├── .gitignore
├── .idea
├── EasyUse_FastApi.iml
├── deployment.xml
├── misc.xml
├── modules.xml
└── vcs.xml
├── LICENSE
├── README.md
├── Text-CNN-client.py
├── Text-CNN-server.py
├── checkpoints
└── textcnn
│ ├── 99
│ ├── best_validation.data-00000-of-00001
│ ├── best_validation.index
│ ├── best_validation.meta
│ └── checkpoint
│ ├── best_validation.data-00000-of-00001
│ ├── best_validation.index
│ ├── best_validation.meta
│ └── checkpoint
├── data
├── 1-1.txt
├── 5-1.txt
├── data
│ ├── bk
│ │ ├── test.txt
│ │ ├── train.txt
│ │ └── train_all.txt
│ ├── neg_all.txt
│ ├── pos_all.txt
│ ├── process.py
│ ├── test.txt
│ ├── train.txt
│ ├── val.txt
│ └── vocab.txt
└── processing.py
├── model
├── cnn_model.py
├── data_loader.py
└── data_processing.py
├── pic
├── api.png
├── backend.png
└── inference.png
└── requirement.txt
/.gitignore:
--------------------------------------------------------------------------------
1 | # Byte-compiled / optimized / DLL files
2 | __pycache__/
3 | *.py[cod]
4 | *$py.class
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27 | *.egg
28 | MANIFEST
29 |
30 | # PyInstaller
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35 |
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80 | # IPython
81 | profile_default/
82 | ipython_config.py
83 |
84 | # pyenv
85 | .python-version
86 |
87 | # pipenv
88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies
90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not
91 | # install all needed dependencies.
92 | #Pipfile.lock
93 |
94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow
95 | __pypackages__/
96 |
97 | # Celery stuff
98 | celerybeat-schedule
99 | celerybeat.pid
100 |
101 | # SageMath parsed files
102 | *.sage.py
103 |
104 | # Environments
105 | .env
106 | .venv
107 | env/
108 | venv/
109 | ENV/
110 | env.bak/
111 | venv.bak/
112 |
113 | # Spyder project settings
114 | .spyderproject
115 | .spyproject
116 |
117 | # Rope project settings
118 | .ropeproject
119 |
120 | # mkdocs documentation
121 | /site
122 |
123 | # mypy
124 | .mypy_cache/
125 | .dmypy.json
126 | dmypy.json
127 |
128 | # Pyre type checker
129 | .pyre/
130 |
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/LICENSE:
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/README.md:
--------------------------------------------------------------------------------
1 | [](https://996.icu)
2 |
3 |
4 | # EasyUse_FastApi
5 | #### 快速使用FastAPI部署机器学习模型,使用全局定义和全局加载模型,提升inference速度。在初始化的时候(第一次推理的时候速度较慢,在第二次使用则恢复正常,在10ms左右)
6 | #### 利用FastApi搭配uvicorn自带的异步的方式进行数据的推理,比Flask+gunicorn更加方便和快一些
7 |
8 | ##### 启动服务 uvicorn Text-CNN-server:app --reload ,开启热启动模式
9 | ##### 启动服务 uvicorn Text-CNN-server:app --port=5000 --workers=4,开启生产模式, 注意: Sanic(FastAPI) 的性能的确很棒,当时技术验证时,测试的时候,不同业务逻辑下,基本都能保证其性能在 Flask 的 1.5 倍以上。但是就目前的使用经验来说 Sanic((FastAPI))距离真正生产可用,还有相当长一段路要走。无论是内部的架构,还是周边的生态,亦或者是其他。大家可以没事拿来玩玩,但是如果要上生产线,请做好被坑的准备
10 |
11 | > backend
12 |
13 |
14 |
15 | > frontend
16 |
17 |
18 |
19 |
20 | > inference
21 |
22 |
23 |
--------------------------------------------------------------------------------
/Text-CNN-client.py:
--------------------------------------------------------------------------------
1 | import requests
2 | import time
3 | import json
4 | # 使用注意,在初始化的时候(第一次使用的时候速度较慢,在第二次使用则恢复正常,在10ms左右)
5 | if __name__ == '__main__':
6 | st = time.clock()
7 | content = '这家酒店真垃圾'
8 | api_url = "http://127.0.0.1:5000/sentiment_analysis_api/{}".format(content)
9 | model_result = requests.get(api_url).json()
10 | print(model_result)
11 | print('time used:{}'.format(time.clock() - st))
--------------------------------------------------------------------------------
/Text-CNN-server.py:
--------------------------------------------------------------------------------
1 | import os
2 | import tensorflow as tf
3 | import numpy as np
4 | import tensorflow.contrib.keras as kr
5 | from model.cnn_model import TCNNConfig, TextCNN
6 | from model.data_processing import read_category, read_vocab
7 | from fastapi import FastAPI
8 | app = FastAPI()
9 | def global_():
10 | # 全局定义和全局加载模型,提升inference速度
11 | global base_dir, vocab_dir, save_dir, save_path, graph, model
12 | base_dir = 'data/data'
13 | vocab_dir = os.path.join(base_dir, 'vocab.txt')
14 | save_dir = 'checkpoints/textcnn'
15 | save_path = os.path.join(save_dir, 'best_validation')
16 | graph = tf.get_default_graph()
17 | model = CnnModel()
18 | class CnnModel:
19 | def __init__(self):
20 | self.config = TCNNConfig()
21 | self.categories, self.cat_to_id = read_category()
22 | self.words, self.word_to_id = read_vocab(vocab_dir)
23 | self.config.vocab_size = len(self.words)
24 | self.model = TextCNN(self.config)
25 | self.session = tf.Session()
26 | self.session.run(tf.global_variables_initializer())
27 | saver = tf.train.Saver()
28 | saver.restore(sess=self.session, save_path=save_path)
29 | def emotion_score(self, message):
30 | data = [self.word_to_id[x] for x in message if x in self.word_to_id]
31 | feed_dict = {
32 | self.model.input_x: kr.preprocessing.sequence.pad_sequences([data], self.config.seq_length),
33 | self.model.keep_prob: 1.0}
34 | # 类别概率的输出
35 | predictions = self.session.run(self.model.softmax_tensor1, feed_dict=feed_dict)
36 | return np.squeeze(predictions)[1]
37 | global_()
38 | @app.get("/sentiment_analysis_api/{content}")
39 | async def predict(content: str):
40 | with graph.as_default():
41 | sa = model.emotion_score(content)
42 | return {"comment": content, "sa": ("%.5f" % sa)}
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/checkpoints/textcnn/99/best_validation.data-00000-of-00001:
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https://raw.githubusercontent.com/CarryChang/EasyUse_FastApi/HEAD/checkpoints/textcnn/99/best_validation.data-00000-of-00001
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/checkpoints/textcnn/99/best_validation.index:
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https://raw.githubusercontent.com/CarryChang/EasyUse_FastApi/HEAD/checkpoints/textcnn/99/best_validation.index
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/checkpoints/textcnn/99/best_validation.meta:
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https://raw.githubusercontent.com/CarryChang/EasyUse_FastApi/HEAD/checkpoints/textcnn/99/best_validation.meta
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/checkpoints/textcnn/99/checkpoint:
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1 | model_checkpoint_path: "best_validation"
2 | all_model_checkpoint_paths: "best_validation"
3 |
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/checkpoints/textcnn/best_validation.data-00000-of-00001:
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/checkpoints/textcnn/best_validation.index:
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https://raw.githubusercontent.com/CarryChang/EasyUse_FastApi/HEAD/checkpoints/textcnn/best_validation.index
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/checkpoints/textcnn/best_validation.meta:
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https://raw.githubusercontent.com/CarryChang/EasyUse_FastApi/HEAD/checkpoints/textcnn/best_validation.meta
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/checkpoints/textcnn/checkpoint:
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1 | model_checkpoint_path: "best_validation"
2 | all_model_checkpoint_paths: "best_validation"
3 |
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/data/data/process.py:
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1 | #!/user/bin/env python3
2 | # -*- coding: utf-8 -*-
3 | # @Time : 2020/2/13 0013 20:08
4 | # @Author : CarryChang
5 | # @Software: PyCharm
6 | # @email: coolcahng@gmail.com
7 | # @web :CarryChang.top
8 | path_list = ['neg_all.txt', 'pos_all.txt']
9 | train_all = open('train_all.txt', 'w', encoding='utf-8')
10 | for path in path_list:
11 | if 'pos' in path:
12 | with open(path, 'r', encoding='utf-8') as file:
13 | for content in file:
14 | train_all.write('5'+'\t'+content.strip() + '\n')
15 | else:
16 | with open(path, 'r', encoding='utf-8') as file:
17 | for content in file:
18 | train_all.write('1' + '\t' + content.strip() + '\n')
19 | train_all.close()
20 |
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/data/data/vocab.txt:
--------------------------------------------------------------------------------
1 |
2 | ,
3 | 的
4 | 不
5 | 。
6 | 是
7 | 了
8 | 有
9 | 很
10 | 我
11 | 好
12 | 一
13 | 房
14 | 间
15 | 这
16 | 还
17 | !
18 | ,
19 | 个
20 | 店
21 | 人
22 | 没
23 | 就
24 | 也
25 | 在
26 | 服
27 | 酒
28 | 到
29 | 上
30 | 务
31 | 来
32 | 大
33 |
34 | .
35 | 都
36 | 住
37 | 说
38 | 要
39 | 以
40 | 点
41 | 0
42 | 差
43 | 小
44 | 时
45 | 价
46 | 看
47 | 可
48 | 比
49 | 们
50 | 本
51 | 错
52 | 生
53 | 后
54 | 下
55 | 1
56 | 多
57 | 能
58 | 去
59 | 过
60 | 2
61 | 书
62 | 么
63 | 得
64 | 位
65 | 感
66 | 前
67 | 用
68 | 会
69 | 次
70 | 觉
71 | 太
72 | 和
73 | 天
74 | 家
75 | 置
76 | 为
77 | 子
78 | 地
79 | 但
80 | 里
81 | 方
82 | 对
83 | 电
84 | 出
85 | 、
86 | 中
87 | 面
88 | 给
89 | 然
90 | 常
91 | 他
92 | 实
93 | 便
94 | 那
95 | 台
96 | 高
97 | 真
98 | 样
99 | 非
100 | 卫
101 | 开
102 | 较
103 | 度
104 | 自
105 | 心
106 | 入
107 | 道
108 | 理
109 | 只
110 | 格
111 | 想
112 | 性
113 | 最
114 | 而
115 | 情
116 | 所
117 | 干
118 | 音
119 | 意
120 | 热
121 | 如
122 | 果
123 | 3
124 | 打
125 | 客
126 | 净
127 | 话
128 | 水
129 | 早
130 | 当
131 | 发
132 | 员
133 | 床
134 | 别
135 | 行
136 | 知
137 | 定
138 | 餐
139 | 环
140 | 现
141 | 8
142 | 老
143 | 晚
144 | 你
145 | 装
146 | 外
147 | 机
148 | 其
149 | 设
150 | 问
151 | 境
152 | 什
153 | 着
154 | 之
155 | 于
156 | 让
157 | 作
158 | 分
159 | :
160 | 再
161 | 经
162 | 5
163 | 通
164 | 第
165 | 无
166 | 4
167 | 门
168 | 买
169 | 重
170 | 隔
171 | 评
172 | 些
173 | 事
174 | 车
175 | 特
176 | 且
177 | 楼
178 | 因
179 | 年
180 | 星
181 | 态
182 | 才
183 | 全
184 | ?
185 | 算
186 | 网
187 | 起
188 | 总
189 | 内
190 | 己
191 | 费
192 | 单
193 | 接
194 | 找
195 | 程
196 | 直
197 | 美
198 | 施
199 | 两
200 | 日
201 | 几
202 | 又
203 | 动
204 | 级
205 | 喜
206 | 提
207 | 种
208 | 候
209 | 近
210 | 完
211 | 体
212 | 结
213 | 进
214 | 板
215 | 明
216 | 欢
217 | 解
218 | 订
219 | 同
220 | 馆
221 | 6
222 | 东
223 | 更
224 | 月
225 | 宾
226 | 被
227 | 空
228 | 读
229 | 换
230 | 回
231 | 满
232 | 题
233 | 味
234 | 二
235 | 做
236 | !
