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增加CPP

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路怀帅
2025-12-26 10:02:00 +08:00
parent 4961794bf5
commit ef6a98d473
22 changed files with 1027 additions and 83 deletions
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190
web.py
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@@ -5,9 +5,65 @@ import sys
import os
import argparse
import numpy as np
import serial
import time
from surround_view import FisheyeCameraModel, BirdView
import surround_view.param_settings as settings
# 串口雷达配置
RADAR_SERIAL_PORT = '/dev/ttyS0'
RADAR_BAUDRATE = 115200 # 根据实际雷达配置调整
RADAR_TIMEOUT = 0.1
# 距离阈值配置（单位：mm）
DISTANCE_THRESHOLD = 3000 # 距离过近阈值，可以根据需要调整
# 雷达ID与方向映射
RADAR_ID_MAP = {1: 'front', 2: 'left', 3: 'back', 4: 'right'}
def parse_radar_data(raw_data):
"""
解析雷达原始数据
数据格式: 0xA5 0x5A [雷达ID-距离高字节-距离低字节]... 0x5A 0xA5
"""
try:
# 查找帧头位置
frame_start = raw_data.find(b'\xA5\x5A')
if frame_start == -1:
return None
# 查找帧尾位置
frame_end = raw_data.find(b'\x5A\xA5', frame_start)
if frame_end == -1:
return None
# 提取完整帧数据
frame_data = raw_data[frame_start+2:frame_end]
# 检查数据长度是否正确（每个雷达3字节 × 4雷达 = 12字节）
if len(frame_data) != 12:
return None
# 解析每个雷达数据
radar_distances = {}
for i in range(4):
radar_id = frame_data[i*3]
if radar_id not in RADAR_ID_MAP:
continue
distance_high = frame_data[i*3+1]
distance_low = frame_data[i*3+2]
distance = (distance_high << 8) + distance_low
direction = RADAR_ID_MAP[radar_id]
radar_distances[direction] = distance
return radar_distances
except Exception as e:
print(f"[ERROR] 雷达数据解析失败: {e}")
return None
sys.path.append(os.path.dirname(__file__)) # 确保能导入 py_utils
from py_utils.coco_utils import COCO_test_helper
from py_utils.rknn_executor import RKNN_model_container # 假设使用 RKNN
@@ -268,6 +324,17 @@ class MultiCameraBirdView:
"left": False,
"right": False
}
# 雷达数据
self.radar_distances = {
"front": 0,
"back": 0,
"left": 0,
"right": 0
}
self.radar_serial = None
self.radar_thread = None
self.radar_running = False
# === 新增：YOLO 人体检测模型 ===
try:
@@ -281,6 +348,9 @@ class MultiCameraBirdView:
self.shared_buffer = SharedFrameBuffer() # 👈 新增
# 初始化雷达串口
self._init_radar_serial()
def overlay_alert(self, birdview_img):
"""在鸟瞰图上叠加半透明红色预警区域"""
h, w = birdview_img.shape[:2]
@@ -369,6 +439,63 @@ class MultiCameraBirdView:
print(f"[ERROR] YOLO检测失败: {e}")
return image, [], []
def _init_radar_serial(self):
"""
初始化雷达串口并启动数据读取线程
"""
try:
self.radar_serial = serial.Serial(
port=RADAR_SERIAL_PORT,
baudrate=RADAR_BAUDRATE,
timeout=RADAR_TIMEOUT
)
print(f"✅ 已打开雷达串口 {RADAR_SERIAL_PORT}")
# 启动雷达数据读取线程
self.radar_running = True
self.radar_thread = threading.Thread(target=self._read_radar_data, daemon=True)
self.radar_thread.start()
print("[INFO] 雷达数据读取线程已启动")
except serial.SerialException as e:
print(f"❌ 无法打开雷达串口 {RADAR_SERIAL_PORT}: {e}")
self.radar_serial = None
except Exception as e:
print(f"[ERROR] 雷达初始化失败: {e}")
self.radar_serial = None
def _read_radar_data(self):
"""
雷达数据读取线程函数
"""
buffer = b''
while self.radar_running and self.radar_serial and self.radar_serial.is_open:
try:
# 读取可用数据
if self.radar_serial.in_waiting > 0:
data = self.radar_serial.read(self.radar_serial.in_waiting)
buffer += data
# 尝试解析数据
parsed_data = parse_radar_data(buffer)
