add models

app.py

@@ -75,14 +75,6 @@ class LateFusionModel(nn.Module):
 
         return fused_logits, image_logits, text_logits, weights
 
-# def unwrap_dataparallel(model):
-#     """Recursively unwrap all DataParallel layers inside a model."""
-#     if isinstance(model, torch.nn.DataParallel):
-#         model = model.module
-#     for name, module in model.named_children():
-#         setattr(model, name, unwrap_dataparallel(module))
-#     return model
-
 # Load model
 model_path = "models/best_fusion_model.pt"
 if os.path.exists(model_path):
@@ -108,21 +100,19 @@ if os.path.exists(image_model_path):
     image_only_model.eval()
     print("Image-only model loaded from state_dict successfully!")
 else:
-    raise FileNotFoundError("Image-only model not found in models/ folder.")
+    print("Image-only model not found locally. Downloading from Hugging Face Hub...")
+    image_model_path = hf_hub_download(repo_id="azzandr/gambling-iamge-model", filename="best_image_model_Adam_lr0.0001_bs32_state_dict.pt")
+    image_only_model = models.efficientnet_b3(weights=models.EfficientNet_B3_Weights.DEFAULT)
+    num_features = image_only_model.classifier[1].in_features
+    image_only_model.classifier = nn.Linear(num_features, 1)
+    image_only_model.load_state_dict(torch.load(image_model_path, map_location=device))
+    image_only_model.to(device)
+    image_only_model.eval()
+    print("Image-only model downloaded and loaded successfully!")
 
 
 # --- Functions ---
 def clean_text(text):
-    # text = re.sub(r"http\S+", "", text)
-    # text = re.sub('\n', '', text)
-    # text = re.sub("[^a-zA-Z^']", " ", text)
-    # text = re.sub(" {2,}", " ", text)
-    # text = text.strip()
-    # text = re.sub(r'\s+', ' ', text)
-    # text = re.sub(r'\b\w{1,2}\b', '', text)
-    # text = re.sub(r'\b\w{20,}\b', '', text)
-    # text = text.lower()
-    # Kata 1–2 huruf yang penting dan tidak boleh dihapus
     exceptions = {
         "di", "ke", "ya"
     }