U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection
Paper • 2005.09007 • Published
How to use reidn3r/u2net-image-rembg with Keras:
# !pip install -U keras tensorflow huggingface_hub
# Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here;
# "jax" and "torch" also work for computation once TensorFlow is installed.
import os
os.environ["KERAS_BACKEND"] = "tensorflow"
import keras
model = keras.saving.load_model("hf://reidn3r/u2net-image-rembg")
Input Shape:(512, 512, 3)
This is an implementation of U²-Net for image background removing purposes based on this paper. The U²-Net architecture is designed to capture both fine details and global context, making it highly effective for image segmentation tasks such as background removal.
Dichotomous Image Segmentation (DIS) is a dataset wich contains around 5k images (images + masks) and it's used in image segmenation model training.
You can find more about this dataset here.
Find me at GitHub: https://github.com/reidn3r
Find me at Linkedin: https://www.linkedin.com/in/reidner-adnan/
Project repository: GitHub repository