AdventImage module
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2 changed files with 93 additions and 78 deletions
83
api/advent22_api/routers/_image.py
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83
api/advent22_api/routers/_image.py
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from dataclasses import dataclass
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import numpy as np
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from PIL import Image, ImageDraw, ImageFont
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@dataclass
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class AdventImage:
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img: Image.Image
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@classmethod
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async def load_standard(cls, fp) -> "AdventImage":
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"""
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Bild laden und einen quadratischen Ausschnitt
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aus der Mitte nehmen
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"""
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# Bild laden
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img = Image.open(fp=fp)
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# Größen bestimmen
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width, height = img.size
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square = min(width, height)
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# Bild zuschneiden und skalieren
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img = img.crop(box=(
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int((width - square)/2),
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int((height - square)/2),
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int((width + square)/2),
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int((height + square)/2),
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))
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img = img.resize(
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size=(500, 500),
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resample=Image.ANTIALIAS,
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)
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# Farbmodell festlegen
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return cls(img=img.convert("RGB"))
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async def get_text_box(
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self,
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xy: tuple[float, float],
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text: str | bytes,
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font: "ImageFont._Font",
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anchor: str | None = "mm",
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**text_kwargs,
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) -> tuple[int, int, int, int] | None:
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"""
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Koordinaten (links, oben, rechts, unten) des betroffenen
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Rechtecks bestimmen, wenn das Bild `img` mit einem Text
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versehen wird
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"""
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# Neues 1-Bit Bild, gleiche Größe
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mask = Image.new(mode="1", size=self.img.size, color=0)
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# Text auf Maske auftragen
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ImageDraw.Draw(mask).text(
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xy=xy,
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text=text,
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font=font,
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anchor=anchor,
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fill=1,
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**text_kwargs,
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)
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# betroffenen Pixelbereich bestimmen
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return mask.getbbox()
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async def get_average_color(
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self,
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box: tuple[int, int, int, int],
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) -> tuple[int, int, int]:
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"""
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Durchschnittsfarbe eines rechteckigen Ausschnitts in
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einem Bild `img` berechnen
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"""
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pixel_data = self.img.crop(box).getdata()
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mean_color: np.ndarray = np.mean(pixel_data, axis=0)
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return tuple(mean_color.astype(int).tolist())
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@ -4,12 +4,12 @@ import re
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# from datetime import date
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from io import BytesIO
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import numpy as np
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from fastapi import APIRouter, Depends
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from fastapi.responses import StreamingResponse
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from PIL import Image, ImageDraw, ImageFont
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from PIL import ImageDraw, ImageFont
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from ..dav_common import get_file, list_files
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from ._image import AdventImage
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router = APIRouter(prefix="/days", tags=["days"])
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@ -65,9 +65,9 @@ _RE_IMAGE_FILE = re.compile(
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)
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async def load_picture_standard(
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async def load_image(
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index: int,
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) -> Image.Image:
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) -> AdventImage:
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"""
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Bild laden und einen quadratischen Ausschnitt
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aus der Mitte nehmen
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@ -78,73 +78,7 @@ async def load_picture_standard(
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dat = rnd.choice(await list_files(_RE_IMAGE_FILE))
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img_buffer = await get_file(dat)
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img = Image.open(img_buffer)
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# Größen bestimmen
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width, height = img.size
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square = min(width, height)
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# Bild zuschneiden und skalieren
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img = img.crop(box=(
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int((width - square)/2),
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int((height - square)/2),
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int((width + square)/2),
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int((height + square)/2),
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))
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img = img.resize(
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size=(500, 500),
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resample=Image.ANTIALIAS,
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)
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# Farbmodell festlegen
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return img.convert("RGB")
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async def get_text_box(
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img: Image.Image,
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xy: tuple[float, float],
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text: str | bytes,
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font: "ImageFont._Font",
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anchor: str | None = "mm",
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**text_kwargs,
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) -> tuple[int, int, int, int] | None:
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"""
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Koordinaten (links, oben, rechts, unten) des betroffenen
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Rechtecks bestimmen, wenn das Bild `img` mit einem Text
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versehen wird
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"""
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# Neues 1-Bit Bild, gleiche Größe
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mask = Image.new(mode="1", size=img.size, color=0)
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# Text auf Maske auftragen
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ImageDraw.Draw(mask).text(
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xy=xy,
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text=text,
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font=font,
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anchor=anchor,
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fill=1,
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**text_kwargs,
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)
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# betroffenen Pixelbereich bestimmen
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return mask.getbbox()
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async def get_average_color(
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img: Image.Image,
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box: tuple[int, int, int, int],
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) -> tuple[int, int, int]:
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"""
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Durchschnittsfarbe eines rechteckigen Ausschnitts in
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einem Bild `img` berechnen
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"""
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pixel_data = img.crop(box).getdata()
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mean_color: np.ndarray = np.mean(pixel_data, axis=0)
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return tuple(mean_color.astype(int).tolist())
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return await AdventImage.load_standard(img_buffer)
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@router.get(
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@ -154,7 +88,7 @@ async def get_average_color(
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async def get_picture_for_day(
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index: int,
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letter: str = Depends(get_letter),
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img: Image.Image = Depends(load_picture_standard),
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adv_img: AdventImage = Depends(load_image),
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) -> StreamingResponse:
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"""
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Bild für einen Tag erstellen
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xy = tuple(rnd.choices(range(30, 470), k=2))
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# betroffenen Bildbereich bestimmen
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text_box = await get_text_box(
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img=img,
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text_box = await adv_img.get_text_box(
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xy=xy,
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text=letter,
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font=font,
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if text_box is not None:
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# Durchschnittsfarbe bestimmen
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text_color = await get_average_color(
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img=img,
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text_color = await adv_img.get_average_color(
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box=text_box,
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)
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text_color = tuple(int(val) for val in text_color)
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# Buchstaben verstecken
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ImageDraw.Draw(img).text(
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ImageDraw.Draw(adv_img.img).text(
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xy=xy,
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text=letter,
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font=font,
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# Bilddaten in Puffer laden
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img_buffer = BytesIO()
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img.save(img_buffer, format="JPEG", quality=85)
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adv_img.img.save(img_buffer, format="JPEG", quality=85)
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img_buffer.seek(0)
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return StreamingResponse(
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