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server.py

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+import os
+import io
+import json
+import traceback
+from uuid import uuid4
+
+# --- FastAPI & Web server imports ---
+import uvicorn
+from fastapi import FastAPI, File, UploadFile, HTTPException, Security, Depends
+from fastapi.security import APIKeyHeader
+from fastapi.responses import JSONResponse
+
+# --- ML & Data processing imports ---
+import torch
+from PIL import Image
+import numpy as np
+
+# --- استيراد من ملفات المشروع الخاصة بك ---
+try:
+    from model import build_interfuser_model
+    from logic import (
+        transform, InterfuserController, ControllerConfig,
+        Tracker, WAYPOINT_SCALE_FACTOR
+    )
+except ImportError as e:
+    print(f"Error importing from project files: {e}")
+    print("Please ensure model.py and logic.py are in the same directory.")
+    exit()
+
+# ==============================================================================
+#           1. إعدادات الخادم، النموذج، والأمان
+# ==============================================================================
+app = FastAPI(
+    title="Interfuser Driving API (Secure & Stateful)",
+    description="An API for driving commands with session management and API key authentication.",
+    version="2.0.0"
+)
+
+# --- تحميل النموذج (يتم مرة واحدة عند بدء التشغيل) ---
+MODEL_NAME = "interfuser_baseline"
+WEIGHTS_PATH = os.path.join("weights", f"{MODEL_NAME}.pth")
+DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+MODEL_CONFIG = {
+    "rgb_backbone_name": "r50", "embed_dim": 256, "direct_concat": True,
+    'get': lambda key, default: MODEL_CONFIG.get(key, default)
+}
+
+print(f"Loading model '{MODEL_NAME}' on device '{DEVICE}'...")
+if not os.path.exists(WEIGHTS_PATH):
+    raise FileNotFoundError(f"Weights file not found at: {WEIGHTS_PATH}")
+
+model = build_interfuser_model(MODEL_CONFIG)
+model.load_state_dict(torch.load(WEIGHTS_PATH, map_location=DEVICE))
+model.to(DEVICE)
+model.eval()
+print("✅ Model loaded successfully!")
+
+# --- إدارة الجلسات والأمان ---
+SESSIONS = {}  # قاموس لتخزين حالات الجلسات: {session_id: Tracker}
+API_KEY_NAME = "X-API-KEY"
+api_key_header = APIKeyHeader(name=API_KEY_NAME, auto_error=False)
+
+# في تطبيق حقيقي، يجب أن تكون هذه المفاتيح في متغيرات بيئة أو خدمة إدارة أسرار
+VALID_API_KEYS = {
+    "your-super-secret-key-for-flutter-app", # مفتاح لتطبيق فلاتر
+    "a-different-key-for-testing"          # مفتاح آخر للاختبار
+}
+
+async def get_api_key(api_key: str = Security(api_key_header)):
+    """تبعية للتحقق من أن مفتاح الـ API صالح."""
+    if api_key in VALID_API_KEYS:
+        return api_key
+    else:
+        raise HTTPException(
+            status_code=403, detail="Could not validate credentials or missing API Key"
+        )
+
+
+# ==============================================================================
+#           2. تعريف نقاط نهاية الـ API (Endpoints)
+# ==============================================================================
+
+# --- حماية جميع نقاط النهاية باستخدام التبعية ---
+# أي طلب لأي نقطة نهاية أدناه يجب أن يجتاز get_api_key أولاً
+app.dependency_overrides[get_api_key] = get_api_key
+
+
+@app.post("/sessions/create", summary="Create a new tracking session")
+async def create_session(api_key: str = Depends(get_api_key)):
+    """
+    ينشئ جلسة تتبع جديدة ويعيد معرفًا فريدًا لها.
+    هذه هي الخطوة الأولى قبل إرسال بيانات الإطارات.
+    """
+    session_id = str(uuid4())
+    SESSIONS[session_id] = {"tracker": Tracker(), "frame_count": 0}
+    print(f"New session created: {session_id}")
+    return JSONResponse(content={"session_id": session_id})
+
+
+@app.post("/predict/{session_id}", summary="Run a single frame prediction for a session")
+async def predict(
+    session_id: str,
+    rgb_image: UploadFile = File(..., description="Front-facing RGB camera image."),
+    measurements_json: UploadFile = File(..., description="JSON file with vehicle measurements."),
+    api_key: str = Depends(get_api_key)
+):
+    """
+    يشغل التنبؤ لإطار واحد ضمن جلسة موجودة.
