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Update app.py
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app.py
CHANGED
@@ -11,353 +11,6 @@ from pydantic import BaseModel
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from torchvision import transforms
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from typing import List, Dict, Any, Optional
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import logging
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# # استيراد من ملفاتنا المحلية
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# from model_definition import InterfuserModel, load_and_prepare_model, create_model_config
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# from simulation_modules import (
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# InterfuserController, ControllerConfig, Tracker, DisplayInterface,
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# render, render_waypoints, render_self_car, WAYPOINT_SCALE_FACTOR,
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# T1_FUTURE_TIME, T2_FUTURE_TIME
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# )
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# # إعداد التسجيل
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# logging.basicConfig(level=logging.INFO)
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# logger = logging.getLogger(__name__)
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# # ================== إعدادات عامة وتحميل النموذج ==================
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# app = FastAPI(
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# title="Baseer Self-Driving API",
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# description="API للقيادة الذاتية باستخدام نموذج InterFuser",
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# version="1.0.0"
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# )
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# device = torch.device("cpu")
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# logger.info(f"Using device: {device}")
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# # تحميل النموذج باستخدام الدالة المحسنة
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# try:
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# # إنشاء إعدادات النموذج باستخدام الإعدادات الصحيحة من التدريب
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# model_config = create_model_config(
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# model_path="model/best_model.pth"
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# # الإعدادات الصحيحة من التدريب ستطبق تلقائياً:
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# # embed_dim=256, rgb_backbone_name='r50', waypoints_pred_head='gru'
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# # with_lidar=False, with_right_left_sensors=False, with_center_sensor=False
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# )
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# # تحميل النموذج مع الأوزان
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# model = load_and_prepare_model(model_config, device)
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# logger.info("✅ تم تحميل النموذج بنجاح")
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# except Exception as e:
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# logger.error(f"❌ خطأ في تحميل النموذج: {e}")
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# logger.info("🔄 محاولة إنشاء نموذج بأوزان عشوائية...")
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# try:
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# model = InterfuserModel()
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# model.to(device)
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# model.eval()
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# logger.warning("⚠️ تم إنشاء النموذج بأوزان عشوائية")
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# except Exception as e2:
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# logger.error(f"❌ فشل في إنشاء النموذج: {e2}")
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# model = None
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# # تهيئة واجهة العرض
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# display = DisplayInterface()
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# # قاموس لتخزين جلسات المستخدمين
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# SESSIONS: Dict[str, Dict] = {}
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# # ================== هياكل بيانات Pydantic ==================
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# class Measurements(BaseModel):
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# pos: List[float] = [0.0, 0.0] # [x, y] position
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# theta: float = 0.0 # orientation angle
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# speed: float = 0.0 # current speed
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# steer: float = 0.0 # current steering
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# throttle: float = 0.0 # current throttle
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# brake: bool = False # brake status
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# command: int = 4 # driving command (4 = FollowLane)
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# target_point: List[float] = [0.0, 0.0] # target point [x, y]
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# class ModelOutputs(BaseModel):
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# traffic: List[List[List[float]]] # 20x20x7 grid
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# waypoints: List[List[float]] # Nx2 waypoints
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# is_junction: float
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# traffic_light_state: float
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# stop_sign: float
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# class ControlCommands(BaseModel):
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# steer: float
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# throttle: float
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# brake: bool
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# class RunStepInput(BaseModel):
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# session_id: str
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# image_b64: str
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# measurements: Measurements
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# class RunStepOutput(BaseModel):
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# model_outputs: ModelOutputs
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# control_commands: ControlCommands
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# dashboard_image_b64: str
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# class SessionResponse(BaseModel):
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# session_id: str
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# message: str
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# # ================== دوال المساعدة ==================
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# def get_image_transform():
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# """إنشاء تحويلات الصورة كما في PDMDataset"""
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# return transforms.Compose([
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# transforms.ToTensor(),
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# transforms.Resize((224, 224), antialias=True),
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# transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
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# ])
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# # إنشاء كائن التحويل مرة واحدة
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# image_transform = get_image_transform()
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# def preprocess_input(frame_rgb: np.ndarray, measurements: Measurements, device: torch.device) -> Dict[str, torch.Tensor]:
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# """
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# تحاكي ما يفعله PDMDataset.__getitem__ لإنشاء دفعة (batch) واحدة.
