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app.py
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1 |
+
# app.py - InterFuser Self-Driving API Server
|
2 |
+
|
3 |
+
import uuid
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4 |
+
import base64
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5 |
+
import cv2
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6 |
+
import torch
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7 |
+
import numpy as np
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8 |
+
from fastapi import FastAPI, HTTPException
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9 |
+
from fastapi.responses import HTMLResponse
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10 |
+
from pydantic import BaseModel
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11 |
+
from torchvision import transforms
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12 |
+
from typing import List, Dict, Any, Optional
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13 |
+
import logging
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14 |
+
import uuid
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15 |
+
import base64
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16 |
+
import cv2
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17 |
+
import torch
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18 |
+
import numpy as np
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19 |
+
import logging
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20 |
+
from fastapi import FastAPI, HTTPException
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21 |
+
from fastapi.responses import HTMLResponse
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22 |
+
from pydantic import BaseModel, Field
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23 |
+
from typing import List, Dict, Tuple
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24 |
+
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25 |
+
from model_definition import InterfuserModel, load_and_prepare_model, get_master_config
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26 |
+
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27 |
+
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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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30 |
+
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31 |
+
# ==============================================================================
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32 |
+
# 2. إعدادات عامة وتطبيق FastAPI
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+
# ==============================================================================
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34 |
+
# إعداد التسجيل (Logging)
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35 |
+
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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36 |
+
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37 |
+
# تهيئة تطبيق FastAPI
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38 |
+
app = FastAPI(
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39 |
+
title="Baseer Self-Driving API",
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+
description="An advanced API for the InterFuser self-driving model, providing real-time control commands and scene analysis.",
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41 |
+
version="1.1.0"
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42 |
+
)
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43 |
+
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44 |
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# متغيرات عامة سيتم تهيئتها عند بدء التشغيل
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45 |
+
MODEL: InterfuserModel = None
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46 |
+
DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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47 |
+
SESSIONS: Dict[str, Dict] = {} # قاموس لتخزين حالة الجلسات النشطة
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48 |
+
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49 |
+
# ==============================================================================
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50 |
+
# 3. تعريف نماذج البيانات (Pydantic Models) للـ API
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51 |
+
# ==============================================================================
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52 |
+
class Measurements(BaseModel):
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53 |
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pos_global: Tuple[float, float] = Field(..., example=(0.0, 0.0), description="Global [X, Y] position of the vehicle.")
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54 |
+
theta: float = Field(..., example=0.0, description="Global orientation angle of the vehicle in radians.")
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55 |
+
speed: float = Field(..., example=0.0, description="Current speed in m/s.")
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56 |
+
target_point: Tuple[float, float] = Field(..., example=(10.0, 0.0), description="Target point relative to the vehicle.")
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57 |
+
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58 |
+
class RunStepRequest(BaseModel):
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+
session_id: str
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60 |
+
image_b64: str = Field(..., description="Base64 encoded string of the vehicle's front camera view (BGR format).")
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61 |
+
measurements: Measurements
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62 |
+
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63 |
+
class ControlCommands(BaseModel):
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64 |
+
steer: float
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65 |
+
throttle: float
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66 |
+
brake: bool
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67 |
+
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68 |
+
class SceneAnalysis(BaseModel):
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69 |
+
is_junction: float
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70 |
+
traffic_light_state: float
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71 |
+
stop_sign: float
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72 |
+
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73 |
+
class RunStepResponse(BaseModel):
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74 |
+
control_commands: ControlCommands
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75 |
+
scene_analysis: SceneAnalysis
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76 |
+
predicted_waypoints: List[Tuple[float, float]]
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77 |
+
dashboard_b64: str = Field(..., description="Base64 encoded string of the comprehensive dashboard view.")
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78 |
+
reason: str = Field(..., description="The reason for the current control action (e.g., 'Following ID 12', 'Red Light').")
