-
Notifications
You must be signed in to change notification settings - Fork 1
Expand file tree
/
Copy pathindex.html
More file actions
662 lines (424 loc) · 24.6 KB
/
Copy pathindex.html
File metadata and controls
662 lines (424 loc) · 24.6 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
<!DOCTYPE html>
<html class="has-navbar-fixed-top">
<head>
<meta charset="utf-8">
<title>黎光</title>
<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1">
<link rel="stylesheet" href="//cdnjs.cloudflare.com/ajax/libs/outdated-browser/1.1.5/outdatedbrowser.min.css">
<link rel="icon" href="/favicon.png">
<link rel="stylesheet" href="//fonts.googleapis.com/css?family=Ovo|Source+Code+Pro">
<link rel="stylesheet" href="//cdnjs.cloudflare.com/ajax/libs/bulma/0.6.2/css/bulma.min.css">
<link rel="stylesheet" href="//cdnjs.cloudflare.com/ajax/libs/lightgallery/1.6.8/css/lightgallery.min.css">
<link rel="stylesheet" href="//cdnjs.cloudflare.com/ajax/libs/justifiedGallery/3.6.5/css/justifiedGallery.min.css">
<link rel="stylesheet" href="/css/style.css">
<script defer src="//use.fontawesome.com/releases/v5.0.8/js/all.js"></script>
</head>
<body>
<nav class="navbar is-transparent is-fixed-top navbar-main" role="navigation" aria-label="main navigation">
<div class="container">
<div class="navbar-brand">
<a class="navbar-item navbar-logo" href="/">
黎光
</a>
<div class="navbar-burger">
<span></span>
<span></span>
<span></span>
</div>
</div>
<div class="navbar-menu navbar-start">
<a class="navbar-item "
href="/archives">Archives</a>
</div>
<div class="navbar-menu navbar-end">
<a class="navbar-item search" href="javascript:;">
<i class="fas fa-search"></i>
</a>
<a class="navbar-item" href="https://github.com/bacterous">
<i class="fab fa-github"></i>
</a>
</div>
</div>
</nav>
<section class="section">
<div class="container">
<article class="article content gallery" itemscope itemprop="blogPost">
<h1 class="article-title is-size-3 is-size-4-mobile" itemprop="name">
<a href="/2018/09/25/Implicit-3D-Orientation-Learning-for-6D-Object-Detection-from-RGB-Images论文笔记/" itemprop="url">Implicit 3D Orientation Learning for 6D Object Detection from RGB Images论文笔记</a>
</h1>
<div class="article-meta columns is-variable is-1 is-multiline is-mobile is-size-7-mobile">
<span class="column is-narrow">
<time datetime="2018-09-25T14:27:09.000Z" itemprop="datePublished">16 天前</time>
</span>
<span class="column is-narrow article-category">
<i class="far fa-folder"></i>
<a class="article-category-link" href="/categories/Deep-Learning/">Deep Learning</a>
</span>
<span class="column is-narrow">
42 分钟 读完 (约 6260 字)
</span>
</div>
<div class="article-entry is-size-6-mobile" itemprop="articleBody">
<blockquote>
<p><a href="http://openaccess.thecvf.com/content_ECCV_2018/html/Martin_Sundermeyer_Implicit_3D_Orientation_ECCV_2018_paper.html" target="_blank" rel="noopener">论文地址</a></p>
<p>注：本文谨代表笔者观点，水平有限，若有不足及疏忽之处，诚请批评指正</p>
</blockquote>
