Do update seed

app.py

@@ -1,11 +1,12 @@
 from diffusers import StableDiffusionXLInpaintPipeline
+from PIL import Image, ImageFilter
+
 import gradio as gr
 import numpy as np
 import time
 import math
 import random
 import imageio
-from PIL import Image, ImageFilter
 import torch
 
 max_64_bit_int = 2**63 - 1
@@ -16,6 +17,16 @@ variant = "fp16" if torch.cuda.is_available() else None
 pipe = StableDiffusionXLInpaintPipeline.from_pretrained("diffusers/stable-diffusion-xl-1.0-inpainting-0.1", torch_dtype = floatType, variant = variant)
 pipe = pipe.to(device)
 
+def update_seed(is_randomize_seed, seed):
+    if is_randomize_seed:
+        return random.randint(0, max_64_bit_int)
+    return seed
+
+def toggle_debug(is_debug_mode):
+    if is_debug_mode:
+        return [gr.update(visible = True)] * 3
+    return [gr.update(visible = False)] * 3
+
 def noise_color(color, noise):
     return color + random.randint(- noise, noise)
 
@@ -136,7 +147,7 @@ def uncrop(
         seed = random.randint(0, max_64_bit_int)
 
     random.seed(seed)
-    #pipe = pipe.manual_seed(seed)
+    torch.manual_seed(seed)
 
     original_height, original_width, original_channel = np.array(input_image).shape
     output_width = enlarge_left + original_width + enlarge_right
@@ -253,17 +264,6 @@ def uncrop(
         mask_image
     ]
 
-def update_seed(is_randomize_seed, seed):
-    if is_randomize_seed:
-        return random.randint(0, max_64_bit_int)
-    return seed
-
-def toggle_debug(is_debug_mode):
-    if is_debug_mode:
-        return [gr.update(visible = True)] * 3
-    else:
-        return [gr.update(visible = False)] * 3
-
 with gr.Blocks() as interface:
     gr.Markdown(
         """
@@ -322,7 +322,7 @@ with gr.Blocks() as interface:
             image_guidance_scale = gr.Slider(minimum = 1, value = 1.5, step = 0.1, label = "Image Guidance Scale", info = "lower=image quality, higher=follow the image")
             strength = gr.Slider(value = 0.99, minimum = 0.01, maximum = 1.0, step = 0.01, label = "Strength", info = "lower=follow the original area (discouraged), higher=redraw from scratch")
             denoising_steps = gr.Number(minimum = 0, value = 1000, step = 1, label = "Denoising", info = "lower=irrelevant result, higher=relevant result")
-            randomize_seed = gr.Checkbox(label = "\U0001F3B2 Randomize seed (not working, always random)", value = True, info = "If checked, result is always different")
+            randomize_seed = gr.Checkbox(label = "\U0001F3B2 Randomize seed", value = True, info = "If checked, result is always different")
             seed = gr.Slider(minimum = 0, maximum = max_64_bit_int, step = 1, randomize = True, label = "Seed")
             debug_mode = gr.Checkbox(label = "Debug mode", value = False, info = "Show intermediate results")
 
@@ -340,7 +340,12 @@ with gr.Blocks() as interface:
     with gr.Row():
         mask_image = gr.Image(label = "Mask image", visible = False)
 
-    submit.click(toggle_debug, debug_mode, [
+    submit.click(fn = update_seed, inputs = [
+        randomize_seed,
+        seed
+    ], outputs = [
+        seed
+    ], queue = False, show_progress = False).then(toggle_debug, debug_mode, [
         original_image,
         enlarged_image,
         mask_image