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PyTorch-based differentiable material graph library for procedural material capture

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just run some test target image is ![bricks](https://github.com/mit-gfx/diffmat/assets/421933/232f7640-654d-47c7-a917-4a360091f15d) and run the following command: ``` python .\test_optimizer.py .\sbs\match_v1\bricks.sbs -e -im bricks.jpg python .\test_hybrid_optimizer.py .\sbs\match_v1\bricks.sbs -e -im bricks.jpg -m combine -ip .\result\bricks\optim_bricks\checkpoints\optimized.pth...

This is a valuable work. But I still have a question, if a certain material (such as **metal or wood or fabric**) is optimized, will the optimization result still maintain...