<h2 id="Abstract"><a href="#Abstract" class="headerlink" title="Abstract"></a>Abstract</h2><p>提出一个RGB-based的实时目标检测和6D姿态估计pipeline。这个新型3D的目标朝向估计（orientation estimation）方法基于去噪自编码器的一个变体，其采用域随机（Domain Randomization）在3D模型的模拟视图上训练，称之为Augmented Autoencoder。与现有方法相比，它的优势在于：无需真实、带姿态标注的训练数据；可泛化至多种测试传感器，并能够内在地（inherently）处理目标与视图的对称性问题。不需学习一个从输入图像到目标姿态的显式映射，本方法给出了目标朝向的隐式表征（implicit representations），由隐空间（latent space）的样本定义。基于 T-LESS 和 LineMOD 数据集的实验表明所提的方法不仅比类似的基于模型的方法有更好的表现，而且表现也接近目前顶级的、需要真实的姿态标注图像的方法。</p>
<p class="article-more-link">
<a href="/2018/09/25/Implicit-3D-Orientation-Learning-for-6D-Object-Detection-from-RGB-Images论文笔记/#more">阅读更多</a>
</p>
</div>
</article>
<article class="article content gallery" itemscope itemprop="blogPost">
<h1 class="article-title is-size-3 is-size-4-mobile" itemprop="name">
<a href="/2018/09/25/Deep-Forest论文笔记/" itemprop="url">Deep Forest论文笔记</a>
</h1>
<div class="article-meta columns is-variable is-1 is-multiline is-mobile is-size-7-mobile">
<span class="column is-narrow">
<time datetime="2018-09-25T14:13:52.000Z" itemprop="datePublished">16 天前</time>
</span>
<span class="column is-narrow article-category">
<i class="far fa-folder"></i>
<a class="article-category-link" href="/categories/Deep-Learning/">Deep Learning</a>
</span>
<span class="column is-narrow">
26 分钟 读完 (约 3860 字)
</span>
</div>
<div class="article-entry is-size-6-mobile" itemprop="articleBody">
<blockquote>
<p>论文链接<a href="https://arxiv.org/abs/1702.08835" target="_blank" rel="noopener">https://arxiv.org/abs/1702.08835</a></p>
<p>注：本文谨代表笔者观点，水平有限，若有不足及疏忽之处，诚请批评指正</p>
</blockquote>
<h2 id="Abstract"><a href="#Abstract" class="headerlink" title="Abstract"></a>Abstract</h2><ul>
<li><p>尝试用不可微模块建立深度模型</p>
</li>
<li><p>推测DNNs成功的秘密在于：</p>
<ul>
<li>layer by layer processing</li>
<li>in-model feature transformation</li>
<li>sufficient model complexity</li>
</ul>
</li>
<li><p>提出gcForest，决策树集合方法，比DNNs更少的超参数，模型复杂度依据数据自动调整。采用默认参数设置，对于不同领域各种类型的数据，在大部分情况下相当鲁棒。</p>
</li>
</ul>
<p class="article-more-link">
<a href="/2018/09/25/Deep-Forest论文笔记/#more">阅读更多</a>
</p>
</div>
</article>
<article class="article content gallery" itemscope itemprop="blogPost">
<h1 class="article-title is-size-3 is-size-4-mobile" itemprop="name">
<a href="/2018/09/13/DBSCAN聚类/" itemprop="url">DBSCAN聚类</a>
</h1>
<div class="article-meta columns is-variable is-1 is-multiline is-mobile is-size-7-mobile">
<span class="column is-narrow">
<time datetime="2018-09-13T13:04:09.000Z" itemprop="datePublished">1 个月前</time>
</span>
<span class="column is-narrow article-category">
<i class="far fa-folder"></i>
<a class="article-category-link" href="/categories/Machine-Learning/">Machine Learning</a>
</span>
<span class="column is-narrow">
18 分钟 读完 (约 2750 字)
</span>
</div>
<div class="article-entry is-size-6-mobile" itemprop="articleBody">
<p>DBSCAN(Density-Based Spatial Clustering of Applications with Noise，具有噪声的基于密度的聚类方法)是一种很典型的密度聚类算法，和K-Means，BIRCH这些一般只适用于凸样本集的聚类相比，DBSCAN既可以适用于凸样本集，也可以适用于非凸样本集。下面我们就对DBSCAN算法的原理做一个总结。</p>
<p class="article-more-link">
<a href="/2018/09/13/DBSCAN聚类/#more">阅读更多</a>
