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--- |
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license: mit |
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task_categories: |
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- image-classification |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: label |
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dtype: |
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class_label: |
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names: |
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'0': '1' |
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'1': '2' |
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'2': '3' |
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'3': '4' |
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'4': '5' |
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'5': '6' |
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splits: |
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- name: train |
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num_bytes: 16680937.624 |
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num_examples: 14694 |
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- name: validation |
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num_bytes: 3191950.1 |
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num_examples: 2100 |
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- name: test |
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num_bytes: 5527485.6 |
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num_examples: 4200 |
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download_size: 24752623 |
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dataset_size: 25400373.324 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: validation |
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path: data/validation-* |
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- split: test |
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path: data/test-* |
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tags: |
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- computer-vision |
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- image-classification |
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- synthetic-data |
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pretty_name: Geometric Shapes Dataset |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Dataset Card for Geometric Shapes Dataset |
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## Dataset Description |
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### Dataset Summary |
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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. |
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### Supported Tasks and Leaderboards |
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- **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. |
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Label | 1 | 2 | 3 | 4 | 5 | 6 |
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--- | --- | --- | --- |--- |--- |--- |
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Shape Name | None | Circle | Triangle | Square | Pentagone | Hexagone |
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Image |  |  |  |  |  |  |
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### Data Instances |
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Each instance in the dataset consists of: |
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- An image (50x50 pixels, RGB) |
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- A label indicating the type of shape |
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### Data Fields |
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- `image`: A 50x50 pixel RGB image in numpy array format. |
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- `label`: A string indicating the shape type. The labels correspond to the following shapes: |
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- "1": No shape, only random text on a colored background |
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- "2": Circle-like shape (polygon with 100 sides) |
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- "3": Triangle |
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- "4": Square |
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- "5": Pentagon |
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Each image contains: |
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1. A randomly colored background |
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2. The specified geometric shape (except for label "1") filled with a different random color |
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3. A short string (4 characters) of random alphanumeric text overlaid on top, partially obscuring the shape |
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Note: The "Circle" (label "2") is approximated by a 100-sided polygon, which appears circular at the given resolution. |
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### Data Splits |
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The dataset is split into train (70%), validation (10%), and test (20%) sets. |
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## Dataset Creation |
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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. |
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### Source Data |
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#### Data Generation |
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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. |
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### Annotations |
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#### Annotation process |
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The annotations (labels) are generated automatically during the image creation process. |
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### Personal and Sensitive Information |
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This dataset does not contain any personal or sensitive information. |
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### Other Known Limitations |
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- The dataset is limited to a small set of predefined shapes. |
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- The image resolution is fixed at 50x50 pixels. |
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- The text overlay is always present, which may not reflect all real-world scenarios. |
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### Licensing Information |
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This dataset is released under the MIT License. |
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