添加卵总展示

This commit is contained in:
2025-10-16 22:29:07 +08:00
parent 7ebcb8add4
commit 4f885554ca
4 changed files with 90 additions and 4 deletions

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assets/img/meme/snaur_1_base.png Executable file

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assets/img/meme/snaur_1_top.png Executable file

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@ -2,11 +2,11 @@ from io import BytesIO
from typing import Iterable, cast
from nonebot import on_message
from nonebot_plugin_alconna import (Alconna, Args, Field, MultiVar, Text,
from nonebot_plugin_alconna import (Alconna, Args, Field, Image, MultiVar, Text,
UniMessage, UniMsg, on_alconna)
from konabot.common.nb.extract_image import extract_image_from_message
from konabot.plugins.memepack.drawing.display import draw_cao_display
from konabot.common.nb.extract_image import PIL_Image, extract_image_from_message
from konabot.plugins.memepack.drawing.display import draw_cao_display, draw_snaur_display
from konabot.plugins.memepack.drawing.saying import (draw_cute_ten,
draw_geimao, draw_mnk,
draw_pt, draw_suan)
@ -139,3 +139,17 @@ async def _(msg: UniMsg, evt: Event, bot: Bot):
.text(err)
.export()
)
snaur_display_cmd = on_alconna(Alconna(
"卵总展示",
Args["image", Image | None],
))
@snaur_display_cmd.handle()
async def _(img: PIL_Image):
img_processed = await draw_snaur_display(img)
img_data = BytesIO()
img_processed.save(img_data, "PNG")
await snaur_display_cmd.send(await UniMessage().image(raw=img_data).export())

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@ -4,10 +4,12 @@ from typing import Any, cast
import cv2
import numpy as np
import PIL.Image
import PIL.ImageChops
import PIL.ImageEnhance
from konabot.common.path import ASSETS_PATH
cao_image = PIL.Image.open(ASSETS_PATH / "img" / "meme" / "caoimg1.png")
cao_image = PIL.Image.open(ASSETS_PATH / "img" / "meme" / "caoimg1.png")
CAO_QUAD_POINTS = np.float32(cast(Any, [
[392, 540],
[577, 557],
@ -15,6 +17,16 @@ CAO_QUAD_POINTS = np.float32(cast(Any, [
[381, 687],
]))
snaur_image_base = PIL.Image.open(ASSETS_PATH / "img" / "meme" / "snaur_1_base.png")
snaur_image_top = PIL.Image.open(ASSETS_PATH / "img" / "meme" / "snaur_1_top.png")
SNAUR_RATIO = (1 / 2) ** .5
SNAUR_QUAD_POINTS = np.float32(cast(Any, [
[0, 466 ],
[673, 471 ],
[640, 1196],
[106, 1280],
]))
def _draw_cao_display(image: PIL.Image.Image):
src = np.array(image.convert("RGB"))
h, w = src.shape[:2]
@ -43,3 +55,63 @@ def _draw_cao_display(image: PIL.Image.Image):
async def draw_cao_display(image: PIL.Image.Image):
return await asyncio.to_thread(_draw_cao_display, image)
def _draw_snaur_display(image: PIL.Image.Image):
src = np.array(image.convert("RGB"))
_h, _w = src.shape[:2]
if _w / _h < SNAUR_RATIO:
_w_target = _w
_h_target = int(_w / SNAUR_RATIO)
else:
_w_target = int(_h * SNAUR_RATIO)
_h_target = _h
x_center = _w / 2
y_center = _h / 2
x1 = int(x_center - _w_target / 2)
x2 = int(x_center + _w_target / 2)
y1 = int(y_center - _h_target / 2)
y2 = int(y_center + _h_target / 2)
src = src[y1:y2, x1:x2, :]
h, w = src.shape[:2]
src_points = np.float32(cast(Any, [
[0, 0],
[w, 0],
[w, h],
[0, h],
]))
dst_points = SNAUR_QUAD_POINTS
M = cv2.getPerspectiveTransform(cast(Any, src_points), cast(Any, dst_points))
output_size = snaur_image_top.size
output_w, output_h = output_size
warped = cv2.warpPerspective(
src,
M,
(output_w, output_h),
flags=cv2.INTER_LINEAR,
borderMode=cv2.BORDER_CONSTANT,
borderValue=(0, 0, 0)
)
result = PIL.Image.fromarray(warped, 'RGB').convert('RGBA')
result = PIL.ImageChops.multiply(result, snaur_image_base)
r, g, b, a = result.split()
a = a.point(lambda p: int(p * 0.8))
result = PIL.Image.merge('RGBA', (r, g, b, a))
enhancer = PIL.ImageEnhance.Color(result)
result = enhancer.enhance(0.85)
result = PIL.Image.alpha_composite(result, snaur_image_top)
return result
async def draw_snaur_display(image: PIL.Image.Image) -> PIL.Image.Image:
return await asyncio.to_thread(_draw_snaur_display, image)