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docs/source/creating/ToonShading.md

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+# 当图像模型遇见 AnimateDiff
+
+我们已经领略到了 Stable Diffusion 模型及其生态模型的强大图像生成能力，现在我们引入一个新的模块：AnimateDiff，这样一来就可以把图像模型的能力迁移到视频中。在本篇文章中，我们为您展示基于 DiffSynth-Studio 搭建的动漫风格视频渲染方案：Diffutoon。
+
+## 下载模型
+
+接下来的例子会用到很多模型，我们先把它们下载好。
+
+* 一个动漫风格的 Stable Diffusion 架构模型
+* 两个 ControlNet 模型
+* 一个 Textual Inversion 模型
+* 一个 AnimateDiff 模型
+
+```python
+from diffsynth import download_models
+
+download_models([
+    "AingDiffusion_v12",
+    "AnimateDiff_v2",
+    "ControlNet_v11p_sd15_lineart",
+    "ControlNet_v11f1e_sd15_tile",
+    "TextualInversion_VeryBadImageNegative_v1.3"
+])
+```
+
+## 下载视频
+
+你可以随意选择任何你喜欢的视频，我们使用[这个视频](https://www.bilibili.com/video/BV1iG411a7sQ)作为演示，你可以通过以下命令下载这个视频文件，但请注意，在没有获得视频原作者的商用版权时，请不要将其用作商业用途。
+
+```
+modelscope download --dataset Artiprocher/examples_in_diffsynth data/examples/diffutoon/input_video.mp4 --local_dir ./
+```
+
+## 生成动漫
+
+```python
+from diffsynth import ModelManager, SDVideoPipeline, ControlNetConfigUnit, VideoData, save_video
+import torch
+
+# Load models
+model_manager = ModelManager(torch_dtype=torch.float16, device="cuda")
+model_manager.load_models([
+    "models/stable_diffusion/aingdiffusion_v12.safetensors",
+    "models/AnimateDiff/mm_sd_v15_v2.ckpt",
+    "models/ControlNet/control_v11p_sd15_lineart.pth",
+    "models/ControlNet/control_v11f1e_sd15_tile.pth",
+])
+
+# Build pipeline
+pipe = SDVideoPipeline.from_model_manager(
+    model_manager,
+    [
+        ControlNetConfigUnit(
+            processor_id="tile",
+            model_path="models/ControlNet/control_v11f1e_sd15_tile.pth",
+            scale=0.5
+        ),
+        ControlNetConfigUnit(
+            processor_id="lineart",
+            model_path="models/ControlNet/control_v11p_sd15_lineart.pth",
+            scale=0.5
+        )
+    ]
+)
+pipe.prompter.load_textual_inversions(["models/textual_inversion/verybadimagenegative_v1.3.pt"])
+
+# Load video
+video = VideoData(
+    video_file="data/examples/diffutoon/input_video.mp4",
+    height=1536, width=1536
+)
+input_video = [video[i] for i in range(30)]
+
+# Generate
+torch.manual_seed(0)
+output_video = pipe(
+    prompt="best quality, perfect anime illustration, light, a girl is dancing, smile, solo",
+    negative_prompt="verybadimagenegative_v1.3",
+    cfg_scale=7, clip_skip=2,
+    input_frames=input_video, denoising_strength=1.0,
+    controlnet_frames=input_video, num_frames=len(input_video),
+    num_inference_steps=10, height=1536, width=1536,
+    animatediff_batch_size=16, animatediff_stride=8,
+)
+
+# Save video
+save_video(output_video, "output_video.mp4", fps=30)
+```
+
+## 效果展示
+
+<video src="https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/b54c05c5-d747-4709-be5e-b39af82404dd" controls="controls"></video>