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notice_ui
| Author | SHA1 | Date | |
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| 274ca0fa9a | |||
| c72cdd6a6b | |||
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16b0451133
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cb34813c4b
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26e10be4ec
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@ -26,7 +26,7 @@ fx [滤镜名称] <参数1> <参数2> ...
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* ```fx 查找边缘```
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* ```fx 平滑```
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* ```fx 暗角 <半径=1.5>```
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* ```fx 发光 <强度=1.5> <模糊半径=15>```
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* ```fx 发光 <强度=0.5> <模糊半径=15>```
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* ```fx 噪点 <数量=0.05>```
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* ```fx 素描```
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* ```fx 阴影 <x偏移量=10> <y偏移量=10> <模糊量=10> <不透明度=0.5> <阴影颜色=black>```
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@ -50,10 +50,11 @@ fx [滤镜名称] <参数1> <参数2> ...
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* ```fx 色调 <颜色="rgb(255,0,0)">```
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* ```fx RGB分离 <偏移量=5>```
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* ```fx 叠加颜色 <颜色列表=[rgb(255,0,0)|(0,0),rgb(0,255,0)|(0,100),rgb(0,0,255)|(50,100)]> <叠加模式=overlay>```
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* ```fx 像素抖动 <最大偏移量=2>```
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### 几何变换滤镜
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* ```fx 平移 <x偏移量=10> <y偏移量=10>```
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* ```fx 缩放 <比例=1.5>```
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* ```fx 缩放 <比例(X)=1.5> <比例Y=None>```
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* ```fx 旋转 <角度=45>```
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* ```fx 透视变换 <变换矩阵>```
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* ```fx 裁剪 <左=0> <上=0> <右=100> <下=100>(百分比)```
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@ -61,9 +62,15 @@ fx [滤镜名称] <参数1> <参数2> ...
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* ```fx 波纹 <振幅=5> <波长=20>```
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* ```fx 光学补偿 <数量=100> <反转=false>```
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* ```fx 球面化 <强度=0.5>```
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* ```fx 镜像 <角度=90>```
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* ```fx 水平翻转```
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* ```fx 垂直翻转```
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* ```fx 复制 <目标位置=(100,100)> <缩放=1.0> <源区域=(0,0,100,100)>(百分比)```
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### 特殊效果滤镜
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* ```fx 色键 <目标颜色="rgb(255,0,0)"> <容差=60>```
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* ```fx 晃动 <最大偏移量=5> <运动模糊=False>```
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* ```fx 动图 <帧率=10>```
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## 颜色名称支持
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- **基本颜色**:红、绿、蓝、黄、紫、黑、白、橙、粉、灰、青、靛、棕
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@ -9,7 +9,7 @@ John: 11-28 16:50:37
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谁来总结一下今天的工作?
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Jack: 11-28 16:50:55
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[引用John的消息] tqszm
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[引用John的消息] @此方Bot tqszm
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此方Bot: 11-28 16:50:56
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slzjyxjtdgz?
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@ -18,7 +18,7 @@ slzjyxjtdgz?
