forked from mttu-developers/konabot
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11 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 09c9d44798 | |||
| 0c4206f461 | |||
| 9fb8fd90dc | |||
| 8c4fa2b5e4 | |||
| fb2c3f1ce2 | |||
| 265415e727 | |||
| 06555b2225 | |||
| f6fd25a41d | |||
| 9f6c70bf0f | |||
| 1c01e49d5d | |||
| 48c719bc33 |
BIN
assets/fonts/LXGWWenKai-Regular.ttf
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assets/fonts/LXGWWenKai-Regular.ttf
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assets/img/dice/stick.png
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assets/img/dice/stick.png
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After Width: | Height: | Size: 80 KiB |
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assets/img/meme/dss.png
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assets/img/meme/dss.png
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After Width: | Height: | Size: 172 KiB |
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assets/img/meme/mnksay.jpg
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assets/img/meme/mnksay.jpg
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After Width: | Height: | Size: 69 KiB |
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assets/img/meme/suanleba.png
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assets/img/meme/suanleba.png
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After Width: | Height: | Size: 364 KiB |
@ -3,8 +3,7 @@ from io import BytesIO
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from nonebot_plugin_alconna import (Alconna, Args, Field, MultiVar, UniMessage,
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on_alconna)
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from konabot.plugins.memepack.drawing.geimao import draw_geimao
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from konabot.plugins.memepack.drawing.pt import draw_pt
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from konabot.plugins.memepack.drawing.saying import draw_geimao, draw_mnk, draw_pt, draw_suan
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geimao = on_alconna(Alconna(
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"给猫说",
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@ -36,3 +35,51 @@ async def _(saying: list[str]):
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img.save(img_bytes, format="PNG")
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await pt.send(await UniMessage().image(raw=img_bytes).export())
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mnk = on_alconna(Alconna(
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"re:小?黑白子?说",
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Args["saying", MultiVar(str, '+'), Field(
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missing_tips=lambda: "你没有写黑白子说了什么"
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)]
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), use_cmd_start=True, use_cmd_sep=False, skip_for_unmatch=False, aliases={"mnk说"})
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@mnk.handle()
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async def _(saying: list[str]):
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img = await draw_mnk("\n".join(saying))
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img_bytes = BytesIO()
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img.save(img_bytes, format="PNG")
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await pt.send(await UniMessage().image(raw=img_bytes).export())
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suan = on_alconna(Alconna(
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"小蒜说",
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Args["saying", MultiVar(str, '+'), Field(
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missing_tips=lambda: "你没有写小蒜说了什么"
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)]
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), use_cmd_start=True, use_cmd_sep=False, skip_for_unmatch=False, aliases=set())
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@suan.handle()
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async def _(saying: list[str]):
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img = await draw_suan("\n".join(saying))
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img_bytes = BytesIO()
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img.save(img_bytes, format="PNG")
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await pt.send(await UniMessage().image(raw=img_bytes).export())
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dsuan = on_alconna(Alconna(
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"大蒜说",
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Args["saying", MultiVar(str, '+'), Field(
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missing_tips=lambda: "你没有写大蒜说了什么"
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)]