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# """
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# # 1. معالجة الصورة الرئيسية
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# from PIL import Image
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# if isinstance(frame_rgb, np.ndarray):
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# frame_rgb = Image.fromarray(frame_rgb)
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# image_tensor = image_transform(frame_rgb).unsqueeze(0).to(device) # إضافة بُعد الدفعة
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# # 2. إنشاء مدخلات الكاميرات الأخرى عن طريق الاستنساخ
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# batch = {
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# 'rgb': image_tensor,
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# 'rgb_left': image_tensor.clone(),
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# 'rgb_right': image_tensor.clone(),
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# 'rgb_center': image_tensor.clone(),
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# }
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# # 3. إنشاء مدخل ليدار وهمي (أصفار)
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# batch['lidar'] = torch.zeros(1, 3, 224, 224, dtype=torch.float32).to(device)
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# # 4. تجميع القياسات بنفس ترتيب PDMDataset
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# m = measurements
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# measurements_tensor = torch.tensor([[
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# m.pos[0], m.pos[1], m.theta,
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# m.steer, m.throttle, float(m.brake),
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# m.speed, float(m.command)
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# ]], dtype=torch.float32).to(device)
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# batch['measurements'] = measurements_tensor
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# # 5. إنشاء نقطة هدف
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# batch['target_point'] = torch.tensor([m.target_point], dtype=torch.float32).to(device)
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# # لا نحتاج إلى قيم ground truth (gt_*) أثناء التنبؤ
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# return batch
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# def decode_base64_image(image_b64: str) -> np.ndarray:
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# """
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# فك تشفير صورة Base64
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# """
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# try:
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# image_bytes = base64.b64decode(image_b64)
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# nparr = np.frombuffer(image_bytes, np.uint8)
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# image = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
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# return image
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# except Exception as e:
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# raise HTTPException(status_code=400, detail=f"Invalid image format: {str(e)}")
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# def encode_image_to_base64(image: np.ndarray) -> str:
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# """
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# تشفير صورة إلى Base64
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# """
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# _, buffer = cv2.imencode('.jpg', image, [cv2.IMWRITE_JPEG_QUALITY, 85])
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# return base64.b64encode(buffer).decode('utf-8')
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# # ================== نقاط نهاية الـ API ==================
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# @app.get("/", response_class=HTMLResponse)
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# async def root():
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# """
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# الصفحة الرئيسية للـ API
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# """
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# html_content = f"""
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# <!DOCTYPE html>
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# <html dir="rtl" lang="ar">
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# <head>
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# <meta charset="UTF-8">
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# <meta name="viewport" content="width=device-width, initial-scale=1.0">
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# <title>🚗 Baseer Self-Driving API</title>
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# <style>
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# * {{
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# margin: 0;
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# padding: 0;
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# box-sizing: border-box;
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# }}
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# body {{
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# font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
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# background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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# min-height: 100vh;
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# display: flex;
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# align-items: center;
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# justify-content: center;
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# padding: 20px;
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# }}
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# .container {{
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# background: rgba(255, 255, 255, 0.95);
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# backdrop-filter: blur(10px);
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# border-radius: 20px;
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# padding: 40px;
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# box-shadow: 0 20px 40px rgba(0, 0, 0, 0.1);
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# text-align: center;
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# max-width: 600px;
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# width: 100%;
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# }}
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# .logo {{
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# font-size: 4rem;
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# margin-bottom: 20px;
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# animation: bounce 2s infinite;
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# }}
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# @keyframes bounce {{
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# 0%, 20%, 50%, 80%, 100% {{ transform: translateY(0); }}
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# 40% {{ transform: translateY(-10px); }}
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# 60% {{ transform: translateY(-5px); }}
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# }}
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# h1 {{
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# color: #333;
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# margin-bottom: 10px;
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# font-size: 2.5rem;
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# }}
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# .subtitle {{
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# color: #666;
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# margin-bottom: 30px;
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# font-size: 1.2rem;
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# }}
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# .status {{
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# display: inline-block;
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# background: #4CAF50;
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# color: white;
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# padding: 8px 16px;
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# border-radius: 20px;
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# margin: 10px 0;
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# font-weight: bold;
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# }}
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# .stats {{
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# display: grid;
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# grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));
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# gap: 20px;
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# margin: 30px 0;
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# }}
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# .stat-card {{
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# background: #f8f9fa;
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# padding: 20px;
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# border-radius: 15px;
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# border-left: 4px solid #667eea;
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# }}
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# .stat-number {{
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# font-size: 2rem;
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# font-weight: bold;
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# color: #667eea;
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# }}