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79 |
+
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80 |
+
# ==============================================================================
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81 |
+
# 4. دوال مساعدة (Helpers)
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82 |
+
# ==============================================================================
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83 |
+
def b64_to_cv2(b64_string: str) -> np.ndarray:
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84 |
+
try:
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85 |
+
img_bytes = base64.b64decode(b64_string)
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86 |
+
img_array = np.frombuffer(img_bytes, dtype=np.uint8)
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87 |
+
return cv2.imdecode(img_array, cv2.IMREAD_COLOR)
|
88 |
+
except Exception:
|
89 |
+
raise HTTPException(status_code=400, detail="Invalid Base64 image string.")
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90 |
+
|
91 |
+
def cv2_to_b64(img: np.ndarray) -> str:
|
92 |
+
_, buffer = cv2.imencode('.jpg', img)
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93 |
+
return base64.b64encode(buffer).decode('utf-8')
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94 |
+
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95 |
+
def prepare_model_input(image: np.ndarray, measurements: Measurements) -> Dict[str, torch.Tensor]:
|
96 |
+
"""
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97 |
+
إعداد دفعة (batch of 1) لتمريرها إلى النموذج.
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98 |
+
"""
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99 |
+
transform = transforms.Compose([
|
100 |
+
transforms.ToTensor(),
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101 |
+
transforms.Resize((224, 224), antialias=True),
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102 |
+
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
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103 |
+
])
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104 |
+
image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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105 |
+
image_tensor = transform(image_rgb).unsqueeze(0).to(DEVICE)
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106 |
+
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107 |
+
measurements_tensor = torch.tensor([[
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108 |
+
measurements.pos_global[0], measurements.pos_global[1], measurements.theta,
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109 |
+
0.0, 0.0, 0.0, # Steer, throttle, brake (not used by model)
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110 |
+
measurements.speed, 4.0 # Command (default to FollowLane)
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111 |
+
]], dtype=torch.float32).to(DEVICE)
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112 |
+
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113 |
+
target_point_tensor = torch.tensor([measurements.target_point], dtype=torch.float32).to(DEVICE)
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114 |
+
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115 |
+
return {
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116 |
+
'rgb': image_tensor,
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117 |
+
'rgb_left': image_tensor.clone(), 'rgb_right': image_tensor.clone(), 'rgb_center': image_tensor.clone(),
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118 |
+
'measurements': measurements_tensor,
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119 |
+
'target_point': target_point_tensor,
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120 |
+
'lidar': torch.zeros_like(image_tensor)
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121 |
+
}
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122 |
+
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123 |
+
# ==============================================================================
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124 |
+
# 5. أحداث دورة حياة التطبيق (Startup/Shutdown)
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125 |
+
# ==============================================================================
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126 |
+
@app.on_event("startup")
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127 |
+
async def startup_event():
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128 |
+
global MODEL
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129 |
+
logging.info("🚗 Server starting up...")
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130 |
+
logging.info(f"Using device: {DEVICE}")
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131 |
+
MODEL = load_and_prepare_model(DEVICE)
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132 |
+
if MODEL:
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133 |
+
logging.info("✅ Model loaded successfully. Server is ready!")
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134 |
+
else:
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135 |
+
logging.error("❌ CRITICAL: Model could not be loaded. The API will not function correctly.")
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136 |
+
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137 |
+
# ==============================================================================
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138 |
+
# 6. نقاط النهاية الرئيسية (API Endpoints)
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139 |
+
# ==============================================================================
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140 |
+
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141 |
+
@app.get("/", response_class=HTMLResponse, include_in_schema=False, tags=["General"])
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142 |
+
async def root():
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143 |
+
"""
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144 |
+
[النسخة النهائية مع التمرير]
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145 |
+
يعرض صفحة رئيسية احترافية وجذابة بصريًا مع تمكين التمرير العمودي.
