Update app.py

app.py

@@ -31,7 +31,7 @@ pipeline.load_lora_weights(lora_weights_path)
 pipeline = pipeline.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024  # Reduce max image size to fit within memory constraints
+MAX_IMAGE_SIZE = 2048  # Reduce max image size to fit within memory constraints
 
 @spaces.GPU
 def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
@@ -63,6 +63,17 @@ body {
     background-color: #ffffff; /* Myntra's white background */
     color: #282c3f; /* Myntra's primary text color */
     font-family: 'Arial', sans-serif;
+    margin: 0;
+    padding: 0;
+}
+
+#header {
+    background-color: #ff3f6c; /* Myntra's pink color */
+    color: white;
+    text-align: center;
+    padding: 20px;
+    font-size: 24px;
+    font-weight: bold;
 }
 
 #col-container {
@@ -104,28 +115,6 @@ body {
     border-radius: 8px;
     margin-top: 20px;
 }
-
-.color-block {
-    height: 100px;
-    width: 100%;
-    margin-bottom: 10px;
-}
-
-.color-block-pink {
-    background-color: #ff3f6c;
-}
-
-.color-block-blue {
-    background-color: #3498db;
-}
-
-.color-block-green {
-    background-color: #2ecc71;
-}
-
-.color-block-yellow {
-    background-color: #f1c40f;
-}
 """
 
 if torch.cuda.is_available():
@@ -134,17 +123,13 @@ else:
     power_device = "CPU"
 
 with gr.Blocks(css=css) as demo:
+    gr.HTML("<div id='header'>Myntra Text-to-Image Generation</div>")
+    
     with gr.Column(elem_id="col-container"):
         gr.Markdown(f"""
-        # Text-to-Image Generation
         Currently running on {power_device}.
         """)
         
-        gr.HTML("<div class='color-block color-block-pink'></div>")
-        gr.HTML("<div class='color-block color-block-blue'></div>")
-        gr.HTML("<div class='color-block color-block-green'></div>")
-        gr.HTML("<div class='color-block color-block-yellow'></div>")
-
         with gr.Row():
             prompt = gr.Textbox(
                 label="Prompt",