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+assets/teaser.png filter=lfs diff=lfs merge=lfs -text
+assets/visual_results/bsr3.png filter=lfs diff=lfs merge=lfs -text
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+assets/visual_results/bsr5.png filter=lfs diff=lfs merge=lfs -text
+assets/visual_results/bsr6.png filter=lfs diff=lfs merge=lfs -text
+assets/visual_results/tiled_sampling.png filter=lfs diff=lfs merge=lfs -text
+assets/visual_results/whole_image1.png filter=lfs diff=lfs merge=lfs -text
+assets/visual_results/whole_image2.png filter=lfs diff=lfs merge=lfs -text

assets/docs/installation_xOS.md

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+# Linux
+Please follow the primary README.md of this repo.
+
+# Windows
+Windows users may stumble when installing the package `triton`. 
+You can choose to run on **CPU** without `xformers` and `triton` installed.
+
+To use **CUDA**, please refer to [issue#24](https://github.com/XPixelGroup/DiffBIR/issues/24) to try solve the problem of `triton` installation.
+
+# MacOS
+<!-- Currenly only CPU device is supported to run DiffBIR on Apple Silicon since most GPU acceleration packages are compatible with CUDA only. 
+
+We are still trying to support MPS device. Stay tuned for our progress! -->
+
+You can try to set up according to the following steps to use CPU or MPS device.
+
+1. Install **torch (Preview/Nighly version)**.
+
+    ```bash
+    # MPS acceleration is available on MacOS 12.3+
+    pip install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cpu
+    ```
+    Check more details in [official document](https://pytorch.org/get-started/locally/).
+
+2. Package `triton` and `xformers` is not needed since they work with CUDA. Remove the related packages. 
+
+    Your requirements.txt should look like:
+    ```bash
+    # requirements.txt
+    pytorch_lightning==1.4.2
+    einops
+    open-clip-torch
+    omegaconf
+    torchmetrics==0.6.0
+    opencv-python-headless
+    scipy
+    matplotlib
+    lpips
+    gradio
+    chardet
+    transformers
+    facexlib
+    ```
+
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+3. [Run the inference script](https://github.com/XPixelGroup/DiffBIR#general_image_inference) and specify `--device cpu` or `--device mps`. Using MPS can accelarate your inference.
+
+    You can specify `--tiled` and related arguments to avoid OOM. 

assets/docs/v1_models.md

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+| Model Name | Description | HuggingFace | BaiduNetdisk | OpenXLab |
+| :--------- | :---------- | :---------- | :---------- | :---------- |
+| general_swinir_v1.ckpt | Stage1 model (SwinIR) for general image restoration. | [download](https://huggingface.co/lxq007/DiffBIR/resolve/main/general_swinir_v1.ckpt) | [download](https://pan.baidu.com/s/1uvSvJgcoL_Knj0h22-9TvA?pwd=v3v6) (pwd: v3v6) | [download](https://download.openxlab.org.cn/models/linxinqi/DiffBIR/weight//diffbir_general_swinir_v1) |
+| general_full_v1.ckpt | Full model for general image restoration. "Full" means it contains both the stage1 and stage2 model. | [download](https://huggingface.co/lxq007/DiffBIR/resolve/main/general_full_v1.ckpt) | [download](https://pan.baidu.com/s/1gLvW1nvkJStdVAKROqaYaA?pwd=86zi) (pwd: 86zi) | [download](https://download.openxlab.org.cn/models/linxinqi/DiffBIR/weight//diffbir_general_full_v1) |
+| face_swinir_v1.ckpt | Stage1 model (SwinIR) for face restoration. | [download](https://huggingface.co/lxq007/DiffBIR/resolve/main/face_swinir_v1.ckpt) | [download](https://pan.baidu.com/s/1cnBBC8437BJiM3q6suaK8g?pwd=xk5u) (pwd: xk5u) | [download](https://download.openxlab.org.cn/models/linxinqi/DiffBIR/weight//diffbir_face_swinir_v1) |
+| face_full_v1.ckpt | Full model for face restoration. | [download](https://huggingface.co/lxq007/DiffBIR/resolve/main/face_full_v1.ckpt) | [download](https://pan.baidu.com/s/1pc04xvQybkynRfzK5Y8K0Q?pwd=ov8i) (pwd: ov8i) | [download](https://download.openxlab.org.cn/models/linxinqi/DiffBIR/weight//diffbir_face_full_v1) |