Update app.py

app.py

@@ -255,6 +255,16 @@ optimize_pipeline_(pipe, image=[Image.new("RGB", (1024, 1024)), Image.new("RGB",
 # --- UI Constants and Helpers ---
 MAX_SEED = np.iinfo(np.int32).max
 
+import requests
+
+def load_image_from_url(url):
+    try:
+        response = requests.get(url, timeout=10)
+        response.raise_for_status()
+        return Image.open(BytesIO(response.content)).convert("RGB")
+    except Exception as e:
+        print(f"Error loading image from URL: {e}")
+        return None
 # --- Main Inference Function (with hardcoded negative prompt) ---
 @spaces.GPU(duration=60)
 def infer(
@@ -267,12 +277,14 @@ def infer(
     height=None,
     width=None,
     num_images_per_prompt=1,
+    image_url=None,
     progress=gr.Progress(track_tqdm=True),
 ):
     """
     Generates an image using the local Qwen-Image diffusers pipeline.
     """
     # Hardcode the negative prompt as requested
+
     negative_prompt = "Vibrant colors, overexposed, static, blurry details, subtitles, style, artwork, painting, image, still, overall grayish, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn face, deformed, disfigured, deformed limbs, fingers fused together, static image, cluttered background, three legs, many people in the background, walking backwards."
     rewrite_prompt=False
     if randomize_seed:
@@ -287,6 +299,11 @@ def infer(
     prompt = prompt.replace(expected_key, "")
     # Load input images into PIL Images
     pil_images = []
+    if not images and image_url:
+        img = load_image_from_url(image_url)
+        if img:
+            pil_images = [img]
+            print(f"Loaded image from URL: {image_url}")        
     if images:
         for item in images:
             try:
@@ -361,7 +378,7 @@ with gr.Blocks(css=css) as demo:
                                           show_label=False, 
                                           type="pil", 
                                           interactive=True)
-
+                image_url = gr.Textbox(label="", placeholder="")
                 prompt = gr.Text(
                     label="Prompt 🪄",
                     show_label=True,
@@ -438,6 +455,7 @@ with gr.Blocks(css=css) as demo:
             num_inference_steps,
             height,
             width,
+            image_url,
         ],
         outputs=[result,upscaled, seed],