Update README.md

README.md

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 ---
+license: mit
 task_categories:
 - image-classification
 dataset_info:
@@ -36,4 +37,92 @@ configs:
     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
+
+#### Initial Data Collection and Normalization
+
+The data is synthetically generated using a custom Python script. 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.
+