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app.py

@@ -1,6 +1,3 @@
-from diffusers import AutoPipelineForImage2Image
-from PIL import Image, ImageFilter
-
 import gradio as gr
 import numpy as np
 import time
@@ -9,11 +6,15 @@ import random
 import imageio
 import torch
 
+from diffusers import AutoPipelineForImage2Image
+from PIL import Image, ImageFilter
+
 max_64_bit_int = 2**63 - 1
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 floatType = torch.float16 if torch.cuda.is_available() else torch.float32
 variant = "fp16" if torch.cuda.is_available() else None
+
 pipe = AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype = floatType, variant = variant)
 pipe = pipe.to(device)
 
@@ -46,7 +47,7 @@ def check(
     if prompt is None or prompt == "":
         raise gr.Error("Please provide a prompt input.")
 
-def inpaint(
+def redraw(
     source_img,
     prompt,
     negative_prompt,
@@ -229,7 +230,7 @@ with gr.Blocks() as interface:
         denoising_steps,
         seed,
         debug_mode
-    ], outputs = [], queue = False, show_progress = False).success(inpaint, inputs = [
+    ], outputs = [], queue = False, show_progress = False).success(redraw, inputs = [
         source_img,
         prompt,
         negative_prompt,
@@ -247,6 +248,7 @@ with gr.Blocks() as interface:
     ], scroll_to_output = True)
 
     gr.Examples(
+        fn = redraw,
 	    inputs = [
             source_img,
             prompt,
@@ -256,7 +258,6 @@ with gr.Blocks() as interface:
             image_guidance_scale,
             strength,
             denoising_steps,
-            randomize_seed,
             seed,
             debug_mode
         ],
@@ -275,7 +276,6 @@ with gr.Blocks() as interface:
                     1.1,
                     0.6,
                     1000,
-                    True,
                     42,
                     False
                 ],