1

pipeline/__init__.py

@@ -5,25 +5,17 @@ from flask import Flask
 FEATURE_WEIGHTS = {"shape": 0.4, "color": 0.5, "texture": 0.1}
 FINAL_SCORE_THRESHOLD = 0.5
 
-# Create Flask app
+# create flask app
 app = Flask(__name__)
 
-# Load models
-print("=" * 50)
+# load models
+print("="*50)
 print("🚀 Initializing application and loading models...")
-
 device_name = os.environ.get("device", "cpu")
-device = torch.device(
-    'cuda' if 'cuda' in device_name and torch.cuda.is_available() else 'cpu'
-)
+device = torch.device('cuda' if 'cuda' in device_name and torch.cuda.is_available() else 'cpu')
 print(f"🧠 Using device: {device}")
 
-from transformers import (
-    AutoProcessor,
-    AutoModelForZeroShotObjectDetection,
-    AutoTokenizer,
-    AutoModel
-)
+from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection, AutoTokenizer, AutoModel
 from segment_anything import SamPredictor, sam_model_registry
 
 print("...Loading Grounding DINO model...")
@@ -53,7 +45,7 @@ models = {
 }
 
 print("✅ All models loaded successfully.")
-print("=" * 50)
+print("="*50)
 
 # Import routes after app and models are defined to avoid circular imports
-from pipeline import routes
+from pipeline import routes