Update app.py

app.py

@@ -7,7 +7,7 @@ import numpy as np
 import PIL.Image
 import torch
 import torchvision.transforms.functional as TF
-from diffusers import DDPMScheduler, StableDiffusionXLAdapterPipeline, T2IAdapter
+from diffusers import EulerAncestralDiscreteScheduler, StableDiffusionXLAdapterPipeline, T2IAdapter
 
 DESCRIPTION = "# T2I-Adapter-SDXL Sketch"
 
@@ -65,7 +65,7 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 if torch.cuda.is_available():
     model_id = "stabilityai/stable-diffusion-xl-base-1.0"
     adapter = T2IAdapter.from_pretrained("TencentARC/t2i-adapter-sketch-sdxl-1.0", torch_dtype=torch.float16, variant="fp16")
-    scheduler = DDPMScheduler.from_pretrained(model_id, subfolder="scheduler")
+    scheduler = EulerAncestralDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
     pipe = StableDiffusionXLAdapterPipeline.from_pretrained(
         model_id,
         adapter=adapter,
@@ -115,7 +115,7 @@ def run(
         adapter_conditioning_scale=adapter_conditioning_scale,
         cond_tau=cond_tau,
     ).images[0]
-    return out
+    return out, image
 
 
 with gr.Blocks() as demo:
@@ -141,7 +141,7 @@ with gr.Blocks() as demo:
                     label="Style"
                 )
                 negative_prompt = gr.Textbox(
-                    label="Negative prompt", value="extra digit, fewer digits, cropped, worst quality, low quality"
+                    label="Negative prompt", value=""
                 )
                 num_steps = gr.Slider(
                     label="Number of steps",
@@ -180,7 +180,8 @@ with gr.Blocks() as demo:
                 )
                 randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
         with gr.Column():
-            result = gr.Image(label="Result", height=600)
+            # result = gr.Image(label="Result", height=600)
+            result = gr.Gallery(label="Result").style(grid=(1,2))
 
     inputs = [
         image,