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Separating Anything from Image in Context

Python 100.00%
decomposition foundation-model in-context-learning open-world lowlevel-visions separating-anything

sefm's Introduction

Separating Anything from Image in Context (in submission)

๐Ÿ’ก Highlight

  • ๐Ÿ˜ ๐Ÿ˜ SeFM is a novel generalist foundation model for separating anything from images.
  • ๐Ÿ˜ ๐Ÿ˜ Only a handy demonstration example is required.
  • ๐Ÿ˜ ๐Ÿ˜ Exhibiting groundbreaking generalization capability to open-world unseen visual components.

๐Ÿท๏ธ TODO

  • Release inference code and demo.
  • Release checkpoints.
  • Release training codes.

๐ŸŽ–๏ธ Framework Architecture

Overall Framework of SeFM

๐Ÿ› ๏ธ Installation

The model is built in PyTorch 1.8.0 and tested on Ubuntu 16.04 environment (Python3.7, CUDA9.0, cuDNN7.5).

  1. Clone the SeFM repository from GitHub:
git clone https://github.com/Jeasco/SeFM
cd SeFM
  1. Install the required dependencies and SeFM:
pip3 install -r requirements.txt
python3 -m pip install -e .

Training

bash sefm_training.sh

Evaluation

  1. Download the pre-trained model and place it in ./checkpoints/

  2. Place the test image in ./test/

  3. Run

python in_context_inference_demo.py
  1. Visual results will be saved in results

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