</p>
</div>
</article>
<article class="article content gallery" itemscope itemprop="blogPost">
<h1 class="article-title is-size-3 is-size-4-mobile" itemprop="name">
<a href="/2018/09/13/TF-IDF原理/" itemprop="url">TF-IDF原理</a>
</h1>
<div class="article-meta columns is-variable is-1 is-multiline is-mobile is-size-7-mobile">
<span class="column is-narrow">
<time datetime="2018-09-13T13:02:49.000Z" itemprop="datePublished">1 个月前</time>
</span>
<span class="column is-narrow article-category">
<i class="far fa-folder"></i>
<a class="article-category-link" href="/categories/Machine-Learning/">Machine Learning</a>
</span>
<span class="column is-narrow">
6 分钟 读完 (约 906 字)
</span>
</div>
<div class="article-entry is-size-6-mobile" itemprop="articleBody">
<blockquote>
<p><a href="https://blog.csdn.net/zrc199021/article/category/6270265" target="_blank" rel="noopener">原文</a></p>
</blockquote>
<p>TF-IDF(Term Frequency-Inverse Document Frequency, 词频-逆文件频率).</p>
<blockquote>
<p>是一种用于资讯检索与资讯探勘的常用加权技术。TF-IDF是一种统计方法，用以评估一字词对于一个文件集或一个语料库中的其中一份文件的重要程度。<strong>字词的重要性随着它在文件中出现的次数成正比增加，但同时会随着它在语料库中出现的频率成反比下降。</strong></p>
</blockquote>
<p class="article-more-link">
<a href="/2018/09/13/TF-IDF原理/#more">阅读更多</a>
</p>
</div>
</article>
<article class="article content gallery" itemscope itemprop="blogPost">
<h1 class="article-title is-size-3 is-size-4-mobile" itemprop="name">
<a href="/2018/09/13/Shutil与OS常用文件操作/" itemprop="url">Shutil与OS常用文件操作</a>
</h1>
<div class="article-meta columns is-variable is-1 is-multiline is-mobile is-size-7-mobile">
<span class="column is-narrow">
<time datetime="2018-09-13T13:02:18.000Z" itemprop="datePublished">1 个月前</time>
</span>
<span class="column is-narrow article-category">
<i class="far fa-folder"></i>
<a class="article-category-link" href="/categories/Python/">Python</a>
</span>
<span class="column is-narrow">
6 分钟 读完 (约 890 字)
</span>
</div>
<div class="article-entry is-size-6-mobile" itemprop="articleBody">
<p>Python 常用文件操作接口。</p>
<p class="article-more-link">
<a href="/2018/09/13/Shutil与OS常用文件操作/#more">阅读更多</a>
</p>
</div>
</article>
<article class="article content gallery" itemscope itemprop="blogPost">
<h1 class="article-title is-size-3 is-size-4-mobile" itemprop="name">
<a href="/2018/09/13/XGBoost完全指南/" itemprop="url">XGBoost完全指南</a>
</h1>
<div class="article-meta columns is-variable is-1 is-multiline is-mobile is-size-7-mobile">
<span class="column is-narrow">
<time datetime="2018-09-13T13:00:54.000Z" itemprop="datePublished">1 个月前</time>
</span>
<span class="column is-narrow article-category">
<i class="far fa-folder"></i>
<a class="article-category-link" href="/categories/Machine-Learning/">Machine Learning</a>
</span>
<span class="column is-narrow">
17 分钟 读完 (约 2503 字)
</span>
</div>
<div class="article-entry is-size-6-mobile" itemprop="articleBody">
<blockquote>
<p>原文地址：<a href="http://www.analyticsvidhya.com/blog/2016/03/complete-guide-parameter-tuning-xgboost-with-codes-python/" target="_blank" rel="noopener">Complete Guide to Parameter Tuning in XGBoost (with codes in Python)</a> </p>
