Update app.py

app.py

@@ -44,7 +44,7 @@ birefnet = AutoModelForImageSegmentation.from_pretrained("ZhengPeng7/BiRefNet",
 image_size = (1024, 1024)
 
 @spaces.GPU
-def evaluate(fg_image: PIL.Image.Image, bg_image: PIL.Image.Image, num_sampling_steps: int = 1):
+def evaluate(fg_image: PIL.Image.Image, bg_image: PIL.Image.Image, num_sampling_steps: int = 4):
     ori_h_bg, ori_w_bg = fg_image.size
     ar_bg = ori_h_bg / ori_w_bg
     closest_ar_bg = min(ASPECT_RATIOS, key=lambda x: abs(float(x) - ar_bg))
@@ -74,10 +74,10 @@ body::before {
     content: "";
     display: block;
     height: 640px;
-    background-color: var(--block-background-fill);  /* Gradio's CSS variable */
+    background-color: inherit;
 }
 button[aria-label="Download"] {
-    transform: scale(2.5);
+    transform: scale(2);
     transform-origin: top right;
     margin: 0 !important;
     padding: 6px !important;
@@ -103,12 +103,9 @@ button[aria-label="Open in new tab"] {
             with gr.Row():
                 submit_button = gr.Button("Rindriço", variant="primary")
             with gr.Row():
-                num_inference_steps = gr.Slider(minimum=1, maximum=4, value=1, step=1, label="Hapat e Inferencës")
+                num_inference_steps = gr.Slider(minimum=1, maximum=4, value=4, step=1, visible=False)
 
-            bg_gallery = gr.Gallery(
-                object_fit="contain",
-                label="Sfondet", value=[path for path in glob.glob("examples/backgrounds/*.jpg")],
-                columns=5, allow_preview=False)
+            bg_gallery = gr.Gallery(object_fit="contain", visible=False)
 
         with gr.Column():
             output_slider = gr.ImageSlider(label="Para / Pas", type="numpy")