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@@ -70,28 +70,16 @@ We provide a first script for sampling from our unconditional models. Start it v
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CUDA_VISIBLE_DEVICES=<GPU_ID> python scripts/sample_diffusion.py -r models/ldm/<model_spec>/model.ckpt -l <logdir> -n <\#samples> --batch_size <batch_size> -c <\#ddim steps> -e <\#eta>
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```
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-# Inpainting
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-
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-
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-Download the pre-trained weights
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-```
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-wget XXX
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-```
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+## Coming Soon...
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-and sample with
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-```
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-python scripts/inpaint.py --indir data/inpainting_examples/ --outdir outputs/inpainting_results
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-```
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-`indir` should contain images `*.png` and masks `<image_fname>_mask.png` like
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-the examples provided in `data/inpainting_examples`.
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-
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-
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-## Comin Soon...
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+
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* Code for training LDMs and the corresponding compression models.
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* Inference scripts for conditional LDMs for various conditioning modalities.
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* In the meantime, you can play with our colab notebook https://colab.research.google.com/drive/1xqzUi2iXQXDqXBHQGP9Mqt2YrYW6cx-J?usp=sharing
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* We will also release some further pretrained models.
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+
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+
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## Comments
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- Our codebase for the diffusion models builds heavily on [OpenAI's codebase](https://github.com/openai/guided-diffusion)
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ablattmann