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或者,你也可以直接以正常指令的方式调用:
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```
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提取首字母 中山大学
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@此方Bot 提取首字母 中山大学
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> zsdx
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```
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@ -19,6 +19,7 @@ from PIL import Image, ImageSequence
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@dataclass
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class FilterItem:
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name: str
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filter: callable
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args: list
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@ -55,7 +56,7 @@ def prase_input_args(input_str: str) -> list[FilterItem]:
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except Exception:
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converted_value = arg_value
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func_args.append(converted_value)
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args.append(FilterItem(filter=filter_func, args=func_args))
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args.append(FilterItem(name=filter_name,filter=filter_func, args=func_args))
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return args
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def apply_filters_to_image(img: Image, filters: list[FilterItem]) -> Image:
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@ -66,16 +67,39 @@ def apply_filters_to_image(img: Image, filters: list[FilterItem]) -> Image:
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return img
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async def apply_filters_to_bytes(image_bytes: bytes, filters: list[FilterItem]) -> BytesIO:
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# 检测是否需要将静态图视作动图处理
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frozen_to_move = any(
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filter_item.name == "动图"
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for filter_item in filters
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)
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static_fps = 10
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# 找到动图参数 fps
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if frozen_to_move:
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for filter_item in filters:
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if filter_item.name == "动图" and filter_item.args:
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try:
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static_fps = int(filter_item.args[0])
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except Exception:
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static_fps = 10
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break
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# 如果 image 是动图,则逐帧处理
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img = Image.open(BytesIO(image_bytes))
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logger.debug("开始图像处理")
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output = BytesIO()
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if getattr(img, "is_animated", False):
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if getattr(img, "is_animated", False) or frozen_to_move:
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frames = []
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all_frames = []
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for frame in ImageSequence.Iterator(img):
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frame_copy = frame.copy()
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all_frames.append(frame_copy)
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if getattr(img, "is_animated", False):
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logger.debug("处理动图帧")
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for frame in ImageSequence.Iterator(img):
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frame_copy = frame.copy()
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all_frames.append(frame_copy)
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else:
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# 将静态图视作单帧动图处理,拷贝多份
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logger.debug("处理静态图为多帧动图")
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for _ in range(10): # 默认复制10帧
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all_frames.append(img.copy())
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img.info['duration'] = int(1000 / static_fps)
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async def process_single_frame(frame: Image.Image, frame_idx: int) -> Image.Image:
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"""处理单帧的异步函数"""
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@ -117,7 +141,6 @@ async def apply_filters_to_bytes(image_bytes: bytes, filters: list[FilterItem])
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output.seek(0)
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return output
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def is_fx_mentioned(evt: BaseEvent, msg: UniMsg) -> bool:
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txt = msg.extract_plain_text()
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if "fx" not in txt[:3].lower():
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@ -1,3 +1,4 @@
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import random
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from PIL import Image, ImageFilter
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from PIL import ImageEnhance
