Update app.py

app.py

@@ -62,17 +62,11 @@ class Prodia:
 
 
 def image_to_base64(image_path):
-    # Open the image with PIL
     with Image.open(image_path) as image:
-        # Convert the image to bytes
         buffered = BytesIO()
-        image.save(buffered, format="PNG")  # You can change format to PNG if needed
-
-        # Encode the bytes to base64
+        image.save(buffered, format="PNG")
         img_str = base64.b64encode(buffered.getvalue())
-
-    return img_str.decode('utf-8')  # Convert bytes to string
-
+    return img_str.decode('utf-8')
 
 
 prodia_client = Prodia(api_key=os.getenv("PRODIA_API_KEY"))
@@ -101,50 +95,35 @@ css = """
 """
 
 with gr.Blocks(css=css) as demo:
-
-
     with gr.Row():
-        with gr.Column(scale=6):
-            model = gr.Dropdown(interactive=True,value="sd_xl_base_1.0.safetensors [be9edd61]", show_label=True, label="Stable Diffusion Checkpoint", choices=prodia_client.list_models())
-
-        with gr.Column(scale=1):
-            gr.Markdown(elem_id="powered-by-prodia", value="AUTOMATIC1111 Stable Diffusion Web UI for SDXL V1.0.<br>Powered by [Prodia](https://prodia.com).")
-
-    with gr.Tab("txt2img"):
-        with gr.Row():
-            with gr.Column(scale=6, min_width=600):
-                prompt = gr.Textbox("space warrior, beautiful, female, ultrarealistic, soft lighting, 8k", placeholder="Prompt", show_label=False, lines=3)
-                negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=False, lines=3, value="3d, cartoon, anime, (deformed eyes, nose, ears, nose), bad anatomy, ugly")
-            with gr.Column():
-                text_button = gr.Button("Generate", variant='primary', elem_id="generate")
-
-        with gr.Row():
-            with gr.Column(scale=3):
-                with gr.Tab("Generation"):
-                    with gr.Row():
-                        with gr.Column(scale=1):
-                            sampler = gr.Dropdown(value="DPM++ 2M Karras", show_label=True, label="Sampling Method", choices=prodia_client.list_samplers())
-
-                        with gr.Column(scale=1):
-                            steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=25, value=20, step=1)
-
-                    with gr.Row():
-                        with gr.Column(scale=1):
-                            width = gr.Slider(label="Width", minimum=512, maximum=1536, value=1024, step=8)
-                            height = gr.Slider(label="Height", minimum=512, maximum=1536, value=1024, step=8)
-                            gr.Markdown(elem_id="resolution", value="*Resolution Maximum: 1MP (1048576 px)*")
-
-                        with gr.Column(scale=1):
-                            batch_size = gr.Slider(label="Batch Size", maximum=1, value=1)
-                            batch_count = gr.Slider(label="Batch Count", maximum=1, value=1)
-
-                    cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)
-                    seed = gr.Number(label="Seed", value=-1)
-
+        with gr.Column():
+            gr.Markdown("# Disney Pixar AI Poster Generator")
+            gr.Markdown("Enter your prompt and adjust the settings to generate a Disney Pixar style AI poster.")
+    
+    with gr.Row():
+        with gr.Column(scale=2):
+            prompt = gr.Textbox("space warrior, beautiful, female, ultrarealistic, soft lighting, 8k", placeholder="Prompt", show_label=False, lines=3)
+            negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=False, lines=3, value="3d, cartoon, anime, (deformed eyes, nose, ears, nose), bad anatomy, ugly")
+            text_button = gr.Button("Generate", variant='primary', elem_id="generate")
 
-            with gr.Column(scale=2):
-                image_output = gr.Image(value="https://cdn-uploads.huggingface.co/production/uploads/noauth/XWJyh9DhMGXrzyRJk7SfP.png")
+        with gr.Column(scale=4):
+            image_output = gr.Image(value="https://cdn-uploads.huggingface.co/production/uploads/noauth/XWJyh9DhMGXrzyRJk7SfP.png", label="Generated Image")
 
-        text_button.click(flip_text, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output)
+    with gr.Row():
+        with gr.Column(scale=2):
+            model = gr.Dropdown(interactive=True, value="sd_xl_base_1.0.safetensors [be9edd61]", show_label=True, label="Stable Diffusion Checkpoint", choices=prodia_client.list_models())
+            sampler = gr.Dropdown(value="DPM++ 2M Karras", show_label=True, label="Sampling Method", choices=prodia_client.list_samplers())
+            steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=25, value=20, step=1)
+            cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)
+            seed = gr.Number(label="Seed", value=-1)
+
+        with gr.Column(scale=2):
+            width = gr.Slider(label="Width", minimum=512, maximum=1536, value=1024, step=8)
+            height = gr.Slider(label="Height", minimum=512, maximum=1536, value=1024, step=8)
+            batch_size = gr.Slider(label="Batch Size", maximum=1, value=1)
+            batch_count = gr.Slider(label="Batch Count", maximum=1, value=1)
+            gr.Markdown("*Resolution Maximum: 1MP (1048576 px)*")
+
+    text_button.click(flip_text, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output)
 
 demo.queue(concurrency_count=24, max_size=32, api_open=False).launch(max_threads=128)