Update app.py

app.py

@@ -31,10 +31,6 @@ pipe.scheduler = EulerAncestralDiscreteScheduler(
 pipe.enable_xformers_memory_efficient_attention()
 pipe.force_zeros_for_empty_prompt = False
 
-from transformers import DPTFeatureExtractor, DPTForDepthEstimation
-depth_estimator = DPTForDepthEstimation.from_pretrained("Intel/dpt-hybrid-midas").to("cuda")
-feature_extractor = DPTFeatureExtractor.from_pretrained("Intel/dpt-hybrid-midas")
-
 def resize_image(image):
     image = image.convert('RGB')
     current_size = image.size
@@ -64,10 +60,10 @@ def process(input_image, prompt, negative_prompt, num_steps, controlnet_conditio
 block = gr.Blocks().queue()
 
 with block:
-    gr.Markdown("## BRIA 2.2 ControlNet Depth")
+    gr.Markdown("## BRIA 2.2 ControlNet Recoloring")
     gr.HTML('''
       <p style="margin-bottom: 10px; font-size: 94%">
-        This is a demo for ControlNet Depth that using
+        This is a demo for ControlNet Recoloring that using
         <a href="https://huggingface.co/briaai/BRIA-2.2" target="_blank">BRIA 2.2 text-to-image model</a> as backbone. 
         Trained on licensed data, BRIA 2.2 provide full legal liability coverage for copyright and privacy infringement.
       </p>