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from PIL import ImageChops
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@ -137,9 +138,22 @@ class ImageFilterImplement:
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# 缩放
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@staticmethod
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def apply_resize(image: Image.Image, scale: float = 1.5) -> Image.Image:
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if scale <= 0:
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scale = 1.0
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def apply_resize(image: Image.Image, scale: float = 1.5, scale_y = None) -> Image.Image:
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# scale 可以为负
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# 如果 scale 为负,则代表翻转
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if scale_y is not None:
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if float(scale_y) < 0:
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image = ImageOps.flip(image)
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scale_y = abs(float(scale_y))
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if scale < 0:
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image = ImageOps.mirror(image)
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scale = abs(scale)
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new_size = (int(image.width * scale), int(image.height * float(scale_y)))
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return image.resize(new_size, Image.Resampling.LANCZOS)
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if scale < 0:
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image = ImageOps.mirror(image)
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image = ImageOps.flip(image)
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scale = abs(scale)
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new_size = (int(image.width * scale), int(image.height * scale))
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return image.resize(new_size, Image.Resampling.LANCZOS)
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@ -224,7 +238,7 @@ class ImageFilterImplement:
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# 发光
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@staticmethod
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def apply_glow(image: Image.Image, intensity: float = 1.5, blur_radius: float = 15) -> Image.Image:
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def apply_glow(image: Image.Image, intensity: float = 0.5, blur_radius: float = 15) -> Image.Image:
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if image.mode != 'RGBA':
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image = image.convert('RGBA')
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# 创建发光图层
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@ -423,6 +437,8 @@ class ImageFilterImplement:
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# 裁剪
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@staticmethod
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def apply_crop(image: Image.Image, left: float = 0, upper: float = 0, right: float = 100, lower: float = 100) -> Image.Image:
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if image.mode != 'RGBA':
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image = image.convert('RGBA')
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# 按百分比裁剪
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width, height = image.size
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left_px = int(width * left / 100)
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@ -451,9 +467,10 @@ class ImageFilterImplement:
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arr = np.array(image)
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noise = np.random.randint(0, 256, arr.shape, dtype=np.uint8)
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# 为每个像素创建掩码,然后扩展到所有通道
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# 为每个像素创建掩码,然后扩展到所有通道,除了 alpha 通道
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mask = np.random.rand(*arr.shape[:2]) < amount
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mask_3d = mask[:, :, np.newaxis] # 添加第三个维度
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mask_3d = np.repeat(mask[:, :, np.newaxis], 4, axis=2)
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mask_3d[:, :, 3] = False # 保持 alpha 通道不变
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# 混合噪点
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result = np.where(mask_3d, noise, arr)
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@ -545,8 +562,8 @@ class ImageFilterImplement:
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def apply_shadow(image: Image.Image,
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x_offset: int = 10,
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y_offset: int = 10,
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blur = 10,
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opacity = 0.5,
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blur: float = 10,
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opacity: float = 0.5,
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shadow_color = "black") -> Image.Image:
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if image.mode != 'RGBA':
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image = image.convert('RGBA')
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@ -887,4 +904,184 @@ class ImageFilterImplement:
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result[:, :, c] = arr[:, :, c] * (1 - distance) + blurred_arr[:, :, c] * distance
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return Image.fromarray(np.clip(result, 0, 255).astype(np.uint8), 'RGBA')
