update torch version

app.py

@@ -158,7 +158,7 @@ pipe_imagen = ZImagePipeline.from_pretrained(
 pipe_imagen.to("cuda")
 
 
-@spaces.GPU
+@spaces.GPU(duration=120)
 def generate_lora(
     input_images,
     progress=gr.Progress(track_tqdm=True),
@@ -173,7 +173,16 @@ def generate_lora(
 
     progress(0.1, desc="Processing images...")
     print("progress: step 1")
-    pil_images = [Image.open(filepath).convert("RGB") for filepath, _ in input_images]
+    # pil_images = [Image.open(filepath).convert("RGB") for filepath, _ in input_images]
+
+    pil_images = []
+    for img in input_images:
+        if isinstance(img, str):
+            pil_images.append(Image.open(img).convert("RGB"))
+        elif isinstance(img, tuple):
+            pil_images.append(Image.open(img[0]).convert("RGB"))
+        else:
+            pil_images.append(Image.fromarray(img).convert("RGB"))
 
     progress(0.3, desc="Encoding images to LoRA...")
     print("progress: step 2")

requirements.txt

@@ -1,5 +1,6 @@
 gradio
-torch
+torch==2.8.0
+torchvision
 transformers
 accelerate
 spaces

static/header.html

@@ -1,11 +1,11 @@
 <div style="text-align: center; max-width: 600px; margin: 0 auto;">
     <h1>
-        Qwen Image to LoRA
+        Z Image to LoRA
     </h1>
     <div class="grid-container" >
         <p>
             Generate LoRA from a few images.
             <br>
-            Demo by <a href="https://aisudo.com/" target="_blank">AiSudo</a> 😊 
+            Demo by <a href="https://aisudo.com/" target="_blank">AiSudo</a> 😊
     </div>
 </div>