Fix FastAPI startup configuration

app.py

@@ -2,7 +2,7 @@
 Blueprint Door and Window Detection - API Server
 """
 
-from fastapi import FastAPI, File, UploadFile
+from fastapi import FastAPI, File, UploadFile, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
 from ultralytics import YOLO
 from PIL import Image
@@ -30,40 +30,36 @@ def load_model():
     
     if os.path.exists(model_path):
         print(f"📦 Loading trained model from: {model_path}")
-        model = YOLO(model_path)  # Using CPU for inference
+        model = YOLO(model_path)
         print("✅ Model loaded successfully!")
     else:
         print("⚠️  Trained model not found. Using pre-trained YOLOv8n for testing.")
         model = YOLO('yolov8n.pt')
         print("🔄 Using default model - train your custom model first!")
 
-@app.route('/', methods=['GET'])
-def home():
+@app.get("/")
+async def home():
     """Health check endpoint"""
-    return jsonify({
+    return {
         "message": "Blueprint Door and Window Detection API",
         "status": "running",
         "version": "1.0.0",
         "model_loaded": model is not None
-    })
+    }
 
-@app.route('/detect', methods=['POST'])
-def detect_objects():
+@app.post("/detect")
+async def detect_objects(file: UploadFile = File(...)):
     """Detection endpoint that accepts image and returns bounding boxes"""
     if model is None:
         load_model()
     
-    if 'image' not in request.files:
-        return jsonify({'error': 'No image file provided'}), 400
-        
-    file = request.files['image']
     if not file.filename.lower().endswith(('.png', '.jpg', '.jpeg')):
-        return jsonify({'error': 'Invalid file format. Only PNG/JPG allowed'}), 400
+        raise HTTPException(status_code=400, detail="Invalid file format. Only PNG/JPG allowed")
     
     try:
         # Read and process image
-        image_bytes = file.read()
-        image = Image.open(io.BytesIO(image_bytes))
+        contents = await file.read()
+        image = Image.open(io.BytesIO(contents))
         
         # Run inference
         results = model(image)[0]
@@ -83,15 +79,16 @@ def detect_objects():
                         round(x2-x1, 1), round(y2-y1, 1)]  # [x, y, width, height]
             })
         
-        return jsonify({
+        return {
             'detections': detections,
             'image_size': {'width': image.width, 'height': image.height},
             'processing_time_ms': round(results.speed['inference'], 1)
-        })
+        }
         
     except Exception as e:
-        return jsonify({'error': f'Error processing image: {str(e)}'}), 500
+        raise HTTPException(status_code=500, detail=f"Error processing image: {str(e)}")
 
-if __name__ == '__main__':
+@app.on_event("startup")
+async def startup_event():
+    """Load the model when the server starts"""
     load_model()
-    app.run(host='0.0.0.0', port=5000)