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# 复制画面
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@staticmethod
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def copy_area(image: Image.Image,
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dst_move: str = '(100,100)',
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scale: float = 1.0,
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src_area: str = '(0,0,100,100)') -> Image.Image:
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if image.mode != 'RGBA':
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image = image.convert('RGBA')
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result = image.copy()
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# 参数表示的是百分比
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width, height = image.size
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# 首先裁剪出源区域
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src_tuple = eval(src_area)
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src_area = ImageFilterImplement.apply_crop(image, src_tuple[0], src_tuple[1], src_tuple[2], src_tuple[3])
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# 计算目标位置
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dst_tuple = eval(dst_move)
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dst_x = int(width * dst_tuple[0] / 100)
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dst_y = int(height * dst_tuple[1] / 100)
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# 缩放源区域
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if scale != 1.0:
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new_width = int(src_area.width * scale)
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new_height = int(src_area.height * scale)
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src_area = src_area.resize((new_width, new_height), Image.Resampling.LANCZOS)
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# 粘贴到目标位置
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result.paste(src_area, (dst_x, dst_y), src_area)
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return result
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# 水平翻转
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@staticmethod
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def apply_flip_horizontal(image: Image.Image) -> Image.Image:
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return image.transpose(Image.Transpose.FLIP_LEFT_RIGHT)
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# 垂直翻转
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@staticmethod
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def apply_flip_vertical(image: Image.Image) -> Image.Image:
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return image.transpose(Image.Transpose.FLIP_TOP_BOTTOM)
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# 依方向镜像一半画面
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@staticmethod
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def apply_mirror_half(image: Image.Image, angle: float = 90) -> Image.Image:
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if image.mode != 'RGBA':
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image = image.convert('RGBA')
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width, height = image.size
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arr = np.array(image, dtype=np.uint8)
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# 角度标准化
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angle = angle % 360
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# 计算折痕的斜率
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# 注意:我们的角度是折痕与水平线的夹角
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# 0° = 垂直线,90° = 水平线
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rad = math.radians(angle)
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# 计算中心点
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center_x = width / 2
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center_y = height / 2
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# 创建坐标网格
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y_coords, x_coords = np.mgrid[0:height, 0:width]
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# 计算折痕的方向向量
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# 折痕方向垂直于法向量
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# 对于角度θ,折痕方向向量为(cosθ, sinθ)
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direction_x = math.cos(rad)
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direction_y = math.sin(rad)
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# 计算法向量(垂直于折痕)
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# 旋转90度:(-sinθ, cosθ)
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normal_x = -direction_y
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normal_y = direction_x
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# 计算每个像素相对于折痕的位置
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# 点到直线的有向距离: (x-cx)*nx + (y-cy)*ny
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rel_x = x_coords - center_x
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rel_y = y_coords - center_y
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signed_distance = rel_x * normal_x + rel_y * normal_y
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source_mask = signed_distance >= 0
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# 创建结果图像
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result = arr.copy()
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# 获取镜像侧的像素(需要被替换的像素)
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mirror_mask = ~source_mask
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if mirror_mask.any():
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# 对于镜像侧的每个像素,计算其关于折痕的镜像点
