initial version

README.md

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+# DiffSynth Studio
+
+## 介绍
+
+DiffSynth is a new Diffusion engine. We have restructured architectures like Text Encoder, UNet, VAE, among others, maintaining compatibility with models from the open-source community while enhancing computational performance. This version is currently in its initial stage, supporting text-to-image and image-to-image functionalities, supporting SD and SDXL architectures. In the future, we plan to develop more interesting features based on this new codebase.
+
+## 安装
+
+If you only want to use DiffSynth Studio at the Python code level, you just need to install torch (a deep learning framework) and transformers (only used for implementing a tokenizer).
+
+```
+pip install torch transformers
+```
+
+If you wish to use the UI, you'll also need to additionally install `streamlit` (a web UI framework) and `streamlit-drawable-canvas` (used for the image-to-image canvas).
+
+```
+pip install streamlit streamlit-drawable-canvas
+```
+
+## 使用
+
+Use DiffSynth Studio in Python
+
+```python
+from diffsynth.models import ModelManager
+from diffsynth.prompts import SDPrompter, SDXLPrompter
+from diffsynth.pipelines import SDPipeline, SDXLPipeline
+
+
+model_manager = ModelManager()
+model_manager.load_from_safetensors("xxxxxxxx.safetensors")
+prompter = SDPrompter()
+pipe = SDPipeline()
+
+prompt = "a girl"
+negative_prompt = ""
+
+image = pipe(
+    model_manager, prompter,
+    prompt, negative_prompt=negative_prompt,
+    num_inference_steps=20, height=512, width=512,
+)
+image.save("image.png")
+```
+
+If you want to use SDXL architecture models, replace `SDPrompter` and `SDPipeline` with `SDXLPrompter` and `SDXLPipeline`, respectively.
+
+Of course, you can also use the UI we provide. The UI is simple but may be changed in the future.
+
+```
+python -m streamlit run Diffsynth_Studio.py
+```