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README.md
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@@ -6,8 +6,6 @@ pretty_name: Human Segmentation Dataset
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# Human Segmentation Dataset
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[GDrvie Download: 61.1 GB](https://drive.google.com/drive/folders/1K1lK6nSoaQ7PLta-bcfol3XSGZA1b9nt?usp=drive_link)
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This dataset was created **for developing the best fully open-source background remover** of images with humans.
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The dataset was crafted with [LayerDiffuse](https://github.com/layerdiffusion/LayerDiffuse), a Stable Diffusion extension for generating transparent images.
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It covers a diverse set of humans: various skin tones, clothes, hair styles etc.
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Since Stable Diffusion is not perfect, the dataset contains images with flaws. Still the dataset is good enough for training background remover models.
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The dataset contains transparent images of humans (`/humans`) which were randomly combined with
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Then the groundtruth (`/gt`) for segmentation was computed based on the transparent images. The results are written to a training and validation dataset.
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I created 4.558 images with people which I have augmented to a set of 9.116 images for training and 2.549 for validation with diverse backgrounds. The backgrounds are optimized for art exhibitions because this is where I want to apply the background remover.
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# Support
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If you identify weaknesses in the data, please contact me.
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# Examples
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---
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# Human Segmentation Dataset
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This dataset was created **for developing the best fully open-source background remover** of images with humans.
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The dataset was crafted with [LayerDiffuse](https://github.com/layerdiffusion/LayerDiffuse), a Stable Diffusion extension for generating transparent images.
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It covers a diverse set of humans: various skin tones, clothes, hair styles etc.
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Since Stable Diffusion is not perfect, the dataset contains images with flaws. Still the dataset is good enough for training background remover models.
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The dataset contains transparent images of humans (`/humans`) which were randomly combined with Stable Diffusion created backgrounds.
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Then the groundtruth (`/gt`) for segmentation was computed based on the transparent images. The results are written to a training and validation dataset.
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I created 4.558 images with people which I have augmented to a set of 9.116 images for training and 2.549 for validation with diverse backgrounds. The backgrounds are optimized for art exhibitions because this is where I want to apply the background remover.
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# Support
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If you identify weaknesses in the data, please contact me.
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I had some trouble with this huge file upload on huggingface. If files are missing use: [GDrvie Download: 61.1 GB](https://drive.google.com/drive/folders/1K1lK6nSoaQ7PLta-bcfol3XSGZA1b9nt?usp=drive_link)
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# Examples
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