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), use_cmd_start=True, use_cmd_sep=False, skip_for_unmatch=False, aliases=set())
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@dsuan.handle()
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async def _(saying: list[str]):
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img = await draw_suan("\n".join(saying), True)
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img_bytes = BytesIO()
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img.save(img_bytes, format="PNG")
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await pt.send(await UniMessage().image(raw=img_bytes).export())
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@ -10,3 +10,4 @@ FontDB.SetDefaultEmojiOptions(EmojiOptions(
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HARMONYOS_SANS_SC_BLACK = FontDB.Query("HarmonyOS_Sans_SC_Black")
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HARMONYOS_SANS_SC_REGULAR = FontDB.Query("HarmonyOS_Sans_SC_Regular")
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LXGWWENKAI_REGULAR = FontDB.Query("LXGWWenKai-Regular")
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@ -1,30 +0,0 @@
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import asyncio
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from typing import Any, cast
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import imagetext_py
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import PIL.Image
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from konabot.common.path import ASSETS_PATH
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from .base.fonts import HARMONYOS_SANS_SC_BLACK
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geimao_image = PIL.Image.open(ASSETS_PATH / "img" / "meme" / "geimao.jpg").convert("RGBA")
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def _draw_geimao(saying: str):
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img = geimao_image.copy()
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with imagetext_py.Writer(img) as iw:
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iw.draw_text_wrapped(
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saying, 960, 50, 00.5, 0, 1920, 240, HARMONYOS_SANS_SC_BLACK,
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imagetext_py.Paint.Color(imagetext_py.Color.from_hex("000000FF")),
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0.8,
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imagetext_py.TextAlign.Center,
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cast(Any, 30.0),
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imagetext_py.Paint.Color(imagetext_py.Color.from_hex("FFFFFFFF")),
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draw_emojis=True,
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)
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return img
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async def draw_geimao(saying: str):
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return await asyncio.to_thread(_draw_geimao, saying)
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@ -1,27 +0,0 @@
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import asyncio
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import imagetext_py
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import PIL.Image
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from konabot.common.path import ASSETS_PATH
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from .base.fonts import HARMONYOS_SANS_SC_REGULAR
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pt_image = PIL.Image.open(ASSETS_PATH / "img" / "meme" / "ptsay.png").convert("RGBA")
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def _draw_pt(saying: str):
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img = pt_image.copy()
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with imagetext_py.Writer(img) as iw:
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iw.draw_text_wrapped(
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saying, 259, 278, 0.5, 0.5, 360, 48, HARMONYOS_SANS_SC_REGULAR,
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imagetext_py.Paint.Color(imagetext_py.Color.from_hex("000000FF")),
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1.0,
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imagetext_py.TextAlign.Center,
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draw_emojis=True,
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)
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return img
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async def draw_pt(saying: str):
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return await asyncio.to_thread(_draw_pt, saying)
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90
konabot/plugins/memepack/drawing/saying.py
Normal file
90
konabot/plugins/memepack/drawing/saying.py
Normal file