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mirror_x = x_coords[mirror_mask]
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mirror_y = y_coords[mirror_mask]
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# 计算相对坐标
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mirror_rel_x = mirror_x - center_x
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mirror_rel_y = mirror_y - center_y
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# 计算到折痕的距离(带符号)
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dist_to_line = signed_distance[mirror_mask]
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# 计算镜像点的相对坐标
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# 镜像公式: p' = p - 2 * (p·n) * n
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# 其中p是相对中心点的向量,n是单位法向量
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mirror_target_rel_x = mirror_rel_x - 2 * dist_to_line * normal_x
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mirror_target_rel_y = mirror_rel_y - 2 * dist_to_line * normal_y
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# 计算镜像点的绝对坐标
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target_x = np.round(center_x + mirror_target_rel_x).astype(int)
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target_y = np.round(center_y + mirror_target_rel_y).astype(int)
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# 确保坐标在图像范围内
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valid = (target_x >= 0) & (target_x < width) & (target_y >= 0) & (target_y < height)
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if valid.any():
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# 将源侧的像素复制到镜像侧的位置
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valid_target_x = target_x[valid]
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valid_target_y = target_y[valid]
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valid_mirror_x = mirror_x[valid]
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valid_mirror_y = mirror_y[valid]
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# 获取源侧的像素值
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source_pixels = arr[valid_target_y, valid_target_x]
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# 复制到镜像位置
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result[valid_mirror_y, valid_mirror_x] = source_pixels
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return Image.fromarray(result, 'RGBA')
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# 随机画面整体晃动,对于动图会很有效
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@staticmethod
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def apply_random_wiggle(image: Image.Image, max_offset: int = 5, motion_blur = False) -> Image.Image:
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if image.mode != 'RGBA':
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image = image.convert('RGBA')
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width, height = image.size
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arr = np.array(image)
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# 生成随机偏移
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x_offset = random.randint(-max_offset, max_offset)
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y_offset = random.randint(-max_offset, max_offset)
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# 画面平移
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translated_image = ImageFilterImplement.apply_translate(image, x_offset, y_offset)
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if motion_blur:
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# 添加运动模糊
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translated_image = ImageFilterImplement.apply_directional_blur(translated_image,
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angle=random.uniform(0, 360),
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distance=max_offset,
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samples=6)
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return translated_image
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||||
# 像素随机抖动
|
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@staticmethod
|
||||
def apply_pixel_jitter(image: Image.Image, max_offset: int = 2) -> Image.Image:
|
||||
if image.mode != 'RGBA':
|
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image = image.convert('RGBA')
|
||||
|
||||
width, height = image.size
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||||
arr = np.array(image)
|
||||
|
||||
# 创建结果图像
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||||
result = np.zeros_like(arr)
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||||
|
||||
# numpy 向量化随机偏移
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x_indices = np.arange(width)
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y_indices = np.arange(height)
|
||||
x_grid, y_grid = np.meshgrid(x_indices, y_indices)
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||||
x_offsets = np.random.randint(-max_offset, max_offset + 1, size=(height, width))
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y_offsets = np.random.randint(-max_offset, max_offset + 1, size=(height, width))
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new_x = np.clip(x_grid + x_offsets, 0, width - 1)
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||||
new_y = np.clip(y_grid + y_offsets, 0, height - 1)
|
||||
result[y_grid, x_grid] = arr[new_y, new_x]
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||||
|
||||
return Image.fromarray(result, 'RGBA')
|
||||
|
||||
class ImageFilterEmpty:
|
||||
# 空滤镜,不做任何处理,形式化参数用
|
||||
@staticmethod
|
||||
def empty_filter(image):
|
||||
return image
|
||||
|
||||
@staticmethod
|
||||
def empty_filter_param(image, param = 10):
|
||||
return image
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
from typing import Optional
|
||||
