File size: 1,328 Bytes
74d76ce
bf74b34
 
 
 
 
 
 
 
74d76ce
 
a7298b7
 
 
248ba99
a7298b7
 
 
 
 
 
 
 
 
 
 
 
74d76ce
 
a7298b7
248ba99
a7298b7
 
74d76ce
 
 
 
 
c6e65fe
 
 
74d76ce
c6e65fe
 
 
31789ce
 
 
 
 
 
 
fb99653
 
 
 
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
---
language:
- en
license: mit
size_categories:
- 100K<n<1M
task_categories:
- text-generation
pretty_name: SVGEN RJU
dataset_info:
  features:
  - name: description
    dtype: string
  - name: image
    struct:
    - name: bytes
      dtype: binary
    - name: path
      dtype: 'null'
  - name: svg
    dtype: string
  - name: uuid
    dtype: string
  - name: json
    dtype: string
  - name: source
    dtype: string
  splits:
  - name: train
    num_bytes: 3151387335
    num_examples: 216275
  download_size: 1843399077
  dataset_size: 3151387335
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- art
- code
---

# SVGEN RJU - SVGEN 500k: Rasterized, JSONified, UUID'ed

I have selected every svg image from svgen that would rasterize under cairosvg, which is significantly less than a 1% failure rate. Under development.


# Reasoning

This is the 1st of many SVG datasets I am collecting, extracting, and rasterizing in an attempt to produce a meaningfully helpful spatial reasoning and vertex manipulation model.

# Usage

The rasterized images are in PNG format, as bytes. They may be extracted through the creation of an `io.BytesIO` instance on the bytes then running `Image.open` on the byte stream. They could also be written to disk first for convenience and storage.