@ -0,0 +1,90 @@
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import asyncio
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from typing import Any, cast
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import imagetext_py
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import PIL.Image
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from konabot.common.path import ASSETS_PATH
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from .base.fonts import HARMONYOS_SANS_SC_BLACK, HARMONYOS_SANS_SC_REGULAR, LXGWWENKAI_REGULAR
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geimao_image = PIL.Image.open(ASSETS_PATH / "img" / "meme" / "geimao.jpg").convert("RGBA")
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pt_image = PIL.Image.open(ASSETS_PATH / "img" / "meme" / "ptsay.png").convert("RGBA")
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mnk_image = PIL.Image.open(ASSETS_PATH / "img" / "meme" / "mnksay.jpg").convert("RGBA")
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dasuan_image = PIL.Image.open(ASSETS_PATH / "img" / "meme" / "dss.png").convert("RGBA")
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suan_image = PIL.Image.open(ASSETS_PATH / "img" / "meme" / "suanleba.png").convert("RGBA")
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def _draw_geimao(saying: str):
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img = geimao_image.copy()
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with imagetext_py.Writer(img) as iw:
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iw.draw_text_wrapped(
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saying, 960, 50, 0.5, 0, 1920, 240, HARMONYOS_SANS_SC_BLACK,
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imagetext_py.Paint.Color(imagetext_py.Color.from_hex("000000FF")),
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0.8,
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imagetext_py.TextAlign.Center,
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cast(Any, 30.0),
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imagetext_py.Paint.Color(imagetext_py.Color.from_hex("FFFFFFFF")),
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draw_emojis=True,
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)
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return img
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async def draw_geimao(saying: str):
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return await asyncio.to_thread(_draw_geimao, saying)
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def _draw_pt(saying: str):
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img = pt_image.copy()
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with imagetext_py.Writer(img) as iw:
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iw.draw_text_wrapped(
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saying, 259, 278, 0.5, 0.5, 360, 48, HARMONYOS_SANS_SC_REGULAR,
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imagetext_py.Paint.Color(imagetext_py.Color.from_hex("000000FF")),
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1.0,
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imagetext_py.TextAlign.Center,
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draw_emojis=True,
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)
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return img
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async def draw_pt(saying: str):
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return await asyncio.to_thread(_draw_pt, saying)
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def _draw_mnk(saying: str):
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img = mnk_image.copy()
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with imagetext_py.Writer(img) as iw:
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iw.draw_text_wrapped(
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saying, 540, 25, 0.5, 0, 1080, 120, HARMONYOS_SANS_SC_BLACK,
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imagetext_py.Paint.Color(imagetext_py.Color.from_hex("000000FF")),
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0.8,
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imagetext_py.TextAlign.Center,
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cast(Any, 15.0),
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imagetext_py.Paint.Color(imagetext_py.Color.from_hex("FFFFFFFF")),
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draw_emojis=True,
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)
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return img
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async def draw_mnk(saying: str):
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return await asyncio.to_thread(_draw_mnk, saying)
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def _draw_suan(saying: str, dasuan: bool = False):
