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  ---
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- dataset_info:
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- features:
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- - name: image_id
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- dtype: string
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- - name: input_image
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- dtype: image
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- - name: target_image
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- dtype: image
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- - name: caption
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- dtype: string
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- - name: task
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- dtype: string
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- splits:
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- - name: train
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- num_bytes: 241596352
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- num_examples: 98
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- download_size: 241601817
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- dataset_size: 241596352
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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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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ license: mit
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+ task_categories:
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+ - image-to-image
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+ - image-classification
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+ tags:
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+ - skin-tone-matching
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+ - inpainting
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+ - lora-training
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+ - computer-vision
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+ pretty_name: Skin Tone Matching LoRA Training Dataset
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+ size_categories:
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+ - n<1K
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+
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+ # Skin Tone Matching LoRA Training Dataset
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+
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+ ## Dataset Description
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+
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+ This dataset is designed for training LoRA (Low-Rank Adaptation) models for skin tone matching and inpainting tasks. The dataset contains 98 image pairs with corresponding text prompts for training generative models to perform natural-looking skin inpainting that matches surrounding skin tone, texture, and lighting.
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+
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+ ## Dataset Structure
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+
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+ The dataset contains the following fields:
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+
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+ - `image_id`: Unique identifier for each image pair
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+ - `input_image`: Input image with green masked areas that need to be inpainted
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+ - `target_image`: Ground truth target image showing the desired inpainting result
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+ - `caption`: Text prompt describing the inpainting task
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+ - `task`: Task category (always "skin_tone_matching")
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+
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+ ## Use Cases
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+
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+ This dataset is suitable for:
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+
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+ - Training LoRA adapters for skin tone matching
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+ - Fine-tuning diffusion models for inpainting tasks
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+ - Research in computer vision and image generation
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+ - Developing tools for photo editing and restoration
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+
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+ ## Dataset Creation
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+
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+ The dataset was created for training models to:
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+ 1. Identify green masked areas in facial images
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+ 2. Generate natural-looking skin that matches the surrounding area
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+ 3. Ensure seamless blending with existing skin tone, texture, and lighting
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+ 4. Maintain realistic shadows and highlights
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+
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+ ## Citation
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+
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+ If you use this dataset in your research, please cite:
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+
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+ ```
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+ @dataset{skin_tone_matching_lora,
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+ title={Skin Tone Matching LoRA Training Dataset},
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+ author={Dataset Creator},
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+ year={2025},
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+ publisher={Hugging Face},
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+ url={https://huggingface.co/datasets/kg-09/SkinTone-Dataset}
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+ }
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+ ```
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+
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+ ## License
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+
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+ This dataset is released under the MIT License.