Adapt information

app.py

@@ -16,8 +16,12 @@ 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
+if torch.cuda.is_available():
+    device = "cuda"
+    floatType = torch.float16
+else:
+    device = "cpu"
+    floatType = torch.float32
 
 controlnet = ControlNetModel.from_pretrained("lllyasviel/control_v11e_sd15_ip2p", torch_dtype = floatType)
 pipe = StableDiffusionControlNetPipeline.from_pretrained(
@@ -38,6 +42,7 @@ def check(
     num_inference_steps,
     guidance_scale,
     image_guidance_scale,
+    is_randomize_seed,
     seed,
     progress = gr.Progress()):
     if input_image is None:
@@ -54,6 +59,7 @@ def pix2pix(
     num_inference_steps,
     guidance_scale,
     image_guidance_scale,
+    is_randomize_seed,
     seed,
     progress = gr.Progress()):
     check(
@@ -64,6 +70,7 @@ def pix2pix(
         num_inference_steps,
         guidance_scale,
         image_guidance_scale,
+        is_randomize_seed,
         seed
     )
     start = time.time()
@@ -136,7 +143,7 @@ def pix2pix(
     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
     ]
 
 with gr.Blocks() as interface:
@@ -146,7 +153,7 @@ with gr.Blocks() as interface:
         <p style="text-align: center;">Modifies your image using a textual instruction, freely, without account, without watermark, without installation, which can be downloaded</p>
         <br/>
         <br/>
-        🚀 Powered by <i>SD 1.5</i> and <i>ControlNet</i>. The result quality extremely varies depending on what we ask.
+        ✨ Powered by <i>SD 1.5</i> and <i>ControlNet</i>. The result quality extremely varies depending on what we ask.
         <br/>
         <ul>
         <li>To change the <b>view angle</b> of your image, I recommend to use <i>Zero123</i>,</li>
@@ -166,9 +173,9 @@ with gr.Blocks() as interface:
     )
     with gr.Column():
         input_image = gr.Image(label = "Your image", sources = ["upload", "webcam", "clipboard"], type = "pil")
-        prompt = gr.Textbox(label = 'Prompt', info = "Instruct what to change in the image", placeholder = 'Order the AI what to change in the image')
+        prompt = gr.Textbox(label = "Prompt", info = "Instruct what to change in the image", placeholder = "Order the AI what to change in the image", lines = 2)
         with gr.Accordion("Advanced options", open = False):
-            negative_prompt = gr.Textbox(label = 'Negative prompt', placeholder = 'Describe what you do NOT want to see in the image', value = 'Watermark')
+            negative_prompt = gr.Textbox(label = "Negative prompt", placeholder = "Describe what you do NOT want to see in the image", value = "Watermark")
             denoising_steps = gr.Slider(minimum = 0, maximum = 1000, value = 0, step = 1, label = "Denoising", info = "lower=irrelevant result, higher=relevant result")
             num_inference_steps = gr.Slider(minimum = 10, maximum = 500, value = 20, step = 1, label = "Number of inference steps", info = "lower=faster, higher=image quality")
             guidance_scale = gr.Slider(minimum = 1, maximum = 13, value = 5, step = 0.1, label = "Classifier-Free Guidance Scale", info = "lower=image quality, higher=follow the prompt")
@@ -176,7 +183,7 @@ with gr.Blocks() as interface:
             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")
 
-        submit = gr.Button("Modify", variant = "primary")
+        submit = gr.Button("🚀 Modify", variant = "primary")
 
         modified_image = gr.Image(label = "Modified image")
         information = gr.Label(label = "Information")
@@ -194,6 +201,7 @@ with gr.Blocks() as interface:
         num_inference_steps,
         guidance_scale,
         image_guidance_scale,
+        randomize_seed,
         seed
     ], outputs = [], queue = False, show_progress = False).success(pix2pix, inputs = [
         input_image,
@@ -203,6 +211,7 @@ with gr.Blocks() as interface:
         num_inference_steps,
         guidance_scale,
         image_guidance_scale,
+        randomize_seed,
         seed
     ], outputs = [
         modified_image,
@@ -219,6 +228,7 @@ with gr.Blocks() as interface:
             num_inference_steps,
             guidance_scale,
             image_guidance_scale,
+            randomize_seed,
             seed
         ],
 	    outputs = [
@@ -234,6 +244,7 @@ with gr.Blocks() as interface:
                     20,
                     5,
                     1.5,
+                    False,
                     42
                 ],
                 [
@@ -244,6 +255,7 @@ with gr.Blocks() as interface:
                     20,
                     5,
                     1.5,
+                    False,
                     42
                 ],
                 [
@@ -254,6 +266,7 @@ with gr.Blocks() as interface:
                     20,
                     5,
                     1.5,
+                    False,
                     42
                 ],
                 [
@@ -264,6 +277,7 @@ with gr.Blocks() as interface:
                     20,
                     5,
                     1.5,
+                    False,
                     42
                 ],
                 [
@@ -274,6 +288,7 @@ with gr.Blocks() as interface:
                     20,
                     5,
                     25,
+                    False,
                     42
                 ],
             ],