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app.py

@@ -22,6 +22,14 @@ import time
 from functools import partial
 from huggingface_hub import hf_hub_download
 
+# ZeroGPU support
+try:
+    import spaces
+    GPU_AVAILABLE = True
+except ImportError:
+    GPU_AVAILABLE = False
+    spaces = None
+
 # ============================================================================
 # SoftPool Implementation (Pure PyTorch)
 # ============================================================================
@@ -160,6 +168,9 @@ class ResnetBlock(nn.Module):
         h = self.block1(x)
         h = self.noise_func(h, time_emb)
         h = self.block2(h)
+        # Resize condition features to match spatial size
+        if c.shape[2:] != h.shape[2:]:
+            c = F.interpolate(c, size=h.shape[2:], mode='bilinear', align_corners=False)
         h = self.c_func(c) + h
         return h + self.res_conv(x)
 
@@ -674,8 +685,8 @@ def load_sar_image(filepath):
     return Image.open(filepath).convert('RGB')
 
 
-def translate_sar(file, num_steps, overlap, enhance_output):
-    """Main translation function."""
+def _translate_sar_impl(file, num_steps, overlap, enhance_output):
+    """Main translation function implementation."""
     global processor
     
     if file is None:
@@ -711,6 +722,13 @@ def translate_sar(file, num_steps, overlap, enhance_output):
     return result_pil, tiff_path, info
 
 
+# Apply GPU decorator if available
+if GPU_AVAILABLE and spaces is not None:
+    translate_sar = spaces.GPU(duration=300)(_translate_sar_impl)
+else:
+    translate_sar = _translate_sar_impl
+
+
 # Create interface
 with gr.Blocks(title="E3Diff: SAR-to-Optical Translation") as demo:
     gr.Markdown("""