chore: restructure for PyPI

Closes #2

.gitignore

@@ -1,9 +1,11 @@
 .vscode
-token.json
 __pycache__
+build
+dist
+*.egg-info
 
 gradient.jpg
 gradient-fried.jpg
 gradient-fried-blue.jpg
 human-fried.jpg
-human-fried-blue.jpg
+human-fried-blue.jpg

MANIFEST.in

@@ -0,0 +1 @@
+include deeppyer/flare.png

deeppyer.py → deeppyer/__init__.py

@@ -1,54 +1,50 @@
-import argparse
-import asyncio
 from collections import namedtuple
-from enum import Enum
+from io import BytesIO
 import math
+import pkgutil
+from typing import Tuple
 
 from PIL import Image, ImageOps, ImageEnhance
 import cv2
 import numpy
 
+__all__ = ('Colour', 'ColourTuple', 'DefaultColours', 'deepfry')
 
-# TODO: instead, take in tuples of colours
-class DeepfryTypes(Enum):
-    """
-    Enum for the various possible effects added to the image.
-    """
-    RED = 1
-    BLUE = 2
+Colour = Tuple[int, int, int]
+ColourTuple = Tuple[Colour, Colour]
 
 
-class Colours:
-    RED = (254, 0, 2)
-    YELLOW = (255, 255, 15)
-    BLUE = (36, 113, 229)
-    WHITE = (255,) * 3
+class DefaultColours:
+    """Default colours provided for deepfrying"""
+    red = ((254, 0, 2), (255, 255, 15))
+    blue = ((36, 113, 229), (255,) * 3)
 
 
-face_cascade = cv2.CascadeClassifier('./face_cascade.xml')
-eye_cascade = cv2.CascadeClassifier('./eye_cascade.xml')
-flare_img = Image.open('./flare.png')
+face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
+flare_img = Image.open(BytesIO(pkgutil.get_data(__package__, 'flare.png')))
 
 FlarePosition = namedtuple('FlarePosition', ['x', 'y', 'size'])
 
 
-async def deepfry(img: Image, type=DeepfryTypes.RED, *, flares: bool = True) -> Image:
+async def deepfry(img: Image, *, colours: ColourTuple = DefaultColours.red, flares: bool = True) -> Image:
     """
     Deepfry a given image.
 
-    :param img: Image to manipulate.
-    :param type: Colours to apply on the image.
-    :param flares: Whether or not to try and detect faces for applying lens flares.
-    :type img: PIL.Image
-    :type type: DeepfryTypes
-    :type flares: bool
-
-    :returns: Deepfried image.
-    :rtype: PIL.Image
+    Parameters
+    ----------
+    img : `Image`
+        Image to manipulate.
+    colours : `ColourTuple`, optional
+        A tuple of the colours to apply on the image.
+    flares : `bool`, optional
+        Whether or not to try and detect faces for applying lens flares.
+
+    Returns
+    -------
+    `Image`
+        Deepfried image.
     """
-    if type not in DeepfryTypes:
-        raise ValueError(f'Unknown deepfry type "{type}", expected a value from deeppyer.DeepfryTypes')
-
     img = img.copy().convert('RGB')
     flare_positions = []
 
@@ -86,15 +82,12 @@ async def deepfry(img: Image, type=DeepfryTypes.RED, *, flares: bool = True) ->
     img = img.resize((width, height), resample=Image.BICUBIC)
     img = ImageOps.posterize(img, 4)
 
-    # Generate red and yellow overlay for classic deepfry effect
+    # Generate colour overlay
     r = img.split()[0]
     r = ImageEnhance.Contrast(r).enhance(2.0)
     r = ImageEnhance.Brightness(r).enhance(1.5)
 
-    if type == DeepfryTypes.RED:
-        r = ImageOps.colorize(r, Colours.RED, Colours.YELLOW)
-    elif type == DeepfryTypes.BLUE:
-        r = ImageOps.colorize(r, Colours.BLUE, Colours.WHITE)
+    r = ImageOps.colorize(r, colours[0], colours[1])
 
     # Overlay red and yellow onto main image and sharpen the hell out of it
     img = Image.blend(img, r, 0.75)
@@ -106,20 +99,3 @@ async def deepfry(img: Image, type=DeepfryTypes.RED, *, flares: bool = True) ->
         img.paste(flare_transformed, (flare.x, flare.y), flare_transformed)
 
     return img
-
-if __name__ == '__main__':
-    parser = argparse.ArgumentParser(description='Deepfry an image.')
-    parser.add_argument('-v', '--version', action='version', version='%(prog)s 1.0', help='Display program version.')
-    parser.add_argument('-o', '--output', help='Filename to output to.')
-    parser.add_argument('-f', '--flares', help='Try and detected faces for adding lens flares.', action='store_true',
-                        default=False)
-    parser.add_argument('file', metavar='FILE', help='File to deepfry.')
-    args = parser.parse_args()
-
-    img = Image.open(args.file)
-    out = args.output or './deepfried.jpg'
-
-    loop = asyncio.get_event_loop()
-    img = loop.run_until_complete(deepfry(img, flares=args.flares))
-
-    img.save(out, 'jpeg')

deeppyer/cli.py

@@ -0,0 +1,24 @@
+import argparse
+import asyncio
+
+from PIL import Image
+
+from . import deepfry
+
+
+def main():
+    parser = argparse.ArgumentParser(description='Deepfry an image.')
+    parser.add_argument('-v', '--version', action='version', version='%(prog)s 1.0.0', help='Display program version.')
+    parser.add_argument('-o', '--output', help='Filename to output to.')
+    parser.add_argument('-f', '--flares', help='Try and detect faces for adding lens flares.', action='store_true',
+                        default=False)
+    parser.add_argument('file', metavar='FILE', help='File to deepfry.')
+    args = parser.parse_args()
+
+    img = Image.open(args.file)
+    out = args.output or './deepfried.jpg'
+
+    loop = asyncio.get_event_loop()
+    img = loop.run_until_complete(deepfry(img, flares=args.flares))
+
+    img.save(out, 'jpeg')