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Birefnet DIS5K
BiRefNet is a deep learning model for high-resolution binary image segmentation, focusing on background removal and mask generation tasks.
Downloads 1,129
Release Time : 8/1/2024
Model Overview
BiRefNet is a PyTorch-implemented binary image segmentation model primarily used for high-resolution image background removal and mask generation. The model improves segmentation accuracy through a bilateral reference mechanism, suitable for various complex scenarios.
Model Features
High-resolution processing
Capable of handling high-resolution images while preserving detail integrity
Bilateral reference mechanism
Employs a bilateral reference strategy to enhance segmentation accuracy
PyTorch implementation
Based on the PyTorch framework, easy to integrate and use
Model Capabilities
Image segmentation
Background removal
Mask generation
High-resolution image processing
Use Cases
Image editing
Product image background removal
Used for product image background removal on e-commerce platforms
Generates high-quality product subject masks
Portrait segmentation
Used for portrait background replacement in photo editing
Precise portrait segmentation effects
Computer vision
Medical image analysis
Used for tissue segmentation in medical images
Improves accuracy in medical diagnosis
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