File size: 1,764 Bytes
07abb6d
 
 
 
 
 
 
 
37028e1
 
07abb6d
 
 
 
 
 
 
ab3e39b
 
 
 
 
 
 
 
 
 
5228512
ab3e39b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
736f766
 
 
ab3e39b
 
 
 
736f766
 
 
 
 
 
 
 
 
 
 
 
 
 
ab3e39b
 
 
 
736f766
 
 
ab3e39b
 
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
---
license: apache-2.0
language:
- ru
tags:
- ocr
- htr
- handwritten text recognition
- near duplicate detection
- reuse detection
pretty_name: HWR200
size_categories:
- 10K<n<100K
---



# HWR200: New open access dataset of handwritten texts images in Russian

This is a dataset of handwritten texts images in Russian created by 200 writers with
different handwriting and photographed in different environment.

### How to download

```
pip install huggingface_hub
apt-get install git-lfs
git clone https://huggingface.co/datasets/AntiplagiatCompany/HWR200
```

### Description
* Total size is 44G
* Total number of images with text is 30030
* Number of writers is 200
* Every handwritten text is photographed in three different ways: scanned, in poor light, in good light
* Different authors could write the same texts
* Some texts are "reuses" . they have copies of sentences from other texts


### Annotation example
```
// for original texts:
{
    sentences: [{id: <id>, text: <sentence>}, ...],
    words_count: <word count>,
    full_text: <full text>
}

// for reuse texts:
{
    reuse_0: {
        sentences: [{id: <id>, text: <sentence>}, ...],
        id: <original text file name>
        intersection_score: <intersection_score>
    }
    reuse_1: {  // if exists
        sentences: [{id: <id>, text: <sentence>}, ...],
        id: <original text file name>
        intersection_score: <intersection_score>
    }
    start clear sentences: [<sentence>, <sentence>, ...]  // if exists
    end clear sentences: [<sentence>, <sentence>, ...]  // if exists
    words_count: <word count>
    full_text: <full text>
}

// for fpr texts:
{
    sentences: [{id: <id>, text: <sentence>}, ...],
    words_count: <word count>,
    full_text: <full text>
}
```