Lenaisten/advent22
4
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity

buchstaben verstecken

Browse source
This commit is contained in:
Jörn-Michael Miehe 2022-10-10 02:12:24 +00:00
parent f49f12c981
commit 2e6daa9da3
3 changed files with 62 additions and 6 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

27
api/advent22_api/routers/days.py
View file

@ -2,6 +2,7 @@ import random
from datetime import date
from io import BytesIO
import numpy as np
from fastapi import APIRouter, Depends
from fastapi.responses import StreamingResponse
from PIL import Image, ImageDraw, ImageFont
@ -86,14 +87,30 @@ async def get_picture_for_day(
font = ImageFont.truetype("Lena.ttf", 50)
txt_layer = Image.new(mode="RGB", size=(400, 400), color=(0, 0, 0))
txt_color = (255, 255, 255)
d1 = ImageDraw.Draw(txt_layer)
d1.text(xy=(300, 300), text=letter, font=font,
anchor="mm", fill=(255, 255, 255))
d1.rectangle(txt_layer.getbbox())
ImageDraw.Draw(txt_layer).text(
xy=(300, 300),
text=letter,
font=font,
anchor="mm",
fill=txt_color,
)
if not (bbox := txt_layer.getbbox()) is None:
mean = np.mean(img.crop(bbox).getdata(), axis=0)
txt_color = tuple(int(val) for val in mean)
ImageDraw.Draw(img).text(
xy=(300, 300),
text=letter,
font=font,
anchor="mm",
fill=txt_color,
)
img_buffer = BytesIO()
txt_layer.save(img_buffer, format="PNG", quality=85)
img.save(img_buffer, format="PNG", quality=85)
img_buffer.seek(0)
return StreamingResponse(

