Update app.py

app.py

@@ -198,13 +198,49 @@ model_path = 'dress_model.pkl'
 with open(model_path, 'rb') as f:
     G = legacy.load_network_pkl(f)['G_ema'].to(device)
 
-# Style mixing between two projected images
+# # Style mixing between two projected images
+# def mix_styles(image1_path, image2_path, styles_to_mix):
+#     image1_name = os.path.splitext(os.path.basename(image1_path))[0]
+#     image2_name = os.path.splitext(os.path.basename(image2_path))[0]
+
+#     latent_vector_1 = np.load(os.path.join("projection_results", image1_name, "projected_w.npz"))['w']
+#     latent_vector_2 = np.load(os.path.join("projection_results", image2_name, "projected_w.npz"))['w']
+
+#     latent_1_tensor = torch.from_numpy(latent_vector_1).to(device)
+#     latent_2_tensor = torch.from_numpy(latent_vector_2).to(device)
+
+#     mixed_latent = latent_1_tensor.clone()
+#     mixed_latent[:, styles_to_mix] = latent_2_tensor[:, styles_to_mix]
+
+#     with torch.no_grad():
+#         image = G.synthesis(mixed_latent, noise_mode='const')
+
+#     image = (image.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8).cpu().numpy()
+#     mixed_image = Image.fromarray(image[0], 'RGB')
+#     return mixed_image
+# ----------- UTIL: ENSURE PROJECTION ----------
+def ensure_projection(image_path):
+    image_name = os.path.splitext(os.path.basename(image_path))[0]
+    proj_dir = os.path.join("projection_results", image_name)
+    proj_file = os.path.join(proj_dir, "projected_w.npz")
+
+    if not os.path.exists(proj_file):
+        print(f"Projection for {image_name} not found. Running projector.py...")
+        os.makedirs(proj_dir, exist_ok=True)
+        subprocess.run([
+            "python", "projector.py",
+            f"--network={NETWORK_PKL}",
+            f"--target={image_path}",
+            f"--outdir={proj_dir}"
+        ], check=True)
+    return proj_file
+
 def mix_styles(image1_path, image2_path, styles_to_mix):
-    image1_name = os.path.splitext(os.path.basename(image1_path))[0]
-    image2_name = os.path.splitext(os.path.basename(image2_path))[0]
+    proj_file1 = ensure_projection(image1_path)
+    proj_file2 = ensure_projection(image2_path)
 
-    latent_vector_1 = np.load(os.path.join("projection_results", image1_name, "projected_w.npz"))['w']
-    latent_vector_2 = np.load(os.path.join("projection_results", image2_name, "projected_w.npz"))['w']
+    latent_vector_1 = np.load(proj_file1)['w']
+    latent_vector_2 = np.load(proj_file2)['w']
 
     latent_1_tensor = torch.from_numpy(latent_vector_1).to(device)
     latent_2_tensor = torch.from_numpy(latent_vector_2).to(device)
@@ -219,6 +255,7 @@ def mix_styles(image1_path, image2_path, styles_to_mix):
     mixed_image = Image.fromarray(image[0], 'RGB')
     return mixed_image
 
+
 # Handles style mixing + output buffer
 def style_mixing_interface(image1, image2, mix_value):
     if image1 is None or image2 is None: