Move transformations to the their own module.

Signed-off-by: Michael Price <loneviking72@gmail.com>

HISTORY.rst

@@ -40,7 +40,8 @@ Next (2018-XX-XX)
 - Move the invalid document markup to a separate HTML template.
 - Update to Fancybox 3.
 - Update to jQuery 3.3.1
-                                
+- Move transfomations to their own module.
+                               
 2.8 (2018-02-27)
 ================
 - Rename the role groups link label from "Members" to "Groups".

mayan/apps/converter/__init__.py

@@ -1,9 +1,9 @@
 from __future__ import unicode_literals
 
-from .classes import (  # NOQA
+from .runtime import converter_class  # NOQA
+from .transformations import (  # NOQA
     BaseTransformation, TransformationResize, TransformationRotate,
     TransformationZoom
 )
-from .runtime import converter_class  # NOQA
 
 default_app_config = 'converter.apps.ConverterApp'

mayan/apps/converter/classes.py

@@ -5,12 +5,11 @@ from io import BytesIO
 import logging
 import os
 
-from PIL import Image, ImageFilter
+from PIL import Image
 import sh
 import yaml
 
-from django.utils.six import text_type
+from django.utils.translation import ugettext_lazy as _
-from django.utils.translation import string_concat, ugettext_lazy as _
 
 from common.settings import setting_temporary_directory
 from common.utils import fs_cleanup, mkdtemp, mkstemp
@@ -232,257 +231,3 @@ class ConverterBase(object):
     def detect_orientation(self, page_number):
         # Must be overrided by subclass
         pass
-
-
-class BaseTransformation(object):
-    """
-    Transformation can modify the appearance of the document's page preview.
-    Some transformation available are: Rotate, zoom, resize and crop.
-    """
-    arguments = ()
-    name = 'base_transformation'
-    _registry = {}
-
-    @staticmethod
-    def encode_hash(decoded_value):
-        return hex(abs(decoded_value))[2:]
-
-    @staticmethod
-    def decode_hash(encoded_value):
-        return int(encoded_value, 16)
-
-    @staticmethod
-    def combine(transformations):
-        result = None
-
-        for index, transformation in enumerate(transformations):
-            if not result:
-                result = hash((BaseTransformation.decode_hash(transformation.cache_hash()), index))
-            else:
-                result ^= hash((BaseTransformation.decode_hash(transformation.cache_hash()), index))
-
-        return BaseTransformation.encode_hash(result)
-
-    @classmethod
-    def register(cls, transformation):
-        cls._registry[transformation.name] = transformation
-
-    @classmethod
-    def get_transformation_choices(cls):
-        return sorted(
-            [
-                (name, klass.get_label()) for name, klass in cls._registry.items()
-            ]
-        )
-
-    @classmethod
-    def get(cls, name):
-        return cls._registry[name]
-
-    @classmethod
-    def get_label(cls):
-        if cls.arguments:
-            return string_concat(cls.label, ': ', ', '.join(cls.arguments))
-        else:
-            return cls.label
-
-    def __init__(self, **kwargs):
-        self.kwargs = {}
-        for argument_name in self.arguments:
-            setattr(self, argument_name, kwargs.get(argument_name))
-            self.kwargs[argument_name] = kwargs.get(argument_name)
-
-    def cache_hash(self):
-        result = text_type.__hash__(self.name)
-        for index, (key, value) in enumerate(self.kwargs.items()):
-            result ^= hash((key, index)) ^ hash((value, index))
-
-        return BaseTransformation.encode_hash(result)
-
-    def execute_on(self, image):
-        self.image = image
-        self.aspect = 1.0 * image.size[0] / image.size[1]
-
-
-class TransformationCrop(BaseTransformation):
-    arguments = ('left', 'top', 'right', 'bottom',)
-    label = _('Crop')
-    name = 'crop'
-
-    def execute_on(self, *args, **kwargs):
-        super(TransformationCrop, self).execute_on(*args, **kwargs)
-
-        return self.image.crop(
-            (self.left, self.top, self.right, self.bottom)
-        )
-
-
-class TransformationFlip(BaseTransformation):
-    arguments = ()
-    label = _('Flip')
-    name = 'flip'
-
-    def execute_on(self, *args, **kwargs):
-        super(TransformationFlip, self).execute_on(*args, **kwargs)
-
-        return self.image.transpose(Image.FLIP_TOP_BOTTOM)
-
-
-class TransformationGaussianBlur(BaseTransformation):
-    arguments = ('radius',)
-    label = _('Gaussian blur')
-    name = 'gaussianblur'
-
-    def execute_on(self, *args, **kwargs):
-        super(TransformationGaussianBlur, self).execute_on(*args, **kwargs)
-
-        return self.image.filter(ImageFilter.GaussianBlur(radius=self.radius))
-
-
-class TransformationLineArt(BaseTransformation):
-    label = _('Line art')
-    name = 'lineart'
-
-    def execute_on(self, *args, **kwargs):
-        super(TransformationLineArt, self).execute_on(*args, **kwargs)
-
-        return self.image.convert('L').point(lambda x: 0 if x < 128 else 255, '1')
-
-
-class TransformationMirror(BaseTransformation):
-    arguments = ()
-    label = _('Mirror')
-    name = 'mirror'
-
-    def execute_on(self, *args, **kwargs):
-        super(TransformationMirror, self).execute_on(*args, **kwargs)
-
-        return self.image.transpose(Image.FLIP_LEFT_RIGHT)
-
-
-class TransformationResize(BaseTransformation):
-    arguments = ('width', 'height')
-    label = _('Resize')
-    name = 'resize'
-
-    def execute_on(self, *args, **kwargs):
-        super(TransformationResize, self).execute_on(*args, **kwargs)
-
-        width = int(self.width)
-        height = int(self.height or 1.0 * width / self.aspect)
-
-        factor = 1
-        while self.image.size[0] / factor > 2 * width and self.image.size[1] * 2 / factor > 2 * height:
-            factor *= 2
-
-        if factor > 1:
-            self.image.thumbnail(
-                (self.image.size[0] / factor, self.image.size[1] / factor),
-                Image.NEAREST
-            )
-
-        # Resize the image with best quality algorithm ANTI-ALIAS
-        self.image.thumbnail((width, height), Image.ANTIALIAS)
-
-        return self.image
-
-
-class TransformationRotate(BaseTransformation):
-    arguments = ('degrees',)
-    label = _('Rotate')
-    name = 'rotate'
-
-    def execute_on(self, *args, **kwargs):
-        super(TransformationRotate, self).execute_on(*args, **kwargs)
-
-        self.degrees %= 360
-
-        if self.degrees == 0:
-            return self.image
-
-        return self.image.rotate(
-            360 - self.degrees, resample=Image.BICUBIC, expand=True
-        )
-
-
-class TransformationRotate90(TransformationRotate):
-    arguments = ()
-    degrees = 90
-    label = _('Rotate 90 degrees')
-    name = 'rotate90'
-
-    def __init__(self, **kwargs):
-        super(TransformationRotate90, self).__init__()
-        self.kwargs['degrees'] = 90
-
-
-class TransformationRotate180(TransformationRotate):
-    arguments = ()
-    degrees = 180
-    label = _('Rotate 180 degrees')
-    name = 'rotate180'
-
-    def __init__(self, **kwargs):
-        super(TransformationRotate180, self).__init__()
-        self.kwargs['degrees'] = 180
-
-
-class TransformationRotate270(TransformationRotate):
-    arguments = ()
-    degrees = 270
-    label = _('Rotate 270 degrees')
-    name = 'rotate270'
-
-    def __init__(self, **kwargs):
-        super(TransformationRotate270, self).__init__()
-        self.kwargs['degrees'] = 270
-
-
-class TransformationUnsharpMask(BaseTransformation):
-    arguments = ('radius', 'percent', 'threshold')
-    label = _('Unsharp masking')
-    name = 'unsharpmask'
-
-    def execute_on(self, *args, **kwargs):
-        super(TransformationUnsharpMask, self).execute_on(*args, **kwargs)
-
-        return self.image.filter(
-            ImageFilter.UnsharpMask(
-                radius=self.radius, percent=self.percent,
-                threshold=self.threshold
-            )
-        )
-
-
-class TransformationZoom(BaseTransformation):
-    arguments = ('percent',)
-    label = _('Zoom')
-    name = 'zoom'
-
-    def execute_on(self, *args, **kwargs):
-        super(TransformationZoom, self).execute_on(*args, **kwargs)
-
-        if self.percent == 100:
-            return self.image
-
-        decimal_value = float(self.percent) / 100
-        return self.image.resize(
-            (
-                int(self.image.size[0] * decimal_value),
-                int(self.image.size[1] * decimal_value)
-            ), Image.ANTIALIAS
-        )
-
-
-BaseTransformation.register(TransformationCrop)
-BaseTransformation.register(TransformationFlip)
-BaseTransformation.register(TransformationGaussianBlur)
-BaseTransformation.register(TransformationLineArt)
-BaseTransformation.register(TransformationMirror)
-BaseTransformation.register(TransformationResize)
-BaseTransformation.register(TransformationRotate)
-BaseTransformation.register(TransformationRotate90)
-BaseTransformation.register(TransformationRotate180)
-BaseTransformation.register(TransformationRotate270)
-BaseTransformation.register(TransformationUnsharpMask)
-BaseTransformation.register(TransformationZoom)