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146 |
+
"""
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147 |
+
active_sessions_count = len(SESSIONS)
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148 |
+
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149 |
+
status_color = "#00ff7f" # SpringGreen
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150 |
+
status_text = "متصل ويعمل"
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151 |
+
if MODEL is None:
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152 |
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status_color = "#ff4757" # Red
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153 |
+
status_text = "خطأ: النموذج غير متاح"
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154 |
+
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155 |
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html_content = f"""
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156 |
+
<!DOCTYPE html>
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157 |
+
<html dir="rtl" lang="ar">
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158 |
+
<head>
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159 |
+
<meta charset="UTF-8">
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160 |
+
<meta name="viewport" content="width=device-width, initial-scale=1.0">
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161 |
+
<title>🚗 Baseer - واجهة القيادة الذاتية</title>
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162 |
+
<style>
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163 |
+
@import url('https://fonts.googleapis.com/css2?family=Cairo:wght@400;700;900&display=swap');
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164 |
+
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165 |
+
:root {{
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166 |
+
--bg-dark: #1a1a2e;
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167 |
+
--panel-dark: #16213e;
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168 |
+
--primary-accent: #0f3460;
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169 |
+
--secondary-accent: #e94560;
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170 |
+
--glow-color: #537895;
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171 |
+
--text-light: #e0e0e0;
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172 |
+
--text-header: #ffffff;
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173 |
+
}}
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174 |
+
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175 |
+
body {{
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176 |
+
font-family: 'Cairo', sans-serif;
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177 |
+
background: var(--bg-dark);
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178 |
+
background-image: linear-gradient(to right top, #1a1a2e, #1c1d32, #1f2037, #22233b, #252640);
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179 |
+
color: var(--text-light);
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+
margin: 0;
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181 |
+
padding: 40px 20px; /* إضافة padding علوي وسفلي للسماح بالمساحة */
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182 |
+
min-height: 100vh;
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183 |
+
box-sizing: border-box; /* لضمان أن padding لا يضيف إلى الارتفاع */
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184 |
+
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185 |
+
/* --- [التصحيح هنا] --- */
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186 |
+
overflow-x: hidden; /* إخفاء التمرير الأفقي غير المرغوب فيه */
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187 |
+
overflow-y: auto; /* السماح بالتمرير العمودي عند الحاجة */
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188 |
+
}}
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189 |
+
|
190 |
+
.main-content {{
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191 |
+
display: flex;
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192 |
+
justify-content: center;
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193 |
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align-items: center;
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194 |
+
width: 100%;
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195 |
+
}}
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196 |
