preprocess image input

app.py

@@ -1,4 +1,5 @@
 import gradio as gr
+from PIL import Image
 from urllib.parse import urlparse
 import requests
 import time
@@ -6,6 +7,47 @@ import os
 
 from utils.gradio_helpers import parse_outputs, process_outputs
 
+# Function to verify the image file type and resize it if necessary
+def preprocess_image(image_path):
+    # Check if the file exists
+    if not os.path.exists(image_path):
+        raise FileNotFoundError(f"No such file: '{image_path}'")
+
+    # Get the file extension and make sure it's a valid image format
+    valid_extensions = ['jpg', 'jpeg', 'png', 'webp']
+    file_extension = image_path.split('.')[-1].lower()
+
+    if file_extension not in valid_extensions:
+        raise ValueError("Invalid file type. Only JPG, PNG, and WEBP are allowed.")
+    
+    # Open the image
+    with Image.open(image_path) as img:
+        width, height = img.size
+
+        # Check if any dimension exceeds 1024 pixels
+        if width > 1024 or height > 1024:
+            # Calculate the new size while maintaining aspect ratio
+            if width > height:
+                new_width = 1024
+                new_height = int((new_width / width) * height)
+            else:
+                new_height = 1024
+                new_width = int((new_height / height) * width)
+            
+            # Resize the image
+            img_resized = img.resize((new_width, new_height), Image.ANTIALIAS)
+            print(f"Resized image to {new_width}x{new_height}.")
+
+            # Save the resized image as 'resized_image.jpg'
+            output_path = 'resized_image.jpg'
+            img_resized.save(output_path, 'JPEG')
+            print(f"Resized image saved as {output_path}")
+            return output_path
+        else:
+            print("Image size is within the limit, no resizing needed.")
+            return image_path
+
+
 def display_uploaded_image(image_in):
     return image_in
 
@@ -170,9 +212,9 @@ with gr.Blocks(css=css) as demo:
     outputs = [result_image]
 
     image.upload(
-        fn = display_uploaded_image,
+        fn = preprocess_image,
         inputs = [image],
-        outputs = [result_image],
+        outputs = [image],
         queue = False
     )