+    يستخدم الـ Tracker المستمر الخاص بالجلسة لتتبع الأجسام عبر الزمن.
+    """
+    if session_id not in SESSIONS:
+        raise HTTPException(status_code=404, detail="Session not found. Please create a new session.")
+
+    session_data = SESSIONS[session_id]
+    tracker = session_data["tracker"]
+    session_data["frame_count"] += 1
+    current_frame = session_data["frame_count"]
+
+    try:
+        # --- قراءة ومعالجة المدخلات ---
+        image_bytes = await rgb_image.read()
+        measurements_string = await measurements_json.read()
+        rgb_pil = Image.open(io.BytesIO(image_bytes)).convert("RGB")
+        m_dict = json.loads(measurements_string)
+
+        # --- تجهيز التنسورات للنموذج ---
+        front_tensor = transform(rgb_pil).unsqueeze(0).to(DEVICE)
+        dummy_tensor = torch.zeros_like(front_tensor)
+        measurements_tensor = torch.tensor([[
+            m_dict.get(k, 0.0) for k in ['x', 'y', 'theta', 'speed', 'steer', 'throttle', 'brake', 'command', 'is_junction', 'should_brake']
+        ]], dtype=torch.float32).to(DEVICE)
+        target_point_tensor = torch.tensor([[0.0, 100.0]], dtype=torch.float32).to(DEVICE)
+
+        inputs = {
+            'rgb': front_tensor, 'rgb_left': dummy_tensor, 'rgb_right': dummy_tensor,
+            'rgb_center': dummy_tensor, 'lidar': dummy_tensor,
+            'measurements': measurements_tensor, 'target_point': target_point_tensor
+        }
+
+        # --- تشغيل النموذج والتحكم ---
+        with torch.no_grad():
+            outputs = model(inputs)
+            traffic, waypoints, is_junction, traffic_light, stop_sign, _ = outputs
+
+        traffic_np = traffic[0].detach().cpu().numpy().reshape(20, 20, -1)
+        waypoints_np = waypoints[0].detach().cpu().numpy() * WAYPOINT_SCALE_FACTOR
+        
+        pos = [m_dict.get('x', 0.0), m_dict.get('y', 0.0)]
+        theta = m_dict.get('theta', 0.0)
+
+        # استخدام Tracker المستمر الخاص بالجلسة
+        updated_traffic = tracker.update_and_predict(traffic_np.copy(), pos, theta, current_frame)
+        
+        controller = InterfuserController(ControllerConfig())
+        steer, throttle, brake, _ = controller.run_step(
+            m_dict.get('speed', 5.0), waypoints_np, is_junction.sigmoid()[0,1].item(),
+            traffic_light.sigmoid()[0,0].item(), stop_sign.sigmoid()[0,1].item(), updated_traffic
+        )
+
+        # --- بناء وإرجاع الاستجابة ---
+        control_commands = {"steer": float(steer), "throttle": float(throttle), "brake": bool(brake)}
+        return JSONResponse(content={"status": "success", "control_commands": control_commands})
+
+    except Exception as e:
+        print(traceback.format_exc())
+        raise HTTPException(status_code=500, detail=f"An internal error occurred: {str(e)}")
+
+
+@app.delete("/sessions/{session_id}", summary="Delete a tracking session")
+async def delete_session(session_id: str, api_key: str = Depends(get_api_key)):
+    """
+    يحذف جلسة تتبع لتحرير الموارد على الخادم.
+    """
+    if session_id in SESSIONS:
+        del SESSIONS[session_id]
+        print(f"Session deleted: {session_id}")
+        return JSONResponse(content={"message": "Session deleted successfully."})
+    raise HTTPException(status_code=404, detail="Session not found.")
+
+
+# ==============================================================================
+#           3. نقطة بداية تشغيل الخادم
+# ==============================================================================
+if __name__ == "__main__":
+    print("--- Interfuser API Server ---")
+    print("API documentation will be available at http://127.0.0.1:8000/docs")
+    uvicorn.run(app, host="0.0.0.0", port=8000)