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README.md
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# BRIA Background Removal v1.4 Model Card
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![examples](t4.png)
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### Model Description
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- **Developed by:** [BRIA AI](https://bria.ai/)
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- **Model type:** Background
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- **License:** [bria-rmbg-1.4](https://bria.ai/bria-huggingface-model-license-agreement/)
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- The model is open for non-commercial use.
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- Commercial use is subject to a commercial agreement with BRIA. [Contact Us](https://bria.ai/contact-us)
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- **Model Description:** BRIA RMBG 1.4 is an
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## Training data
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Bria-RMBG model was trained over
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Distribution of images:
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| Category | Distribution |
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| Single main foreground object | 51.42% |
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| Multiple objects in the foreground | 48.58% |
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All images were manualy labeled pixel-wise accuratly.
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## Qualitative Evaluation
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# BRIA Background Removal v1.4 Model Card
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RMBG v1.4 is our state-of-the-art background removal model, designed to effectively separate foreground from background in a range of
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categories and image types. This model has been trained on a carefully selected dataset, which includes:
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general stock images, e-commerce, gaming, and advertising content, making it suitable for various use cases.
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Developed by BRIA AI, RMBG v1.4 is available as an open-source tool for non-commercial use.
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![examples](t4.png)
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### Model Description
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- **Developed by:** [BRIA AI](https://bria.ai/)
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- **Model type:** Background Removal
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- **License:** [bria-rmbg-1.4](https://bria.ai/bria-huggingface-model-license-agreement/)
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- The model is open for non-commercial use.
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- Commercial use is subject to a commercial agreement with BRIA. [Contact Us](https://bria.ai/contact-us)
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- **Model Description:** BRIA RMBG 1.4 is an saliency segmentation model trained exclusively on a professional-grade dataset.
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## Training data
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Bria-RMBG model was trained over 12,000 high-quality, high-resolution, fully licensed images.
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All images were manualy labeled pixel-wise accuratly.
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For clarity, we provide our data distribution according to different categories, demonstrating our model’s versatility:
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Distribution of images:
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| Category | Distribution |
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| Single main foreground object | 51.42% |
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| Multiple objects in the foreground | 48.58% |
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## Qualitative Evaluation
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