if parsed_data:
print(f"[RADAR] 前:{parsed_data.get('front', 0):4d}cm 后:{parsed_data.get('back', 0):4d}cm 左:{parsed_data.get('left', 0):4d}cm 右:{parsed_data.get('right', 0):4d}cm")
# 更新雷达距离数据
self.radar_distances.update(parsed_data)
# 清空已解析的缓冲区
buffer = buffer[buffer.find(b'\x5A\xA5')+2:]
time.sleep(0.01) # 降低CPU占用
except serial.SerialException as e:
print(f"❌ 雷达串口异常: {e}")
break
except Exception as e:
print(f"[ERROR] 雷达数据读取失败: {e}")
time.sleep(0.1)
def _initialize_weights(self):
try:
images = [os.path.join(os.getcwd(), "images", name + ".png") for name in self.names]
@@ -404,6 +531,9 @@ class MultiCameraBirdView:
current_view = "front"
frame_count = 0
detection_interval = 3 # 每5帧进行一次检测，避免性能问题
# 雷达触发视图切换的方向优先级（距离过近时优先显示哪个方向）
radar_priority = ['front', 'left', 'right', 'back']
while self.running:
raw_frames = {}
@@ -414,7 +544,7 @@ class MultiCameraBirdView:
ret, frame = cap.read()
raw_frames[name] = frame
# self.shared_buffer.update(raw_frames[current_view])
p_frame = self.process_frame_once(frame, model)
@@ -427,6 +557,18 @@ class MultiCameraBirdView:
self.birdview.make_white_balance()
self.birdview.copy_car_image()
# 检查雷达距离，自动切换视图
auto_switch_view = None
for direction in radar_priority:
distance = self.radar_distances.get(direction, 0)
if distance > 0 and distance < DISTANCE_THRESHOLD:
auto_switch_view = direction
break
if auto_switch_view:
current_view = auto_switch_view
print(f"[INFO] 雷达检测到{auto_switch_view}方向距离过近 ({self.radar_distances[auto_switch_view]}cm)，自动切换视图")
# 获取单路图像（仅去畸变）
single_img = self.process_frame_undistort(
raw_frames[current_view],
@@ -465,49 +607,23 @@ class MultiCameraBirdView:
bird_resized = cv2.resize(birdview_with_alert, (w_bird, h_display))
single_resized = cv2.resize(single_img, (w_single, h_display))
display = np.hstack((bird_resized, single_resized))
# 在显示窗口上添加状态信息
# info_text = f"View: {current_view} | Persons detected: {len(person_boxes) if 'person_boxes' in locals() else 0}"
# cv2.putText(display, info_text, (10, 30),
# cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), 2)
self.shared_buffer.update(display)
# 全屏显示
cv2.namedWindow('Video', cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty('Video', cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)
cv2.imshow("Video", display)
key = cv2.waitKey(1) & 0xFF
# if key == ord('q'):
# self.running = False
# break
# elif key == ord('1'):
# current_view = "front"
# elif key == ord('2'):
# current_view = "back"
# elif key == ord('3'):
# current_view = "left"
# elif key == ord('4'):
# current_view = "right"
# # 新增：预警控制
# elif key == ord('5'):
# self.alerts["front"] = True
# elif key == ord('6'):
# self.alerts["back"] = True
# elif key == ord('7'):
# self.alerts["left"] = True
# elif key == ord('8'):
# self.alerts["right"] = True
# elif key == ord('0'):
# # 清除所有预警
# for k in self.alerts:
# self.alerts[k] = False
# elif key == ord('d'):
# # 手动触发一次检测
# single_img, person_boxes, person_scores = self.detect_persons(single_img)
# 清理雷达资源
self.radar_running = False
if self.radar_thread and self.radar_thread.is_alive():
self.radar_thread.join(timeout=1.0)
if self.radar_serial and self.radar_serial.is_open:
self.radar_serial.close()
print("🔌 雷达串口已关闭")
for cap in self.caps:
cap.release()
cv2.destroyAllWindows()