Update app.py

app.py

@@ -2,22 +2,33 @@ import gradio as gr
 import cv2
 import numpy as np
 
-# Define a function that performs the image operation
-def perform_image_operation(image1, image2):
+# Define a function that performs the image operation with adjustable blending weight
+def perform_image_operation(image1, image2, image3, image4, image5, image6, image7, image8, blending_weight=0.5):
+    # Convert the Gradio input images to NumPy arrays
+    images = [image1, image2, image3, image4, image5, image6, image7, image8]
+
     # Perform the image operation (e.g., blending)
-    alpha = 0.5  # Adjust alpha for blending
-    blended_image = cv2.addWeighted(image1, alpha, image2, 1 - alpha, 0)
+    result_image = images[0].copy()
+    for img in images[1:]:
+        result_image = cv2.addWeighted(result_image, 1 - blending_weight, img, blending_weight, 0)
 
     # Convert the result image to PIL format for Gradio display
-    result_pil_image = cv2.cvtColor(blended_image, cv2.COLOR_BGR2RGB)
+    result_pil_image = cv2.cvtColor(result_image, cv2.COLOR_BGR2RGB)
     return result_pil_image
 
-# Define the Gradio interface
+# Define the Gradio interface with an adjustable blending weight slider
 iface = gr.Interface(
     fn=perform_image_operation,
     inputs=[
         gr.inputs.Image(label="Input Image 1"),
-        gr.inputs.Image(label="Input Image 2")
+        gr.inputs.Image(label="Input Image 2"),
+        gr.inputs.Image(label="Input Image 3"),
+        gr.inputs.Image(label="Input Image 4"),
+        gr.inputs.Image(label="Input Image 5"),
+        gr.inputs.Image(label="Input Image 6"),
+        gr.inputs.Image(label="Input Image 7"),
+        gr.inputs.Image(label="Input Image 8"),
+        gr.inputs.Slider(label="Blending Weight", minimum=0.0, maximum=1.0, default=0.5, step=0.01)
     ],
     outputs=gr.outputs.Image(type="pil", label="Blended Image")
 )