update example

app.py

@@ -3,10 +3,6 @@ from diffusers import UniPCMultistepScheduler
 import gradio as gr
 import torch
 
-# Constants
-low_threshold = 100
-high_threshold = 200
-
 # Models
 controlnet_pose = ControlNetModel.from_pretrained(
     "lllyasviel/sd-controlnet-openpose", torch_dtype=torch.float16
@@ -16,21 +12,22 @@ controlnet_canny = ControlNetModel.from_pretrained(
 )
 
 pipe = StableDiffusionControlNetPipeline.from_pretrained(
-    "runwayml/stable-diffusion-v1-5", 
-    controlnet=[controlnet_pose,controlnet_canny], 
+    "runwayml/stable-diffusion-v1-5",
+    controlnet=[controlnet_pose, controlnet_canny],
     safety_checker=None, torch_dtype=torch.float16
-)
+).to('cuda')
 pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
 
 # This command loads the individual model components on GPU on-demand. So, we don't
 # need to explicitly call pipe.to("cuda").
-pipe.enable_model_cpu_offload()
+#pipe.enable_model_cpu_offload()
 
 # xformers
 pipe.enable_xformers_memory_efficient_attention()
 
 # Generator seed,
-generator = torch.manual_seed(0)
+generator = torch.manual_seed(3)
+
 
 def generate_images(pose_image, canny_image, prompt):
     output = pipe(
@@ -56,12 +53,17 @@ gr.Interface(
         gr.Textbox(
             label="Enter your prompt",
             max_lines=1,
-            placeholder="best quality, extremely detailed, a girl wearing white dress",
+            placeholder="masterpiece, a professional portrait of woman wearing white shirts",
         ),
     ],
     outputs=gr.Gallery().style(grid=[2], height="auto"),
     title="Generate controlled outputs with Mult-ControlNet and Stable Diffusion using 🤗Diffusers",
     description="This Space uses pose lines and canny edged image as the additional conditioning. Please refer to the \"Examples\" for what kind of images are appropriate.",
-    examples=[["sample_pose_body.png", "sample_canny_hand.png", "best quality, extremely detailed, a girl wearing white dress"]],
+    examples=[
+        ["p2_clip.png",
+         "c2_clip.png",
+         "masterpiece, a professional portrait of woman wearing white shirts"
+         ],
+    ],
     allow_flagging=False,
-).launch(enable_queue=True)
+).launch(enable_queue=True)