updated

app.py

@@ -18,16 +18,16 @@ DEFAULT_NEGATIVE_PROMPT = "worst quality, abstract, clumsy pose, deformed hand,
 
 def ui():
     device = "cuda" if torch.cuda.is_available() else "cpu"
-    # model_file = hf_hub_download(
-    #     repo_id='Lykon/AAM_XL_AnimeMix',
-    #     filename='AAM_XL_Anime_Mix.safetensors',
-    #     cache_dir=CACHE_DIR,
-    # )
     model_file = hf_hub_download(
-        repo_id='Eugeoter/artiwaifu-diffusion-1.0',
-        filename='artiwaifu-diffusion-v1.safetensors',
+        repo_id='Lykon/AAM_XL_AnimeMix',
+        filename='AAM_XL_Anime_Mix.safetensors',
         cache_dir=CACHE_DIR,
     )
+    # model_file = hf_hub_download(
+    #     repo_id='Eugeoter/artiwaifu-diffusion-1.0',
+    #     filename='artiwaifu-diffusion-v1.safetensors',
+    #     cache_dir=CACHE_DIR,
+    # )
     unet_file = hf_hub_download(
         repo_id=REPO_ID,
         filename=UNET_FILENAME,
@@ -63,7 +63,9 @@ def ui():
 
     with gr.Blocks(css=css) as demo:
         gr.Markdown(f"""
-        # [ControlNeXt](https://github.com/dvlab-research/ControlNeXt) Official Demo
+        # ControlNeXt-SDXL Demo
+        The Gradio has bug currently and is just for demo.
+        More better results please refer to the [official project page](https://github.com/dvlab-research/ControlNeXt).
         """)
         with gr.Row():
             with gr.Column(scale=9):
@@ -180,4 +182,4 @@ def ui():
 
 if __name__ == '__main__':
     demo = ui()
-    demo.queue().launch()
+    demo.queue().launch(server_port=6006)

models/controlnet.py

@@ -353,10 +353,10 @@ class ControlNetModel(ModelMixin, ConfigMixin):
             nn.Conv2d(3, 64, kernel_size=3, stride=2, padding=1),
             nn.GroupNorm(2, 64),
             nn.ReLU(),
-            nn.Conv2d(64, 64, kernel_size=3, padding=1),
+            nn.Conv2d(64, 64, kernel_size=3),
             nn.GroupNorm(2, 64),
             nn.ReLU(),
-            nn.Conv2d(64, 128, kernel_size=3, padding=1),
+            nn.Conv2d(64, 128, kernel_size=3),
             nn.GroupNorm(2, 128),
             nn.ReLU(),
         )

utils/tools.py

@@ -1,5 +1,6 @@
 import os
 import torch
+import gc
 from torch import nn
 from diffusers import UniPCMultistepScheduler, AutoencoderKL
 from safetensors.torch import load_file
@@ -119,6 +120,10 @@ def get_pipeline(
     if enable_xformers_memory_efficient_attention:
         pipeline.enable_xformers_memory_efficient_attention()
 
+    gc.collect()
+    if torch.cuda.is_available():
+        torch.cuda.empty_cache()
+
     return pipeline