Init project

main.py

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+import gradio as gr
+from skimage import filters, color
+import numpy as np
+import cv2
+
+# 邊緣檢測函數
+def edge_detection(image, threshold1, threshold2, method):
+    if method == "Canny (OpenCV)":
+        edges = cv2.Canny(image, threshold1, threshold2)
+    elif method == "Sobel (skimage)":
+        gray = color.rgb2gray(image) if len(image.shape) == 3 else image
+        edges = filters.sobel(gray)
+        edges = (edges * 255).astype(np.uint8)  # 轉換為 0-255 範圍
+    else:
+        raise ValueError("Unknown method selected.")
+    return edges
+
+# 動態更新閾值參數的顯示狀態
+def update_threshold_visibility(method):
+    if method == "Canny (OpenCV)":
+        return gr.update(visible=True), gr.update(visible=True)
+    else:
+        return gr.update(visible=False), gr.update(visible=False)
+
+# 設定 Gradio UI
+def main():
+    with gr.Blocks() as demo:
+        gr.Markdown("# Edge Detection App")
+        gr.Markdown("### Upload an image or select an example to detect edges.")
+        
+        with gr.Row():
+            with gr.Column():
+                input_image = gr.Image(label="Input Image", type="numpy")
+                method = gr.Radio(
+                    ["Canny (OpenCV)", "Sobel (skimage)"], 
+                    value="Canny (OpenCV)", 
+                    label="Edge Detection Method"
+                )
+                low_threshold = gr.Slider(0, 255, value=100, step=1, label="Low Threshold", visible=True)
+                high_threshold = gr.Slider(0, 255, value=200, step=1, label="High Threshold", visible=True)
+            with gr.Column():
+                output_image = gr.Image(label="Output Image")
+        
+        # 示例圖片與參數
+        examples = gr.Examples(
+            examples=[
+                ["lenna.png", "Canny (OpenCV)", 100, 200],
+                ["coin.png", "Sobel (skimage)", 0, 0],
+                ["flower.png", "Canny (OpenCV)", 50, 150],
+            ],
+            inputs=[input_image, method, low_threshold, high_threshold],
+        )
+        
+        # 動態更新閾值參數的顯示
+        method.change(
+            update_threshold_visibility, 
+            inputs=[method], 
+            outputs=[low_threshold, high_threshold]
+        )
+        
+        # 自動執行邊緣檢測
+        input_image.change(
+            edge_detection, 
+            inputs=[input_image, low_threshold, high_threshold, method], 
+            outputs=[output_image]
+        )
+        
+        # 手動按鈕執行（備選方式）
+        submit_btn = gr.Button("Detect Edges")
+        submit_btn.click(
+            edge_detection, 
+            inputs=[input_image, low_threshold, high_threshold, method], 
+            outputs=[output_image]
+        )
+
+    return demo
+
+# 啟動應用
+if __name__ == "__main__":
+    app = main()
+    app.launch()