237 | 安
238 | 系
239 | 三
240 | 离
241 | 调
242 | 相
243 | 般
244 | 交
245 | 已
246 | 从
247 | 气
248 | 吃
249 | 手
250 | 9
251 | 值
252 | 送
253 | …
254 | 像
255 | 该
256 | 望
257 | 整
258 | 推
259 | 超
260 | 工
261 | 携
262 | 成
263 | 应
264 | 放
265 | 洗
266 | 正
267 | 她
268 | 7
269 | 合
270 | 边
271 | 西
272 | 品
273 | 等
274 | 您
275 | 头
276 | 退
277 | 新
278 | 钱
279 | 走
280 | )
281 | 国
282 | 收
283 | 者
284 | 快
285 | ~
286 | 友
287 | 把
288 | 口
289 | 吧
290 | 带
291 | i
292 | 关
293 | 法
294 | 舒
295 | ;
296 | (
297 | 少
298 | 学
299 | 元
300 | 标
301 | “
302 | 此
303 | 孩
304 | 爱
305 | 修
306 | 卡
307 | 怎
308 | ”
309 | 窗
310 | 挺
311 | 荐
312 | 半
313 | 盘
314 | 加
315 | 景
316 | 反
317 | 睡
318 | 选
319 | 华
320 | 声
321 | 受
322 | 见
323 | 女
324 | 啊
325 | 路
326 | 风
327 | 文
328 | 容
329 | 旧
330 | 每
331 | 难
332 | 朋
333 | 件
334 | 公
335 | 主
336 | 预
337 | 部
338 | 统
339 | 长
340 | 量
341 | 强
342 | 适
343 | 原
344 | 信
345 | 物
346 | 儿
347 | e
348 | 待
349 | 连
350 | 清
351 | 场
352 | 字
353 | 象
354 | 简
355 | 处
356 | 先
357 | 写
358 | 质
359 | 色
360 | 视
361 | 周
362 | 与
363 | 观
364 | 虽
365 | *
366 | t
367 | 建
368 | 商
369 | 配
370 | 十
371 | 光
372 | 确
373 | 四
374 | 身
375 | 户
376 | 显
377 | 拿
378 | 站
379 | 议
380 | 贵
381 | 准
382 | 套
383 | 钟
384 | 并
385 | 居
386 | 温
387 | P
388 | 力
389 | 优
390 | 旅
391 | 海
392 | 浴
393 | 求
394 | 谢
395 | 硬
396 | a
397 | 平
398 | 跟
399 | 够
400 | 听
401 | 游
402 | 记
403 | 亮
404 | 市
405 | 利
406 | 改
407 | 办
408 | -
409 | 图
410 | 告
411 | 饭
412 | 包
413 | o
414 | 择
415 | 认
416 | 团
417 | 需
418 | 免
419 | s
420 | 活
421 | 希
422 | 键
423 | 马
424 | 根
425 | 呵
426 | 宽
427 | 货
428 | 惠
429 | 脏
430 | 夜
431 | 庆
432 | 论
433 | 竟
434 | 号
435 | 期
436 | 区
437 | 赞
438 | 冷
439 | 屏
440 | 管
441 | 失
442 | 另
443 | 及
444 | 吵
445 | 却
446 | 何
447 | 厅
448 | 哈
449 | 器
450 | 使
451 | 坏
452 | 片
453 | 五
454 | 故
455 | n
456 | 它
457 | 始
458 | 速
459 | 极
460 | 语
461 | 由
462 | 帮
463 | 金
464 | 刚
465 | 驱
466 | 张
467 | 充
468 | 足
469 | 各
470 | 远
471 | 花
472 | 业
473 | 白
474 | I
475 | c
476 | 备
477 | 将
478 | 续
479 | 宝
480 | 洁
481 | 深
482 | 停
483 | 表
484 | 叫
485 | 姐
486 | 计
487 | 效
488 | 条
489 | 呢
490 | 思
491 | 补
492 | 宜
493 | 保
494 | 玩
495 | 层
496 | 式
497 | 节
498 | 至
499 | S
500 | 名
501 | 线
502 | 存
503 | 诉
504 | 细
505 | 棒
506 | 基
507 | 划
508 | 讲
509 | 购
510 | 江
511 | 》
512 | 《
513 | 街
514 | 死
515 | h
516 | 散
517 | 消
518 | 或
519 | 影
520 | X
521 | 流
522 | ?
523 | 慢
524 | 排
525 | D
526 | p
527 | 任
528 | 静
529 | 响
530 | A
531 | 供
532 | T
533 | 识
534 | 步
535 | 示
536 | 京
537 | 考
538 | 毛
539 | 向
540 | 绝
541 | r
542 | 漂
543 | 决
544 | 代
545 | 块
546 | 黑
547 | 火
548 | 易
549 | 哪
550 | 版
551 | 午
552 | 山
553 | 轻
554 | 除
555 | 言
556 | 许
557 | 豪
558 | 吗
559 | 运
560 | 烦
561 | 历
562 | 梯
563 | 澡
564 | 巾
565 | 碑
566 | 附
567 | 教
568 | 照
569 | 堂
570 | l
571 | 达
572 | 低
573 | 精
574 | 按
575 | 化
576 | 脑
577 | 复
578 | 请
579 | 数
580 | 际
581 | 取
582 | 变
583 | 段
584 | 乎
585 | )
586 | 眼
587 | 类
588 | 池
589 | 厕
590 | 试
591 | C
592 | 世
593 | 繁
594 | 今
595 | 留
596 | 久
597 | 万
598 | 搞
599 | 笑
600 | 型
601 | 注
602 | 幕
603 | 升
604 | 拉
605 | 习
606 | 麻
607 | 菜
608 | 刷
609 | G
610 | 室
611 | 具
612 | 敞
613 | 指
614 | 越
615 | 临
616 | 况
617 | 查
618 | 陈
619 | 验
620 | 掉
621 | 目
622 | 青
623 | 铁
624 | 缺
625 | 乐
626 | 款
627 | 翻
628 | 必
629 | 印
630 | 衣
631 | (
632 | 致
633 | 百
634 | 似
635 | 馨
636 | 灯
637 | 妈
638 | 首
639 | 馈
640 | 恶
641 | 垃
642 | 圾
643 | 城
644 | 联
645 | d
646 | 左
647 | 牌
648 | 男
649 | 敢
650 | 助
651 | 遇
652 | 破
653 | 功
654 | 齐
655 | 画
656 | 亲
657 | 介
658 | 切
659 | 随
660 | 纸
661 | 米
662 | 付
663 | 持
664 | 坐
665 | M
666 | 笔
667 | 偏
668 | 右
669 | 围
670 | :
671 | 奇
672 | 烈
673 | 靠
674 | 句
675 | 烂
676 | 倒
677 | 李
678 | 千
679 | 旁
680 | V
681 | k
682 | 角
683 | 微
684 | 兴
685 | 息
686 | 司
687 | O
688 | ~
689 | 壁
690 | .
691 | 醒
692 | 南
693 | 否
694 | 香
695 | 答
696 | 乱
697 | 往
698 | 转
699 | 唯
700 | 专
701 | u
702 | 假
703 | 票
704 | 股
705 | 广
706 | 史
707 | 导
708 | 未
709 | B
710 | 楚
711 | 普
712 | 引
713 | 软
714 | m
715 | 北
716 | 双
717 | 稍
718 | 制
719 | 终
720 | 命
721 | 洞
722 | 异
723 | 份
724 | 岁
725 | 哦
726 | 绍
727 | 扫
728 | 尽
729 | 形
730 | 班
731 | 界
732 | 传
733 | 距
734 | 骗
735 | /
736 | 刻
737 | 立
738 | 肯
739 | 雅
740 | 师
741 | 闷
742 | 招
743 | 墙
744 | 谁
745 | 断
746 | 趣
747 | 弄
748 | 底
749 | E
750 | 料
751 | 怕
752 | N
753 | 浪
754 | 忍
755 | 证
756 | 懂
757 | 即
758 | 落
759 | 独
760 | 烟
761 | 贴
762 | 赶
763 | 啦
764 | 童
765 | 阅
766 | x
767 | 富
768 | 爽
769 | 尤
770 | 规
771 | U
772 | 怪
773 | 投
774 | 局
775 | 食
776 | 州
777 | 拖
778 | 顾
779 | 严
780 | 民
781 | 页
782 | 社
783 | 阳
784 | 政
785 | 英
786 | 据
787 | 仅
788 | 坑
789 | 锁
790 | 鼠
791 | 触
792 | 虑
793 | 误
794 | 令
795 | 忘
796 | 帐
797 | 幸
798 | 闹
799 | 霉
800 | 园
801 | 维
802 | H
803 | 共
804 | 诚
805 | 念
806 | 飞
807 | 害
808 | 忙
809 | L
810 | 吸
811 | 插
812 | 善
813 | 符
814 | 礼
815 | 噪
816 | 约
817 | 造
818 | 神
819 | 脸
820 | 漫
821 | 龙
822 | 述
823 | 宿
824 | 支
825 | 租
826 | 臭
827 | 释
828 | 歉
829 | 挂
830 | 八
831 | "
832 | 积
833 | 毯
834 | v
835 | 折
836 | 跑
837 | 紧
838 | 吹
839 | 丰
840 | 箱
841 | 牙
842 | w
843 | 谓
844 | ;
845 | 初
846 | 桶
847 | 愿
848 | 冲
849 | 港
850 | 黄
851 | 暖
852 | 源
853 | g
854 | 布
855 | 责
856 | 则
857 | 遍
858 | 报
859 | 晨
860 | 窄
861 | 洪
862 | 产
863 | 崖
864 | 杂
865 | 冰
866 | 六
867 | 称
868 | —
869 | 淋
870 | 士
871 | 育
872 | 红
873 | 狭
874 | 素
875 | 疑
876 | 廊
877 | 词
878 | 劲
879 | 估
880 | 控
881 | 戏
882 | 医
883 | 甚
884 | 阿
885 | 耐
886 | 怀
887 | 惯
888 | 义
889 | 泉
890 | 屋
891 | 厚
892 | 饮
893 | 母
894 | 背
895 | 鞋
896 | 登
897 | 蛮
898 | 庭
899 | 郁
900 | 休
901 | 济
902 | f
903 | 络
904 | 坚
905 | 码
906 | 领
907 | 顶
908 | 巧
909 | 健
910 | 暗
911 | 卖
912 | 伤
913 | 娘
914 | 七
915 | 承
916 | 惊
917 | 妹
918 | 索
919 | 摸
920 | 属
921 | 惜
922 | 概
923 | 糟
924 | 顺
925 | 短
926 | 良
927 | 啥
928 | 桌
929 | 列
930 | 巴
931 | 透
932 | 呀
933 | 启
934 | 蓝
935 | 淡
936 | 毕
937 | 丽
938 | K
939 | 灰
940 | b
941 | 负
942 | 银
943 | 父
944 | 穿
945 | 典
946 | 脚
947 | 须
948 | 集
949 | 漏
950 | 询
951 | 模
952 | 担
953 | 摄
954 | 争
955 | 哥
956 | 扇
957 | 展
958 | 彩
959 | 封
960 | 略
961 | 遗
962 | 林
963 | 尚
964 | R
965 | 章
966 | 盖
967 | 苦
968 | 漠
969 | 例
970 | 依
971 | 描
972 | 享
973 | 降
974 | 迎
975 | 航
976 | 尊
977 | 福
978 | 职
979 | 病
980 | 缸
981 | 喝
982 | 悔
983 | 省
984 | 沙
985 | 档
986 | 古
987 | 操
988 | 篇
989 | y
990 | 潮
991 | 茶
992 | 迷
993 | 晕
994 | 牛
995 | 协
996 | 突
997 | 湖
998 | 柜
999 | 漆
1000 | 痛
1001 | 鸡
1002 | 继
1003 | 座
1004 | 皮
1005 | 养
1006 | 寓
1007 | 尔
1008 | 架
1009 | 貌
1010 | 凉
1011 | 湿
1012 | 曾
1013 | 鲜
1014 | 既
1015 | 销
1016 | 糕
1017 | 康
1018 | 凌
1019 | 碰
1020 | 率
1021 | 梦
1022 | 扰
1023 | 余
1024 | 劣
1025 | 迹
1026 | 抱
1027 | 油
1028 | 借
1029 | 泳
1030 | 拍
1031 | W
1032 | 押
1033 | 资
1034 | 薄
1035 | 灵
1036 | 枕
1037 | 德
1038 | 权
1039 | 瓶
1040 | 春
1041 | 九
1042 | 压
1043 | 术
1044 | 藏
1045 | 松
1046 | 欺
1047 | 益
1048 | 录
1049 | 究
1050 | 仍
1051 | 呼
1052 | 王
1053 | 锅
1054 | 赠
1055 | 急
1056 | 浅
1057 | 嘛
1058 | 寸
1059 | 熟
1060 | 营
1061 | 朝
1062 | 敬
1063 | 桥
1064 | 愉
1065 | 累
1066 | 忽
1067 | 颜
1068 | 血
1069 | 畅
1070 | 闻
1071 | 培
1072 | 签
1073 | 纹
1074 | 册
1075 | 院
1076 | 谈
1077 | 账
1078 | 训
1079 | 捷
1080 | 爸
1081 | 憾
1082 | 扣
1083 | 恐
1084 | 某
1085 | F
1086 | 聊
1087 | 伙
1088 | 垫
1089 | 托
1090 | 含
1091 | 参
1092 | 频
1093 | 沟
1094 | 沉
1095 | 载
1096 | 科
1097 | 技
1098 | 岛
1099 | 护
1100 | 项
1101 | 密
1102 | 映
1103 | 均
1104 | 逛
1105 | 烧
1106 | 杯
1107 | 陋
1108 | 仔
1109 | 蚊
1110 | 佳
1111 | 永
1112 | 哎
1113 | 状
1114 | 莫
1115 | 敲
1116 | 券
1117 | 著
1118 | 汉
1119 | 露
1120 | 轨
1121 | 愤
1122 | 势
1123 | 滴
1124 | 忆
1125 | 稳
1126 | 扬
1127 | 摆
1128 | 雨
1129 | 官
1130 | 检
1131 | 木
1132 | 云
1133 | 涉
1134 | 伴
1135 | 河
1136 | 纪
1137 | 案
1138 | 奶
1139 | 途
1140 | 污