+
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+
.container {{
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+
background: rgba(22, 33, 62, 0.85);
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199 |
+
backdrop-filter: blur(15px);
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+
border-radius: 25px;
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+
padding: 40px 50px;
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202 |
+
box-shadow: 0 25px 50px rgba(0, 0, 0, 0.3);
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+
text-align: center;
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204 |
+
max-width: 750px;
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205 |
+
width: 100%;
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206 |
+
border: 1px solid rgba(255, 255, 255, 0.1);
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207 |
+
position: relative;
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208 |
+
z-index: 1;
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209 |
+
}}
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210 |
+
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211 |
+
/* ... باقي كود CSS يبقى كما هو تمامًا ... */
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212 |
+
.logo {{
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213 |
+
font-size: 5rem;
|
214 |
+
margin-bottom: 10px;
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215 |
+
text-shadow: 0 0 15px var(--glow-color);
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+
animation: float 4s ease-in-out infinite;
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217 |
+
}}
|
218 |
+
|
219 |
+
@keyframes float {{
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220 |
+
0% {{ transform: translateY(0px); }}
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221 |
+
50% {{ transform: translateY(-15px); }}
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+
100% {{ transform: translateY(0px); }}
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223 |
+
}}
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+
|
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+
h1 {{
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+
font-size: 3rem;
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227 |
+
font-weight: 900;
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228 |
+
color: var(--text-header);
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229 |
+
margin-bottom: 5px;
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230 |
+
letter-spacing: 1px;
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+
}}
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+
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233 |
+
.subtitle {{
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+
font-size: 1.3rem;
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color: #a7a9be;
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+
margin-bottom: 25px;
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237 |
+
}}
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+
|
239 |
+
.status-badge {{
|
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+
display: inline-flex;
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+
align-items: center;
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242 |
+
gap: 10px;
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243 |
+
background-color: rgba(255, 255, 255, 0.05);
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244 |
+
border: 1px solid {status_color};
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245 |
+
color: {status_color};
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246 |
+
padding: 10px 22px;
|
247 |
+
border-radius: 50px;
|
248 |
+
font-weight: bold;
|
249 |
+
margin-bottom: 35px;
|
250 |
+
font-size: 1.1rem;
|
251 |
+
box-shadow: 0 0 15px {status_color}33;
|
252 |
+
}}
|
253 |
+
|
254 |
+
.stats-grid {{
|
255 |
+
display: grid;
|
256 |
+
grid-template-columns: 1fr 1fr;
|
257 |
+
gap: 25px;
|
258 |
+
margin-bottom: 40px;
|
259 |
+
}}
|
260 |
+
|
261 |
+
.stat-card {{
|
262 |
+
background: var(--primary-accent);
|
263 |
+
padding: 25px;
|
264 |
+
border-radius: 20px;
|
265 |
+
transition: transform 0.3s ease, box-shadow 0.3s ease;
|
266 |
+
}}
|
267 |
+
|
268 |
+
.stat-card:hover {{
|
269 |
+
transform: scale(1.05);
|
270 |
+
box-shadow: 0 0 25px var(--secondary-accent)44;
|
271 |
+
}}
|
272 |
+
|
273 |
+
