Update app.py

app.py

@@ -266,11 +266,44 @@ def sepia(input_img):
     fig = draw_plot(pred_img, seg)
     return fig
 
-demo = gr.Interface(fn=sepia,
-                    inputs=gr.Image(shape=(400, 600)),
-                    outputs=['plot'],
-                    examples=["c-1.jpg", "c-2.jpg", "c-3.jpg"],
-                    allow_flagging='never')
+def custom_interface(input_image):
+    # Process input image
+    input_img = Image.fromarray(input_image)
+    inputs = feature_extractor(images=input_img, return_tensors="tf")
+    outputs = model(**inputs)
+    logits = outputs.logits
 
+    logits = tf.transpose(logits, [0, 2, 3, 1])
+    logits = tf.image.resize(
+        logits, input_img.size[::-1]
+    )
+    seg = tf.math.argmax(logits, axis=-1)[0]
+
+    color_seg = np.zeros(
+        (seg.shape[0], seg.shape[1], 3), dtype=np.uint8
+    )
+    for label, color in enumerate(colormap):
+        color_seg[seg.numpy() == label, :] = color
+
+    # Combine original image and mask
+    pred_img = np.array(input_img) * 0.5 + color_seg * 0.5
+    pred_img = pred_img.astype(np.uint8)
+
+    # Create a figure with custom style
+    fig = plt.figure(figsize=(10, 10))
+    plt.imshow(pred_img)
+    plt.axis('off')
+    plt.title("Segmented Image", fontsize=18, color="#333")  # Customize title
+    return fig
+
+# Create the Gradio interface with the custom style
+demo = gr.Interface(
+    fn=custom_interface,
+    inputs=gr.Image(shape=(400, 600)),
+    outputs=["plot"],
+    examples=["c-1.jpg", "c-2.jpg", "c-3.jpg"],
+    allow_flagging="never",
+    live=False  # Disabling live updates for this example
+)
 
 demo.launch()