1141 | 泡
1142 | 纯
1143 | 漱
1144 | 售
1145 | 宁
1146 | 智
1147 | 姨
1148 | 丢
1149 | 镜
1150 | 杀
1151 | 蛋
1152 | 磨
1153 | 胡
1154 | 激
1155 | 授
1156 | 厦
1157 | 获
1158 | 昨
1159 | 铺
1160 | 壳
1161 | 毒
1162 | 众
1163 | 圈
1164 | 悲
1165 | 止
1166 | 吓
1167 | 悠
1168 | 增
1169 | 烫
1170 | 佛
1171 | 剧
1172 | 锦
1173 | 籍
1174 | 糊
1175 | 努
1176 | 烤
1177 | 浓
1178 | 材
1179 | 副
1180 | 追
1181 | 塑
1182 | 限
1183 | 液
1184 | 慎
1185 | 译
1186 | 志
1187 | 测
1188 | 夫
1189 | 采
1190 | 钢
1191 | 琴
1192 | 泰
1193 | 毫
1194 | 延
1195 | 克
1196 | 炒
1197 | 详
1198 | 玻
1199 | 虫
1200 | 研
1201 | 默
1202 | 璃
1203 | 困
1204 | 斯
1205 | 战
1206 | 缘
1207 | 脱
1208 | 挑
1209 | 予
1210 | 爬
1211 | 狗
1212 | 若
1213 | 粗
1214 | 递
1215 | 醉
1216 | 偶
1217 | 俗
1218 | 舍
1219 | 亚
1220 | 石
1221 | 阴
1222 | 括
1223 | 拥
1224 | 序
1225 | 范
1226 | 企
1227 | 冒
1228 | 硕
1229 | 腾
1230 | 晰
1231 | 药
1232 | 骚
1233 | 巨
1234 | 球
1235 | 尝
1236 | 虚
1237 | 妙
1238 | 派
1239 | 央
1240 | 震
1241 | 豆
1242 | 季
1243 | 艺
1244 | 涨
1245 | 梅
1246 | 寄
1247 | 奈
1248 | 队
1249 | 皇
1250 | 府
1251 | 凑
1252 | 摩
1253 | 圆
1254 | 袋
1255 | 举
1256 | 拾
1257 | 束
1258 | 损
1259 | 丝
1260 | 练
1261 | 批
1262 | 归
1263 | 欣
1264 | 肉
1265 | 厨
1266 | 编
1267 | 遥
1268 | 欠
1269 | 蟑
1270 | 威
1271 | 针
1272 | 悦
1273 | 怜
1274 | 哭
1275 | 幽
1276 | 螂
1277 | 汤
1278 | 顿
1279 | 歌
1280 | 波
1281 | 校
1282 | 贝
1283 | 痕
1284 | -
1285 | 演
1286 | 嘿
1287 | #
1288 | 私
1289 | 绿
1290 | ―
1291 | 败
1292 | 警
1293 | Q
1294 | 劝
1295 | 核
1296 | 掌
1297 | 讨
1298 | 防
1299 | 赔
1300 | 罗
1301 | 吐
1302 | 端
1303 | 跳
1304 | 抽
1305 | 寻
1306 | 敏
1307 | 曲
1308 | 喷
1309 | &
1310 | 衡
1311 | 耳
1312 | 懒
1313 | 察
1314 | 雪
1315 | 勇
1316 | 夏
1317 | 洲
1318 | 抢
1319 | 草
1320 | 堵
1321 | 猫
1322 | 汽
1323 | 闭
1324 | 搭
1325 | 尘
1326 | 帘
1327 | 矿
1328 | 村
1329 | 晓
1330 | 盆
1331 | 婚
1332 | 唉
1333 | 芯
1334 | 恭
1335 | 怖
1336 | 勉
1337 | 侧
1338 | 痒
1339 | 刺
1340 | 催
1341 | 晶
1342 | 额
1343 | 庄
1344 | 擦
1345 | 零
1346 | 尾
1347 | 赏
1348 | 迟
1349 | 鱼
1350 | 辑
1351 | 乘
1352 | 堆
1353 | 辈
1354 | 邮
1355 | 弱
1356 | 构
1357 | 博
1358 | 泪
1359 | 险
1360 | 苏
1361 | 财
1362 | 鬼
1363 | 治
1364 | 拆
1365 | 斑
1366 | 搬
1367 | 丹
1368 | 汗
1369 | 帅
1370 | 拒
1371 | 群
1372 | 末
1373 | 避
1374 | 悟
1375 | 鼓
1376 | +
1377 | 混
1378 | 土
1379 | 创
1380 | 返
1381 | >
1382 | 融
1383 | 湾
1384 | 犹
1385 | 滑
1386 | 挤
1387 | 蒙
1388 | 厉
1389 | %
1390 | 宣
1391 | 申
1392 | 津
1393 | 恋
1394 | 哒
1395 | 冬
1396 | 奥
1397 | 粉
1398 | 祝
1399 | 族
1400 | 乏
1401 | 椅
1402 | 拼
1403 | 组
1404 | 婆
1405 | 卷
1406 | 迫
1407 | 洋
1408 | 欲
1409 | 偿
1410 | 弟
1411 | ^
1412 | _
1413 | 冻
1414 | 绕
1415 | 叶
1416 | 韩
1417 | 缝
1418 | 栋
1419 | 川
1420 | 睛
1421 | 咖
1422 | 玲
1423 | 珍
1424 | 匪
1425 | 弹
1426 | 幼
1427 | 颗
1428 | 析
1429 | 促
1430 | 亏
1431 | 兰
1432 | 野
1433 | 啡
1434 | 遭
1435 | 匙
1436 | 武
1437 | 课
1438 | 树
1439 | 槽
1440 | 钥
1441 | 剩
1442 | 阶
1443 | 占
1444 | 仿
1445 | 隐
1446 | 壶
1447 | 辣
1448 | 减
1449 | 厂
1450 | 盗
1451 | 竞
1452 | 诗
1453 | 倍
1454 | 傻
1455 | 龄
1456 | 咯
1457 | 粥
1458 | 佩
1459 | 僻
1460 | 怨
1461 | 监
1462 | 执
1463 | 鸣
1464 | 替
1465 | 陪
1466 | 爆
1467 | 址
1468 | 渍
1469 | 厌
1470 | 斗
1471 | 虎
1472 | 拜
1473 | 喊
1474 | 狂
1475 | 残
1476 | 诺
1477 | 秋
1478 | 夸
1479 | 哟
1480 | 凡
1481 | 罢
1482 | 谱
1483 | 眠
1484 | 廉
1485 | 饰
1486 | 咋
1487 | 悉
1488 | 寒
1489 | 盛
1490 | 暂
1491 | 纳
1492 | 陷
1493 | 赚
1494 | 秀
1495 | 昏
1496 | 1
1497 | 胆
1498 | 凭
1499 | 間
1500 | 闲
1501 | 0
1502 | 呆
1503 | 浮
1504 | 扔
1505 | 拨
1506 | 弃
1507 | 挨
1508 | Y
1509 | 疼
1510 | 👍
1511 | 删
1512 | 堪
1513 | 咨
1514 | 衷
1515 | 盒
1516 | 愧
1517 | 亦
1518 | 姓
1519 | 鼻
1520 | 恨
1521 | 赖
1522 | 柔
1523 | 兼
1524 | 叹
1525 | 娱
1526 | 躺
1527 | 朗
1528 | 互
1529 | 孕
1530 | <
1531 | 孔
1532 | 帝
1533 | 农
1534 | 杜
1535 | 览
1536 | 涂
1537 | 逃
1538 | 础
1539 | 恢
1540 | 怒
1541 | 律
1542 | 慧
1543 | 守
1544 | 腻
1545 | 侣
1546 | 废
1547 | 宗
1548 | 滩
1549 | 洒
1550 | 惑
1551 | 移
1552 | 绘
1553 | 丁
1554 | 嫌
1555 | 彻
1556 | 骨
1557 | 君
1558 | 胜
1559 | 奉
1560 | 兄
1561 | 耽
1562 | 钻
1563 | 惨
1564 | 珠
1565 | 氛
1566 | 串
1567 | 幻
1568 | 播
1569 | 膜
1570 | 逸
1571 | 欧
1572 | 域
1573 | 姑
1574 | 豫
1575 | 嗯
1576 | 抵
1577 | 嘴
1578 | 辛
1579 | 菲
1580 | 陵
1581 | 桑
1582 | 郑
1583 | 固
1584 | 轮
1585 | 筑
1586 | 镇
1587 | 骂
1588 | 励
1589 | 库
1590 | 嘉
1591 | 塞
1592 | 這
1593 | 船
1594 | 番
1595 | 输
1596 | 肤
1597 | 偷
1598 | 粘
1599 | 哲
1600 | 殊
1601 | 糙
1602 | 森
1603 | 疯
1604 | 咬
1605 | 握
1606 | 麦
1607 | 渐
1608 | 兮
1609 | 酸
1610 | 秘
1611 | 刘
1612 | 隆
1613 | 贯
1614 | 魔
1615 | 柳
1616 | 拔
1617 | 慰
1618 | 尼
1619 | 碗
1620 | 陆
1621 | 拐
1622 | "
1623 | 胶
1624 | 狼
1625 | 币
1626 | 叭
1627 | ‘
1628 | 汇
1629 | 朴
1630 | 鉴
1631 | 匆
1632 | 戴
1633 | 阁
1634 | 酷
1635 | 染
1636 | 谨
1637 | 禁
1638 | 荡
1639 | 抑
1640 | 驾
1641 | 逼
1642 | 誉
1643 | 泛
1644 | 军
1645 | 忠
1646 | 尺
1647 | 挡
1648 | 屁
1649 | 嘻
1650 | 幅
1651 | 孤
1652 | 吉
1653 | 炉
1654 | 俱
1655 | 辆
1656 | 旺
1657 | 鸟
1658 | 喇
1659 | 稀
1660 | 框
1661 | 孙
1662 | 综
1663 | 击
1664 | 徐
1665 | 沒
1666 | 刀
1667 | 邻
1668 | 😡
1669 | 裂
1670 | 沐
1671 | 抓
1672 | 脆
1673 |
1674 | 叙
1675 | 乡
1676 | 膏
1677 | 務
1678 | '
1679 | 判
1680 | 横
1681 | 弥
1682 | 傅
1683 | 吱
1684 | 泥
1685 | ’
1686 | 障
1687 | 昌
1688 | 纠
1689 | 撕
1690 | 罪
1691 | 哗
1692 | 犯
1693 | 聘
1694 | 哄
1695 | 抗
1696 | 昆
1697 | 奋
1698 | 奔
1699 | 肚
1700 | 踏
1701 | 丑
1702 | 阵
1703 | 滨
1704 | 耗
1705 | 探
1706 | 苍
1707 | 梳
1708 | 危
1709 | 添
1710 | 彼
1711 | 痴
1712 | 革
1713 | 浆
1714 | 疗
1715 | 轰
1716 | 牵
1717 | 碎
1718 | 尖
1719 | 耍
1720 | 甜
1721 | 唱
1722 | 剔
1723 | 爷
1724 | 傲
1725 | 恩
1726 | 瑞
1727 | 饱
1728 | 撇
1729 | 碟
1730 | 胃
1731 | 辨
1732 | 嘈
1733 | 玉
1734 | 肥
1735 | 暴
1736 | 宫
1737 | 矩
1738 | 😄
1739 | 塌
1740 | 奖
1741 | 乌
1742 | 井
1743 | 俩
1744 | 唐
1745 | \
1746 | 捧
1747 | 摇
1748 | 凶
1749 | 妇
1750 | 缩
1751 | 崇
1752 | 2
1753 | 措
1754 | 搜
1755 | 裤
1756 | 闪
1757 | 糖
1758 | 灾
1759 | 旋
1760 | 沿
1761 | 悬
1762 | 迪
1763 | 還
1764 | 迅
1765 | 绪
1766 | 圣
1767 | 淘
1768 | 罩
1769 | 诸
1770 | 卧
1771 | 燕
1772 | 虹
1773 | 阔
1774 | 腿
1775 | 忧
1776 | 寺
1777 | 伟
1778 | 涩
1779 | 瓜
1780 | 践
1781 | 😂
1782 | 逐
1783 | 扑
1784 | 夹
1785 | 冠
1786 | 栈
1787 | 伦
1788 | 杨
1789 | 呜
1790 | `
1791 | 扎
1792 | 聚
1793 | 曰
1794 | 剂
1795 | 叔
1796 | 谅
1797 | 霸
1798 | 缓
1799 | 熏
1800 | 慕
1801 | 榻
1802 | 聪
1803 | 羊
1804 | 扭
1805 | 恼
1806 | 吊
1807 | 扯
1808 | 恳
1809 | 诈
1810 | 尬
1811 | 晃
1812 | 卸
1813 | 灭
1814 | 熊
1815 | 抬
1816 | 艳
1817 | 煌
1818 | 榜
1819 | 苑
1820 | 磁
1821 | 燥
1822 | 坡
1823 | 涵
1824 | 尴
1825 | 褥
1826 | 颇
1827 | 斜
1828 | 恰
1829 | 弯
1830 | 兔
1831 | 凯
1832 | 锈
1833 | 荒
1834 | 辩
1835 | 妥
1836 | 粹
1837 | 仓
1838 | 妻
1839 | 陌
1840 | 宰
1841 | 猪
1842 | 墅
1843 | 访
1844 | 跌
1845 | 逗
1846 | 摔
1847 | 救
1848 | 沈
1849 | 雷
1850 | 哀
1851 | 劳
1852 | 胖
1853 | 坛
1854 | 敌
1855 | 蜜
1856 | 皆
1857 | 杭
1858 | 贸
1859 | 墨
1860 | 纷
1861 | 扩
1862 | 戒
1863 | 宏
1864 | 委
1865 | 攻
1866 | 逻
1867 | 穷
1868 | 献
1869 | 荣
1870 | 奢
1871 | 祖
1872 | 鲁
1873 | 窝
1874 | 雄
1875 | 尿
1876 | 猜
1877 | 娜
1878 | 😊
1879 | 挚
1880 | 隙
1881 | 征
1882 | 摊
1883 | 庸
1884 | 仁
1885 | 飘
1886 | 碍
1887 | 蛛
1888 | 滋
1889 | 溪
1890 | 魂
1891 | 來
1892 | 塔
1893 | 喻
1894 | 阐
1895 | 雾
1896 | 庙
1897 | 勒
1898 | 逝
1899 | 羡
1900 | 趟
1901 | 沾
1902 | 峰
1903 | 渴
1904 | 慨
1905 | 後
1906 | 穴
1907 | 壮
1908 | 审
1909 | 舞
1910 | 崩
1911 | 皂
1912 | 帆
1913 | 姆
1914 | 亡
1915 | 煎
1916 | 簧
1917 | 洛
1918 | 哇
1919 | 個
1920 | 腰
1921 | 挥
1922 | 坪
1923 | 敦
1924 | 瘾
1925 | 枯
1926 | 砸
1927 | 旦
1928 | 3
1929 | 腐
1930 | 旗
1931 | 织
1932 | 策
1933 | 患
1934 | 碌
1935 | 辞
1936 | 刮
1937 | 冤
1938 | 笼
1939 | 叮
1940 | 峡
1941 | 宋
1942 | 倾
1943 | 诱
1944 | 督
1945 | 鄙
1946 | 寨
1947 | 砂
1948 | 桃
1949 | 宅
1950 | 谷
1951 | 喧
1952 | 睹
1953 | 4
1954 | 熬
1955 | 伞
1956 | 衍
1957 | 蹲
1958 | 席
1959 | 滚