.stat-number {{
|
274 |
+
font-size: 3rem;
|
275 |
+
font-weight: 700;
|
276 |
+
color: var(--secondary-accent);
|
277 |
+
}}
|
278 |
+
|
279 |
+
.stat-label {{
|
280 |
+
font-size: 1rem;
|
281 |
+
color: #a7a9be;
|
282 |
+
margin-top: 5px;
|
283 |
+
}}
|
284 |
+
|
285 |
+
.button-group {{
|
286 |
+
display: flex;
|
287 |
+
gap: 20px;
|
288 |
+
justify-content: center;
|
289 |
+
}}
|
290 |
+
|
291 |
+
.btn {{
|
292 |
+
padding: 15px 35px;
|
293 |
+
border-radius: 50px;
|
294 |
+
text-decoration: none;
|
295 |
+
font-weight: 700;
|
296 |
+
font-size: 1.1rem;
|
297 |
+
transition: all 0.3s ease;
|
298 |
+
border: none;
|
299 |
+
cursor: pointer;
|
300 |
+
position: relative;
|
301 |
+
overflow: hidden;
|
302 |
+
}}
|
303 |
+
|
304 |
+
.btn-primary {{
|
305 |
+
background: var(--secondary-accent);
|
306 |
+
color: var(--text-header);
|
307 |
+
box-shadow: 0 5px 15px {status_color}44;
|
308 |
+
}}
|
309 |
+
|
310 |
+
.btn-primary:hover {{
|
311 |
+
box-shadow: 0 8px 25px {status_color}66;
|
312 |
+
transform: translateY(-3px);
|
313 |
+
}}
|
314 |
+
|
315 |
+
.btn-secondary {{
|
316 |
+
background: transparent;
|
317 |
+
color: var(--text-light);
|
318 |
+
border: 2px solid var(--glow-color);
|
319 |
+
}}
|
320 |
+
|
321 |
+
.btn-secondary:hover {{
|
322 |
+
background: var(--glow-color);
|
323 |
+
color: var(--text-header);
|
324 |
+
border-color: var(--glow-color);
|
325 |
+
}}
|
326 |
+
|
327 |
+
</style>
|
328 |
+
</head>
|
329 |
+
<body>
|
330 |
+
<div class="main-content">
|
331 |
+
<div class="container">
|
332 |
+
<div class="logo">🚀</div>
|
333 |
+
<h1>بصيـر API</h1>
|
334 |
+
<p class="subtitle">مستقبل القيادة الذاتية بين يديك</p>
|
335 |
+
|
336 |
+
<div class="status-badge">
|
337 |
+
<span style="width: 12px; height: 12px; background-color: {status_color}; border-radius: 50%;"></span>
|
338 |
+
<span>{status_text}</span>
|
339 |
+
</div>
|
340 |
+
|
341 |
+
<div class="stats-grid">
|
342 |
+
<div class="stat-card">
|
343 |
+
<div class="stat-number">{active_sessions_count}</div>
|
344 |
+
<div class="stat-label">الجلسات النشطة</div>
|
345 |
+
</div>
|
346 |
+
<div class="stat-card">
|
347 |
+
<div class="stat-number">1.1</div>
|
348 |
+
<div class="stat-label">الإصدار</div>
|
349 |
+
</div>
|
350 |
+
</div>
|
351 |
+
|
352 |
+
<div class="button-group">
|
353 |
+
<a href="/docs" target="_blank" class="btn btn-primary">📚 التوثيق التفاعلي</a>
|
354 |
+
<a href="/sessions" target="_blank" class="btn btn-secondary">📊 عرض الجلسات</a>
|
355 |
+
</div>
|
356 |
+
</div>
|
357 |
+
</div>
|
358 |
+
</body>
|
359 |
+
</html>
|
360 |
+
"""
|
361 |
+
return HTMLResponse(content=html_content)
|
362 |
+
|
363 |
+
@app.post("/start_session", summary="Start a new driving session", tags=["Session Management"])
|
364 |
+
def start_session():
|
365 |
+
session_id = str(uuid.uuid4())
|
366 |
+
|
367 |
+
# 1. الحصول على الإعدادات الكاملة من المصدر الوحيد
|
368 |
+
config = get_master_config()
|
369 |
+
|
370 |
+
# 2. استخراج الإعدادات المطلوبة لكل مكون بشكل صريح
|
371 |
+
grid_conf = config['grid_conf']
|
372 |
+
controller_params = config['controller_params']
|
373 |
+
simulation_freq = config['simulation']['frequency']
|
374 |
+
|
375 |
+
# 3. تهيئة المتتبع (Tracker) بمعلماته المحددة
|
376 |
+
tracker = Tracker(
|
377 |
+
grid_conf=grid_conf,
|
378 |
+
match_threshold=controller_params.get('tracker_match_thresh', 2.5),
|
379 |
+
prune_age=controller_params.get('tracker_prune_age', 5)
|
380 |
+
)
|
381 |
+
|
382 |
+
# 4. تهيئة المتحكم (Controller)
|
383 |
+
controller = InterfuserController({
|
384 |
+
'controller_params': controller_params,
|
385 |
+
'grid_conf': grid_conf,
|
386 |
+
'frequency': simulation_freq
|
387 |
+
})
|
388 |
+
|
389 |
+
# 5. إنشاء الجلسة بالكائنات المهيأة
|
390 |
+
SESSIONS[session_id] = {
|
391 |
+
'tracker': tracker,
|
392 |
+
'controller': controller,
|
393 |
+
'frame_num': 0
|
394 |
+
}
|
395 |
+
|
396 |
+
logging.info(f"New session started: {session_id}")
|
397 |
+
return {"session_id": session_id}
|
398 |
+
|
399 |
+
@app.post("/run_step", response_model=RunStepResponse, summary="Process a single simulation step", tags=["Core"])
|
400 |
+
@torch.no_grad()
|
401 |
+
def run_step(request: RunStepRequest):
|
402 |
+
if MODEL is None:
|
403 |
+
raise HTTPException(status_code=503, detail="Model is not available.")
|
404 |
+
|
405 |
+
session = SESSIONS.get(request.session_id)
|
406 |
+
if not session:
|
407 |
+
raise HTTPException(status_code=404, detail="Session ID not found.")