mayan/apps/converter/transformations.py

@@ -0,0 +1,264 @@
+from __future__ import unicode_literals
+
+import logging
+
+from PIL import Image, ImageFilter
+
+from django.utils.six import text_type
+from django.utils.translation import string_concat, ugettext_lazy as _
+
+logger = logging.getLogger(__name__)
+
+
+class BaseTransformation(object):
+    """
+    Transformation can modify the appearance of the document's page preview.
+    Some transformation available are: Rotate, zoom, resize and crop.
+    """
+    arguments = ()
+    name = 'base_transformation'
+    _registry = {}
+
+    @staticmethod
+    def encode_hash(decoded_value):
+        return hex(abs(decoded_value))[2:]
+
+    @staticmethod
+    def decode_hash(encoded_value):
+        return int(encoded_value, 16)
+
+    @staticmethod
+    def combine(transformations):
+        result = None
+
+        for index, transformation in enumerate(transformations):
+            if not result:
+                result = hash((BaseTransformation.decode_hash(transformation.cache_hash()), index))
+            else:
+                result ^= hash((BaseTransformation.decode_hash(transformation.cache_hash()), index))
+
+        return BaseTransformation.encode_hash(result)
+
+    @classmethod
+    def register(cls, transformation):
+        cls._registry[transformation.name] = transformation
+
+    @classmethod
+    def get_transformation_choices(cls):
+        return sorted(
+            [
+                (name, klass.get_label()) for name, klass in cls._registry.items()
+            ]
+        )
+
+    @classmethod
+    def get(cls, name):
+        return cls._registry[name]
+
+    @classmethod
+    def get_label(cls):
+        if cls.arguments:
+            return string_concat(cls.label, ': ', ', '.join(cls.arguments))
+        else:
+            return cls.label
+
+    def __init__(self, **kwargs):
+        self.kwargs = {}
+        for argument_name in self.arguments:
+            setattr(self, argument_name, kwargs.get(argument_name))
+            self.kwargs[argument_name] = kwargs.get(argument_name)
+
+    def cache_hash(self):
+        result = text_type.__hash__(self.name)
+        for index, (key, value) in enumerate(self.kwargs.items()):
+            result ^= hash((key, index)) ^ hash((value, index))
+
+        return BaseTransformation.encode_hash(result)
+
+    def execute_on(self, image):
+        self.image = image
+        self.aspect = 1.0 * image.size[0] / image.size[1]
+
+
+class TransformationCrop(BaseTransformation):
+    arguments = ('left', 'top', 'right', 'bottom',)
+    label = _('Crop')
+    name = 'crop'
+
+    def execute_on(self, *args, **kwargs):
+        super(TransformationCrop, self).execute_on(*args, **kwargs)
+
+        return self.image.crop(
+            (self.left, self.top, self.right, self.bottom)
+        )
+
+
+class TransformationFlip(BaseTransformation):
+    arguments = ()
+    label = _('Flip')
+    name = 'flip'
+
+    def execute_on(self, *args, **kwargs):
+        super(TransformationFlip, self).execute_on(*args, **kwargs)
+
+        return self.image.transpose(Image.FLIP_TOP_BOTTOM)
+
+
+class TransformationGaussianBlur(BaseTransformation):
+    arguments = ('radius',)
+    label = _('Gaussian blur')
+    name = 'gaussianblur'
+
+    def execute_on(self, *args, **kwargs):
+        super(TransformationGaussianBlur, self).execute_on(*args, **kwargs)
+
+        return self.image.filter(ImageFilter.GaussianBlur(radius=self.radius))
+
+
+class TransformationLineArt(BaseTransformation):
+    label = _('Line art')
+    name = 'lineart'
+
+    def execute_on(self, *args, **kwargs):
+        super(TransformationLineArt, self).execute_on(*args, **kwargs)
+
+        return self.image.convert('L').point(lambda x: 0 if x < 128 else 255, '1')
+
+
+class TransformationMirror(BaseTransformation):
+    arguments = ()
+    label = _('Mirror')
+    name = 'mirror'
+
+    def execute_on(self, *args, **kwargs):
