "rgb2gray" function. Link to reference: https://in.mathworks.com/help/matlab/ref/rgb2gray.html """ Converts the image to grayscale. The coefficients correspond to the Y' component of the Y'UV color system. Returns ---------- Loading Loading @@ -1405,7 +1425,8 @@ class DataTransforms(Transformer): Parameters ---------- size - The kernel size in pixels. size: int The kernel size in pixels. Returns ---------- Loading
