Update

app.py

@@ -8,6 +8,7 @@ import shlex
 import subprocess
 
 import gradio as gr
+import torch
 
 if os.getenv('SYSTEM') == 'spaces':
     with open('patch') as f:
@@ -43,7 +44,7 @@ from app_scribble_interactive import \
 from app_seg import create_demo as create_demo_seg
 from model import Model, download_all_controlnet_weights
 
-DESCRIPTION = '# [ControlNet](https://github.com/lllyasviel/ControlNet)'
+DESCRIPTION = '# [ControlNet v1.0](https://github.com/lllyasviel/ControlNet)'
 
 SPACE_ID = os.getenv('SPACE_ID')
 ALLOW_CHANGING_BASE_MODEL = SPACE_ID != 'hysts/ControlNet'
@@ -51,12 +52,16 @@ ALLOW_CHANGING_BASE_MODEL = SPACE_ID != 'hysts/ControlNet'
 if SPACE_ID is not None:
     DESCRIPTION += f'\n<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. <a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true"><img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></a></p>'
 
+if torch.cuda.is_available():
+    DESCRIPTION += '\n<p>Running on GPU 🔥</p>'
+    if os.getenv('SYSTEM') == 'spaces':
+        download_all_controlnet_weights()
+else:
+    DESCRIPTION += '\n<p>Running on CPU 🥶 This demo does not work on CPU.'
+
 MAX_IMAGES = int(os.getenv('MAX_IMAGES', '3'))
 DEFAULT_NUM_IMAGES = min(MAX_IMAGES, int(os.getenv('DEFAULT_NUM_IMAGES', '1')))
 
-if os.getenv('SYSTEM') == 'spaces':
-    download_all_controlnet_weights()
-
 DEFAULT_MODEL_ID = os.getenv('DEFAULT_MODEL_ID',
                              'runwayml/stable-diffusion-v1-5')
 model = Model(base_model_id=DEFAULT_MODEL_ID, task_name='canny')
@@ -147,4 +152,4 @@ with gr.Blocks(css='style.css') as demo:
                                    inputs=new_base_model_id,
                                    outputs=current_base_model)
 
-demo.queue(api_open=False).launch(file_directories=['/tmp'])
+demo.queue(api_open=False, max_size=10).launch()

model.py

@@ -18,13 +18,16 @@ repo_dir = pathlib.Path(__file__).parent
 submodule_dir = repo_dir / 'ControlNet'
 sys.path.append(submodule_dir.as_posix())
 
-from annotator.canny import apply_canny
-from annotator.hed import apply_hed, nms
-from annotator.midas import apply_midas
-from annotator.mlsd import apply_mlsd
-from annotator.openpose import apply_openpose
-from annotator.uniformer import apply_uniformer
-from annotator.util import HWC3, resize_image
+try:
+    from annotator.canny import apply_canny
+    from annotator.hed import apply_hed, nms
+    from annotator.midas import apply_midas
+    from annotator.mlsd import apply_mlsd
+    from annotator.openpose import apply_openpose
+    from annotator.uniformer import apply_uniformer
+    from annotator.util import HWC3, resize_image
+except Exception:
+    pass
 
 CONTROLNET_MODEL_IDS = {
     'canny': 'lllyasviel/sd-controlnet-canny',
@@ -54,6 +57,8 @@ class Model:
         self.pipe = self.load_pipe(base_model_id, task_name)
 
     def load_pipe(self, base_model_id: str, task_name) -> DiffusionPipeline:
+        if self.device.type == 'cpu':
+            return None
         if base_model_id == self.base_model_id and task_name == self.task_name and hasattr(
                 self, 'pipe'):
             return self.pipe