Show image file in the result from the URL

URL.txt

@@ -0,0 +1,4 @@
+# Red jumper
+https://assets.digitalcontent.marksandspencer.app/images/w_1024,q_auto,f_auto/SD_01_T38_1842T_B4_X_EC_90/Sparkly-Crew-Neck-Relaxed-Jumper
+# Red trousers
+https://www.crewclothing.co.uk/images/products/large/BEC101_POPPYRED.jpg

app.py

@@ -5,7 +5,7 @@ import requests
 from PIL import Image
 from io import BytesIO
 
-fashion_items = ['top', 'trousers', 'jumper']
+fashion_items = ['top', 'trousers', 'jumper', "shirt", "shorts"]
 
 # Load model and processor
 model_name = 'Marqo/marqo-fashionSigLIP'
@@ -44,16 +44,16 @@ def predict_from_url(url):
         image_features = image_features / image_features.norm(dim=-1, keepdim=True)
         text_probs = (100 * image_features @ text_features.T).softmax(dim=-1)
 
-    return {fashion_items[i]: float(text_probs[0, i]) for i in range(len(fashion_items))}
+    return {fashion_items[i]: float(text_probs[0, i]) for i in range(len(fashion_items))}, url
 
 
 # Gradio interface
 demo = gr.Interface(
     fn=predict_from_url,
     inputs=gr.Textbox(label="Enter Image URL"),
-    outputs=gr.Label(label="Classification Results"),
+    outputs=[gr.Label(label="Classification Results"), "image"],
     title="Fashion Item Classifier",
-    allow_flagging="never"
+    flagging_mode="never"
 )
 
 # Launch the interface