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if dasuan:
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img = dasuan_image.copy()
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else:
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img = suan_image.copy()
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with imagetext_py.Writer(img) as iw:
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iw.draw_text_wrapped(
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saying, 1020, 290, 0.5, 0.5, 400, 48, LXGWWENKAI_REGULAR,
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imagetext_py.Paint.Color(imagetext_py.Color.from_hex("000000FF")),
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1.0,
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imagetext_py.TextAlign.Center,
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draw_emojis=True,
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)
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return img
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async def draw_suan(saying: str, dasuan: bool = False):
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return await asyncio.to_thread(_draw_suan, saying, dasuan)
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@ -1,11 +1,11 @@
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from typing import Optional
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from typing import Optional, Union
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from nonebot.adapters import Event as BaseEvent
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from nonebot.adapters.console.event import MessageEvent as ConsoleMessageEvent
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from nonebot.adapters.discord.event import MessageEvent as DiscordMessageEvent
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from nonebot_plugin_alconna import Alconna, Args, UniMessage, on_alconna
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from konabot.plugins.roll_dice.roll_dice import generate_dice_image
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from konabot.plugins.roll_dice.roll_number import get_random_number, roll_number
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from konabot.plugins.roll_dice.roll_number import get_random_number, get_random_number_string, roll_number
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evt = on_alconna(Alconna(
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"摇数字"
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@ -22,21 +22,26 @@ async def _(event: BaseEvent):
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evt = on_alconna(Alconna(
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"摇骰子",
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Args["f1?", int]["f2?", int]
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Args["f1?", str]["f2?", str]
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), use_cmd_start=True, use_cmd_sep=False, skip_for_unmatch=True)
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@evt.handle()
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async def _(event: BaseEvent, f1: Optional[int] = None, f2: Optional[int] = None):
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async def _(event: BaseEvent, f1: Optional[str] = None, f2: Optional[str] = None):
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# if isinstance(event, DiscordMessageEvent):
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# await evt.send(await UniMessage().text("```\n" + roll_dice() + "\n```").export())
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# elif isinstance(event, ConsoleMessageEvent):
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number = 0
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number = ""
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if(f1 is not None and f2 is not None):
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number = get_random_number(f1, f2)
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number = get_random_number_string(f1, f2)
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elif f1 is not None:
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number = get_random_number(1, f1)
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if(float(f1) > 1):
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number = get_random_number_string("1", f1)
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elif (float(f1) > 0):
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number = get_random_number_string("0", f1)
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else:
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number = get_random_number_string(f1, "0")
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else:
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number = get_random_number()
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number = get_random_number_string()
