Update app.py

app.py

@@ -12,7 +12,7 @@ feature_extractor = SegformerFeatureExtractor.from_pretrained(
 )
 model = TFSegformerForSemanticSegmentation.from_pretrained(
     "nickmuchi/segformer-b4-finetuned-segments-sidewalk",
-    from_pt=True
+
 )
 
 def ade_palette():
@@ -71,7 +71,7 @@ def label_to_color_image(label):
         raise ValueError("label value too large.")
     return colormap[label]
 
-def draw_plot(pred_img, seg, cursor_pos):
+def draw_plot_with_label(pred_img, seg, selected_label):
     fig = plt.figure(figsize=(20, 15))
 
     grid_spec = gridspec.GridSpec(1, 2, width_ratios=[6, 1])
@@ -79,25 +79,27 @@ def draw_plot(pred_img, seg, cursor_pos):
     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])
-    cursor_x, cursor_y = cursor_pos
 
-    mask = seg.numpy() == seg.numpy()[cursor_x, cursor_y]
-    mask_image = FULL_COLOR_MAP[mask].reshape(pred_img.shape)
+    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(mask_image.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 sepia(input_img, cursor_pos):
+def view_segmented_image(input_img, selected_label):
     input_img = Image.fromarray(input_img)
 
     inputs = feature_extractor(images=input_img, return_tensors="tf")
@@ -110,14 +112,22 @@ def sepia(input_img, cursor_pos):
     )
     seg = tf.math.argmax(logits, axis=-1)[0]
 
-    fig = draw_plot(np.array(input_img), seg, cursor_pos)
+    fig = draw_plot_with_label(np.array(input_img), seg, selected_label)
     return fig
 
-demo = gr.Interface(fn=sepia,
-                    inputs=["image", "canvas"],
-                    outputs="plot",
-                    examples=[["side-1.jpg", [200, 300]], ["side-2.jpg", [150, 250]], ["side-3.jpg", [100, 200]], ["side-4.jpg", [250, 400]]],
-                    live=True,
-                    allow_flagging='never')
+# 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.launch()