+        super(TransformationMirror, self).execute_on(*args, **kwargs)
+
+        return self.image.transpose(Image.FLIP_LEFT_RIGHT)
+
+
+class TransformationResize(BaseTransformation):
+    arguments = ('width', 'height')
+    label = _('Resize')
+    name = 'resize'
+
+    def execute_on(self, *args, **kwargs):
+        super(TransformationResize, self).execute_on(*args, **kwargs)
+
+        width = int(self.width)
+        height = int(self.height or 1.0 * width / self.aspect)
+
+        factor = 1
+        while self.image.size[0] / factor > 2 * width and self.image.size[1] * 2 / factor > 2 * height:
+            factor *= 2
+
+        if factor > 1:
+            self.image.thumbnail(
+                (self.image.size[0] / factor, self.image.size[1] / factor),
+                Image.NEAREST
+            )
+
+        # Resize the image with best quality algorithm ANTI-ALIAS
+        self.image.thumbnail((width, height), Image.ANTIALIAS)
+
+        return self.image
+
+
+class TransformationRotate(BaseTransformation):
+    arguments = ('degrees',)
+    label = _('Rotate')
+    name = 'rotate'
+
+    def execute_on(self, *args, **kwargs):
+        super(TransformationRotate, self).execute_on(*args, **kwargs)
+
+        self.degrees %= 360
+
+        if self.degrees == 0:
+            return self.image
+
+        return self.image.rotate(
+            360 - self.degrees, resample=Image.BICUBIC, expand=True
+        )
+
+
+class TransformationRotate90(TransformationRotate):
+    arguments = ()
+    degrees = 90
+    label = _('Rotate 90 degrees')
+    name = 'rotate90'
+
+    def __init__(self, **kwargs):
+        super(TransformationRotate90, self).__init__()
+        self.kwargs['degrees'] = 90
+
+
+class TransformationRotate180(TransformationRotate):
+    arguments = ()
+    degrees = 180
+    label = _('Rotate 180 degrees')
+    name = 'rotate180'
+
+    def __init__(self, **kwargs):
+        super(TransformationRotate180, self).__init__()
+        self.kwargs['degrees'] = 180
+
+
+class TransformationRotate270(TransformationRotate):
+    arguments = ()
+    degrees = 270
+    label = _('Rotate 270 degrees')
+    name = 'rotate270'
+
+    def __init__(self, **kwargs):
+        super(TransformationRotate270, self).__init__()
+        self.kwargs['degrees'] = 270
+
+
+class TransformationUnsharpMask(BaseTransformation):
+    arguments = ('radius', 'percent', 'threshold')
+    label = _('Unsharp masking')
+    name = 'unsharpmask'
+
+    def execute_on(self, *args, **kwargs):
+        super(TransformationUnsharpMask, self).execute_on(*args, **kwargs)
+
+        return self.image.filter(
+            ImageFilter.UnsharpMask(
+                radius=self.radius, percent=self.percent,
+                threshold=self.threshold
+            )
+        )
+
+
+class TransformationZoom(BaseTransformation):
+    arguments = ('percent',)
+    label = _('Zoom')
+    name = 'zoom'
+
+    def execute_on(self, *args, **kwargs):
+        super(TransformationZoom, self).execute_on(*args, **kwargs)
+
+        if self.percent == 100:
+            return self.image
+
+        decimal_value = float(self.percent) / 100
+        return self.image.resize(
+            (
+                int(self.image.size[0] * decimal_value),
+                int(self.image.size[1] * decimal_value)
+            ), Image.ANTIALIAS
+        )
+
+
+BaseTransformation.register(TransformationCrop)
+BaseTransformation.register(TransformationFlip)
+BaseTransformation.register(TransformationGaussianBlur)
+BaseTransformation.register(TransformationLineArt)
+BaseTransformation.register(TransformationMirror)
+BaseTransformation.register(TransformationResize)
+BaseTransformation.register(TransformationRotate)
+BaseTransformation.register(TransformationRotate90)
+BaseTransformation.register(TransformationRotate180)
+BaseTransformation.register(TransformationRotate270)
+BaseTransformation.register(TransformationUnsharpMask)
+BaseTransformation.register(TransformationZoom)