Update app.py

app.py

@@ -1,44 +1,43 @@
 import gradio as gr
-from skimage import io, filters, color
+from skimage.restoration import inpaint
+from skimage import color
 import cv2
 import numpy as np
-from skimage.restoration import inpaint
 
 # 邊緣檢測函式
 def edge_detection(image, threshold1, threshold2):
-    # 轉為灰階圖片
     gray_image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
-    # 使用 Canny 邊緣檢測
     edges = cv2.Canny(gray_image, threshold1, threshold2)
     return edges
 
 # 圖像分割函式
 def image_segmentation(image, compactness):
     from skimage.segmentation import slic
-    # 使用 SLIC 方法進行圖像分割
     segments = slic(image, compactness=compactness, n_segments=200)
     return color.label2rgb(segments, image, kind='avg')
 
 # 圖像修復函式
 def inpaint_image(image, mask_threshold):
     # 確保圖片格式為 RGB
-    if image.shape[-1] == 4:  # 若圖片有 alpha 通道
+    if image.shape[-1] == 4:  # 如果圖片有 alpha 通道
         image = cv2.cvtColor(image, cv2.COLOR_RGBA2RGB)
     elif image.shape[-1] == 3:
         image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
     
+    # 轉為灰階圖片
     gray_image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+    # 根據遮罩閾值生成遮罩
     _, mask = cv2.threshold(gray_image, mask_threshold, 255, cv2.THRESH_BINARY)
     mask = mask.astype(bool)
     
+    # 如果遮罩無效，拋出錯誤
     if not mask.any():
         raise ValueError("遮罩生成失敗，請調整遮罩閾值參數。")
     
+    # 使用 biharmonic 方法修復圖像
     inpainted = inpaint.inpaint_biharmonic(image, mask, multichannel=True)
     return inpainted
 
-
-
 # 主應用程式
 def app():
     with gr.Blocks() as demo:
@@ -53,7 +52,11 @@ def app():
                 threshold1 = gr.Slider(0, 255, value=100, step=1, label="閾值1")
                 threshold2 = gr.Slider(0, 255, value=200, step=1, label="閾值2")
             edge_button = gr.Button("執行邊緣檢測")
-            edge_button.click(edge_detection, inputs=[input_image, threshold1, threshold2], outputs=edge_result)
+            edge_button.click(
+                fn=edge_detection, 
+                inputs=[input_image, threshold1, threshold2], 
+                outputs=edge_result
+            )
         
         with gr.Tab("圖像分割"):
             with gr.Row():
@@ -62,7 +65,11 @@ def app():
             with gr.Row():
                 compactness = gr.Slider(0.1, 100, value=10, step=0.1, label="分割緊湊度")
             seg_button = gr.Button("執行圖像分割")
-            seg_button.click(image_segmentation, inputs=[input_image, compactness], outputs=seg_result)
+            seg_button.click(
+                fn=image_segmentation, 
+                inputs=[input_image, compactness], 
+                outputs=seg_result
+            )
         
         with gr.Tab("圖像修復"):
             with gr.Row():
@@ -75,12 +82,11 @@ def app():
                 fn=inpaint_image, 
                 inputs=[input_image, mask_threshold], 
                 outputs=inpaint_result,
-                show_error=True  # 這會將錯誤訊息顯示在 UI 上
+                show_error=True  # 在 UI 上顯示錯誤訊息
             )
-
     
     return demo
 
 # 啟動應用程式
 if __name__ == "__main__":
-    app().launch()
+    app().launch()