from konabot.plugins.fx_process.fx_handle import ImageFilterImplement
|
||||
from konabot.plugins.fx_process.fx_handle import ImageFilterEmpty, ImageFilterImplement
|
||||
|
||||
class ImageFilterManager:
|
||||
filter_map = {
|
||||
@ -40,6 +40,13 @@ class ImageFilterManager:
|
||||
"方向模糊": ImageFilterImplement.apply_directional_blur,
|
||||
"边缘模糊": ImageFilterImplement.apply_focus_blur,
|
||||
"缩放模糊": ImageFilterImplement.apply_zoom_blur,
|
||||
"镜像": ImageFilterImplement.apply_mirror_half,
|
||||
"水平翻转": ImageFilterImplement.apply_flip_horizontal,
|
||||
"垂直翻转": ImageFilterImplement.apply_flip_vertical,
|
||||
"复制": ImageFilterImplement.copy_area,
|
||||
"晃动": ImageFilterImplement.apply_random_wiggle,
|
||||
"动图": ImageFilterEmpty.empty_filter_param,
|
||||
"像素抖动": ImageFilterImplement.apply_pixel_jitter,
|
||||
}
|
||||
|
||||
@classmethod
|
||||
@ -48,4 +55,6 @@ class ImageFilterManager:
|
||||
|
||||
@classmethod
|
||||
def has_filter(cls, name: str) -> bool:
|
||||
return name in cls.filter_map
|
||||
return name in cls.filter_map
|
||||
|
||||
|
||||
@ -6,24 +6,11 @@ import PIL
|
||||
import PIL.Image
|
||||
import cv2
|
||||
import imageio.v3 as iio
|
||||
from nonebot import on_message
|
||||
from nonebot.adapters import Bot
|
||||
from nonebot_plugin_alconna import Alconna, Args, Image, Option, UniMessage, on_alconna
|
||||
import numpy
|
||||
|
||||
from konabot.common.nb.exc import BotExceptionMessage
|
||||
from konabot.common.nb.extract_image import DepImageBytes, DepPILImage
|
||||
from konabot.common.nb.match_keyword import match_keyword
|
||||
from konabot.common.nb.reply_image import reply_image
|
||||
|
||||
# 保持不变
|
||||
cmd_black_white = on_message(rule=match_keyword("黑白"))
|
||||
|
||||
|
||||
@cmd_black_white.handle()
|
||||
async def _(img: DepPILImage, bot: Bot):
|
||||
# 保持不变
|
||||
await reply_image(cmd_black_white, bot, img.convert("LA"))
|
||||
from konabot.common.nb.extract_image import DepImageBytes
|
||||
|
||||
|
||||
# 保持不变
|
||||
|
||||
26
konabot/plugins/notice_ui/__init__.py
Normal file
26
konabot/plugins/notice_ui/__init__.py
Normal file
@ -0,0 +1,26 @@
|
||||
from loguru import logger
|
||||
import nonebot
|
||||
from nonebot.adapters import Event as BaseEvent
|
||||
from nonebot.adapters.discord.event import MessageEvent as DiscordMessageEvent
|
||||
from nonebot_plugin_alconna import (
|
||||
UniMessage,
|
||||
UniMsg
|
||||
)
|
||||
from konabot.plugins.notice_ui.notice import NoticeUI
|
||||
from nonebot_plugin_alconna import on_alconna, Alconna, Args
|
||||
|
||||
evt = on_alconna(Alconna(
|
||||
"notice",
|
||||
Args["title", str],
|
||||
Args["message", str]
|
||||
),
|
||||
use_cmd_start=True, use_cmd_sep=False, skip_for_unmatch=True
|
||||
)
|
||||
|
||||
@evt.handle()
|
||||
async def _(title: str, message: str, msg: UniMsg, event: BaseEvent):
|
||||
logger.debug(f"Received notice command with title: {title}, message: {message}")
|
||||
|
||||
out = await NoticeUI.render_notice(title, message)
|
||||
|
||||
await evt.send(await UniMessage().image(raw=out).export())
|
||||
53
konabot/plugins/notice_ui/notice.py
Normal file
53
konabot/plugins/notice_ui/notice.py
Normal file
@ -0,0 +1,53 @@
|
||||
from io import BytesIO
|
||||
from PIL import Image
|
||||
from konabot.common.web_render import konaweb
|
||||
from konabot.common.web_render.core import WebRenderer
|
||||
|
||||
from playwright.async_api import Page
|
||||
|
||||
class NoticeUI:
|
||||
@staticmethod
|
||||
async def render_notice(title: str, message: str) -> bytes:
|
||||
"""
|
||||
渲染一个通知图片,包含标题和消息内容。
|
||||
"""
|
||||
async def page_function(page: Page):
|
||||
# 直到 setMaskMode 函数加载完成
|
||||
await page.wait_for_function("typeof setMaskMode === 'function'", timeout=1000)
|
||||
await page.evaluate('setMaskMode(false)')
|
||||
# 直到 setContent 函数加载完成
|
||||
await page.wait_for_function("typeof setContent === 'function'", timeout=1000)
|
||||
# 设置标题和消息内容
|
||||
await page.evaluate(f'setContent("{title}", "{message}")')
|
||||
|
||||
async def mask_function(page: Page):
|
||||
# 直到 setContent 函数加载完成
|
||||
await page.wait_for_function("typeof setContent === 'function'", timeout=1000)
|
||||
# 设置标题和消息内容
|
||||
await page.evaluate(f'setContent("{title}", "{message}")')
|
||||
# 直到 setMaskMode 函数加载完成
|
||||
await page.wait_for_function("typeof setMaskMode === 'function'", timeout=1000)
|
||||
await page.evaluate('setMaskMode(true)')
|
||||
|
||||
image_bytes = await WebRenderer.render_with_persistent_page(
|
||||
"notice_renderer",
|
||||
konaweb('notice'),
|
||||
target='#main',
|
||||
other_function=page_function,
|
||||
)
|
||||
|
||||
mask_bytes = await WebRenderer.render_with_persistent_page(
|
||||
"notice_renderer",
|
||||
konaweb('notice'),
|
||||
target='#main',
|
||||
other_function=mask_function)
|
||||
|
||||
image = Image.open(BytesIO(image_bytes)).convert("RGBA")
|
||||
mask = Image.open(BytesIO(mask_bytes)).convert("L")
|
||||
# 应用遮罩
|
||||
image.putalpha(mask)
|
||||
|
||||
output_buffer = BytesIO()
|
||||
image.save(output_buffer, format="GIF", disposal=2, loop=0)
|
||||
output_buffer.seek(0)
|
||||
return output_buffer.getvalue()
|
||||
@ -6,6 +6,7 @@ from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
import nanoid
|
||||
from konabot.plugins.notice_ui.notice import NoticeUI
|
||||
import nonebot
|
||||
from loguru import logger
|
||||
from nonebot import get_plugin_config, on_message
|
||||
@ -107,6 +108,10 @@ async def _(task: LongTask):
|
||||
await task.target.send_message(
|
||||
UniMessage().text(f"代办提醒:{message}")
|
||||
)
|
||||
notice_bytes = NoticeUI.render_notice("代办提醒", message)
|
||||
await task.target.send_message(
|
||||
await UniMessage().image(raw=notice_bytes).export()
|
||||
)
|
||||
async with DATA_FILE_LOCK:
|
||||
data = load_notify_config()
|
||||
if (chan := data.notify_channels.get(task.target.target_id)) is not None:
|
||||
|
||||
Reference in New Issue
Block a user