Upload app.py

app.py

@@ -40,11 +40,8 @@ try:
 except ImportError:
     brisque = None
 
-# ================================================================
-# 3. DDColor import — path FIRST, then import
-# ================================================================
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "DDColor"))
-from ddcolor import DDColor
+import sys, os
+from huggingface_hub import snapshot_download, PyTorchModelHubMixin
 # ================================================================
 # 5. LOAD ALL MODELS AT STARTUP (no lazy loading)
 # ================================================================
@@ -94,6 +91,20 @@ esrgan_model.to("cuda").eval()
 ESRGAN_SCALE = int(esrgan_model.scale) 
 print("Enhancement model loaded. Scale factor:", ESRGAN_SCALE)
 
+# ================================================================
+# 4. DDColor — download source, then load model
+# ================================================================
+import sys, os
+from huggingface_hub import snapshot_download, PyTorchModelHubMixin
+
+print("🚀 Downloading DDColor source code...")
+ddcolor_repo_root = snapshot_download(
+    repo_id="kunhsiang/cv-final-colorize-demo",
+    repo_type="space",
+    allow_patterns="ddcolor_repo/ddcolor/*.py",
+    local_dir="/tmp/ddcolor_source",
+)
+
 class DDColorHF(DDColor, PyTorchModelHubMixin):
     def __init__(self, config=None, **kwargs):
         if isinstance(config, dict):
@@ -106,7 +117,6 @@ ddcolor_model = (
 )
 print("✅ DDColor loaded on cuda.")
 
-
 print("🚀 Loading CLIP for metrics...")
 clip_model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32").to("cuda")
 clip_processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")