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  short_description: Synthetic data generation for training using diffusion model
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
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  short_description: Synthetic data generation for training using diffusion model
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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+ Features:
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+ Stable Diffusion Integration: Leverages the StableDiffusionImg2ImgPipeline for versatile image generation.
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+ Class Misclassification Analysis: Automatically identifies misclassified class pairs for focused image generation.
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+ Advanced Prompt Interpolation: Utilizes spherical linear interpolation (slerp) to generate smooth transitions between text embeddings for more natural image outputs.
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+ Structural Similarity Scoring: Calculates SSIM scores to measure the quality of generated images compared to input references.
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+ Comprehensive Metadata Management: Captures extensive details about the generation process for easy reproducibility and debugging.
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+ Dynamic Directory Management: Automatically creates and organizes directories for class pairs and metadata files.
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+ Highly Configurable: Supports advanced optimization options like torch.compile and DeepCache for performance improvements.