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README.md

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+# Geometric Shapes Dataset
+
+This dataset contains procedurally generated images of various geometric shapes with corresponding captions. It's designed for educational purposes and testing of diffusion models.
+
+## Dataset Overview
+
+- **Content**: 100,000 images of geometric shapes with detailed metadata
+- **Image size**: 512x512 pixels
+- **Format**: PNG images with CSV metadata
+- **Features**: Various shapes, colors, sizes, and descriptive captions
+- **Purpose**: Educational use for training and testing single-step diffusion models
+
+## Dataset Creation
+
+The dataset was generated using the included Python script (`create_dataset.py`), which was created with the assistance of Claude AI (Anthropic). The script generates a wide variety of geometric shapes with different properties:
+
+- **Shapes**: 50+ different shapes including basic shapes (circle, square, triangle) and more complex ones (hypocycloid, lemniscate, star)
+- **Colors**: 30 different colors with their hex values
+- **Sizes**: Randomly scaled from 10% to 100% with corresponding descriptive terms
+- **Captions**: Diverse, randomly generated descriptions of the shapes in various formats
+
+## Usage
+
+### Using the Dataset
+
+This dataset is designed for educational purposes only. It's particularly useful for:
+
+- Learning to build diffusion models from scratch
+- Experimenting with simple image-to-text and text-to-image models
+- Testing model performance on synthetic data
+- Educational demonstrations of computer vision concepts
+
+### OPTIONAL - If you want to createw youe own images
+
+If you want to generate your own version of the dataset or modify the parameters:
+
+1. Install the required dependencies:
+   ```bash
+   pip install numpy matplotlib tqdm
+   ```
+
+2. Run the script:
+   create a folder "geometric_shapes", and save create_dataset.py the in the folder, and execute it
+   ```bash
+   python create_dataset.py
+   ```
+   ```
+   Generating Images: 100%|█████████████████████████████████████████████████| 100000/100000 [07:36<00:00, 218.96it/s]
+   Generated 100000 images in 456.89 seconds
+   Size: 100000 images
+   ```
+   
+3. By default, the script will:
+   - Generate 100,000 images in the `dataset/images` directory
+   - Create a `dataset/metadata.csv` file with image filenames and captions
+   - Use 10 CPU cores for parallel processing
+
+4. You can modify these parameters in the `__main__` section of the script:
+   ```python
+   generate_images_multiprocess(
+       num_images=100000,  # Change this number to generate fewer/more images
+       max_workers=10,     # Change based on your CPU cores
+       img_size=(512, 512) # Modify image dimensions
+   )
+   ```
+
+5.  Ensure your dataset is organized as follows:
+
+```
+geometric_shapes/
+├── README.md
+├── create_dataset.py
+├── dataset/
+│   ├── images_001/
+│   │   ├── image1.jpg
+│   │   ├── image2.jpg
+│   │   ├── ...
+```
+
+6. Upload Instructions
+
+   Log in to Hugging Face:
+
+   ```sh
+   huggingface-cli login
+   ```
+
+   Upload the dataset:
+
+   ```sh
+   cd .. && huggingface-cli upload-large-folder anokimchen/geometric_shapes geometric_shapes  --repo-type dataset && cd geometric_shapes
+   ```
+
+## License
+
+This dataset is provided for educational and research purposes only.
+
+## Acknowledgements
+
+- Code generated with the assistance of Claude (Anthropic)
+- Dataset created for learning purposes to build and test single-step diffusion models
+
+## Citation
+
+If you use this dataset in your research or educational projects, please include a reference to this repository.