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await evt.send(await UniMessage().image(raw=await generate_dice_image(number)).export())
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# else:
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# await evt.send(await UniMessage().text(roll_dice(wide=True)).export())
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@ -152,27 +152,208 @@ def precise_blend_with_perspective(background, foreground, corners):
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return result
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async def generate_dice_image(number: int) -> BytesIO:
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def draw_line_bresenham(image, x0, y0, x1, y1, color):
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"""使用Bresenham算法画线,避免间隙"""
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dx = abs(x1 - x0)
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dy = abs(y1 - y0)
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sx = 1 if x0 < x1 else -1
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sy = 1 if y0 < y1 else -1
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err = dx - dy
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while True:
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if 0 <= x0 < image.shape[1] and 0 <= y0 < image.shape[0]:
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image[y0, x0] = color
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if x0 == x1 and y0 == y1:
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break
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|
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e2 = 2 * err
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if e2 > -dy:
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err -= dy
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x0 += sx
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if e2 < dx:
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err += dx
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y0 += sy
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def slice_and_stretch(image, slice_lines, direction):
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'''
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image: 图像
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slice_lines: 切割线(两个点的列表),一般是倾斜45度的直线
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direction: 移动方向向量(二元数组)
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'''
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# 获取图片的尺寸
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height, width = image.shape[:2]
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# 创建一个由移动方向扩充后,更大的图片
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new_width = int(width + abs(direction[0]))
|
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new_height = int(height + abs(direction[1]))
|
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new_image = np.zeros((new_height, new_width, 4), dtype=image.dtype)
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# 先把图片放在新图的和方向相反的一侧
|
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offset_x = int(abs(min(0, direction[0])))
|
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offset_y = int(abs(min(0, direction[1])))
|
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new_image[offset_y:offset_y+height, offset_x:offset_x+width] = image
|
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# 切割线也跟着偏移
|
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slice_lines = [(x + offset_x, y + offset_y) for (x, y) in slice_lines]
|
||||
# 复制切割线经过的像素,沿着方向移动,实现类似拖尾的效果
|
||||
apply_trail_effect_vectorized(new_image, slice_lines, direction)
|
||||
apply_stroke_vectorized(new_image, slice_lines, direction)
|
||||
|
||||
|
||||
return new_image, offset_x, offset_y
|
||||
|
||||
def apply_trail_effect_vectorized(new_image, slice_lines, direction):
|
||||
"""向量化实现拖尾效果"""
|
||||
height, width = new_image.shape[:2]
|
||||
|
||||
# 创建坐标网格
|
||||
y_coords, x_coords = np.mgrid[0:height, 0:width]
|
||||
|
||||
# 向量化计算点到直线的距离
|
||||
line_vec = np.array([slice_lines[1][0] - slice_lines[0][0],
|
||||
slice_lines[1][1] - slice_lines[0][1]])
|
||||
point_vecs = np.stack([x_coords - slice_lines[0][0],
|
||||
y_coords - slice_lines[0][1]], axis=-1)
|
||||
|
||||
# 计算叉积(有向距离)
|
||||
cross_products = (line_vec[0] * point_vecs[:, :, 1] -
|
||||
line_vec[1] * point_vecs[:, :, 0])
|
||||
|
||||
# 选择直线右侧的像素 (d1 > 0)
|
||||
mask = cross_products > 0
|
||||
|
||||
# 计算目标位置
|
||||
target_x = (x_coords + direction[0]).astype(int)
|
||||
target_y = (y_coords + direction[1]).astype(int)
|
||||
|
||||
# 创建有效位置掩码
|
||||
valid_mask = mask & (target_x >= 0) & (target_x < width) & \
|
||||
(target_y >= 0) & (target_y < height)
|
||||
|
||||
# 批量复制像素
|
||||
new_image[target_y[valid_mask], target_x[valid_mask]] = \
|
||||
new_image[y_coords[valid_mask], x_coords[valid_mask]]
|
||||
