Adapt information

app.py

@@ -3,7 +3,6 @@ import numpy as np
 import time
 import math
 import random
-import imageio
 import torch
 
 from diffusers import AutoPipelineForImage2Image
@@ -11,9 +10,15 @@ 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
+# Automatic device detection
+if torch.cuda.is_available():
+    device = "cuda"
+    floatType = torch.float16
+    variant = "fp16"
+else:
+    device = "cpu"
+    floatType = torch.float32
+    variant = None
 
 pipe = AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype = floatType, variant = variant)
 pipe = pipe.to(device)
@@ -24,9 +29,7 @@ def update_seed(is_randomize_seed, seed):
     return seed
 
 def toggle_debug(is_debug_mode):
-    if is_debug_mode:
-        return [gr.update(visible = True)]
-    return [gr.update(visible = False)]
+    return [gr.update(visible = is_debug_mode)]
 
 def check(
     source_img,
@@ -38,6 +41,7 @@ def check(
     strength,
     denoising_steps,
     seed,
+    is_randomize_seed,
     debug_mode,
     progress = gr.Progress()
 ):
@@ -56,6 +60,7 @@ def redraw(
     image_guidance_scale,
     strength,
     denoising_steps,
+    is_randomize_seed,
     seed,
     debug_mode,
     progress = gr.Progress()
@@ -69,6 +74,7 @@ def redraw(
         image_guidance_scale,
         strength,
         denoising_steps,
+        is_randomize_seed,
         seed,
         debug_mode
     )
@@ -163,7 +169,7 @@ def redraw(
     minutes = minutes - (hours * 60)
     return [
         output_image,
-        "Start again to get a different result. The new image is " + str(output_width) + " pixels large and " + str(output_height) + " pixels high, so an image of " + f'{output_width * output_height:,}' + " pixels. The image have been generated in " + str(hours) + " h, " + str(minutes) + " min, " + str(secondes) + " sec." + limitation,
+        ("Start again to get a different result. " if is_randomize_seed else "") + "The new image is " + str(output_width) + " pixels large and " + str(output_height) + " pixels high, so an image of " + f'{output_width * output_height:,}' + " pixels. The image have been generated in " + str(hours) + " h, " + str(minutes) + " min, " + str(secondes) + " sec." + limitation,
         input_image
     ]
 
@@ -174,7 +180,7 @@ with gr.Blocks() as interface:
         <p style="text-align: center;">Modifies the global render of your image, at any resolution, freely, without account, without watermark, without installation, which can be downloaded</p>
         <br/>
         <br/>
-        🚀 Powered by <i>SDXL Turbo</i> artificial intellingence. For illustration purpose, not information purpose. The new content is not based on real information but imagination.
+        ✨ Powered by <i>SDXL Turbo</i> artificial intellingence. For illustration purpose, not information purpose. The new content is not based on real information but imagination.
         <br/>
         <ul>
         <li>To change the <b>view angle</b> of your image, I recommend to use <i>Zero123</i>,</li>
@@ -195,7 +201,7 @@ with gr.Blocks() as interface:
     )
     with gr.Column():
         source_img = gr.Image(label = "Your image", sources = ["upload", "webcam", "clipboard"], type = "pil")
-        prompt = gr.Textbox(label = "Prompt", info = "Describe the subject, the background and the style of image; 77 token limit", placeholder = "Describe what you want to see")
+        prompt = gr.Textbox(label = "Prompt", info = "Describe the subject, the background and the style of image; 77 token limit", placeholder = "Describe what you want to see", lines = 2)
         strength = gr.Slider(value = 0.5, minimum = 0.01, maximum = 1.0, step = 0.01, label = "Strength", info = "lower=follow the original image, higher=follow the prompt")
         with gr.Accordion("Advanced options", open = False):
              negative_prompt = gr.Textbox(label = "Negative prompt", placeholder = "Describe what you do NOT want to see", value = "Ugly, malformed, noise, blur, watermark")
@@ -207,14 +213,15 @@ with gr.Blocks() as interface:
              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")
 
-        submit = gr.Button("Redraw", variant = "primary")
+        submit = gr.Button("🚀 Redraw", variant = "primary")
 
         redrawn_image = gr.Image(label = "Redrawn image")
         information = gr.Label(label = "Information")
         original_image = gr.Image(label = "Original image", visible = False)
 
     submit.click(update_seed, inputs = [
-        randomize_seed, seed
+        randomize_seed,
+        seed
     ], outputs = [
         seed
     ], queue = False, show_progress = False).then(toggle_debug, debug_mode, [
@@ -228,6 +235,7 @@ with gr.Blocks() as interface:
         image_guidance_scale,
         strength,
         denoising_steps,
+        randomize_seed,
         seed,
         debug_mode
     ], outputs = [], queue = False, show_progress = False).success(redraw, inputs = [
@@ -239,6 +247,7 @@ with gr.Blocks() as interface:
         image_guidance_scale,
         strength,
         denoising_steps,
+        randomize_seed,
         seed,
         debug_mode
     ], outputs = [
@@ -258,6 +267,7 @@ with gr.Blocks() as interface:
             image_guidance_scale,
             strength,
             denoising_steps,
+            randomize_seed,
             seed,
             debug_mode
         ],
@@ -276,6 +286,7 @@ with gr.Blocks() as interface:
                     1.1,
                     0.6,
                     1000,
+                    False,
                     42,
                     False
                 ],