Update app.py

app.py

@@ -8,7 +8,7 @@ import gradio as gr
 from torchvision import transforms 
 
 controlnet = ControlNetModel.from_pretrained(
-    "briaai/BRIA-2.2-ControlNet-Canny",
+    "briaai/BRIA-2.2-ControlNet-Depth",
     torch_dtype=torch.float16
 ).to('cuda')
 
@@ -78,15 +78,15 @@ def process(input_image, prompt, negative_prompt, num_steps, controlnet_conditio
         generator=generator,
         ).images
 
-    return [canny_image, images[0]]
+    return [depth_image, images[0]]
     
 block = gr.Blocks().queue()
 
 with block:
-    gr.Markdown("## BRIA 2.2 ControlNet Canny")
+    gr.Markdown("## BRIA 2.2 ControlNet Depth")
     gr.HTML('''
       <p style="margin-bottom: 10px; font-size: 94%">
-        This is a demo for ControlNet Canny that using
+        This is a demo for ControlNet Depth 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>