metadata

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:

A randomly colored background
The specified geometric shape (except for label "1") filled with a different random color
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.