|
408 |
+
|
409 |
+
# --- 1. الإدراك (Perception) ---
|
410 |
+
image = b64_to_cv2(request.image_b64)
|
411 |
+
model_input = prepare_model_input(image, request.measurements)
|
412 |
+
traffic, waypoints, junc, light, stop, _ = MODEL(model_input)
|
413 |
+
|
414 |
+
# --- 2. معالجة مخرجات النموذج ---
|
415 |
+
traffic_processed = torch.cat([torch.sigmoid(traffic[0][:, 0:1]), traffic[0][:, 1:]], dim=1)
|
416 |
+
traffic_np = traffic_processed.cpu().numpy().reshape(20, 20, -1)
|
417 |
+
waypoints_np = waypoints[0].cpu().numpy()
|
418 |
+
junction_prob = torch.softmax(junc, dim=1)[0, 1].item()
|
419 |
+
light_prob = torch.softmax(light, dim=1)[0, 1].item()
|
420 |
+
stop_prob = torch.softmax(stop, dim=1)[0, 1].item()
|
421 |
+
|
422 |
+
# --- 3. التتبع والتحكم ---
|
423 |
+
ego_pos = np.array(request.measurements.pos_global)
|
424 |
+
ego_theta = request.measurements.theta
|
425 |
+
frame_num = session['frame_num']
|
426 |
+
|
427 |
+
active_tracks = session['tracker'].process_frame(traffic_np, ego_pos, ego_theta, frame_num)
|
428 |
+
steer, throttle, brake, ctrl_info = session['controller'].run_step(
|
429 |
+
speed=request.measurements.speed, waypoints=torch.from_numpy(waypoints_np),
|
430 |
+
junction=junction_prob, traffic_light=light_prob, stop_sign=stop_prob,
|
431 |
+
bev_map=traffic_np, ego_pos=ego_pos, ego_theta=ego_theta, frame_num=frame_num
|
432 |
+
)
|
433 |
+
|
434 |
+
# --- 4. إنشاء الواجهة المرئية ---
|
435 |
+
display_iface = DisplayInterface(DisplayConfig(width=1280, height=720))
|
436 |
+
bev_maps = render_bev(active_tracks, waypoints_np, ego_pos, ego_theta)
|
437 |
+
display_data = {
|
438 |
+
'camera_view': image, 'map_t0': bev_maps['t0'], 'map_t1': bev_maps['t1'], 'map_t2': bev_maps['t2'],
|
439 |
+
'frame_num': frame_num, 'speed': request.measurements.speed * 3.6,
|
440 |
+
'target_speed': ctrl_info.get('target_speed', 0) * 3.6,
|
441 |
+
'steer': steer, 'throttle': throttle, 'brake': brake,
|
442 |
+
'light_prob': light_prob, 'stop_prob': stop_prob,
|
443 |
+
'object_counts': {'car': len(active_tracks)}
|
444 |
+
}
|
445 |
+
dashboard = display_iface.run_interface(display_data)
|
446 |
+
|
447 |
+
# --- 5. تحديث الجلسة وإرجاع الرد ---
|
448 |
+
session['frame_num'] += 1
|
449 |
+
|
450 |
+
return RunStepResponse(
|
451 |
+
control_commands=ControlCommands(steer=steer, throttle=throttle, brake=brake),
|
452 |
+
scene_analysis=SceneAnalysis(is_junction=junction_prob, traffic_light_state=light_prob, stop_sign=stop_prob),
|
453 |
+
predicted_waypoints=[tuple(wp) for wp in waypoints_np.tolist()],
|
454 |
+
dashboard_b64=cv2_to_b64(dashboard),
|
455 |
+
reason=ctrl_info.get('brake_reason', "Cruising")
|
456 |
+
)
|
457 |
+
|
458 |
+
@app.post("/end_session", summary="End and clean up a session", tags=["Session Management"])
|
459 |
+
def end_session(session_id: str):
|
460 |
+
if session_id in SESSIONS:
|
461 |
+
del SESSIONS[session_id]
|
462 |
+
logging.info(f"Session ended: {session_id}")
|
463 |
+
return {"message": f"Session {session_id} ended."}
|
464 |
+
raise HTTPException(status_code=404, detail="Session not found.")
|
465 |
+
# ================== تشغيل الخادم ==================
|
466 |
+
if __name__ == "__main__":
|
467 |
+
import uvicorn
|
468 |
+
uvicorn.run(app, host="0.0.0.0", port=7860)
|