birefnet-lite-web

These ONNX files are derived from BiRefNet_lite, created by Peng Zheng, Dehong Gao,
Deng-Ping Fan, Li Liu, Jorma Laaksonen, Wanli Ouyang and Nicu Sebe:

  "Bilateral Reference for High-Resolution Dichotomous Image Segmentation",
  CAAI Artificial Intelligence Research, 2024 (arXiv:2401.03407).
  Code and weights: https://github.com/ZhengPeng7/BiRefNet and
  https://huggingface.co/ZhengPeng7/BiRefNet_lite, MIT licence,
  Copyright (c) 2024 ZhengPeng.

Changes made by clevr.tools (see README.md for details and validation):
  - deformable convolution rewritten as a per-kernel-position bilinear gather, so it fits in browser GPU memory
  - wide Split operators regrouped to stay within WebGPU's storage-buffer limit
  - separate static-shape exports at 768 and 512 pixels
  - float32 weights stored as float16 and cast back to float32 when the model loads
  - ONNX Runtime graph optimisation (basic level) applied before the weight conversion

The model's weights were not retrained or fine-tuned.