From 3fe1944b98e8762205f806eda5a38d9c7b6cd010 Mon Sep 17 00:00:00 2001
From: Victor Phan <me@victorphan.net>
Date: Mon, 26 Jan 2026 13:55:18 +0700
Subject: [PATCH] update 01

---
 .gitignore    |  1 +
 api_server.py | 12 ++++++------
 2 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/.gitignore b/.gitignore
index 42c3021..931aba3 100644
--- a/.gitignore
+++ b/.gitignore
@@ -76,6 +76,7 @@ model_train/*.feather
 model_train/*.db
 model_train/*.sqlite
 model_train/*.log
+cloud_removal_model/
 
 # VSCode settings
 .vscode/
diff --git a/api_server.py b/api_server.py
index 73ab2ac..b4c912a 100644
--- a/api_server.py
+++ b/api_server.py
@@ -510,12 +510,12 @@ async def get_cloud_removal_methods():
 @app.get("/api/cloud-removal/models")
 async def list_cloud_removal_models():
     """Liệt kê các cloud removal models đã train"""
-    model_dir = Path("model_train")
+    model_dir = Path("cloud_removal_model")
     if not model_dir.exists():
         return {"models": [], "count": 0}
     
     models = []
-    # Search for ALL .pth files in model_train and subdirectories
+    # Search for ALL .pth files in cloud_removal_model and subdirectories
     for model_file in model_dir.rglob("*.pth"):
         # Skip non-cloud-removal models (keep land classification models separate)
         if any(x in model_file.name.lower() for x in ['mobilenet', 'cnn_', 'swin', 'xgboost', 'random_forest']):
@@ -635,7 +635,7 @@ async def train_cloud_removal(config: CloudRemovalTrainingConfig, background_tas
                 num_epochs=config.num_epochs,
                 learning_rate=config.learning_rate,
                 device="cuda" if config.use_gpu else "cpu",
-                save_dir="model_train"
+                save_dir="cloud_removal_model"
             )
             
             print(f"[CLOUD REMOVAL TRAINING] Completed {training_id}")
@@ -708,7 +708,7 @@ async def upload_cloud_removal_model(
         raise HTTPException(status_code=400, detail="Invalid filename")
     
     try:
-        model_dir = Path("model_train")
+        model_dir = Path("cloud_removal_model")
         model_dir.mkdir(exist_ok=True)
         
         # Save uploaded file
@@ -767,7 +767,7 @@ async def upload_cloud_removal_model(
 @app.delete("/api/cloud-removal/models/{filename}")
 async def delete_cloud_removal_model(filename: str):
     """Xóa cloud removal model"""
-    model_dir = Path("model_train")
+    model_dir = Path("cloud_removal_model")
     model_path = model_dir / filename
     
     # Security check
@@ -1748,7 +1748,7 @@ async def run_prediction(config: PredictionConfig):
         s2_data, cloud_metadata = process_cloud_removal(
             s2_data=s2_data,
             method=cloud_removal_method,
-            model_path=f"model_train/{cloud_removal_model}" if cloud_removal_model else None,
+            model_path=f"cloud_removal_model/{cloud_removal_model}" if cloud_removal_model else None,
             verbose=True
         )