|
||||
def apply_stroke_vectorized(new_image, slice_lines, direction):
|
||||
"""使用向量化操作优化笔画效果"""
|
||||
height, width = new_image.shape[:2]
|
||||
|
||||
# 1. 找到所有非透明像素
|
||||
non_transparent = np.where(new_image[:, :, 3] > 0)
|
||||
if len(non_transparent[0]) == 0:
|
||||
return
|
||||
|
||||
y_coords, x_coords = non_transparent
|
||||
|
||||
# 2. 向量化计算点到直线的距离
|
||||
line_vec = np.array([slice_lines[1][0] - slice_lines[0][0],
|
||||
slice_lines[1][1] - slice_lines[0][1]])
|
||||
point_vecs = np.column_stack([x_coords - slice_lines[0][0],
|
||||
y_coords - slice_lines[0][1]])
|
||||
|
||||
# 计算叉积(距离)
|
||||
cross_products = (line_vec[0] * point_vecs[:, 1] -
|
||||
line_vec[1] * point_vecs[:, 0])
|
||||
|
||||
# 3. 选择靠近直线的像素
|
||||
mask = np.abs(cross_products) < 1.0
|
||||
selected_y = y_coords[mask]
|
||||
selected_x = x_coords[mask]
|
||||
selected_pixels = new_image[selected_y, selected_x]
|
||||
|
||||
if len(selected_x) == 0:
|
||||
return
|
||||
|
||||
# 4. 预计算采样点
|
||||
length = np.sqrt(direction[0]**2 + direction[1]**2)
|
||||
if length == 0:
|
||||
return
|
||||
|
||||
# 创建采样偏移
|
||||
dx_dy = np.array([(dx, dy) for dx in [-0.5, 0, 0.5]
|
||||
for dy in [-0.5, 0, 0.5]])
|
||||
|
||||
# 5. 批量计算目标位置
|
||||
steps = max(1, int(length * 2))
|
||||
alpha = 0.7
|
||||
|
||||
for k in range(1, steps + 1):
|
||||
# 对所有选中的像素批量计算新位置
|
||||
scale = k / steps
|
||||
|
||||
# 为每个像素和每个采样点计算目标位置
|
||||
for dx, dy in dx_dy:
|
||||
target_x = np.round(selected_x + dx + direction[0] * scale).astype(int)
|
||||
target_y = np.round(selected_y + dy + direction[1] * scale).astype(int)
|
||||
|
||||
# 创建有效位置掩码
|
||||
valid_mask = (target_x >= 0) & (target_x < width) & \
|
||||
(target_y >= 0) & (target_y < height)
|
||||
|
||||
if np.any(valid_mask):
|
||||
valid_target_x = target_x[valid_mask]
|
||||
valid_target_y = target_y[valid_mask]
|
||||
valid_source_idx = np.where(valid_mask)[0]
|
||||
|
||||
# 批量混合像素
|
||||
source_pixels = selected_pixels[valid_source_idx]
|
||||
target_pixels = new_image[valid_target_y, valid_target_x]
|
||||
|
||||
new_image[valid_target_y, valid_target_x] = (
|
||||
alpha * source_pixels + (1 - alpha) * target_pixels
|
||||
)
|
||||
|
||||
async def generate_dice_image(number: str) -> BytesIO:
|
||||
# 将文本转换为带透明背景的图像
|
||||
text = str(number)
|
||||
text = number
|
||||
|
||||
# 如果文本太长,直接返回金箍棒
|
||||
if(len(text) > 50):
|
||||
output = BytesIO()
|
||||
push_image = Image.open(ASSETS_PATH / "img" / "dice" / "stick.png")
|
||||
push_image.save(output,format='PNG')
|
||||
output.seek(0)
|
||||
return output
|
||||
|
||||
text_image = text_to_transparent_image(
|
||||
text,
|
||||
font_size=60,
|
||||
text_color=(0, 0, 0) # 黑色文字
|
||||
)
|
||||
|
||||
|
||||
# 获取长宽比
|
||||
height, width = text_image.shape[:2]
|
||||
aspect_ratio = width / height
|
||||
|
||||
# 根据长宽比设置拉伸系数
|
||||
stretch_k = 1
|
||||
if aspect_ratio > 1:
|
||||
stretch_k = aspect_ratio
|
||||
|
||||
# 骰子的方向
|
||||
up_direction = (51 - 16, 5 - 30) # 右上角点 - 左上角点
|
||||
|
||||
move_distance = (up_direction[0] * (stretch_k - 1), up_direction[1] * (stretch_k - 1))
|
||||
|
||||
# 加载背景图像,保留透明通道
|
||||
background = cv2.imread(str(ASSETS_PATH / "img" / "dice" / "template.png"), cv2.IMREAD_UNCHANGED)
|
||||
assert background is not None
|
||||
|
||||
height, width = background.shape[:2]
|
||||
|
||||
background, offset_x, offset_y = slice_and_stretch(background,
|
||||
[(10,10),(0,0)],
|
||||
move_distance)
|
||||
|
||||
# 定义3D变换的四个角点(透视效果)
|
||||
# 顺序: [左上, 右上, 右下, 左下]
|
||||
corners = np.array([
|
||||
[16, 30], # 左上
|
||||
[51, 5], # 右上(上移,创建透视)
|
||||
[88, 33], # 右下
|
||||
[51 + move_distance[0], 5 + move_distance[1]], # 右上(上移,创建透视)
|
||||
[88 + move_distance[0], 33 + move_distance[1]], # 右下
|
||||
[49, 62] # 左下(下移)
|
||||
], dtype=np.float32)
|
||||
corners[:, 0] += offset_x
|
||||
corners[:, 1] += offset_y
|
||||
|
||||
# 加载背景图像,保留透明通道
|
||||
background = cv2.imread(str(ASSETS_PATH / "img" / "dice" / "template.png"), cv2.IMREAD_UNCHANGED)
|
||||
|
||||
|
||||
# 对文本图像进行3D变换(保持透明通道)
|
||||
transformed_text, transform_matrix = perspective_transform(text_image, background, corners)
|
||||
@ -186,6 +367,26 @@ async def generate_dice_image(number: int) -> BytesIO:
|
||||
images: list[Image.Image] = [Image.open(ASSETS_PATH / "img" / "dice" / f"{i}.png") for i in range(1, 12)]
|
||||
images.append(pil_final)
|
||||
frame_durations = [100] * (len(images) - 1) + [100000]
|
||||
# 将导入的图像尺寸扩展为和 pil_final 相同的大小,随帧数进行扩展,然后不放大的情况下放在最中间
|
||||
if(aspect_ratio > 1):
|
||||
target_size = pil_final.size
|
||||
for i in range(len(images) - 1):
|
||||
k = i / (len(images) - 1)
|
||||
now_distance = (move_distance[0] * k, move_distance[1] * k)
|
||||
img = np.array(images[i])
|
||||
img, _, _ = slice_and_stretch(img,
|
||||
[(10,10),(0,0)],
|
||||
now_distance)
|
||||
# 只扩展边界,图像本身不放大
|
||||
img_width, img_height = img.shape[1], img.shape[0]
|
||||
new_img = Image.new("RGBA", target_size, (0, 0, 0, 0))
|
||||
this_offset_x = (target_size[0] - img_width) // 2