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# .stat-label {{
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# color: #666;
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# margin-top: 5px;
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# }}
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# .buttons {{
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# display: flex;
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# gap: 15px;
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# justify-content: center;
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# flex-wrap: wrap;
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# margin-top: 30px;
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# }}
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# .btn {{
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# display: inline-block;
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# padding: 12px 24px;
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# border-radius: 25px;
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# text-decoration: none;
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# font-weight: bold;
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# transition: all 0.3s ease;
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# border: none;
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# cursor: pointer;
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# }}
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# .btn-primary {{
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# background: #667eea;
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# color: white;
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# }}
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# .btn-secondary {{
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# background: #6c757d;
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# color: white;
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# }}
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# .btn:hover {{
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# transform: translateY(-2px);
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# box-shadow: 0 5px 15px rgba(0, 0, 0, 0.2);
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# }}
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# .features {{
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# text-align: right;
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# margin-top: 30px;
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# padding: 20px;
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# background: #f8f9fa;
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# border-radius: 15px;
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# }}
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# .features h3 {{
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# color: #333;
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# margin-bottom: 15px;
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# }}
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# .features ul {{
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# list-style: none;
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# padding: 0;
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# }}
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# .features li {{
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# padding: 5px 0;
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# color: #666;
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# }}
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# .features li:before {{
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# content: "✅ ";
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# margin-left: 10px;
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# }}
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# </style>
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# </head>
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# <body>
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# <div class="container">
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# <div class="logo">🚗</div>
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# <h1>Baseer Self-Driving API</h1>
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# <p class="subtitle">نظام القيادة الذاتية المتقدم</p>
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# <div class="status">🟢 يعمل بنجاح</div>
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# <div class="stats">
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# <div class="stat-card">
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# <div class="stat-number">{len(SESSIONS)}</div>
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# <div class="stat-label">الجلسات النشطة</div>
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# </div>
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# <div class="stat-card">
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# <div class="stat-number">v1.0</div>
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# <div class="stat-label">الإصدار</div>
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# </div>
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# <div class="stat-card">
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# <div class="stat-number">FastAPI</div>
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# <div class="stat-label">التقنية</div>
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# </div>
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# </div>
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# <div class="buttons">
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# <a href="/docs" class="btn btn-primary">📚 توثيق API</a>
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# <a href="/sessions" class="btn btn-secondary">📊 الجلسات</a>
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# </div>
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# <div class="features">
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# <h3>🌟 الميزات الرئيسية</h3>
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# <ul>
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# <li>نموذج InterFuser للقيادة الذاتية</li>
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# <li>معالجة الصور في الوقت الفعلي</li>
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# <li>اكتشاف الكائنات المرورية</li>
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# <li>تحديد المسارات الذكية</li>
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# <li>واجهة RESTful سهلة الاستخدام</li>
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# <li>إدارة جلسات متعددة</li>
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# </ul>
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# </div>
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# </div>
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# </body>
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# </html>
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# """
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# return html_content
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import uuid
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import base64
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import cv2
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from pydantic import BaseModel, Field
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from typing import List, Dict, Tuple
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# ==============================================================================
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# 1. استيراد كل مكونات المشروع التي قمنا بتطويرها
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# (تأكد من أن هذه الملفات موجودة في نفس المجلد)
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# ==============================================================================
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# من ملف النموذج (يحتوي على كلاس Interfuser والدوال المساعدة)
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from model_definition import InterfuserModel, load_and_prepare_model, get_master_config
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from simulation_modules import InterfuserController, Tracker
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from simulation_modules import DisplayInterface, render_bev, unnormalize_image, DisplayConfig
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-
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# from model_definition import InterfuserModel, load_and_prepare_model, create_model_config
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# from simulation_modules import (
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# InterfuserController, ControllerConfig, Tracker, DisplayInterface,
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# render, render_waypoints, render_self_car, WAYPOINT_SCALE_FACTOR,
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# T1_FUTURE_TIME, T2_FUTURE_TIME
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# )
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# ==============================================================================
|
390 |
# 2. إعدادات عامة وتطبيق FastAPI
|
391 |
# ==============================================================================
|
@@ -477,9 +119,7 @@ def prepare_model_input(image: np.ndarray, measurements: Measurements) -> Dict[s
|
|
477 |
'target_point': target_point_tensor,
|
478 |
'lidar': torch.zeros_like(image_tensor)
|
479 |
}
|
480 |
-
|
481 |
-
# model_path="model/best_model.pth"
|
482 |
-
# )
|
483 |
# ==============================================================================
|
484 |
# 5. أحداث دورة حياة التطبيق (Startup/Shutdown)
|
485 |
# ==============================================================================
|
@@ -494,44 +134,198 @@ async def startup_event():
|
|
494 |
logging.info("✅ Model loaded successfully. Server is ready!")
