Update app.py

app.py

@@ -71,7 +71,7 @@ def label_to_color_image(label):
         raise ValueError("label value too large.")
     return colormap[label]
 
-def draw_plot_with_label(pred_img, seg, selected_label):
+def draw_plot(pred_img, seg):
     fig = plt.figure(figsize=(20, 15))
 
     grid_spec = gridspec.GridSpec(1, 2, width_ratios=[6, 1])
@@ -79,27 +79,21 @@ def draw_plot_with_label(pred_img, seg, selected_label):
     plt.subplot(grid_spec[0])
     plt.imshow(pred_img)
     plt.axis('off')
-
     LABEL_NAMES = np.asarray(labels_list)
     FULL_LABEL_MAP = np.arange(len(LABEL_NAMES)).reshape(len(LABEL_NAMES), 1)
     FULL_COLOR_MAP = label_to_color_image(FULL_LABEL_MAP)
 
     unique_labels = np.unique(seg.numpy().astype("uint8"))
     ax = plt.subplot(grid_spec[1])
-
-    if selected_label in unique_labels:
-        mask = seg.numpy() == selected_label
-        mask_image = FULL_COLOR_MAP[mask].reshape(pred_img.shape)
-        plt.imshow(mask_image.astype(np.uint8), interpolation="nearest")
-        plt.yticks([0], [LABEL_NAMES[selected_label]])
-    else:
-        plt.text(0.5, 0.5, "Label not found", fontsize=20, ha='center')
-
+    plt.imshow(FULL_COLOR_MAP[unique_labels].astype(np.uint8), interpolation="nearest")
+    ax.yaxis.tick_right()
+    plt.yticks(range(len(unique_labels)), LABEL_NAMES[unique_labels])
     plt.xticks([], [])
     ax.tick_params(width=0.0, labelsize=25)
     return fig
 
-def view_segmented_image(input_img, selected_label):
+
+def sepia(input_img):
     input_img = Image.fromarray(input_img)
 
     inputs = feature_extractor(images=input_img, return_tensors="tf")
@@ -109,25 +103,27 @@ def view_segmented_image(input_img, selected_label):
     logits = tf.transpose(logits, [0, 2, 3, 1])
     logits = tf.image.resize(
         logits, input_img.size[::-1]
-    )
+    )  # We reverse the shape of `image` because `image.size` returns width and height.
     seg = tf.math.argmax(logits, axis=-1)[0]
 
-    fig = draw_plot_with_label(np.array(input_img), seg, selected_label)
+    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
+
+    # Show image + mask
+    pred_img = np.array(input_img) * 0.5 + color_seg * 0.5
+    pred_img = pred_img.astype(np.uint8)
+
+    fig = draw_plot(pred_img, seg)
     return fig
 
-# 그래디오 인터페이스 설정
-demo = gr.Interface(
-    fn=view_segmented_image,
-    inputs=["image", "dropdown"],
-    outputs="plot",
-    examples=[
-        ["side-1.jpg", "sidewalk"],
-        ["side-2.jpg", "person"],
-        ["side-3.jpg", "car"],
-        ["side-4.jpg", "building"]
-    ],
-    live=True,
-    allow_flagging='never'
-)
+demo = gr.Interface(fn=sepia,
+                    inputs=gr.Image(shape=(400, 600)),
+                    outputs=['plot'],
+                    examples=["person-1.jpg", "person-2.jpg", "person-3.jpg", "person-4.jpg", "person-5.jpg"],
+                    allow_flagging='never')
+
 
-demo.launch()
+demo.launch()