1960 | 症
1961 | 凤
1962 | 瘦
1963 | 咔
1964 | 剪
1965 | 苹
1966 | 蜘
1967 | 勾
1968 | 圳
1969 | 砖
1970 | 狠
1971 | 罚
1972 | 宇
1973 | 钮
1974 | 茫
1975 | 敷
1976 | 肃
1977 | 铜
1978 | 链
1979 | 浑
1980 | 巷
1981 | 乖
1982 | 妆
1983 | 艰
1984 | 咱
1985 | 屈
1986 | ∩
1987 | 娓
1988 | 召
1989 | 翼
1990 | 帽
1991 | 芝
1992 | 溧
1993 | 覆
1994 | 媒
1995 | 勤
1996 | 掩
1997 | 毁
1998 | 吴
1999 | 棉
2000 | 陶
2001 | 俺
2002 | 脾
2003 | 凳
2004 | 讯
2005 | 赛
2006 | 矛
2007 | 岂
2008 | 唤
2009 | 仪
2010 | 為
2011 | 汁
2012 | 贼
2013 | 過
2014 | 揭
2015 | 溃
2016 | 蝇
2017 | 秦
2018 | 兵
2019 | 渣
2020 | 😓
2021 | 浦
2022 | 筒
2023 | 咳
2024 | 拎
2025 | 紫
2026 | 仰
2027 | 朔
2028 | 噩
2029 | 兽
2030 | 竹
2031 | 辉
2032 | 伏
2033 | 莉
2034 | *
2035 | 铭
2036 | 馒
2037 | 掏
2038 | 逢
2039 | 疏
2040 | 撑
2041 | 允
2042 | 潢
2043 | 瑕
2044 | 碧
2045 | 甲
2046 | 拦
2047 | 玄
2048 | 税
2049 | q
2050 | 時
2051 | 党
2052 | 趋
2053 | 耻
2054 | 谐
2055 | 填
2056 | 田
2057 | 炼
2058 | 朵
2059 | 宵
2060 | 潜
2061 | 瞬
2062 | 噢
2063 | ¥
2064 | 渡
2065 | 咸
2066 | 盾
2067 | =
2068 | 挖
2069 | 斩
2070 | 疵
2071 | 伪
2072 | 甘
2073 | 奏
2074 | 颖
2075 | 岗
2076 | 晦
2077 | 說
2078 | 肠
2079 | 娃
2080 | 疲
2081 | 撒
2082 | 徒
2083 | 肋
2084 | 庐
2085 | 伸
2086 | 遮
2087 | 莲
2088 | 歪
2089 | 厘
2090 | 啤
2091 | 讶
2092 | 螺
2093 | 铃
2094 | 夕
2095 | 羽
2096 | 墓
2097 | 宴
2098 | 裕
2099 | 溢
2100 | 們
2101 | 戚
2102 | 胎
2103 | 逊
2104 | 卵
2105 | 乳
2106 | 裸
2107 | 撤
2108 | 撼
2109 | 蓬
2110 | 锡
2111 | 县
2112 | 秒
2113 | 萨
2114 | 饿
2115 | 幢
2116 | 坦
2117 | 斤
2118 | 贪
2119 | 贫
2120 | 谋
2121 | 咕
2122 | 耶
2123 | 径
2124 | 辘
2125 | 侨
2126 | 谊
2127 | 躁
2128 | 贡
2129 | 涯
2130 | 骄
2131 | 【
2132 | 】
2133 | 霞
2134 | 蔡
2135 | z
2136 | 勿
2137 | 垢
2138 | 覺
2139 | 炸
2140 | 晾
2141 | 振
2142 | 傍
2143 | 8
2144 | 叠
2145 | 橙
2146 | 啪
2147 | @
2148 | 牢
2149 | 抛
2150 | 坝
2151 | 晋
2152 | 絮
2153 | 胞
2154 | 蒋
2155 | 岸
2156 | 撞
2157 | 悄
2158 | 驻
2159 | ️
2160 | 肮
2161 | 阻
2162 | 射
2163 | 赵
2164 | 截
2165 | 逆
2166 | 疙
2167 | 瘩
2168 | 兜
2169 | 咀
2170 | 茂
2171 | 5
2172 | 嘎
2173 | 煮
2174 | 虾
2175 | 恒
2176 | 鸭
2177 | 润
2178 | 杰
2179 | 浸
2180 | 溜
2181 | 牲
2182 | 橱
2183 | 斥
2184 | 坊
2185 | 妨
2186 | 歇
2187 | 艾
2188 | 會
2189 | 莱
2190 | 凸
2191 | 點
2192 | 赤
2193 | 坎
2194 | 乃
2195 | 書
2196 | 稚
2197 | 咚
2198 | 跨
2199 | 漓
2200 | 抄
2201 | 寂
2202 | 姜
2203 | 眉
2204 | 惬
2205 | 彬
2206 | 翘
2207 | 饼
2208 | 琐
2209 | 滥
2210 | 梭
2211 | 旨
2212 | 狱
2213 | 浏
2214 | 忌
2215 | 歧
2216 | 锋
2217 | 脉
2218 | 颠
2219 | 绒
2220 | 9
2221 | 凰
2222 | 給
2223 | 踪
2224 | 植
2225 | 瞎
2226 | 熙
2227 | 缠
2228 | 愁
2229 | 巫
2230 | 鸿
2231 | 轱
2232 | 卑
2233 | 瑾
2234 | 嗡
2235 | 渝
2236 | 夷
2237 | 瓷
2238 | 闺
2239 | 嗦
2240 | 蒸
2241 | 袍
2242 | 憋
2243 | 驳
2244 | 遵
2245 | 屉
2246 | 踩
2247 | 辱
2248 | 浩
2249 | 電
2250 | 炫
2251 | 郊
2252 | 氏
2253 | 凹
2254 | 於
2255 | 怡
2256 | 玫
2257 | 泽
2258 | 儒
2259 | 睿
2260 | 噜
2261 | 埋
2262 | 吻
2263 | 萌
2264 | 痘
2265 | 盼
2266 | 丛
2267 | 琢
2268 | Z
2269 | 牺
2270 | 违
2271 | 淑
2272 | 矮
2273 | 腔
2274 | 呕
2275 | 躲
2276 | 員
2277 | 侃
2278 | 坷
2279 | 窟
2280 | 绵
2281 | 仇
2282 | 兑
2283 | 摘
2284 | 捡
2285 | 惧
2286 | 扮
2287 | 瑜
2288 | 赢
2289 | 魅
2290 | 枪
2291 | 靓
2292 | 剥
2293 | 丧
2294 | 曼
2295 | 抹
2296 | 割
2297 | 睁
2298 | 鼎
2299 | 梁
2300 | J
2301 | 讽
2302 | 壤
2303 | 姻
2304 | 纱
2305 | 枉
2306 | 睬
2307 | 麼
2308 | 晒
2309 | 桂
2310 | 吝
2311 | 錯
2312 | 栏
2313 | 奸
2314 | 锣
2315 | 诞
2316 | 翠
2317 | 劫
2318 | 撰
2319 | 驴
2320 | 挣
2321 | 呛
2322 | 惹
2323 | 茄
2324 | 粤
2325 | 锐
2326 | 渗
2327 | 麽
2328 | 蔽
2329 | 嗽
2330 | 纵
2331 | 饥
2332 | 韵
2333 | 钉
2334 | 實
2335 | 淹
2336 | 匹
2337 | 叨
2338 | 悍
2339 | 锻
2340 | 喔
2341 | 筋
2342 | 跃
2343 | 雕
2344 | 葛
2345 | 胸
2346 | 弦
2347 | 誓
2348 | 卓
2349 | 裁
2350 | 塘
2351 | 阜
2352 | 愣
2353 | 涤
2354 | 轴
2355 | 俄
2356 | 薇
2357 | 盐
2358 | 翁
2359 | 態
2360 | 侄
2361 | 耀
2362 | 較
2363 | 吞
2364 | 浙
2365 | 瑰
2366 | 谎
2367 | 卢
2368 | 汰
2369 | 啬
2370 | 唧
2371 | 篮
2372 | 恬
2373 | 诠
2374 | 咪
2375 | [
2376 | ]
2377 | 窍
2378 | 蛇
2379 | 姿
2380 | 妮
2381 | 娇
2382 | 孝
2383 | 宠
2384 | 僵
2385 | 寅
2386 | 掘
2387 | 铝
2388 | 烘
2389 | 該
2390 | 狡
2391 | 笨
2392 | 仙
2393 | 咽
2394 | 恍
2395 | 莞
2396 | 蚁
2397 | 迁
2398 | 朱
2399 | 嘟
2400 | 邪
2401 | 衔
2402 | 储
2403 | 豁
2404 | 沫
2405 | 鹰
2406 | 赫
2407 | 呈
2408 | 炎
2409 | 祥
2410 | 谦
2411 | 對
2412 | 婉
2413 | 夺
2414 | 藤
2415 | 臣
2416 | 祈
2417 | 葩
2418 | 😤
2419 | 帖
2420 | 旷
2421 | 價
2422 | 熨
2423 | 肩
2424 | 捏
2425 | 炮
2426 | 瓦
2427 | 垮
2428 | 昧
2429 | 诀
2430 | 煙
2431 | 岩
2432 | 莎
2433 | 跤
2434 | 屑
2435 | 遣
2436 | 篷
2437 | 設
2438 | 窃
2439 | 煤
2440 | 芒
2441 | 岳
2442 | +
2443 | 盯
2444 | 喂
2445 | 芳
2446 | 粒
2447 | 渔
2448 | 杆
2449 | 捣
2450 | 拟
2451 | 荷
2452 | 哑
2453 | 蕴
2454 | 菌
2455 | 郎
2456 | 呐
2457 | 疾
2458 | 肌
2459 | 吾
2460 | 愚
2461 | 届
2462 | 蚤
2463 | 钓
2464 | 搁
2465 | 皱
2466 | 诊
2467 | 拧
2468 | 钩
2469 | 灌
2470 | 倡
2471 | 竣
2472 | 邀
2473 | %
2474 | 胁
2475 | 泊
2476 | 樓
2477 | 趁
2478 | 萝
2479 | 帧
2480 | 渊
2481 | 饶
2482 | 哨
2483 | 歹
2484 | 洽
2485 | 祸
2486 | 暇
2487 | 愈
2488 | 叽
2489 | 舟
2490 | 邦
2491 | 咫
2492 | 汕
2493 | 燃
2494 | 洼
2495 | 苛
2496 | 黎
2497 | 惫
2498 | 闯
2499 | 瞧
2500 | 绎
2501 | 峨
2502 | 弗
2503 | 伯
2504 | 狐
2505 | ·
2506 | 😒
2507 | 冉
2508 | 擅
2509 | 竭
2510 | 嘘
2511 | 循
2512 | 械
2513 | 雀
2514 | 蹦
2515 | 盲
2516 | 饺
2517 | 贤
2518 | 嫁
2519 | $
2520 | 盏
2521 | 當
2522 | 椒
2523 | 泻
2524 | 栽
2525 | 沧
2526 | P
2527 | 蝶
2528 | 囊
2529 | 扶
2530 | 棋
2531 | 殷
2532 | 柏
2533 | 贱
2534 | 凄
2535 | 衬
2536 | 翅
2537 | 羞
2538 | 伍
2539 | 涌
2540 | 衰
2541 | 澈
2542 | 暑
2543 | 诶
2544 | 绰
2545 | 窒
2546 | 吼
2547 | 浒
2548 | 谧
2549 | 绚
2550 | 泣
2551 | 趴
2552 | 辙
2553 | 秉
2554 | 拽
2555 | 驶
2556 | 肆
2557 | 嘲
2558 | 阮
2559 | 鹅
2560 | 辜
2561 | 堤
2562 | 砍
2563 | 沦
2564 | 機
2565 | 問
2566 | 韧
2567 | 6
2568 | 經
2569 | 畔
2570 | 亭
2571 | 纤
2572 | 厮
2573 | 苗
2574 | 蚂
2575 | 竖
2576 | 桐
2577 | 邯
2578 | 郸
2579 | 泄
2580 | 寝
2581 | 碜
2582 | 稿
2583 | 毅
2584 | 話
2585 | 堰
2586 | 坟
2587 | 颈
2588 | 潘
2589 | 袜
2590 | 猎
2591 | 挪
2592 | 琼
2593 | 寰
2594 | 辟
2595 | 婴
2596 | 丸
2597 | 蟹
2598 | 樣
2599 | 迈
2600 | 猛
2601 | 挫
2602 | 茨
2603 | 剖
2604 | 畏
2605 | 狸
2606 | 宕
2607 | 俊
2608 | 喳
2609 | 婷
2610 | 👎
2611 | 😔
2612 | 甩
2613 | 勺
2614 | 滔
2615 | 胀
2616 | 轩
2617 | 袭
2618 | 嫩
2619 | 抖
2620 | 苟
2621 | 冗
2622 | 國
2623 | 腕
2624 | 骤
2625 | 侮
2626 | 慈
2627 | 惟
2628 | 耿
2629 | 攘
2630 | 亿
2631 | 磕
2632 | O
2633 | 標
2634 | 栅
2635 | 贺
2636 | 缴
2637 | 妒
2638 | 斋
2639 | 玛
2640 | 腊
2641 | 媳
2642 | C
2643 | 膀
2644 | 嚣
2645 | 鸦
2646 | 伽
2647 | 疹
2648 | 烹
2649 | 伊
2650 | 啰
2651 | 侯
2652 | 拓
2653 | |
2654 | 峪
2655 | 揣
2656 | 妖
2657 | 宙
2658 | 箭
2659 | 泼
2660 | 寞
2661 | 廖
2662 | 鹭
2663 | ▽
2664 | ⊙
2665 | 骑
2666 | 柴
2667 | 蠢
2668 | 歡
2669 | 粮
2670 | 腥
2671 | 侠
2672 | 稻
2673 | 尸
2674 | 渠
2675 | 脊
2676 | 醛
2677 | 酬
2678 | 楞
2679 | 叼
2680 | 诧
2681 | 诬
2682 | 盈
2683 | 搓
2684 | 啧
2685 | 蝴
2686 | 拢
2687 | 赘
2688 | 煲
2689 | 孟
2690 | 纽
2691 | 剑
2692 | 肿
2693 | 冯
2694 | 盟
2695 | 侵
2696 | 忒
2697 | 懵
2698 | N
2699 | 硌
2700 | 棵
2701 | 暮
2702 | 绩
2703 | 淀
2704 | 琳
2705 | {
2706 | }
2707 | 披
2708 | 幾
2709 | 筝
2710 | 茅
2711 | 藻
2712 | 丈
2713 | 裹
2714 | 蜂
2715 | 坞
2716 | 舌
2717 | 兩
2718 | 捉
2719 | 穆
2720 | 癖
2721 | 曹
2722 | 蒂
2723 | 掀
2724 | 揪
2725 | 翔
2726 | 眷
2727 | 肇
2728 | 沥
2729 | 崽
2730 | 蹭
2731 | 嗖
2732 | 谬
2733 | 齿
2734 | 龟
2735 | 寥
2736 | 旬
2737 | 膨
2738 | 條
2739 | 呗
2740 | 蜡
2741 | 嗒
2742 | 笙
2743 | □
2744 | 谛
2745 | 拷
2746 | 吟
2747 | 赃
2748 | 矫
2749 | 題
2750 | 妄
2751 | 應
2752 | 彰
2753 | 搅
2754 | 雖
2755 | 芦
2756 | 開
2757 | 讓
2758 | 聆
2759 | 亨
2760 | 噼
2761 | 乒
2762 | 陕
2763 | 瓣
2764 | 霜
2765 | 寡
2766 | 沸
2767 | 袖
2768 | ぃ
2769 | 甄
2770 | 譬
2771 | 笛
2772 | 墟
2773 | 佰
2774 | 堕
2775 | 瀑
2776 | 捂
2777 | 匀
2778 | 肴