|
495 |
else:
|
496 |
logging.error("❌ CRITICAL: Model could not be loaded. The API will not function correctly.")
|
497 |
-
# # تحميل النموذج باستخدام الدالة المحسنة
|
498 |
-
# try:
|
499 |
-
# # إنشاء إعدادات النموذج باستخدام الإعدادات الصحيحة من التدريب
|
500 |
-
|
501 |
-
|
502 |
-
# # تحميل النموذج مع الأوزان
|
503 |
-
#
|
504 |
-
# logger.info("✅ تم تحميل النموذج بنجاح")
|
505 |
-
|
506 |
-
# except Exception as e:
|
507 |
-
# logger.error(f"❌ خطأ في تحميل النموذج: {e}")
|
508 |
-
# logger.info("🔄 محاولة إنشاء نموذج بأوزان عشوائية...")
|
509 |
-
# try:
|
510 |
-
# model = InterfuserModel()
|
511 |
-
# model.to(device)
|
512 |
-
# model.eval()
|
513 |
-
# logger.warning("⚠️ تم إنشاء النموذج بأوزان عشوائية")
|
514 |
-
# except Exception as e2:
|
515 |
-
# logger.error(f"❌ فشل في إنشاء النموذج: {e2}")
|
516 |
-
# model = None
|
517 |
|
518 |
# ==============================================================================
|
519 |
# 6. نقاط النهاية الرئيسية (API Endpoints)
|
520 |
# ==============================================================================
|
521 |
-
|
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|
522 |
async def root():
|
523 |
-
|
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|
532 |
</html>
|
533 |
"""
|
534 |
-
|
535 |
|
536 |
@app.post("/start_session", summary="Start a new driving session", tags=["Session Management"])
|
537 |
def start_session():
|
|
|
11 |
from torchvision import transforms
|
12 |
from typing import List, Dict, Any, Optional
|
13 |
import logging
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|
14 |
import uuid
|
15 |
import base64
|
16 |
import cv2
|
|
|
22 |
from pydantic import BaseModel, Field
|
23 |
from typing import List, Dict, Tuple
|
24 |
|
|
|
|
|
|
|
|
|
|
|
25 |
from model_definition import InterfuserModel, load_and_prepare_model, get_master_config
|
26 |
|
27 |
+
|
28 |
from simulation_modules import InterfuserController, Tracker
|
29 |
from simulation_modules import DisplayInterface, render_bev, unnormalize_image, DisplayConfig
|
30 |
+
|
|
|
|
|
|
|
|
|
|
|
|
|
31 |
# ==============================================================================
|
32 |
# 2. إعدادات عامة وتطبيق FastAPI
|
33 |
# ==============================================================================
|
|
|
119 |
'target_point': target_point_tensor,
|
120 |
'lidar': torch.zeros_like(image_tensor)
|
121 |
}
|
122 |
+
|
|
|
|
|
123 |
# ==============================================================================
|
124 |
# 5. أحداث دورة حياة التطبيق (Startup/Shutdown)
|
125 |
# ==============================================================================
|
|
|
134 |
logging.info("✅ Model loaded successfully. Server is ready!")