</blockquote>
<p>XGBoost(eXtreme Gradient Boosting)是Gradient Boosting算法的一个优化的版本。因为我在前一篇文章，<a href="http://www.analyticsvidhya.com/blog/2016/02/complete-guide-parameter-tuning-gradient-boosting-gbm-python/" target="_blank" rel="noopener">基于Python的Gradient Boosting算法参数调整完全指南</a>，里面已经涵盖了Gradient Boosting算法的很多细节了。我强烈建议大家在读本篇文章之前，把那篇文章好好读一遍。它会帮助你对Boosting算法有一个宏观的理解，同时也会对GBM的参数调整有更好的体会。 </p>
<p class="article-more-link">
<a href="/2018/09/13/XGBoost完全指南/#more">阅读更多</a>
</p>
</div>
</article>
<article class="article content gallery" itemscope itemprop="blogPost">
<h1 class="article-title is-size-3 is-size-4-mobile" itemprop="name">
<a href="/2018/09/13/LightGBM使用/" itemprop="url">LightGBM使用</a>
</h1>
<div class="article-meta columns is-variable is-1 is-multiline is-mobile is-size-7-mobile">
<span class="column is-narrow">
<time datetime="2018-09-13T12:54:43.000Z" itemprop="datePublished">1 个月前</time>
</span>
<span class="column is-narrow article-category">
<i class="far fa-folder"></i>
<a class="article-category-link" href="/categories/Machine-Learning/">Machine Learning</a>
</span>
<span class="column is-narrow">
22 分钟 读完 (约 3286 字)
</span>
</div>
<div class="article-entry is-size-6-mobile" itemprop="articleBody">
<p>xgboost的出现，让数据民工们告别了传统的机器学习算法们：RF、GBM、SVM、LASSO……..。微软推出了一个新的boosting框架，想要挑战xgboost的江湖地位。</p>
<p>顾名思义，lightGBM包含两个关键点：light即轻量级，GBM 梯度提升机。</p>
<p class="article-more-link">
<a href="/2018/09/13/LightGBM使用/#more">阅读更多</a>
</p>
</div>
</article>
<article class="article content gallery" itemscope itemprop="blogPost">
<h1 class="article-title is-size-3 is-size-4-mobile" itemprop="name">
<a href="/2018/09/13/Knowing-When-to-Look-Adaptive-Attention-via-A-Visual-Sentinel-for-Image-Captioning/" itemprop="url">Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning</a>
</h1>
<div class="article-meta columns is-variable is-1 is-multiline is-mobile is-size-7-mobile">
<span class="column is-narrow">
<time datetime="2018-09-13T12:50:36.000Z" itemprop="datePublished">1 个月前</time>
</span>
<span class="column is-narrow article-category">
<i class="far fa-folder"></i>
<a class="article-category-link" href="/categories/Deep-Learning/">Deep Learning</a>
</span>
<span class="column is-narrow">
22 分钟 读完 (约 3365 字)
</span>
</div>
<div class="article-entry is-size-6-mobile" itemprop="articleBody">
<blockquote>
<p>论文链接：<a href="https://arxiv.org/abs/1612.01887" target="_blank" rel="noopener">https://arxiv.org/abs/1612.01887</a></p>
</blockquote>
<h3 id="Abstract"><a href="#Abstract" class="headerlink" title="Abstract"></a>Abstract</h3><p>基于注意力的神经编码-译码框架（Attention-based neural encoder-decoder frameworks）已经在图像标注任务中广泛采用。大部分方法在生成词语时，强行令视觉注意信息发挥效力。然而，译码器在预测诸如“the”和“of”等“非视觉”（non-visual）词汇时，可能几乎不需要从图片中获取视觉信息。其它看上来像视觉词汇的词语，例如在“behind a red stop”之后的“sign”，或者“talking on a cell”之后的“phone”，经常可依赖语言模型进行可靠的预测。在本文中，我们提出了一个新的带视觉哨兵（visual sentinel）的自适应注意力模型(adaptive attention model)。在预测的每一步，我们的 模型会决定是注意图像（如果是，具体到哪块区域），还是注意视觉哨兵。模型决定了是否要聚焦于图像以及其具体区域，以为序列词语的生成提取出有效信息。在COCO和Flickr30K上的测试结果显示，我们的方法以显著优势重置了新的state-of-the-art水准。</p>