2779 | 绳
2780 | 闸
2781 | 淌
2782 | 柱
2783 | 绑
2784 | 珑
2785 | 妞
2786 | 柿
2787 | 魄
2788 | 郭
2789 | 蔷
2790 | 谭
2791 | 顽
2792 | 娴
2793 | 樱
2794 | 凝
2795 | 惩
2796 | 佼
2797 | 赌
2798 | ☺
2799 | 叉
2800 | 御
2801 | 佣
2802 | 跷
2803 | 忐
2804 | 忑
2805 | 萧
2806 | 恕
2807 | 钝
2808 | 掺
2809 | /
2810 | 屡
2811 | 蜗
2812 | 7
2813 | 媲
2814 | 筷
2815 | 記
2816 | 疆
2817 | 拭
2818 | 癌
2819 | 氣
2820 | 換
2821 | 媚
2822 | 溅
2823 | 踹
2824 | 調
2825 | 錢
2826 | 契
2827 | 疚
2828 | 秩
2829 | 乓
2830 | 卜
2831 | 蹋
2832 | 乾
2833 | 悚
2834 | 叛
2835 | 蓄
2836 | 惦
2837 | 汪
2838 | 搪
2839 | T
2840 | S
2841 | 阱
2842 | 侈
2843 | 準
2844 | 拙
2845 | 滞
2846 | 廷
2847 | 倦
2848 | 诡
2849 | 侦
2850 | 淮
2851 | 醋
2852 | 氧
2853 | 岭
2854 | 喽
2855 | 颐
2856 | 庞
2857 | 辰
2858 | 瑶
2859 | 矣
2860 | 屎
2861 | 蔓
2862 | 悸
2863 | 辅
2864 | 衫
2865 | 爹
2866 | 風
2867 | 孛
2868 | 車
2869 | 澳
2870 | 菩
2871 | 巢
2872 | 倔
2873 | 搏
2874 | 灼
2875 | 缚
2876 | 芜
2877 | 窥
2878 | 琅
2879 | 谜
2880 | 隧
2881 | 朽
2882 | 腹
2883 | 兆
2884 | 扉
2885 | 邓
2886 | 薛
2887 | 焦
2888 | 赋
2889 | 蕾
2890 | 刃
2891 | 汀
2892 | 蔼
2893 | 乔
2894 | 捐
2895 | 😱
2896 | 😁
2897 | ❤
2898 | 😜
2899 | 桩
2900 | 焉
2901 | 薯
2902 | 爵
2903 | 呃
2904 | 讹
2905 | 臂
2906 | 鞍
2907 | 闽
2908 | 無
2909 | 評
2910 | 嫂
2911 | 嬉
2912 | 敛
2913 | 禮
2914 | 抠
2915 | 阀
2916 | ┬
2917 | 網
2918 | 谴
2919 | 扛
2920 | 犀
2921 | X
2922 | 拌
2923 | 舊
2924 | 憧
2925 | 憬
2926 | 湮
2927 | 吭
2928 | 昂
2929 | °
2930 | 掰
2931 | び
2932 | 禅
2933 | 衛
2934 | 嚼
2935 | 焕
2936 | 帕
2937 | 姊
2938 | 稽
2939 | 驰
2940 | 砌
2941 | 懦
2942 | 嫉
2943 | 熱
2944 | 缭
2945 | 讳
2946 | 華
2947 | 髓
2948 | 迄
2949 | 關
2950 | 棚
2951 | 煽
2952 | 甥
2953 | 坠
2954 | 酌
2955 | 猩
2956 | 嗨
2957 | 脖
2958 | 饪
2959 | 徘
2960 | 徊
2961 | 總
2962 | 鞭
2963 | 晏
2964 | 〉
2965 | 蕉
2966 | 費
2967 | 確
2968 | 葬
2969 | 毋
2970 | 發
2971 | 慌
2972 | 蔬
2973 | 竿
2974 | 蛙
2975 | 眺
2976 | 屯
2977 | 哉
2978 | 熄
2979 | 丫
2980 | 鹤
2981 | 拘
2982 | 援
2983 | 沃
2984 | 娟
2985 | 袁
2986 | 觅
2987 | 酱
2988 | 灿
2989 | 嚷
2990 | 沛
2991 | 瑟
2992 | 迦
2993 | 芸
2994 | 聂
2995 | 耋
2996 | 楠
2997 | 锤
2998 | 🐭
2999 | 舱
3000 | 沱
3001 | 😍
3002 | ๑
3003 | 蛾
3004 | 吁
3005 | 颤
3006 | 寿
3007 | 婶
3008 | 痰
3009 | 枝
3010 | 鲍
3011 | 厄
3012 | 厢
3013 | 內
3014 | 從
3015 | 請
3016 | 嗎
3017 | 攴
3018 | 螨
3019 | 喀
3020 | 辦
3021 | 棕
3022 | 呻
3023 | 刁
3024 | 訂
3025 | 夠
3026 | 捅
3027 | <
3028 | >
3029 | 葫
3030 | 簡
3031 | 滿
3032 | 廳
3033 | 俯
3034 | 楷
3035 | 贷
3036 | 沓
3037 | 啃
3038 | 珀
3039 | 诙
3040 | 遂
3041 | 棍
3042 | 巡
3043 | 咻
3044 | 镁
3045 | 崛
3046 | 處
3047 | 诫
3048 | 噱
3049 | 赴
3050 | 茉
3051 | 湘
3052 | 喘
3053 | 膊
3054 | 垂
3055 | 淄
3056 | 菇
3057 | D
3058 | 裙
3059 | 蔑
3060 | 仲
3061 | 踢
3062 | I
3063 | 暧
3064 | 嘀
3065 | 耸
3066 | 哼
3067 | 涕
3068 | 萍
3069 | 潍
3070 | 東
3071 | 芙
3072 | 蓉
3073 | j
3074 | 楂
3075 | 劵
3076 | 窜
3077 | 動
3078 | 嗓
3079 | 杠
3080 | 婪
3081 | 哩
3082 | 殖
3083 | 黏
3084 | 薪
3085 | 寫
3086 | 環
3087 | 翩
3088 | 昔
3089 | 鹿
3090 | 梵
3091 | 斌
3092 | 菊
3093 | 姬
3094 | 卿
3095 | 郝
3096 | 渺
3097 | 拳
3098 | 瞰
3099 | 匠
3100 | 脂
3101 | 肪
3102 | 肝
3103 | 榷
3104 | 穗
3105 | 滇
3106 | 焊
3107 | 琪
3108 | 鑫
3109 | 骏
3110 | 坨
3111 | 獒
3112 | 😭
3113 | ‼
3114 |
3115 | 😀
3116 | ω
3117 | 😎
3118 | 哧
3119 | 蹩
3120 | 掂
3121 | 種
3122 | 驿
3123 | 龌
3124 | 龊
3125 | 弊
3126 | 挠
3127 | 乞
3128 | 褒
3129 | 惰
3130 | 秤
3131 | 戈
3132 | 溶
3133 | 诣
3134 | 論
3135 | 謝
3136 | 亟
3137 | 虞
3138 | 珨
3139 | 岆
3140 | 鼾
3141 | 滤
3142 | 烊
3143 | 單
3144 | 卻
3145 | 櫃
3146 | 葱
3147 | 柄
3148 | 淨
3149 | 備
3150 | 雙
3151 | 區
3152 | 搂
3153 | 舰
3154 | 進
3155 | 裡
3156 | 赐
3157 | 猴
3158 | 芋
3159 | 侍
3160 | 颁
3161 | 颓
3162 | 桦
3163 | 聋
3164 | 涮
3165 | 颂
3166 | 烩
3167 | 雁
3168 | 預
3169 | 醺
3170 | 拱
3171 | 漉
3172 | 刹
3173 | 刊
3174 | 捆
3175 | 僚
3176 | 「
3177 | 」
3178 | 憎
3179 | 裏
3180 | 別
3181 | 犬
3182 | 俏
3183 | 嵌
3184 | 絕
3185 | 淳
3186 | 認
3187 | 門
3188 | 朦
3189 | 胧
3190 | 翡
3191 | E
3192 | 赣
3193 | 臺
3194 | 現
3195 | ︶
3196 | 澜
3197 | 汶
3198 | 呦
3199 | 渲
3200 | 強
3201 | 诵
3202 | 曦
3203 | 埃
3204 | 圭
3205 | 缆
3206 | 牧
3207 | 魏
3208 | 旳
3209 | 仆
3210 | 莹
3211 | 惆
3212 | 怅
3213 | 憩
3214 | 埔
3215 | 捕
3216 | 巩
3217 | 晴
3218 | 惘
3219 | 扼
3220 | 骆
3221 | 筹
3222 | 狮
3223 | 涓
3224 | 惋
3225 | 鸠
3226 | 癫
3227 | 敖
3228 | 墩
3229 | 驯
3230 | 挞
3231 | 债
3232 | 窿
3233 | 挲
3234 | 莽
3235 | =
3236 | 😠
3237 | ◡
3238 | 😃
3239 | 🤗
3240 | ✪
3241 | ✌
3242 | 🙋
3243 | •
3244 | ั
3245 | 撬
3246 | 場
3247 | 桔
3248 | 贩
3249 | 瞻
3250 | 贿
3251 | 喉
3252 | 董
3253 | 許
3254 | 剃
3255 | 咣
3256 | 岱
3257 | 扂
3258 | 浊
3259 | 酶
3260 | 質
3261 | 視
3262 | 畸
3263 | 焚
3264 | 灶
3265 | 級
3266 | 瞌
3267 | 虐
3268 | 扁
3269 | 轿
3270 | 弛
3271 | 啸
3272 | 璋
3273 | 邊
3274 | 髒
3275 | 飙
3276 | 扒
3277 | 愕
3278 | 镑
3279 | 語
3280 | 業
3281 | 苞
3282 | 蕊
3283 | 瘴
3284 | 啼
3285 | 毗
3286 | 胳
3287 | 沪
3288 | 離
3289 | 裝
3290 | 嘱
3291 | 咐
3292 | 瞒
3293 | 選
3294 | 擇
3295 | 瘪
3296 | 徽
3297 | 纲
3298 | 馊
3299 | 荤
3300 | U
3301 | L
3302 | M
3303 | A
3304 | 瞟
3305 | 榨
3306 | 烁
3307 | 惕
3308 | 乍
3309 | 氓
3310 | 結
3311 | 邋
3312 | 遢
3313 | 仗
3314 | 難
3315 | 铅
3316 | 撩
3317 | 眩
3318 | 署
3319 | 佬
3320 | 弧
3321 | 惡
3322 | 層
3323 | 嗅
3324 | 削
3325 | 隶
3326 | 蹈
3327 | 蜕
3328 | 芬
3329 | 佑
3330 | 頭
3331 | 衢
3332 | 張
3333 | 爛
3334 | 雇
3335 | 挽
3336 | 涑
3337 | 讀
3338 | 劉
3339 | 役
3340 | 幫
3341 | 圖
3342 | 螃
3343 | 祭
3344 | 柯
3345 | 拇
3346 | 羁
3347 | 涛
3348 | 泯
3349 | 钦
3350 | 奴
3351 | 彦
3352 | 贾
3353 | 藩
3354 | 愛
3355 | 璧
3356 | 绛
3357 | 弘
3358 | 佚
3359 | 蚯
3360 | 蚓
3361 | 丘
3362 | 鳅
3363 | 罐
3364 | 肖
3365 | 攀
3366 | 肺
3367 | 痧
3368 | 腮
3369 | 摧
3370 | 僅
3371 | 枫
3372 | 仑
3373 | 磊
3374 | 痊
3375 | 崔
3376 | 谣
3377 | ٩
3378 | ´
3379 | 枢
3380 | 🙃
3381 | 嘭
3382 | ➕
3383 | 😘
3384 | 😏
3385 | ⁎
3386 | ♥
3387 | 薦
3388 | 囔
3389 | 沽
3390 | 锯
3391 | 阉
3392 | 唆
3393 | 橘
3394 | 殡
3395 | 規
3396 | 億
3397 | 哆
3398 | 衅
3399 | 烛
3400 | 汐
3401 | 冕
3402 | 硐
3403 | 跺
3404 | 瞄
3405 | 攒
3406 | 兢
3407 | 簾
3408 | 摞
3409 | 檯
3410 | Τ
3411 | 飕
3412 | 飯
3413 | 筛
3414 | 潔
3415 | 購
3416 | 橡
3417 | 粪
3418 | 怂
3419 | 恿
3420 | 躬
3421 | 辄
3422 | 抒
3423 | 鹏
3424 | 沼
3425 | 蹊
3426 | 囧
3427 | 焖
3428 | 笋
3429 | 艿
3430 | 曙
3431 | 辽
3432 | 埠
3433 | 噔
3434 | 噶
3435 | 蔚
3436 | ×
3437 | 簸
3438 | 唠
3439 | 勘
3440 | 細
3441 | 箍
3442 | 糨
3443 | 呱
3444 | H
3445 | G
3446 | 屿
3447 | 氡
3448 | 隘
3449 | 孰
3450 | 梆
3451 | 馬
3452 | 驭
3453 | 咧
3454 | 沮
3455 | 洱
3456 | 羹
3457 | 連
3458 | 喋
3459 | 壹
3460 | 芹
3461 | 議
3462 | 攜
3463 | 雍
3464 | 鸢
3465 | 煞
3466 | 謂
3467 | 伐
3468 | 偌
3469 | 髦
3470 | 筏
3471 | 孽
3472 | 槛
3473 | 堅
3474 | 棘
3475 | 宛
3476 | 戰
3477 | 見
3478 | 〈
3479 | 翰
3480 | 惚
3481 | 喃
3482 | 揉
3483 | 爪
3484 | 冥
3485 | 匮
3486 | 枷
3487 | 嗔
3488 | 愫
3489 | 唇
3490 | 尹
3491 | 骇
3492 | 係
3493 | 寶
3494 | 陀
3495 | 恣
3496 | 澎
3497 | 跋
3498 | 彤
3499 | 眶
3500 | 酪
3501 | 眸
3502 | 荆
3503 | 抉
3504 | 沏
3505 | 惭
3506 | 汹
3507 | 鸳
3508 | 贬
3509 | 烙
3510 | 禽
3511 | 潇
3512 | 糯
3513 | 伎
3514 | 绷
3515 | 貝
3516 | 豌
3517 | 珈
3518 | 唏
3519 | 懈
3520 | 栩
3521 | 荃
3522 | 堡
3523 | 檫
3524 | 斟
3525 | 俨
3526 | 葡
3527 | 萄
3528 | 嗜
3529 | 兹
3530 | 霍
3531 | 雌
3532 | 惺
3533 | 棠
3534 | 柠
3535 | 檬
3536 | 筱
3537 | 潸
3538 | 鐘
3539 | 鲤
3540 | 钗
3541 | 霄
3542 | B
3543 | 諵
3544 | 牟
3545 | 掠
3546 | 枣
3547 | 嚏
3548 | 轼
3549 | 蝌
3550 | 蚪
3551 | 墉
3552 | 闫
3553 | 炕
3554 | 拗
3555 | 茸
3556 | 韦
3557 | 琦
3558 | 铛
3559 | 酿
3560 | 踬
3561 | 猁
3562 | 斓
3563 | 眭
3564 | 攝
3565 | 彭
3566 | 坴
3567 | 倚
3568 | 囡
3569 | 讼
3570 | 缕
3571 | 痣
3572 | 奘
3573 | 🙄
3574 | 啷
3575 | 。
3576 | 🙂
3577 | 🏻
3578 | 🐶
3579 | 嬢
3580 | 🐛
3581 | 孃
3582 | 喵
3583 | ฅ
3584 | ⁍
3585 | ̴
3586 | ♡
3587 | ❁
3588 | ≧
3589 | ≦
3590 | 冼
3591 | 滓
3592 | 溺
3593 | 莅
3594 | 靡
3595 | 齊
3596 | 惮
3597 | 奎
3598 | 缤
