Update app.py

app.py

@@ -95,7 +95,7 @@ def draw_plot(pred_img, seg):
     return fig
 
 
-def sepia(input_img, title):
+def sepia(input_img):
     input_img = Image.fromarray(input_img)
 
     inputs = feature_extractor(images=input_img, return_tensors="tf")
@@ -108,22 +108,19 @@ def sepia(input_img, title):
     )  # We reverse the shape of `image` because `image.size` returns width and height.
     seg = tf.math.argmax(logits, axis=-1)[0]
 
-    unique_labels = np.unique(seg.numpy())
-    label_images = {}
+    color_seg = np.zeros(
+        (seg.shape[0], seg.shape[1], 3), dtype=np.uint8
+    )  # height, width, 3
+    for label, color in enumerate(colormap):
+        color_seg[seg.numpy() == label, :] = color
 
-    for label in unique_labels:
-        mask = (seg.numpy() == label)
-        color_mask = np.zeros((seg.shape[0], seg.shape[1], 3), dtype=np.uint8)
-        color_mask[mask, :] = colormap[label]
-        pred_img = np.array(input_img) * 0.5 + color_mask * 0.5
-        pred_img = pred_img.astype(np.uint8)
-        fig = draw_plot(pred_img, seg)
-        label_images[str(label)] = fig
+    # Show image + mask
+    pred_img = np.array(input_img) * 0.5 + color_seg * 0.5
+    pred_img = pred_img.astype(np.uint8)
 
-    # Add title to the figure
-    plt.suptitle(title, fontsize=20)
+    fig = draw_plot(pred_img, seg)
+    return fig
 
-    return label_images
 
 demo = gr.Interface(fn=sepia,
                     inputs=[gr.Image(shape=(400, 600), label="Input Image"), "text"],