Update app.py

app.py

@@ -1,3 +1,54 @@
 import gradio as gr
+from PIL import Image
+from PIL import ImageOps
+import numpy as np
 
-gr.Interface.load("models/ostris/super-cereal-sdxl-lora").launch()
+def create_cereal_box(input_image):
+    # Convert the input numpy array to PIL Image
+    cover_img = Image.fromarray((input_image.astype(np.uint8)))
+
+    # Load the template image
+    template_img = Image.open('CerealBoxMaker/template.jpeg')
+
+    # Define scaling factor for diagonal resizing
+    scaling_factor = 1.5
+
+    # Resize cover image
+    rect_height = int(template_img.height * 0.32)
+    new_width = int(rect_height * 0.70)
+    cover_resized = cover_img.resize((new_width, rect_height), Image.LANCZOS)
+
+    # Apply diagonal scaling
+    new_width_scaled = int(new_width * scaling_factor)
+    new_height_scaled = int(rect_height * scaling_factor)
+    cover_resized_scaled = cover_resized.resize((new_width_scaled, new_height_scaled), Image.LANCZOS)
+
+    # Positioning the resized cover image on the template
+    left_x = int(template_img.width * 0.085)
+    left_y = int((template_img.height - new_height_scaled) // 2 + template_img.height * 0.012)
+    left_position = (left_x, left_y)
+    
+    right_x = int(template_img.width * 0.82) - new_width_scaled
+    right_y = left_y
+    right_position = (right_x, right_y)
+
+    # Create a copy of the template to paste on
+    template_copy = template_img.copy()
+
+    # Paste the resized and scaled cover image
+    template_copy.paste(cover_resized_scaled, left_position)
+    template_copy.paste(cover_resized_scaled, right_position)
+
+    # Convert the PIL Image back to a numpy array
+    template_copy_array = np.array(template_copy)
+    
+    return template_copy_array
+
+# Your existing Gr.Interface for the model that takes text and returns an image
+iface = gr.Interface.load("models/ostris/super-cereal-sdxl-lora")
+
+# Chain the existing interface with your new cereal box creation function
+chained_iface = gr.Interface(create_cereal_box, inputs=iface.outputs, outputs="image")
+
+# Launch the chained interface
+chained_iface.launch()