|
||||
this_offset_y = (target_size[1] - img_height) // 2
|
||||
# new_img.paste(img, (this_offset_x, this_offset_y))
|
||||
new_img.paste(Image.fromarray(img), (this_offset_x, this_offset_y))
|
||||
images[i] = new_img
|
||||
|
||||
|
||||
# 保存为BytesIO对象
|
||||
output = BytesIO()
|
||||
images[0].save(output,
|
||||
@ -194,4 +395,6 @@ async def generate_dice_image(number: int) -> BytesIO:
|
||||
duration=frame_durations,
|
||||
format='GIF',
|
||||
loop=1)
|
||||
output.seek(0)
|
||||
# pil_final.save(output, format='PNG')
|
||||
return output
|
||||
@ -42,6 +42,24 @@ def get_random_number(min: int = 1, max: int = 6) -> int:
|
||||
import random
|
||||
return random.randint(min, max)
|
||||
|
||||
def get_random_number_string(min_value: str = "1", max_value: str = "6") -> str:
|
||||
import random
|
||||
|
||||
# 先判断二者是不是整数
|
||||
if (float(min_value).is_integer()
|
||||
and float(max_value).is_integer()
|
||||
and "." not in min_value
|
||||
and "." not in max_value):
|
||||
return str(random.randint(int(float(min_value)), int(float(max_value))))
|
||||
|
||||
# 根据传入小数的位数,决定保留几位小数
|
||||
if "." in str(min_value) or "." in str(max_value):
|
||||
decimal_places = max(len(str(min_value).split(".")[1]) if "." in str(min_value) else 0,
|
||||
len(str(max_value).split(".")[1]) if "." in str(max_value) else 0)
|
||||
return str(round(random.uniform(float(min_value), float(max_value)), decimal_places))
|
||||
|
||||
# 如果没有小数点,很可能二者都是指数表示或均为 inf,直接返回随机小数
|
||||
return str(random.uniform(float(min_value), float(max_value)))
|
||||
def roll_number(wide: bool = False) -> str:
|
||||
raw = number_arts[get_random_number()]
|
||||
if wide:
|
||||
|
||||
@ -185,9 +185,18 @@ async def _(msg: UniMsg, mEvt: Event):
|
||||
|
||||
driver = nonebot.get_driver()
|
||||
|
||||
NOTIFIED_FLAG = {
|
||||
"task_added": False,
|
||||
}
|
||||
|
||||
|
||||
@driver.on_bot_connect
|
||||
async def _():
|
||||
if NOTIFIED_FLAG["task_added"]:
|
||||
return
|
||||
|
||||
NOTIFIED_FLAG["task_added"] = True
|
||||
|
||||
await DATA_FILE_LOCK.acquire()
|
||||
tasks = []
|
||||
cfg = load_notify_config()
|
||||
|
||||
268
konabot/plugins/ytpgif/__init__.py
Normal file
268
konabot/plugins/ytpgif/__init__.py
Normal file
@ -0,0 +1,268 @@
|
||||
import os
|
||||
import tempfile
|
||||
from typing import Optional
|
||||
|
||||
from PIL import Image, ImageSequence
|
||||
from nonebot.adapters import Event as BaseEvent
|
||||
from nonebot.plugin import PluginMetadata
|
||||
from nonebot_plugin_alconna import (
|
||||
Alconna,
|
||||
Args,
|
||||
Field,
|
||||
UniMessage,
|
||||
on_alconna,
|
||||
)
|
||||
|
||||
__plugin_meta__ = PluginMetadata(
|
||||
name="ytpgif",
|
||||
description="生成来回镜像翻转的仿 YTPMV 动图。",
|
||||
usage="ytpgif [倍速=1.0] (倍速范围:0.1~20.0)",
|
||||
type="application",
|
||||
config=None,
|
||||
homepage=None,
|
||||
)
|
||||
|
||||
# 参数定义
|
||||
BASE_SEGMENT_DURATION = 0.25
|
||||
BASE_INTERVAL = 0.25
|
||||
MAX_SIZE = 256
|
||||
MIN_SPEED = 0.1
|
||||
MAX_SPEED = 20.0
|
||||
MAX_FRAMES_PER_SEGMENT = 500
|
||||
|
||||
# 提示语
|
||||
SPEED_TIPS = f"倍速必须是 {MIN_SPEED} 到 {MAX_SPEED} 之间的数字"
|
||||
|
||||
|
||||
# 定义命令 + 参数校验
|
||||
ytpgif_cmd = on_alconna(
|
||||
Alconna(
|
||||
"ytpgif",
|
||||
Args[
|
||||
"speed?",
|
||||
float,
|
||||
Field(
|
||||
default=1.0,
|
||||
unmatch_tips=lambda x: f"“{x}”不是有效数值。{SPEED_TIPS}",
|
||||
),
|
||||
],
|
||||
),
|
||||
use_cmd_start=True,
|
||||
use_cmd_sep=False,
|
||||
skip_for_unmatch=False,
|
||||
)
|
||||
|
||||
|
||||
async def get_image_url(event: BaseEvent) -> Optional[str]:
|
||||
"""从事件中提取图片 URL,支持直接消息和回复"""
|
||||
msg = event.get_message()
|
||||
for seg in msg:
|
||||
if seg.type == "image" and seg.data.get("url"):
|
||||
return str(seg.data["url"])
|
||||
|
||||
if hasattr(event, "reply") and (reply := event.reply):
|
||||
reply_msg = reply.message
|
||||
for seg in reply_msg:
|
||||
if seg.type == "image" and seg.data.get("url"):
|
||||
return str(seg.data["url"])
|
||||
return None
|
||||
|
||||
|
||||
async def download_image(url: str) -> bytes:
|
||||
import httpx
|
||||
async with httpx.AsyncClient() as client:
|
||||
resp = await client.get(url, timeout=10)
|
||||
resp.raise_for_status()
|
||||
return resp.content
|
||||
|
||||
|
||||
def resize_frame(frame: Image.Image) -> Image.Image:
|
||||
"""缩放图像,保持宽高比,不超过 MAX_SIZE"""
|
||||
w, h = frame.size
|
||||
if w <= MAX_SIZE and h <= MAX_SIZE:
|
||||
return frame
|
||||
|
||||
scale = MAX_SIZE / max(w, h)
|
||||
new_w = int(w * scale)
|
||||
new_h = int(h * scale)
|
||||
return frame.resize((new_w, new_h), Image.Resampling.LANCZOS)
|
||||
|
||||
|
||||
@ytpgif_cmd.handle()
|
||||
async def handle_ytpgif(event: BaseEvent, speed: float = 1.0):
|
||||
# === 校验 speed 范围 ===
|
||||
if not (MIN_SPEED <= speed <= MAX_SPEED):
|
||||
await ytpgif_cmd.send(
|
||||
await UniMessage.text(f"❌ {SPEED_TIPS}").export()
|
||||
)
|
||||
return
|
||||
|
||||
img_url = await get_image_url(event)
|
||||
if not img_url:
|
||||
await ytpgif_cmd.send(