|
135 |
else:
|
136 |
logging.error("❌ CRITICAL: Model could not be loaded. The API will not function correctly.")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
137 |
|
138 |
# ==============================================================================
|
139 |
# 6. نقاط النهاية الرئيسية (API Endpoints)
|
140 |
# ==============================================================================
|
141 |
+
|
142 |
+
@app.get("/", response_class=HTMLResponse, include_in_schema=False, tags=["General"])
|
143 |
async def root():
|
144 |
+
"""
|
145 |
+
يعرض صفحة رئيسية احترافية وتفاعلية لواجهة برمجة التطبيقات.
|
146 |
+
"""
|
147 |
+
# الحصول على عدد الجلسات النشطة حاليًا
|
148 |
+
active_sessions_count = len(SESSIONS)
|
149 |
+
|
150 |
+
# تحديد لون حالة النظام
|
151 |
+
status_color = "#4CAF50" # أخضر
|
152 |
+
status_text = "يعمل بنجاح"
|
153 |
+
if MODEL is None:
|
154 |
+
status_color = "#F44336" # أحمر
|
155 |
+
status_text = "خطأ: النموذج غير محمل"
|
156 |
+
|
157 |
+
html_content = f"""
|
158 |
+
<!DOCTYPE html>
|
159 |
+
<html dir="rtl" lang="ar">
|
160 |
+
<head>
|
161 |
+
<meta charset="UTF-8">
|
162 |
+
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
163 |
+
<title>🚗 Baseer Self-Driving API</title>
|
164 |
+
<style>
|
165 |
+
@import url('https://fonts.googleapis.com/css2?family=Tajawal:wght@400;700&display=swap');
|
166 |
+
|
167 |
+
:root {{
|
168 |
+
--primary-color: #4a69bd;
|
169 |
+
--secondary-color: #6a89cc;
|
170 |
+
--text-color: #333;
|
171 |
+
--bg-color: #f4f7f6;
|
172 |
+
--panel-bg: #ffffff;
|
173 |
+
--shadow: 0 10px 30px rgba(0, 0, 0, 0.1);
|
174 |
+
}}
|
175 |
+
|
176 |
+
body {{
|
177 |
+
font-family: 'Tajawal', sans-serif;
|
178 |
+
background-color: var(--bg-color);
|
179 |
+
color: var(--text-color);
|
180 |
+
margin: 0;
|
181 |
+
display: flex;
|
182 |
+
justify-content: center;
|
183 |
+
align-items: center;
|
184 |
+
min-height: 100vh;
|
185 |
+
padding: 20px;
|
186 |
+
}}
|
187 |
+
|
188 |
+
.container {{
|
189 |
+
background: var(--panel-bg);
|
190 |
+
border-radius: 20px;
|
191 |
+
padding: 40px;
|
192 |
+
box-shadow: var(--shadow);
|
193 |
+
text-align: center;
|
194 |
+
max-width: 700px;
|
195 |
+
width: 100%;
|
196 |
+
border-top: 5px solid var(--primary-color);
|
197 |
+
}}
|
198 |
+
|
199 |
+
.logo {{
|
200 |
+
font-size: 4rem;
|
201 |
+
margin-bottom: 15px;
|
202 |
+
animation: car-drive 3s ease-in-out infinite;
|
203 |
+
}}
|
204 |
+
|
205 |
+
@keyframes car-drive {{
|
206 |
+
0% {{ transform: translateX(-20px); }}
|
207 |
+
50% {{ transform: translateX(20px); }}
|
208 |
+
100% {{ transform: translateX(-20px); }}
|
209 |
+
}}
|
210 |
+
|
211 |
+
h1 {{
|
212 |
+
font-size: 2.8rem;
|
213 |
+
font-weight: 700;
|
214 |
+
color: var(--primary-color);
|
215 |
+
margin-bottom: 10px;
|
216 |
+
}}
|
217 |
+
|
218 |
+
.subtitle {{
|
219 |
+
font-size: 1.2rem;
|
220 |
+
color: #777;
|
221 |
+
margin-bottom: 25px;
|
222 |
+
}}
|
223 |
+
|
224 |
+
.status-badge {{
|
225 |
+
display: inline-block;
|
226 |
+