3599 | 則
3600 | 畴
3601 | 牍
3602 | 蛂
3603 | 杏
3604 | 亂
3605 | 粕
3606 | 梨
3607 | 銀
3608 | 逍
3609 | 棱
3610 | 際
3611 | \
3612 | 瞪
3613 | 買
3614 | 瘫
3615 | 貴
3616 | 蚝
3617 | 逞
3618 | 卦
3619 | 蜈
3620 | 钞
3621 | 鞠
3622 | 捞
3623 | 掬
3624 | 疮
3625 | 怠
3626 | 诿
3627 | 茵
3628 | 茬
3629 | 潭
3630 |
3631 | 專
3632 | 侥
3633 | 唬
3634 | 纬
3635 | 恃
3636 | 篱
3637 | 揍
3638 | 狈
3639 | 酥
3640 | 辗
3641 | 篓
3642 | 嘶
3643 | V
3644 | 疤
3645 | 撮
3646 | 斐
3647 | 琶
3648 | 腺
3649 | 亵
3650 | 渎
3651 | 箸
3652 | 郴
3653 | 婿
3654 | 赂
3655 | `
3656 | ①
3657 | 辖
3658 | 诟
3659 | 藉
3660 | 聽
3661 | 歷
3662 | 嗷
3663 | 蜀
3664 | 盡
3665 | 帶
3666 | 憤
3667 | 齡
3668 | 贈
3669 | 忱
3670 | 匕
3671 | 蛆
3672 | 瞥
3673 | 募
3674 | 筆
3675 | 將
3676 | 積
3677 | 須
3678 | 顯
3679 | 舆
3680 | 诽
3681 | 谤
3682 | 亢
3683 | 玷
3684 | 惶
3685 | 缀
3686 | 聲
3687 | 昭
3688 | 菸
3689 | 僧
3690 | 祯
3691 | 體
3692 | 顏
3693 | 決
3694 | 睽
3695 | 铰
3696 | ︿
3697 | 擂
3698 | 淆
3699 | 泌
3700 | 襄
3701 | 樊
3702 | 哮
3703 | 僮
3704 | 節
3705 | 謀
3706 | 權
3707 | 爭
3708 | 輕
3709 | 炖
3710 | 涟
3711 | 瞅
3712 | 溫
3713 | 竽
3714 | 垄
3715 | 哐
3716 | ②
3717 | 绅
3718 | 悯
3719 | 疫
3720 | 屹
3721 | 拯
3722 | 峥
3723 | 豹
3724 | 忿
3725 | 昰
3726 | ﹗
3727 | 澄
3728 | 邂
3729 | 逅
3730 | 崭
3731 | 溯
3732 | 恸
3733 | 躯
3734 | 饕
3735 | 餮
3736 | 荫
3737 | 枚
3738 | 怯
3739 | 胤
3740 | 戮
3741 | 笺
3742 | 罕
3743 | [
3744 | ]
3745 | 抚
3746 | 沌
3747 | 佐
3748 | 痹
3749 | 哽
3750 | 叻
3751 | 拈
3752 | 赅
3753 | 炽
3754 | 湃
3755 | 酣
3756 | 漾
3757 | 芮
3758 | 熔
3759 | 阂
3760 | 驼
3761 | 噎
3762 | 藐
3763 | 刑
3764 | 仕
3765 | 祷
3766 | ╯
3767 | ╰
3768 | 睐
3769 | 俑
3770 | 纰
3771 | 瘸
3772 | 峙
3773 | 囫
3774 | 囵
3775 | 迂
3776 | 绞
3777 | 薰
3778 | 遨
3779 | 贞
3780 | 谑
3781 | 裨
3782 | 陡
3783 | 黯
3784 | 凋
3785 | 瀚
3786 | 琛
3787 | 苓
3788 | 踵
3789 | 莓
3790 | 顧
3791 | 霾
3792 | 仄
3793 | 誠
3794 | 倪
3795 | 痞
3796 | 擎
3797 | 號
3798 | 骼
3799 | 闆
3800 | 匣
3801 | 幌
3802 | 璜
3803 | و
3804 | 戳
3805 | 丐
3806 | 撵
3807 | 😞
3808 | 嘞
3809 | 黢
3810 | 晩
3811 | 诋
3812 | →
3813 | 🈶
3814 | 😈
3815 | 😨
3816 | 😋
3817 | 🙏
3818 | 😚
3819 | 魁
3820 | ̀
3821 | ́
3822 | 😆
3823 | 👌
3824 | 🌷
3825 | 💐
3826 | 🀄
3827 | ˊ
3828 | ˋ
3829 | 🤔
3830 | 💨
3831 | 💖
3832 | 甭
3833 | 涠
3834 | 炬
3835 | 廣
3836 | 犄
3837 | 婺
3838 | 耷
3839 | 兀
3840 | 诩
3841 | 逮
3842 | 浇
3843 | 摁
3844 | 瞠
3845 | 荔
3846 | 擞
3847 | 滦
3848 | 泱
3849 | 吠
3850 | 褶
3851 | 苔
3852 | 绣
3853 | 衄
3854 | 觞
3855 | 婓
3856 | 丿
3857 | 嬴
3858 | 棺
3859 | 韭
3860 | 馅
3861 | 灸
3862 | 冈
3863 | 變
3864 | 丟
3865 | 闵
3866 | 霎
3867 | ず
3868 | 掛
3869 | 證
3870 | 遲
3871 | 訓
3872 | 偕
3873 | 嫦
3874 | 娥
3875 | 恁
3876 | 廈
3877 | 廁
3878 | 盤
3879 | 緊
3880 | 餘
3881 | 納
3882 | 履
3883 | 筵
3884 | 慮
3885 | 蚣
3886 | 呸
3887 | 骷
3888 | 髅
3889 | s
3890 | p
3891 | 昙
3892 | 蹄
3893 | 泵
3894 | 渤
3895 | 妓
3896 | 毡
3897 | 砰
3898 | 砞
3899 | 琁
3900 | 畉
3901 |
3902 | 秸
3903 | ρ
3904 | ┍
3905 | 乜
3906 | 唰
3907 | 罔
3908 | 坤
3909 | 殘
3910 | ぇ
3911 | ネ
3912 | キ
3913 | τ
3914 | 漳
3915 | 拄
3916 | Y
3917 | 蚌
3918 | 嘹
3919 | 艇
3920 | 嚴
3921 | 猿
3922 | 搽
3923 | 杳
3924 | 仨
3925 | 彈
3926 | 柑
3927 | 悖
3928 | 極
3929 | 爾
3930 | 檐
3931 | 補
3932 | 蛤
3933 | 琵
3934 | 簿
3935 | 缔
3936 | 捻
3937 | 聒
3938 | 瘙
3939 | @
3940 | 淫
3941 | 拣
3942 | 秃
3943 | 蟋
3944 | 蟀
3945 | 飛
3946 | 掣
3947 | 計
3948 | 維
3949 | 矢
3950 | 佃
3951 | 碴
3952 | 镀
3953 | 咎
3954 | 阙
3955 | 秽
3956 | 寬
3957 | 釋
3958 | 圬
3959 | 臆
3960 | 娶
3961 | 祠
3962 | 牯
3963 | 燈
3964 | 牆
3965 | 噻
3966 | 憨
3967 | 蹂
3968 | 躏
3969 | 搔
3970 | 灑
3971 | 損
3972 | 仟
3973 | 圓
3974 | 姗
3975 | 浃
3976 | 吩
3977 | R
3978 | 荞
3979 | 硅
3980 | 浔
3981 | 函
3982 | 沆
3983 | 瀣
3984 | 靶
3985 | 塊
3986 | 滕
3987 | 嵋
3988 | 勁
3989 | 蠻
3990 | 曬
3991 | 臥
3992 | 檢
3993 | 稱
3994 | 協
3995 | 參
3996 | 蟠
3997 | 锺
3998 | 叩
3999 | 玺
4000 | 臊
4001 | 絡
4002 | 訴
4003 | ℃
4004 | 遐
4005 | 宦
4006 | 咆
4007 | 窩
4008 | 並
4009 | 項
4010 | 與
4011 | 譯
4012 | 屢
4013 | 試
4014 | 紊
4015 | 奠
4016 | 講
4017 | 遠
4018 |
4019 | 漪
4020 | 鸽
4021 | 咙
4022 | 館
4023 | 勃
4024 | 炙
4025 | 殉
4026 | 谙
4027 | 帜
4028 | 鹩
4029 | 勋
4030 | 缥
4031 | 缈
4032 | 虔
4033 | 椰
4034 | 俭
4035 | 麟
4036 | 蠡
4037 | 袱
4038 | 邑
4039 | 缜
4040 | 焙
4041 | 垒
4042 | 荧
4043 | 谚
4044 | 嗲
4045 | 俪
4046 | 烨
4047 | 砺
4048 | 貂
4049 | 巅
4050 | 踮
4051 | 瞭
4052 | 潦
4053 | 盂
4054 | 镯
4055 | 簪
4056 | 禛
4057 | 蹉
4058 | 跎
4059 | 襟
4060 | 阑
4061 | 瑗
4062 | 纫
4063 | 邵
4064 | 剁
4065 | 葳
4066 | 杉
4067 | 阎
4068 | 瞩
4069 | 紀
4070 | 頁
4071 | 绸
4072 | 撅
4073 | 涣
4074 | 匝
4075 | 刨
4076 | 罹
4077 | 铸
4078 | 弈
4079 | 娅
4080 | 湛
4081 |
4082 | 獾
4083 | 祉
4084 | 嗣
4085 | 摒
4086 | 鄂
4087 | 瓴
4088 | 谆
4089 | 氦
4090 | 鼹
4091 | 醍
4092 | 醐
4093 | 砭
4094 | 蜻
4095 | 蜓
4096 | ╮
4097 | ╭
4098 | 榭
4099 | 黛
4100 | 彷
4101 | 株
4102 | 鐵
4103 | 俞
4104 | 懑
4105 | 姥
4106 | 榕
4107 | 曝
4108 | 锢
4109 | 焰
4110 | 妃
4111 | 匿
4112 | 帚
4113 | 绽
4114 | 遛
4115 | 噌
4116 | 碘
4117 | 芽
4118 | 缅
4119 | 笈
4120 | 迥
4121 | 鞅
4122 | 島
4123 | 樂
4124 | 紅
4125 | 戆
4126 | 凇
4127 | 囱
4128 | 缄
4129 | 崎
4130 | 桀
4131 | 骜
4132 | 顷
4133 | 瀛
4134 | 垚
4135 | 蛐
4136 | 膳
4137 | 蜿
4138 | 蜒
4139 | 枋
4140 | 锲
4141 | 迢
4142 | 肢
4143 | 皖
4144 | 胄
4145 | W
4146 | 詹
4147 | 淙
4148 | 坂
4149 | 潺
4150 | 沁
4151 | 瞿
4152 | 袄
4153 | 衩
4154 | 褪
4155 | 茱
4156 | 揶
4157 | 揄
4158 | 辫
4159 | 狄
4160 | 妊
4161 | 娠
4162 | 绊
4163 | 璐
4164 | 鸾
4165 | 靜
4166 | 袅
4167 | 咏
4168 | 昼
4169 | 篆
4170 | 冢
4171 | 鱿
4172 | 菁
4173 | 跻
4174 | 媽
4175 | 硝
4176 | 箫
4177 | 佷
4178 | 蘑
4179 | 傣
4180 | 腦
4181 | 葆
4182 | 殿
4183 | 羌
4184 | 篝
4185 | 彧
4186 | ゴ
4187 | 陇
4188 | 媪
4189 | お
4190 | 炭
4191 | 栗
4192 | 褣
4193 | 掞
4194 | 汲
4195 | 蒜
4196 | 牡
4197 | 榉
4198 | 葵
4199 | 镶
4200 | 纨
4201 | 绔
4202 | 皎
4203 | 廓
4204 | 盥
4205 | 诰
4206 | 園
4207 | 優
4208 | ★
4209 | 陽
4210 | 親
4211 | 鸥
4212 | 煦
4213 | 適
4214 | 霓
4215 | 護
4216 | 膝
4217 | 傢
4218 | 魍
4219 | 魉
4220 | 垣
4221 | 資
4222 | 陣
4223 | 釵
4224 | 蓥
4225 | 粟
4226 | 讷
4227 | 😢
4228 | 嚎
4229 | 堑
4230 | 糠
4231 | ӧ
4232 | 苤
4233 | 🔒
4234 | 岀
4235 | ⭐
4236 | 喆
4237 | 膈
4238 | 嗑
4239 | 谍
4240 | 嘤
4241 | 💔
4242 | 窖
4243 | 😰
4244 | 擠
4245 | 💘
4246 | 猖
4247 | 噁
4248 | 💩
4249 | 簌
4250 | 負
4251 | 導
4252 | 達
4253 | 咩
4254 | 嗞
4255 | 👿
4256 | 乂
4257 | 💯
4258 | ԅ
4259 | ¯
4260 | ✲
4261 | ゚
4262 | す
4263 | 罒
4264 | 😝
4265 | 撸
4266 | ε
4267 | ó
4268 | ∀
4269 | ・
4270 | 🚽
4271 | ▼
4272 | 🚇
4273 | ^
4274 | 敝
4275 | 恵
4276 | 粼
4277 | ͈
4278 | ᴗ
4279 | º
4280 | ❛
4281 | 倩
4282 | Ő
4283 | 😬
4284 | 喱
4285 | 💗
4286 | ง
4287 | ็
4288 | ✧
4289 | 锏
4290 | 螯
4291 | 嚓
4292 | 兒
4293 | 涅
4294 | 碶
4295 | 箔
4296 | 虱
4297 | 驹
4298 | 枳
4299 | 咝
4300 | 倛
4301 | 婄
4302 | 涴
4303 | 觓
4304 | 軘
4305 | 郔
4306 | 蹿
4307 | 幣
4308 | 簽
4309 | 週
4310 | 詢
4311 | 懶
4312 | 統
4313 | 诲
4314 | 捱
4315 | 銷
4316 | 聯
4317 | 繫
4318 | 貨
4319 | 審
4320 | 痪
4321 | 數
4322 | 驐
4323 | 擀
4324 | 吆
4325 | 胚
4326 | 廚
4327 | 爐
4328 | 憐
4329 | 闊
4330 | 貼
4331 | 飲
4332 | 濟
4333 | 飨
4334 | 灘
4335 | 溝
4336 | 扳
4337 | 祑
4338 | 筳
4339 |
4340 | 疍
4341 |
4342 |
4343 |
4344 |
4345 | ⊿
4346 | 琌
4347 |
4348 | 瞊
4349 | ∣
4350 | 続
4351 |
4352 |
4353 | 皊
4354 | 讚
4355 | 綵
4356 | 霆
4357 | 荟
4358 | 萃
4359 | 吋
4360 | 贻
4361 | 赳
4362 | 墊
4363 | 飾
4364 | 濱
4365 | 劈
4366 | 䜣
4367 | 黟
4368 | K
4369 |
4370 | 覌
4371 | 龇
4372 | 缉
4373 | 枭
4374 | 責
4375 | 啞
4376 | 黃
4377 | 挎
4378 | 埸
4379 | 赊
4380 | 羆
4381 | 狝
4382 |
4383 |
4384 |
4385 |
4386 |
4387 | 穨
4388 | 筁
4389 |
4390 | 胕
4391 | 磌
4392 | 類
4393 | 剛
4394 | 刽
4395 | 涼
4396 | 洌
4397 | 滲
4398 | 蹟
4399 | 邢
4400 | 擋
4401 | 濕
4402 | 漬
4403 | 嘚
4404 | 晤
4405 | 樯
4406 | 橹
4407 | 帳
4408 | 撥
4409 | 灣
4410 | 铲
4411 | 緩
4412 | 汝
4413 | 鄱
4414 | 跡
4415 | 寢
4416 | 銹
4417 | 減
4418 | 賠
4419 | 償
4420 | 軟
4421 | 擔
