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---
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
### 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.
| Label | Shape Name | Image |
|:--------------:|:------------:|:--------------------------------------------------------------:|
| 1 | None |  |
| 2 | Circle |  |
| 3 | Triangle |  |
| 4 | Square |  |
| 5 | Pentagone |  |
| 6 | Hexagone |  |
### 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
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.
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