background-color: {status_color};
|
227 |
+
color: white;
|
228 |
+
padding: 10px 20px;
|
229 |
+
border-radius: 25px;
|
230 |
+
font-weight: bold;
|
231 |
+
margin-bottom: 30px;
|
232 |
+
font-size: 1rem;
|
233 |
+
}}
|
234 |
+
|
235 |
+
.stats-grid {{
|
236 |
+
display: grid;
|
237 |
+
grid-template-columns: 1fr 1fr;
|
238 |
+
gap: 20px;
|
239 |
+
margin-bottom: 30px;
|
240 |
+
}}
|
241 |
+
|
242 |
+
.stat-card {{
|
243 |
+
background: #f8f9fa;
|
244 |
+
padding: 20px;
|
245 |
+
border-radius: 15px;
|
246 |
+
}}
|
247 |
+
|
248 |
+
.stat-number {{
|
249 |
+
font-size: 2.5rem;
|
250 |
+
font-weight: 700;
|
251 |
+
color: var(--primary-color);
|
252 |
+
}}
|
253 |
+
|
254 |
+
.stat-label {{
|
255 |
+
font-size: 1rem;
|
256 |
+
color: #666;
|
257 |
+
margin-top: 5px;
|
258 |
+
}}
|
259 |
+
|
260 |
+
.button-group {{
|
261 |
+
display: flex;
|
262 |
+
gap: 15px;
|
263 |
+
justify-content: center;
|
264 |
+
}}
|
265 |
+
|
266 |
+
.btn {{
|
267 |
+
padding: 14px 28px;
|
268 |
+
border-radius: 30px;
|
269 |
+
text-decoration: none;
|
270 |
+
font-weight: bold;
|
271 |
+
font-size: 1rem;
|
272 |
+
transition: all 0.3s ease;
|
273 |
+
border: 2px solid transparent;
|
274 |
+
cursor: pointer;
|
275 |
+
}}
|
276 |
+
|
277 |
+
.btn-primary {{
|
278 |
+
background: var(--primary-color);
|
279 |
+
color: white;
|
280 |
+
}}
|
281 |
+
|
282 |
+
.btn-primary:hover {{
|
283 |
+
background: var(--secondary-color);
|
284 |
+
transform: translateY(-3px);
|
285 |
+
}}
|
286 |
+
|
287 |
+
.btn-secondary {{
|
288 |
+
background: transparent;
|
289 |
+
color: var(--primary-color);
|
290 |
+
border-color: var(--primary-color);
|
291 |
+
}}
|
292 |
+
|
293 |
+
.btn-secondary:hover {{
|
294 |
+
background: var(--primary-color);
|
295 |
+
color: white;
|
296 |
+
transform: translateY(-3px);
|
297 |
+
}}
|
298 |
+
|
299 |
+
</style>
|
300 |
+
</head>
|
301 |
+
<body>
|
302 |
+
<div class="container">
|
303 |
+
<div class="logo">🚗</div>
|
304 |
+
<h1>Baseer Self-Driving API</h1>
|
305 |
+
<p class="subtitle">واجهة برمجية متقدمة للقيادة الذاتية</p>
|
306 |
+
|
307 |
+
<div class="status-badge">{status_text}</div>
|
308 |
+
|
309 |
+
<div class="stats-grid">
|
310 |
+
<div class="stat-card">
|
311 |
+
<div class="stat-number">{active_sessions_count}</div>
|
312 |
+
<div class="stat-label">الجلسات النشطة</div>
|
313 |
+
</div>
|
314 |
+
<div class="stat-card">
|
315 |
+
<div class="stat-number">1.1.0</div>
|
316 |
+
<div class="stat-label">إصدار الـ API</div>
|
317 |
+
</div>
|
318 |
+
</div>
|
319 |
+
|
320 |
+
<div class="button-group">
|
321 |
+
<a href="/docs" target="_blank" class="btn btn-primary">📚 التوثيق التفاعلي (Docs)</a>
|
322 |
+
<a href="/sessions" target="_blank" class="btn btn-secondary">📊 عرض الجلسات</a>
|
323 |
+
</div>
|
324 |
+
</div>
|
325 |
+
</body>
|
326 |
</html>
|
327 |
"""
|
328 |
+
return HTMLResponse(content=html_content)
|
329 |
|
330 |
@app.post("/start_session", summary="Start a new driving session", tags=["Session Management"])
|
331 |
def start_session():
|