Update app.py

app.py

@@ -1,7 +1,35 @@
 import gradio as gr
+import cv2
+import numpy as np
+import watershed  # Your Python bindings module
 
-def greet(name):
-    return "Hello " + name + "!!"
+def segment_image(input_image):
+    # Convert the image received from Gradio into a format suitable for our C++ function
+    is_success, im_buf_arr = cv2.imencode(".jpg", input_image)
+    byte_im = im_buf_arr.tobytes()
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+    # You can save this to a file or directly pass it if your C++ function can handle byte streams
+    with open("temp_input.jpg", "wb") as f:
+        f.write(byte_im)
+
+    # Call the C++ watershed_segmentation function
+    watershed.watershed_segmentation("temp_input.jpg", "output.jpg")
+
+    # Read the output image to display in Gradio
+    output_img = cv2.imread("output.jpg")
+
+    # Convert from BGR (OpenCV format) to RGB (for displaying in Gradio)
+    output_img = cv2.cvtColor(output_img, cv2.COLOR_BGR2RGB)
+    return output_img
+
+# Define Gradio interface
+interface = gr.Interface(
+    fn=segment_image, 
+    inputs=gr.inputs.Image(type="numpy", label="Input Image"), 
+    outputs=gr.outputs.Image(type="numpy", label="Segmented Image"),
+    live=True,
+    title="Watershed Image Segmentation",
+    description="Upload an image for watershed segmentation."
+)
+
+interface.launch()