<p class="article-more-link">
<a href="/2018/09/13/Knowing-When-to-Look-Adaptive-Attention-via-A-Visual-Sentinel-for-Image-Captioning/#more">阅读更多</a>
</p>
</div>
</article>
<article class="article content gallery" itemscope itemprop="blogPost">
<h1 class="article-title is-size-3 is-size-4-mobile" itemprop="name">
<a href="/2018/05/22/Restricted Boltzmann Machine/" itemprop="url">Restricted Boltzmann Machine</a>
</h1>
<div class="article-meta columns is-variable is-1 is-multiline is-mobile is-size-7-mobile">
<span class="column is-narrow">
<time datetime="2018-05-22T08:14:35.000Z" itemprop="datePublished">5 个月前</time>
</span>
<span class="column is-narrow article-category">
<i class="far fa-folder"></i>
<a class="article-category-link" href="/categories/Machine-Learning/">Machine Learning</a>
</span>
<span class="column is-narrow">
24 分钟 读完 (约 3592 字)
</span>
</div>
<div class="article-entry is-size-6-mobile" itemprop="articleBody">
<p>受限玻尔兹曼机（Restricted Boltzmann Machine，RBM）是G.Hinton教授的一宝。Hinton教授是深度学习的开山鼻祖，也正是他在2006年的关于深度信念网络DBN的工作，以及逐层预训练的训练方法，开启了深度学习的序章。其中，DBN中在层间的预训练就采用了RBM算法模型。RBM是一种无向图模型，也是一种神经网络模型。 </p>
<p><img src="https://img-blog.csdn.net/20150406200045638" alt="RBM"></p>
<p class="article-more-link">
<a href="/2018/05/22/Restricted Boltzmann Machine/#more">阅读更多</a>
</p>
</div>
</article>
<article class="article content gallery" itemscope itemprop="blogPost">
<h1 class="article-title is-size-3 is-size-4-mobile" itemprop="name">
<a href="/2018/05/21/Python Numpy Tutorial/" itemprop="url">Numpy and Matplotlib Tutorial</a>
</h1>
<div class="article-meta columns is-variable is-1 is-multiline is-mobile is-size-7-mobile">
<span class="column is-narrow">
<time datetime="2018-05-21T08:43:35.000Z" itemprop="datePublished">5 个月前</time>
</span>
<span class="column is-narrow article-category">
<i class="far fa-folder"></i>
<a class="article-category-link" href="/categories/Python/">Python</a>
</span>
<span class="column is-narrow">
17 分钟 读完 (约 2531 字)
</span>
</div>
<div class="article-entry is-size-6-mobile" itemprop="articleBody">
<h2 id="Numpy"><a href="#Numpy" class="headerlink" title="Numpy"></a>Numpy</h2><p>Numpy is the core library for scientific computing in Python. It provides a high-performance multidimensional array object, and tools for working with these arrays.</p>
<p class="article-more-link">
<a href="/2018/05/21/Python Numpy Tutorial/#more">阅读更多</a>
</p>
</div>
</article>
<nav class="pagination is-centered is-rounded" role="navigation" aria-label="pagination">
<div class="pagination-previous is-invisible is-hidden-mobile">
<a href="/page/0/">上一页</a>
</div>
<div class="pagination-next">
<a href="/page/2/">下一页</a>
</div>
<ul class="pagination-list is-hidden-mobile">
<li><a class="pagination-link is-current" href="/">1</a></li>
<li><a class="pagination-link" href="/page/2/">2</a></li>
</ul>
</nav>
</div>
</section>
<footer class="footer">
