File size: 3,656 Bytes
39d0e8b
4d63067
39d0e8b
 
67eaf4e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4d63067
 
 
 
 
 
 
67eaf4e
4d63067
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5d33d66
4d63067
5d33d66
4d63067
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: mit
task_categories:
- image-classification
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': '1'
          '1': '2'
          '2': '3'
          '3': '4'
          '4': '5'
          '5': '6'
  splits:
  - name: train
    num_bytes: 16680937.624
    num_examples: 14694
  - name: validation
    num_bytes: 3191950.1
    num_examples: 2100
  - name: test
    num_bytes: 5527485.6
    num_examples: 4200
  download_size: 24752623
  dataset_size: 25400373.324
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
tags:
- computer-vision
- image-classification
- synthetic-data
pretty_name: Geometric Shapes Dataset
size_categories:
- 1K<n<10K
---

# Dataset Card for Geometric Shapes Dataset

## Dataset Description

- **Repository:** https://huggingface.co/datasets/0-ma/geometric-shapes

### Dataset Summary

The Geometric Shapes Dataset is a synthetic dataset containing images of various geometric shapes with superimposed random text. Each image features a polygon (or just text) on a randomly colored background, with a short string of random characters partially obscuring the shape. This dataset is designed for tasks such as shape classification, image recognition, and robustness testing of computer vision models.

### Supported Tasks and Leaderboards

- **Image Classification**: The primary task for this dataset is multi-class image classification, where the goal is to identify the type of shape (or lack thereof) in each image.


### Data Instances

Each instance in the dataset consists of:
- An image (50x50 pixels, RGB)
- A label indicating the type of shape

### Data Fields

- `image`: A 50x50 pixel RGB image in numpy array format.
- `label`: A string indicating the shape type. The labels correspond to the following shapes:
  - "1": No shape, only random text on a colored background
  - "2": Circle-like shape (polygon with 100 sides)
  - "3": Triangle
  - "4": Square
  - "5": Pentagon

Each image contains:
1. A randomly colored background
2. The specified geometric shape (except for label "1") filled with a different random color
3. A short string (4 characters) of random alphanumeric text overlaid on top, partially obscuring the shape

Note: The "Circle" (label "2") is approximated by a 100-sided polygon, which appears circular at the given resolution.



### Data Splits

The dataset is split into train (70%), validation (10%), and test (20%) sets.

## Dataset Creation

### Curation Rationale

This dataset was created to provide a simple, controlled environment for testing image classification models, particularly in scenarios where the primary subject (the geometric shape) is partially obscured by text.

### Source Data

#### Data Generation

The data is synthetically generated using the 'generate_geometric_shapes_dataset.py' of the project from the project https://github.com/0-ma/geometric-shape-detector. No external data sources were used.


### Annotations

#### Annotation process

The annotations (labels) are generated automatically during the image creation process.


### Personal and Sensitive Information

This dataset does not contain any personal or sensitive information.


### Other Known Limitations

- The dataset is limited to a small set of predefined shapes.
- The image resolution is fixed at 50x50 pixels.
- The text overlay is always present, which may not reflect all real-world scenarios.


### Licensing Information

This dataset is released under the MIT License.