|
||||
await UniMessage.text(
|
||||
"请发送一张图片或回复一张图片来生成镜像动图。"
|
||||
).export()
|
||||
)
|
||||
return
|
||||
|
||||
try:
|
||||
image_data = await download_image(img_url)
|
||||
except Exception as e:
|
||||
print(f"[YTPGIF] 下载失败: {e}")
|
||||
await ytpgif_cmd.send(
|
||||
await UniMessage.text("❌ 图片下载失败,请重试。").export()
|
||||
)
|
||||
return
|
||||
|
||||
input_path = output_path = None
|
||||
try:
|
||||
with tempfile.NamedTemporaryFile(delete=False, suffix=".gif") as tmp_in:
|
||||
tmp_in.write(image_data)
|
||||
input_path = tmp_in.name
|
||||
|
||||
with tempfile.NamedTemporaryFile(delete=False, suffix=".gif") as tmp_out:
|
||||
output_path = tmp_out.name
|
||||
|
||||
with Image.open(input_path) as src_img:
|
||||
# === 判断是否为动图 ===
|
||||
try:
|
||||
n_frames = getattr(src_img, "n_frames", 1)
|
||||
is_animated = n_frames > 1
|
||||
except Exception:
|
||||
is_animated = False
|
||||
|
||||
output_frames = []
|
||||
output_durations_ms = []
|
||||
|
||||
if is_animated:
|
||||
# === 动图模式:截取正向 + 镜像两段 ===
|
||||
frames_with_duration = []
|
||||
palette = src_img.getpalette()
|
||||
|
||||
for idx in range(n_frames):
|
||||
src_img.seek(idx)
|
||||
frame = src_img.copy()
|
||||
# 检查是否需要透明通道
|
||||
has_alpha = (
|
||||
frame.mode in ("RGBA", "LA")
|
||||
or (frame.mode == "P" and "transparency" in frame.info)
|
||||
)
|
||||
if has_alpha:
|
||||
frame = frame.convert("RGBA")
|
||||
else:
|
||||
frame = frame.convert("RGB")
|
||||
resized_frame = resize_frame(frame)
|
||||
|
||||
# 若原图有调色板,尝试保留(可选)
|
||||
if palette and resized_frame.mode == "P":
|
||||
try:
|
||||
resized_frame.putpalette(palette)
|
||||
except Exception: # noqa
|
||||
pass
|
||||
|
||||
ms = frame.info.get("duration", int(BASE_SEGMENT_DURATION * 1000))
|
||||
dur_sec = max(0.01, ms / 1000.0)
|
||||
frames_with_duration.append((resized_frame, dur_sec))
|
||||
|
||||
max_dur = BASE_SEGMENT_DURATION * speed
|
||||
accumulated = 0.0
|
||||
frame_count = 0
|
||||
|
||||
# 正向段
|
||||
for img, dur in frames_with_duration:
|
||||
if accumulated + dur > max_dur or frame_count >= MAX_FRAMES_PER_SEGMENT:
|
||||
break
|
||||
output_frames.append(img)
|
||||
output_durations_ms.append(int(dur * 1000))
|
||||
accumulated += dur
|
||||
frame_count += 1
|
||||
|
||||
if frame_count == 0:
|
||||
await ytpgif_cmd.send(
|
||||
await UniMessage.text("动图帧太短,无法生成有效片段。").export()
|
||||
)
|
||||
return
|
||||
|
||||
# 镜像段(从头开始)
|
||||
accumulated = 0.0
|
||||
frame_count = 0
|
||||
for img, dur in frames_with_duration:
|
||||
if accumulated + dur > max_dur or frame_count >= MAX_FRAMES_PER_SEGMENT:
|
||||
break
|
||||
flipped = img.transpose(Image.FLIP_LEFT_RIGHT)
|
||||
output_frames.append(flipped)
|
||||
output_durations_ms.append(int(dur * 1000))
|
||||
accumulated += dur
|
||||
frame_count += 1
|
||||
|
||||
else:
|
||||
# === 静态图模式:制作翻转动画 ===
|
||||
raw_frame = src_img.convert("RGBA")
|
||||
resized_frame = resize_frame(raw_frame)
|
||||
|
||||
interval_sec = max(0.025, min(2.5, BASE_INTERVAL / speed))
|
||||
duration_ms = int(interval_sec * 1000)
|
||||
|
||||
frame1 = resized_frame
|
||||
frame2 = resized_frame.transpose(Image.FLIP_LEFT_RIGHT)
|
||||
|
||||
output_frames = [frame1, frame2]
|
||||
output_durations_ms = [duration_ms, duration_ms]
|
||||
|
||||
if len(output_frames) < 1:
|
||||
await ytpgif_cmd.send(
|
||||
await UniMessage.text("未能生成任何帧。").export()
|
||||
)
|
||||
return
|
||||
|
||||
# === 🔐 关键修复:防止无透明图的颜色被当成透明 ===
|
||||
need_transparency = False
|
||||
for frame in output_frames:
|
||||
if frame.mode == "RGBA":
|
||||
alpha_channel = frame.getchannel("A")
|
||||
if any(pix < 255 for pix in alpha_channel.getdata()):
|
||||
need_transparency = True
|
||||
break
|
||||
elif frame.mode == "P" and "transparency" in frame.info:
|
||||
need_transparency = True
|
||||
break
|
||||
|
||||
# 如果不需要透明,则统一转为 RGB 避免调色板污染
|
||||
if not need_transparency:
|
||||
output_frames = [f.convert("RGB") for f in output_frames]
|
||||
|
||||
# 构建保存参数
|
||||
save_kwargs = {
|
||||
"save_all": True,
|
||||
"append_images": output_frames[1:],
|
||||
"format": "GIF",
|
||||
"loop": 0, # 无限循环
|
||||
"duration": output_durations_ms,
|
||||
"disposal": 2, # 清除到背景色,避免残留
|
||||
"optimize": False, # 关闭抖动(等效 -dither none)
|
||||
}
|
||||
|
||||
# 只有真正需要透明时才启用 transparency
|
||||
if need_transparency:
|
||||
save_kwargs["transparency"] = 0
|
||||
|
||||
output_frames[0].save(output_path, **save_kwargs)
|
||||
|
||||
# 发送结果
|
||||
with open(output_path, "rb") as f:
|
||||
result_image = UniMessage.image(raw=f.read())
|
||||
await ytpgif_cmd.send(await result_image.export())
|
||||
|
||||
except Exception as e:
|
||||
print(f"[YTPGIF] 处理失败: {e}")
|
||||
await ytpgif_cmd.send(
|
||||
await UniMessage.text("❌ 处理失败,可能是图片格式不支持、文件损坏或过大。").export()
|
||||
)
|
||||
finally:
|
||||
for path in filter(None, [input_path, output_path]):
|
||||
if os.path.exists(path):
|
||||
try:
|
||||
os.unlink(path)
|
||||
except: # noqa
|
||||
pass
|
||||
Reference in New Issue
Block a user