FreeToolsPro third-party notices

AI models (served from tools.freetoolspro.com, run in the visitor's browser)
- Fast (U²-NetP): u2netp.onnx, 4574861 bytes, SHA-256 309c8469258dda742793dce0ebea8e6dd393174f89934733ecc8b14c76f4ddd8
  Source: https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2netp.onnx
  Licence: Apache-2.0 (model, U-2-Net); ONNX conversion distributed by rembg (MIT)
  Citation: U²-Net: Qin, Zhang, Huang, Dehghan, Zaiane, Jagersand. “U²-Net: Going Deeper with Nested U-Structure for Salient Object Detection”, Pattern Recognition 106, 2020. https://github.com/xuebinqin/U-2-Net
- Portrait (MODNet): modnet.onnx, 25888640 bytes, SHA-256 07c308cf0fc7e6e8b2065a12ed7fc07e1de8febb7dc7839d7b7f15dd66584df9
  Source: https://huggingface.co/Xenova/modnet/resolve/main/onnx/model.onnx
  Licence: Apache-2.0 (model, MODNet; ONNX conversion Xenova/modnet, Apache-2.0)
  Citation: MODNet: Ke, Sun, Li, Yan, Lau. “MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition”, AAAI 2022. https://github.com/ZHKKKe/MODNet
- Quality (U²-Net): u2net.onnx, 175997641 bytes, SHA-256 8d10d2f3bb75ae3b6d527c77944fc5e7dcd94b29809d47a739a7a728a912b491
  Source: https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2net.onnx
  Licence: Apache-2.0 (model, U-2-Net); ONNX conversion distributed by rembg (MIT)
  Citation: U²-Net (full): Qin et al., Pattern Recognition 2020. https://github.com/xuebinqin/U-2-Net

[object Promise]===== Xenova/modnet (ONNX conversion of MODNet) =====
Licensed apache-2.0 per its model card (https://huggingface.co/Xenova/modnet).