4422 | 憂
4423 | 瘀
4424 | 卤
4425 | 锥
4426 | 馄
4427 | 饨
4428 | $
4429 | 邡
4430 | 賓
4431 | 誇
4432 | 炝
4433 | 蟊
4434 | g
4435 | 沖
4436 | 聨
4437 | 擊
4438 | 掦
4439 | 葺
4440 | 绯
4441 | 腳
4442 | 雞
4443 | 瘋
4444 | 謹
4445 | 勸
4446 | 狀
4447 | 運
4448 | 獻
4449 | 饵
4450 | 嗤
4451 | 熹
4452 | 祀
4453 | 陸
4454 | 髮
4455 | 搀
4456 |
4457 | 翴
4458 |
4459 |
4460 | 狹
4461 | ﹡
4462 | 礛
4463 | 逾
4464 | 註
4465 | 畫
4466 | 農
4467 | 煸
4468 | 忝
4469 | 倨
4470 | 俾
4471 | 睨
4472 | 煩
4473 | 異
4474 | 韶
4475 | 勢
4476 | 舵
4477 | 涿
4478 | 蚩
4479 | 孢
4480 | 瘆
4481 | 偎
4482 | 茴
4483 | 讴
4484 | 陳
4485 | 纂
4486 | 妍
4487 | 纭
4488 | 佘
4489 | 囤
4490 | 蓦
4491 | 瞑
4492 | 吨
4493 | 惇
4494 | 唔
4495 | 蝉
4496 | 吕
4497 | 驮
4498 | 珂
4499 | 迭
4500 | 戛
4501 | 钰
4502 | 陨
4503 | 亘
4504 | 脈
4505 | 啓
4506 | 伶
4507 | 仃
4508 | 拮
4509 | 澂
4510 | 虢
4511 | 刍
4512 | 稔
4513 | 蕙
4514 | 娆
4515 | 耕
4516 | Ⅰ
4517 | 蹴
4518 | 濑
4519 | 畜
4520 | 鸫
4521 | 擺
4522 | 隨
4523 | 筐
4524 | 祁
4525 | 栎
4526 | 丞
4527 | 羲
4528 | 抨
4529 | 衮
4530 | 蘅
4531 | 斧
4532 | 麒
4533 | 婵
4534 | 鳕
4535 | 嘣
4536 | 倌
4537 | 凈
4538 | 玑
4539 | 斡
4540 | 芭
4541 | 戾
4542 | 镖
4543 | 箴
4544 | 涎
4545 | 蚀
4546 | 卉
4547 | 钛
4548 | 鸵
4549 | 赎
4550 | 擒
4551 | 矽
4552 | 邃
4553 | 棣
4554 | 璠
4555 | 靳
4556 | 皓
4557 | 寇
4558 | 蚱
4559 | 谪
4560 | 帷
4561 | 幄
4562 | 赁
4563 | 竺
4564 | 怦
4565 | 稣
4566 | 屝
4567 | 岚
4568 | 眯
4569 | 鹌
4570 | 鹑
4571 | 眨
4572 | 墈
4573 | 約
4574 | 谀
4575 | 苕
4576 | 漢
4577 | ㄧ
4578 | 坳
4579 | 粽
4580 | 裘
4581 | 佻
4582 | 孵
4583 | 畿
4584 | 啻
4585 | 妾
4586 | 夙
4587 | 曳
4588 | 踌
4589 | 躇
4590 | 勞
4591 | 荀
4592 | 倭
4593 | 勝
4594 | 脐
4595 | 萤
4596 | 尧
4597 | 舜
4598 | 菱
4599 | 蝎
4600 | │
4601 | 杖
4602 | 亩
4603 | 嵇
4604 | 茗
4605 | 缢
4606 | 莠
4607 | 徨
4608 | 蝼
4609 | 菅
4610 | 腑
4611 | 踊
4612 | 颊
4613 | 靴
4614 | 鲸
4615 | 秫
4616 | 肾
4617 | 沂
4618 | 錡
4619 | 掷
4620 | 骰
4621 | 谄
4622 | 隼
4623 | 隽
4624 | 薏
4625 | 嬷
4626 | 耒
4627 | 悼
4628 | 瞳
4629 | 盎
4630 | 摈
4631 | 孱
4632 | 沅
4633 | 氿
4634 | 彗
4635 | 捺
4636 | 暨
4637 | 鳖
4638 | 鹊
4639 | 髻
4640 | 叟
4641 | 俚
4642 | 绫
4643 | 煜
4644 | 擾
4645 | 逵
4646 | 伉
4647 | 晖
4648 | 灏
4649 | 醇
4650 | 癀
4651 | 蛳
4652 | 珉
4653 | 锒
4654 | 埂
4655 | 溉
4656 | 撷
4657 | 慵
4658 | 遏
4659 | 嫘
4660 | 囿
4661 | 賺
4662 | 淚
4663 | 獨
4664 | 魇
4665 | 铎
4666 | 缎
4667 | 捍
4668 | 恙
4669 | 茯
4670 | 唾
4671 | 旱
4672 | 轶
4673 | 氰
4674 | 胺
4675 | 昕
4676 | 琥
4677 | 徜
4678 | 徉
4679 | 揽
4680 | 蹇
4681 | 庚
4682 | 旭
4683 | 孚
4684 | 锄
4685 | 谗
4686 | 錚
4687 | 瑣
4688 | 嬗
4689 | 遺
4690 | 術
4691 | 甸
4692 | 毓
4693 | 檀
4694 | 拂
4695 | 庋
4696 | 粱
4697 | 夭
4698 | 怢
4699 | 嶱
4700 | 宎
4701 | 眒
4702 | 嶲
4703 | 斮
4704 | 疶
4705 | 芵
4706 | 綎
4707 | 稛
4708 | 茞
4709 | 淩
4710 | 桸
4711 | 酕
4712 | 毞
4713 | 豖
4714 | 弇
4715 | 瘤
4716 | 猾
4717 | 徙
4718 | 寐
4719 | 羔
4720 | 肽
4721 | 孑
4722 | h
4723 | i
4724 | n
4725 | k
4726 | a
4727 | d
4728 | 榴
4729 | 羸
4730 | 慑
4731 | 囚
4732 | 矗
4733 | 铮
4734 | 倘
4735 | 佯
4736 | 猥
4737 | 磋
4738 | 學
4739 | 趕
4740 | 賞
4741 | 嵊
4742 | 鳶
4743 | 『
4744 | 』
4745 | 骥
4746 | 锂
4747 | 颏
4748 | 禟
4749 | 嫻
4750 | 徹
4751 | 弓
4752 | 恤
4753 | 骋
4754 | 鳄
4755 | 駕
4756 | 霁
4757 | 趾
4758 | 糜
4759 | 磣
4760 | 檔
4761 | 擬
4762 | 儀
4763 | 汞
4764 | 俎
4765 | 濡
4766 | 镛
4767 | 岖
4768 | 侷
4769 | 綠
4770 | 構
4771 | 黠
4772 | 勐
4773 | 垅
4774 | 槐
4775 | 刖
4776 | 飓
4777 | 饋
4778 | 萦
4779 | 吒
4780 | 迸
4781 | 凛
4782 | 倜
4783 | 傥
4784 | 珏
4785 | 婢
4786 | 瓢
4787 | 芡
4788 | 焯
4789 | 呒
4790 | 酵
4791 | 忖
4792 | 賬
4793 | 矜
4794 | 峻
4795 | 掇
4796 | 谏
4797 | 偉
4798 | 詞
4799 | 頓
4800 | 諾
4801 | 獎
4802 | 執
4803 | 閃
4804 | 撲
4805 | 襲
4806 | 彪
4807 | 抺
4808 | 拴
4809 | 捎
4810 | 哔
4811 | 欸
4812 |
4813 | 捋
4814 | 烬
4815 | 🌟
4816 | 🍄
4817 | 掐
4818 | 霹
4819 | 雳
4820 | 蜷
4821 | 🤙
4822 | 😅
4823 | 🤷
4824 |
4825 | ♀
4826 | ⃣
4827 | ﹏
4828 | 💡
4829 | 🌝
4830 | 讥
4831 | 💆
4832 | 灬
4833 | 😪
4834 | 梗
4835 | 睫
4836 | 匾
4837 | ☝
4838 | 扈
4839 | 胩
4840 | ❌
4841 | ☄
4842 | 龅
4843 | 叵
4844 | 橇
4845 | 呪
4846 | 📺
4847 | 丶
4848 | 𣎴
4849 | 䃼
4850 | 誤
4851 | 慶
4852 | 師
4853 | 終
4854 | 譜
4855 | 脅
4856 | 順
4857 | 驗
4858 | 颧
4859 | 蚕
4860 | 👊
4861 | 🚧
4862 | 獗
4863 | 犟
4864 | 🔑
4865 | 😥
4866 | 漕
4867 | 懊
4868 | 噗
4869 | 欻
4870 | 簇
4871 | 😩
4872 | 😫
4873 | 💰
4874 | 蔗
4875 | 呤
4876 | 旮
4877 | 旯
4878 | 蹾
4879 | 碱
4880 | 槟
4881 | Ω
4882 | 氺
4883 | 椎
4884 | 😳
4885 | 㐅
4886 | 🏪
4887 | 囗
4888 | 㟍
4889 | 🎉
4890 | 😛
4891 | 蛟
4892 | 腌
4893 | 啾
4894 | 🙊
4895 | ㅂ
4896 | に
4897 | か
4898 | っ
4899 | た
4900 | で
4901 | よ
4902 | ね
4903 | あ
4904 | り
4905 | が
4906 | と
4907 | う
4908 | ご
4909 | ざ
4910 | い
4911 | ま
4912 | 磅
4913 | 💛
4914 | 😌
4915 | 璾
4916 | 🍺
4917 | 岔
4918 | 拚
4919 | 焗
4920 | 🉐
4921 | 吖
4922 | づ
4923 | ど
4924 | 柚
4925 | 🚗
4926 | ☕
4927 | 皿
4928 | ₃
4929 | ۶
4930 | з
4931 | 攸
4932 | 犷
4933 | 👉
4934 | 👈
4935 | 冮
4936 | ❀
4937 | 燜
4938 | 賣
4939 | 婊
4940 | 💁
4941 | 睦
4942 | 💊
4943 | 👄
4944 | 😶
4945 | ௰
4946 | 🔻
4947 | 🌚
4948 | 👋
4949 | 菠
4950 | 👻
4951 | 💕
4952 | 珊
4953 | 💜
4954 | 💞
4955 | 撘
4956 | 淇
4957 | 🌸
4958 | 殺
4959 | 遊
4960 | 🙈
4961 | 👧
4962 | 懿
4963 | 〜
4964 | 碚
4965 | 砚
4966 |
--------------------------------------------------------------------------------
/data/processing.py:
--------------------------------------------------------------------------------
1 | #!/user/bin/env python3
2 | # -*- coding: utf-8 -*-
3 | # @Time : 2020/2/13 0013 13:20
4 | # @Author : CarryChang
5 | # @Software: PyCharm
6 | # @email: coolcahng@gmail.com
7 | # @web :CarryChang.top
8 | def file_read(number,path):
9 | pos_val = []
10 | with open(path, 'r', encoding='utf-8') as content:
11 | for con1 in content.readlines()[:number]:
12 | pos_val.append(con1.strip())
13 | return pos_val
14 | # if __name__ == '__main__':
15 | # number = 100
16 | # path = '1-1.txt'
17 | # content = file_read(number,path)
18 | # print(len(content))
19 | # print(content)
--------------------------------------------------------------------------------
/model/cnn_model.py:
--------------------------------------------------------------------------------
1 | # coding: utf-8
2 | import tensorflow as tf
3 | class TCNNConfig(object):
4 | """CNN配置参数"""
5 | embedding_dim = 300 # 词向量维度
6 | seq_length = 200 # 序列长度
7 | num_classes = 2 # 类别数
8 | num_filters = 512 # 卷积核数目
9 | kernel_size = 4 # 卷积核尺寸
10 | vocab_size = 5000 # 词汇表大小
11 | hidden_dim = 512 # 全连接层神经元
12 | dropout_keep_prob = 0.1 # dropout保留比例
13 | learning_rate = 1e-4 # 学习率
14 | batch_size = 512 # 每批训练大小
15 | num_epochs = 30 # 总迭代轮次
16 | print_per_batch = 64 # 每多少轮输出一次结果
17 | save_per_batch = 128 # 每多少轮存入tensorboard
18 | class TextCNN(object):
19 | """文本分类,CNN模型"""
20 | def __init__(self, config):
21 | self.config = config
22 | # 三个待输入的数据
23 | self.softmax_tensor1 = None
24 | self.input_x = tf.placeholder(tf.int32, [None, self.config.seq_length], name='input_x')
25 | self.input_y = tf.placeholder(tf.float32, [None, self.config.num_classes], name='input_y')
26 | self.keep_prob = tf.placeholder(tf.float32, name='keep_prob')
27 | self.cnn()
28 | def cnn(self):
29 | """CNN模型"""
30 | # 词向量映射,使用GPU
31 | with tf.device('/gpu:0'):
32 | embedding = tf.get_variable('embedding', [self.config.vocab_size, self.config.embedding_dim])
33 | embedding_inputs = tf.nn.embedding_lookup(embedding, self.input_x)
34 | # 单层cnn,一层convolutin layer,一层max_pooling
35 | with tf.name_scope("cnn"):
36 | # CNN layer
37 | conv = tf.layers.conv1d(embedding_inputs, self.config.num_filters, self.config.kernel_size, name='conv')
38 | # global max pooling layer
39 | gmp = tf.reduce_max(conv, reduction_indices=[1], name='gmp')
40 | with tf.name_scope("score"):