40
api/poetry.lock generated
View file

@ -79,6 +79,14 @@ category = "main"
optional = false
python-versions = ">=3.5"
[[package]]
name = "numpy"
version = "1.23.3"
description = "NumPy is the fundamental package for array computing with Python."
category = "main"
optional = false
python-versions = ">=3.8"
[[package]]
name = "Pillow"
version = "9.2.0"
@ -212,7 +220,7 @@ python-versions = ">=3.7"
[metadata]
lock-version = "1.1"
python-versions = "^3.10"
content-hash = "5d4c72b8811bc7d6f587ec8e978596adac1ec53c000ba5f2c156b7f6cf02f454"
content-hash = "fa252faeeadce1a90970a8139850140aabcc180ea7d0b91aa2d72ad751fa3331"
[metadata.files]
anyio = [
@ -282,6 +290,36 @@ idna = [
{file = "idna-3.4-py3-none-any.whl", hash = "sha256:90b77e79eaa3eba6de819a0c442c0b4ceefc341a7a2ab77d7562bf49f425c5c2"},
{file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
]
numpy = [
{file = "numpy-1.23.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c9f707b5bb73bf277d812ded9896f9512a43edff72712f31667d0a8c2f8e71ee"},
{file = "numpy-1.23.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:ffcf105ecdd9396e05a8e58e81faaaf34d3f9875f137c7372450baa5d77c9a54"},
{file = "numpy-1.23.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0ea3f98a0ffce3f8f57675eb9119f3f4edb81888b6874bc1953f91e0b1d4f440"},
{file = "numpy-1.23.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:004f0efcb2fe1c0bd6ae1fcfc69cc8b6bf2407e0f18be308612007a0762b4089"},
{file = "numpy-1.23.3-cp310-cp310-win32.whl", hash = "sha256:98dcbc02e39b1658dc4b4508442a560fe3ca5ca0d989f0df062534e5ca3a5c1a"},
{file = "numpy-1.23.3-cp310-cp310-win_amd64.whl", hash = "sha256:39a664e3d26ea854211867d20ebcc8023257c1800ae89773cbba9f9e97bae036"},
{file = "numpy-1.23.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:1f27b5322ac4067e67c8f9378b41c746d8feac8bdd0e0ffede5324667b8a075c"},
{file = "numpy-1.23.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2ad3ec9a748a8943e6eb4358201f7e1c12ede35f510b1a2221b70af4bb64295c"},
{file = "numpy-1.23.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bdc9febce3e68b697d931941b263c59e0c74e8f18861f4064c1f712562903411"},
{file = "numpy-1.23.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:301c00cf5e60e08e04d842fc47df641d4a181e651c7135c50dc2762ffe293dbd"},
{file = "numpy-1.23.3-cp311-cp311-win32.whl", hash = "sha256:7cd1328e5bdf0dee621912f5833648e2daca72e3839ec1d6695e91089625f0b4"},
{file = "numpy-1.23.3-cp311-cp311-win_amd64.whl", hash = "sha256:8355fc10fd33a5a70981a5b8a0de51d10af3688d7a9e4a34fcc8fa0d7467bb7f"},
{file = "numpy-1.23.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:bc6e8da415f359b578b00bcfb1d08411c96e9a97f9e6c7adada554a0812a6cc6"},
{file = "numpy-1.23.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:22d43376ee0acd547f3149b9ec12eec2f0ca4a6ab2f61753c5b29bb3e795ac4d"},
{file = "numpy-1.23.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a64403f634e5ffdcd85e0b12c08f04b3080d3e840aef118721021f9b48fc1460"},
{file = "numpy-1.23.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:efd9d3abe5774404becdb0748178b48a218f1d8c44e0375475732211ea47c67e"},
{file = "numpy-1.23.3-cp38-cp38-win32.whl", hash = "sha256:f8c02ec3c4c4fcb718fdf89a6c6f709b14949408e8cf2a2be5bfa9c49548fd85"},
{file = "numpy-1.23.3-cp38-cp38-win_amd64.whl", hash = "sha256:e868b0389c5ccfc092031a861d4e158ea164d8b7fdbb10e3b5689b4fc6498df6"},
{file = "numpy-1.23.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:09f6b7bdffe57fc61d869a22f506049825d707b288039d30f26a0d0d8ea05164"},
{file = "numpy-1.23.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:8c79d7cf86d049d0c5089231a5bcd31edb03555bd93d81a16870aa98c6cfb79d"},
{file = "numpy-1.23.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e5d5420053bbb3dd64c30e58f9363d7a9c27444c3648e61460c1237f9ec3fa14"},
{file = "numpy-1.23.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d5422d6a1ea9b15577a9432e26608c73a78faf0b9039437b075cf322c92e98e7"},
{file = "numpy-1.23.3-cp39-cp39-win32.whl", hash = "sha256:c1ba66c48b19cc9c2975c0d354f24058888cdc674bebadceb3cdc9ec403fb5d1"},
{file = "numpy-1.23.3-cp39-cp39-win_amd64.whl", hash = "sha256:78a63d2df1d947bd9d1b11d35564c2f9e4b57898aae4626638056ec1a231c40c"},
{file = "numpy-1.23.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:17c0e467ade9bda685d5ac7f5fa729d8d3e76b23195471adae2d6a6941bd2c18"},
{file = "numpy-1.23.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:91b8d6768a75247026e951dce3b2aac79dc7e78622fc148329135ba189813584"},
{file = "numpy-1.23.3-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:94c15ca4e52671a59219146ff584488907b1f9b3fc232622b47e2cf832e94fb8"},
{file = "numpy-1.23.3.tar.gz", hash = "sha256:51bf49c0cd1d52be0a240aa66f3458afc4b95d8993d2d04f0d91fa60c10af6cd"},
]
Pillow = [
{file = "Pillow-9.2.0-cp310-cp310-macosx_10_10_x86_64.whl", hash = "sha256:a9c9bc489f8ab30906d7a85afac4b4944a572a7432e00698a7239f44a44e6efb"},
{file = "Pillow-9.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:510cef4a3f401c246cfd8227b300828715dd055463cdca6176c2e4036df8bd4f"},

1
api/pyproject.toml
View file

@ -13,6 +13,7 @@ fastapi = "^0.85.0"
python = "^3.10"
uvicorn = {extras = ["standard"], version = "^0.18.3"}
Pillow = "^9.2.0"
numpy = "^1.23.3"
[tool.poetry.dev-dependencies]