Update app.py

app.py

@@ -1,16 +1,18 @@
 import cv2
 import gradio as gr
+import numpy as np
 
 # Define a function for marker-based segmentation using the OpenCV watershed algorithm
 def watershed_segmentation(input_image, markers_image):
-    # Load the input image
-    image = cv2.imdecode(input_image, cv2.IMREAD_COLOR)
-    
+    # Convert input images to numpy arrays
+    input_image = np.array(input_image)
+    markers_image = np.array(markers_image)
+
     # Load the marker image (binary image with markers)
-    markers = cv2.imdecode(markers_image, cv2.IMREAD_GRAYSCALE)
+    markers = cv2.cvtColor(markers_image, cv2.COLOR_BGR2GRAY)
     
     # Apply the watershed algorithm
-    image_copy = image.copy()
+    image_copy = input_image.copy()
     cv2.watershed(image_copy, markers)
     
     # Apply color mapping to the segmented regions
@@ -19,8 +21,8 @@ def watershed_segmentation(input_image, markers_image):
     return segmented_image
 
 # Define Gradio interfaces for the input and output
-input_image = gr.inputs.Image()
-markers_image = gr.inputs.Image()
+input_image = gr.inputs.Image(type="numpy")
+markers_image = gr.inputs.Image(type="numpy")
 output_image = gr.outputs.Image()
 
 # Create a Gradio app