41 | # 全连接层,后面接dropout以及relu激活
42 | fc = tf.layers.dense(gmp, self.config.hidden_dim, name='fc1')
43 | fc = tf.contrib.layers.dropout(fc, self.keep_prob)
44 | fc = tf.nn.relu(fc)
45 | # 分类器
46 | self.logits = tf.layers.dense(fc, self.config.num_classes, name='fc2')
47 | self.softmax_tensor1 = tf.nn.softmax(self.logits)
48 | self.y_pred_cls = tf.argmax(tf.nn.softmax(self.logits), 1)
49 | with tf.name_scope("optimize"):
50 | # 损失函数,交叉熵
51 | cross_entropy = tf.nn.softmax_cross_entropy_with_logits_v2(logits=self.logits, labels=self.input_y)
52 | self.loss = tf.reduce_mean(cross_entropy)
53 | # 优化器
54 | self.optim = tf.train.AdamOptimizer(learning_rate=self.config.learning_rate).minimize(self.loss)
55 | with tf.name_scope("accuracy"):
56 | # 准确率
57 | correct_pred = tf.equal(tf.argmax(self.input_y, 1), self.y_pred_cls)
58 | self.acc = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
59 |
60 | # Confusion Matrix...
61 | # [[1985 15]
62 | # [ 24 1976]]
63 |
--------------------------------------------------------------------------------
/model/data_loader.py:
--------------------------------------------------------------------------------
1 | # coding: utf-8
2 | import sys
3 | from collections import Counter
4 | import numpy as np
5 | import tensorflow.contrib.keras as kr
6 | def open_file(filename, mode='r'):
7 | return open(filename, mode, encoding='utf-8', errors='ignore')
8 | def read_file(filename):
9 | """读取文件数据"""
10 | contents, labels = [], []
11 | with open_file(filename) as f:
12 | for line in f:
13 | try:
14 | label, content = line.strip().split('\t')
15 | if content:
16 | contents.append(list(content))
17 | labels.append(label)
18 | except:
19 | pass
20 | return contents, labels
21 | def build_vocab(train_dir, vocab_dir, vocab_size=5000):
22 | """根据训练集构建词汇表,存储"""
23 | data_train, _ = read_file(train_dir)
24 | all_data = []
25 | for content in data_train:
26 | all_data.extend(content)
27 | counter = Counter(all_data)
28 | count_pairs = counter.most_common(vocab_size - 1)
29 | words, _ = list(zip(*count_pairs))
30 | # 添加一个 来将所有文本pad为同一长度
31 | words = [''] + list(words)
32 | open_file(vocab_dir, mode='w').write('\n'.join(words) + '\n')
33 | def read_vocab(vocab_dir):
34 | """读取词汇表"""
35 | # words = open_file(vocab_dir).read().strip().split('\n')
36 | with open_file(vocab_dir) as fp:
37 | # 如果是py2 则每个值都转化为unicode
38 | words = [_.strip() for _ in fp.readlines()]
39 | word_to_id = dict(zip(words, range(len(words))))
40 | return words, word_to_id
41 | def read_category():
42 | """读取分类目录,固定"""
43 | categories = ['1', '5']
44 | categories = [x for x in categories]
45 | cat_to_id = dict(zip(categories, range(len(categories))))
46 | return categories, cat_to_id
47 | def to_words(content, words):
48 | """将id表示的内容转换为文字"""
49 | return ''.join(words[x] for x in content)
50 | def process_file(filename, word_to_id, cat_to_id, max_length=200):
51 | """将文件转换为id表示"""
52 | contents, labels = read_file(filename)
53 | data_id, label_id = [], []
54 | for i in range(len(contents)):
55 | data_id.append([word_to_id[x] for x in contents[i] if x in word_to_id])
56 | label_id.append(cat_to_id[labels[i]])
57 | # 使用keras提供的pad_sequences来将文本pad为固定长度
58 | x_pad = kr.preprocessing.sequence.pad_sequences(data_id, max_length)
59 | y_pad = kr.utils.to_categorical(label_id, num_classes=len(cat_to_id)) # 将标签转换为one-hot表示
60 | return x_pad, y_pad
61 | def batch_iter(x, y, batch_size=64):
62 | """生成批次数据"""
63 | data_len = len(x)
64 | num_batch = int((data_len - 1) / batch_size) + 1
65 | indices = np.random.permutation(np.arange(data_len))
66 | x_shuffle = x[indices]
67 | y_shuffle = y[indices]
68 | for i in range(num_batch):
69 | start_id = i * batch_size
70 | end_id = min((i + 1) * batch_size, data_len)
71 | yield x_shuffle[start_id:end_id], y_shuffle[start_id:end_id]
72 |
--------------------------------------------------------------------------------
/model/data_processing.py:
--------------------------------------------------------------------------------
1 | # coding: utf-8
2 | import sys
3 | from collections import Counter
4 | import numpy as np
5 | import tensorflow.contrib.keras as kr
6 | def read_file(filename):
7 | """读取文件数据"""
8 | contents, labels = [], []
9 | with open(filename, encoding='utf-8') as f:
10 | for line in f:
11 | try:
12 | label, content = line.strip().split('\t')
13 | if content:
14 | contents.append(list(content))
15 | labels.append(label)
16 | except:
17 | pass
18 | return contents, labels
19 | def build_vocab(train_dir, vocab_dir, vocab_size=5000):
20 | """根据训练集构建词汇表,存储"""
21 | data_train, _ = read_file(train_dir)
22 | all_data = []
23 | for content in data_train:
24 | all_data.extend(content)
25 | counter = Counter(all_data)
26 | count_pairs = counter.most_common(vocab_size - 1)
27 | words, _ = list(zip(*count_pairs))
28 | # 添加一个 来将所有文本pad为同一长度
29 | words = [''] + list(words)
30 | open(vocab_dir, 'w', encoding='utf-8').write('\n'.join(words) + '\n')
31 | def read_vocab(vocab_dir):
32 | """读取词汇表"""
33 | # words = open_file(vocab_dir).read().strip().split('\n')
34 | with open(vocab_dir,encoding='utf-8') as fp:
35 | # 如果是py2 则每个值都转化为unicode
36 | words = [_.strip() for _ in fp.readlines()]
37 | word_to_id = dict(zip(words, range(len(words))))
38 | return words, word_to_id
39 | def read_category():
40 | """读取分类目录,固定"""
41 | categories = ['1', '5']
42 | categories = [x for x in categories]
43 | cat_to_id = dict(zip(categories, range(len(categories))))
44 | return categories, cat_to_id
45 | def to_words(content, words):
46 | """将id表示的内容转换为文字"""
47 | return ''.join(words[x] for x in content)
48 | def process_file(filename, word_to_id, cat_to_id, max_length=100):
49 | """将文件转换为id表示"""
50 | contents, labels = read_file(filename)
51 | data_id, label_id = [], []
52 | for i in range(len(contents)):
53 | data_id.append([word_to_id[x] for x in contents[i] if x in word_to_id])
54 | label_id.append(cat_to_id[labels[i]])
55 | x_pad = kr.preprocessing.sequence.pad_sequences(data_id, max_length)
56 | # 将标签转换为one-hot表示
57 | y_pad = kr.utils.to_categorical(label_id, num_classes=len(cat_to_id))
58 | return x_pad, y_pad
59 | def batch_iter(x, y, batch_size=64):
60 | """生成批次数据"""
61 | data_len = len(x)
62 | num_batch = int((data_len - 1) / batch_size) + 1
63 | indices = np.random.permutation(np.arange(data_len))
64 | x_shuffle = x[indices]
65 | y_shuffle = y[indices]
66 | for i in range(num_batch):
67 | start_id = i * batch_size
68 | end_id = min((i + 1) * batch_size, data_len)
69 | yield x_shuffle[start_id:end_id], y_shuffle[start_id:end_id]
70 |
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/pic/api.png:
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https://raw.githubusercontent.com/CarryChang/EasyUse_FastApi/HEAD/pic/api.png
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/pic/backend.png:
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https://raw.githubusercontent.com/CarryChang/EasyUse_FastApi/HEAD/pic/backend.png
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/pic/inference.png:
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https://raw.githubusercontent.com/CarryChang/EasyUse_FastApi/HEAD/pic/inference.png
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/requirement.txt:
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1 | uvicorn
2 | fastapi
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