<div class="container">
<div class="columns content">
<div class="column is-narrow has-text-centered">
© 2018 Joey Lee
Powered by <a href="http://hexo.io/" target="_blank">Hexo</a> & <a
href="http://github.com/ppoffice/hexo-theme-minos">Minos</a>
</div>
<div class="column is-hidden-mobile"></div>
<div class="column is-narrow">
<div class="columns is-mobile is-multiline is-centered">
<a class="column is-narrow has-text-black" href="https://github.com/bacterous">
GitHub
</a>
</div>
</div>
</div>
</div>
</footer>
<script src="//cdnjs.cloudflare.com/ajax/libs/jquery/3.3.1/jquery.min.js"></script>
<!-- test if the browser is outdated -->
<div id="outdated">
<h6>Your browser is out-of-date!</h6>
<p>Update your browser to view this website correctly. <a id="btnUpdateBrowser" href="http://outdatedbrowser.com/">Update my browser now </a></p>
<p class="last"><a href="#" id="btnCloseUpdateBrowser" title="Close">×</a></p>
</div>
<script src="//cdnjs.cloudflare.com/ajax/libs/outdated-browser/1.1.5/outdatedbrowser.min.js"></script>
<script>
$(document).ready(function () {
//plugin function, place inside DOM ready function
outdatedBrowser({
bgColor: '#f25648',
color: '#ffffff',
lowerThan: 'flex'
})
});
</script>
<script>
window.FontAwesomeConfig = {
searchPseudoElements: true
}
</script>
<script type="text/x-mathjax-config">
MathJax.Hub.Config({
"HTML-CSS": {matchFontHeight: false},
SVG: {matchFontHeight: false},
CommonHTML: {matchFontHeight: false},
tex2jax: {
inlineMath: [ ['$','$'], ['\\(','\\)'] ],
processEscapes: true
}
});
</script>
<!-- Use cdnjs as CDN provider -->
<script type="text/javascript" async
src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS_CHTML">
</script>
<script src="//cdnjs.cloudflare.com/ajax/libs/lightgallery/1.6.8/js/lightgallery-all.min.js"></script>
<script src="//cdnjs.cloudflare.com/ajax/libs/justifiedGallery/3.6.5/js/jquery.justifiedGallery.min.js"></script>
<script>
(function ($) {
$(document).ready(function () {
if (typeof($.fn.lightGallery) === 'function') {
$('.article.gallery').lightGallery({ selector: '.gallery-item' });
}
if (typeof($.fn.justifiedGallery) === 'function') {
$('.justified-gallery').justifiedGallery();
}
});
})(jQuery);
</script>
<script src="/js/script.js"></script>
<div class="searchbox ins-search">
<div class="searchbox-mask"></div>
<div class="searchbox-container ins-search-container">
<div class="searchbox-input-wrapper">
<input type="text" class="searchbox-input ins-search-input" placeholder="站内搜索" />
<span class="searchbox-close ins-close ins-selectable"><i class="fa fa-times-circle"></i></span>
</div>
<div class="searchbox-result-wrapper ins-section-wrapper">
<div class="ins-section-container"></div>
</div>
</div>
</div>
<script>
(function (window) {
var INSIGHT_CONFIG = {
TRANSLATION: {
POSTS: '文章',
PAGES: '页面',
CATEGORIES: '分类',
TAGS: '标签',
UNTITLED: '(无标题)',
},
CONTENT_URL: '/content.json',
};
window.INSIGHT_CONFIG = INSIGHT_CONFIG;
})(window);
</script>
<script src="/js/insight.js"></script>
</body>
</html>