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.gitattributes

@@ -1,7 +1,24 @@
 *.pt filter=lfs diff=lfs merge=lfs -text
 *.safetensors filter=lfs diff=lfs merge=lfs -text
+content_images/Beach.jpg filter=lfs diff=lfs merge=lfs -text
 content_images/Bridge.jpg filter=lfs diff=lfs merge=lfs -text
+content_images/CameraGirl.jpg filter=lfs diff=lfs merge=lfs -text
+content_images/NYCSkyline.jpg filter=lfs diff=lfs merge=lfs -text
+content_images/PaintedLadies.jpg filter=lfs diff=lfs merge=lfs -text
+content_images/StandingOnCliff.png filter=lfs diff=lfs merge=lfs -text
+content_images/Surfer.jpg filter=lfs diff=lfs merge=lfs -text
+content_images/TajMahal.jpg filter=lfs diff=lfs merge=lfs -text
+content_images/baseball.jpg filter=lfs diff=lfs merge=lfs -text
+content_images/bleachers.jpg filter=lfs diff=lfs merge=lfs -text
+content_images/dancers.jpg filter=lfs diff=lfs merge=lfs -text
+content_images/ladies.jpg filter=lfs diff=lfs merge=lfs -text
+media/figure1.jpg filter=lfs diff=lfs merge=lfs -text
+style_images/Bokeh.jpg filter=lfs diff=lfs merge=lfs -text
+style_images/Great_Wave.jpg filter=lfs diff=lfs merge=lfs -text
+style_images/Lego_Bricks.jpg filter=lfs diff=lfs merge=lfs -text
 style_images/Mosaic.jpg filter=lfs diff=lfs merge=lfs -text
+style_images/Oil_Painting.jpg filter=lfs diff=lfs merge=lfs -text
 style_images/Scream.jpg filter=lfs diff=lfs merge=lfs -text
 style_images/Starry_Night.jpg filter=lfs diff=lfs merge=lfs -text
 style_images/Starry_Night_v2.jpg filter=lfs diff=lfs merge=lfs -text
+style_images/Watercolor.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -51,8 +51,9 @@ cached_style_features = {
 }
 
 @spaces.GPU(duration=15)
-def run(content_image, style_name, style_strength=len(lrs), apply_to_background=False):
+def run(content_image, style_name, style_strength=len(lrs), apply_to_background=False, progress=gr.Progress()):
     yield None
+    progress(0)
     content_img, original_size = preprocess_img(content_image, img_size)
     content_img_normalized, _ = preprocess_img(content_image, img_size, normalize=True)
     content_img, content_img_normalized = content_img.to(device), content_img_normalized.to(device)
@@ -70,6 +71,7 @@ def run(content_image, style_name, style_strength=len(lrs), apply_to_background=
         style_features=style_features,
         lr=lrs[style_strength-1],
         apply_to_background=apply_to_background,
+        progress=progress,
     )
     print(f'{time.time()-st:.2f}s')
     

inference.py

@@ -26,6 +26,7 @@ def inference(
     content_image_norm,
     style_features,
     apply_to_background,
+    progress,
     lr=1.5e-2,
     iterations=51,
     optim_caller=optim.AdamW,
@@ -56,11 +57,12 @@ def inference(
         total_loss.backward()
         return total_loss
     
-    for _ in range(iterations):
+    for iter in range(iterations):
         optimizer.step(closure)
         if apply_to_background:
             with torch.no_grad():
                 fg_mask = F.interpolate(1 - bg_masks[0], size=generated_image.shape[2:], mode='nearest')
                 generated_image.data.mul_(1 - fg_mask).add_(content_image.data * fg_mask)
-                
+        progress((iter+1)/iterations)
+    
     return generated_image