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39b40d6d99
Pillow will use nearest neighbour as the resampling algorithm if the source image is either 1-bit or a color palette using 8 bits. If we convert to RGB before scaling, we'll probably get a better result.
134 lines
4.9 KiB
Python
134 lines
4.9 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright 2014-2016 OpenMarket Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import logging
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from io import BytesIO
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import PIL.Image as Image
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logger = logging.getLogger(__name__)
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EXIF_ORIENTATION_TAG = 0x0112
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EXIF_TRANSPOSE_MAPPINGS = {
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2: Image.FLIP_LEFT_RIGHT,
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3: Image.ROTATE_180,
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4: Image.FLIP_TOP_BOTTOM,
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5: Image.TRANSPOSE,
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6: Image.ROTATE_270,
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7: Image.TRANSVERSE,
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8: Image.ROTATE_90,
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}
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class Thumbnailer(object):
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FORMATS = {"image/jpeg": "JPEG", "image/png": "PNG"}
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def __init__(self, input_path):
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self.image = Image.open(input_path)
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self.width, self.height = self.image.size
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self.transpose_method = None
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try:
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# We don't use ImageOps.exif_transpose since it crashes with big EXIF
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image_exif = self.image._getexif()
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if image_exif is not None:
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image_orientation = image_exif.get(EXIF_ORIENTATION_TAG)
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self.transpose_method = EXIF_TRANSPOSE_MAPPINGS.get(image_orientation)
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except Exception as e:
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# A lot of parsing errors can happen when parsing EXIF
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logger.info("Error parsing image EXIF information: %s", e)
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def transpose(self):
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"""Transpose the image using its EXIF Orientation tag
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Returns:
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Tuple[int, int]: (width, height) containing the new image size in pixels.
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"""
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if self.transpose_method is not None:
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self.image = self.image.transpose(self.transpose_method)
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self.width, self.height = self.image.size
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self.transpose_method = None
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# We don't need EXIF any more
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self.image.info["exif"] = None
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return self.image.size
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def aspect(self, max_width, max_height):
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"""Calculate the largest size that preserves aspect ratio which
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fits within the given rectangle::
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(w_in / h_in) = (w_out / h_out)
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w_out = min(w_max, h_max * (w_in / h_in))
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h_out = min(h_max, w_max * (h_in / w_in))
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Args:
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max_width: The largest possible width.
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max_height: The larget possible height.
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"""
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if max_width * self.height < max_height * self.width:
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return max_width, (max_width * self.height) // self.width
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else:
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return (max_height * self.width) // self.height, max_height
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def _resize(self, width, height):
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# 1-bit or 8-bit color palette images need converting to RGB
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# otherwise they will be scaled using nearest neighbour which
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# looks awful
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if self.image.mode in ["1", "P"]:
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self.image = self.image.convert("RGB")
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return self.image.resize((width, height), Image.ANTIALIAS)
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def scale(self, width, height, output_type):
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"""Rescales the image to the given dimensions.
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Returns:
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BytesIO: the bytes of the encoded image ready to be written to disk
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"""
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scaled = self._resize(width, height)
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return self._encode_image(scaled, output_type)
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def crop(self, width, height, output_type):
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"""Rescales and crops the image to the given dimensions preserving
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aspect::
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(w_in / h_in) = (w_scaled / h_scaled)
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w_scaled = max(w_out, h_out * (w_in / h_in))
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h_scaled = max(h_out, w_out * (h_in / w_in))
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Args:
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max_width: The largest possible width.
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max_height: The larget possible height.
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Returns:
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BytesIO: the bytes of the encoded image ready to be written to disk
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"""
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if width * self.height > height * self.width:
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scaled_height = (width * self.height) // self.width
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scaled_image = self._resize(width, scaled_height)
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crop_top = (scaled_height - height) // 2
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crop_bottom = height + crop_top
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cropped = scaled_image.crop((0, crop_top, width, crop_bottom))
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else:
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scaled_width = (height * self.width) // self.height
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scaled_image = self._resize(scaled_width, height)
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crop_left = (scaled_width - width) // 2
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crop_right = width + crop_left
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cropped = scaled_image.crop((crop_left, 0, crop_right, height))
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return self._encode_image(cropped, output_type)
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def _encode_image(self, output_image, output_type):
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output_bytes_io = BytesIO()
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output_image.save(output_bytes_io, self.FORMATS[output_type], quality=80)
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return output_bytes_io
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