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import math
import cv2
import threading
import time
from myutils.ConfigManager import myCongif
from myutils.MyDeque import MyDeque
from myutils.MyLogger_logger import LogHandler
class CapManager:
def __init__(self):
self.logger = LogHandler().get_logger("CapManager")
self.mycap_map = {} #source,VideoCaptureWithFPS
self.lock = threading.Lock()
def __del__(self):
pass
def start_get_video(self,source,type=1):
vcf = None
with self.lock:
if source in self.mycap_map:
vcf = self.mycap_map[source]
vcf.addcount()
else:
vcf = VideoCaptureWithFPS(source,type)
self.mycap_map[source] = vcf
return vcf
def stop_get_video(self,source):
with self.lock:
if source in self.mycap_map:
vcf = self.mycap_map[source]
vcf.delcount()
if vcf.icount == 0:
del self.mycap_map[source]
else:
self.logger.error("数据存在问题!")
mCap = CapManager()
class VideoCaptureWithFPS:
'''视频捕获的封装类,是一个通道一个
打开摄像头 0--USB摄像头1-RTSP,2-海康SDK
'''
def __init__(self, source,type=1):
self.source = self.ensure_udp_transport(source)
self.width = None
self.height = None
self.bok = False
self.icount = 1 #引用次数
# GStreamer --- 内存占用太高,且工作环境的部署也不简单
# self.pipeline = (
# "rtspsrc location=rtsp://192.168.3.102/live1 protocols=udp latency=100 ! "
# "rtph264depay !"
# " h264parse !"
# " avdec_h264 !"
# " videoconvert !"
# " appsink"
# )
#self.cap = cv2.VideoCapture(self.pipeline, cv2.CAP_GSTREAMER)
# opencv -- 后端默认使用的就是FFmpeg -- 不支持UDP
self.running = True
#self.frame_queue = queue.Queue(maxsize=1)
self.frame_queue = MyDeque(5)
self.frame = None
self.read_lock = threading.Lock()
self.thread = threading.Thread(target=self.update)
self.thread.start()
def addcount(self):
self.icount += 1
def delcount(self):
self.icount -= 1
if self.icount ==0: #结束线程
self.release()
def openViedo_opencv(self,source):
self.cap = cv2.VideoCapture(source,cv2.CAP_FFMPEG)
# self.cap.set(cv2.CAP_PROP_BUFFERSIZE, 3)
if self.cap.isOpened(): # 若没有打开成功,在读取画面的时候,已有判断和处理 -- 这里也要检查下内存的释放情况
self.width = int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
self.height = int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
# self.fps = fps # 线程保持最大帧率的刷新画面---过高的帧率会影响CPU性能,但过地的帧率会造成帧积压
self.fps = math.ceil(
self.cap.get(cv2.CAP_PROP_FPS) / float(myCongif.get_data("verify_rate"))) - 1 # 向上取整。
#print(self.width, self.height, self.fps)
else:
raise ValueError("无法打开视频源")
def ensure_udp_transport(self,source): #使用udp拉流时使用
# 检查 source 是否已经包含 '?transport=udp'
# if not source.endswith("?transport=udp"):
# # 如果没有,则添加 '?transport=udp'
# if "?" in source:
# # 如果已有其他查询参数,用 '&' 拼接
# source += "&transport=udp"
# else:
# # 否则直接添加 '?transport=udp'
# source += "?transport=udp"
return source
def update(self):
sleep_time = myCongif.get_data("cap_sleep_time")
reconnect_attempts = myCongif.get_data("reconnect_attempts")
frame_interval = 1 / (myCongif.get_data("verify_rate")+1)
last_frame_time = time.time()
while self.running:
try:
# ffmpeg_process = subprocess.Popen(
# ['ffmpeg', '-i', self.source, '-f', 'image2pipe', '-pix_fmt', 'bgr24', '-vcodec', 'rawvideo', '-'],
# stdout=subprocess.PIPE, stderr=subprocess.PIPE
# )
#读取帧后,对帧数据进行处理
# frame = np.frombuffer(raw_frame, np.uint8).reshape((480, 640, 3))
# frame = np.copy(frame) # 创建一个可写的副本
self.openViedo_opencv(self.source)
if not self.cap.isOpened():
raise RuntimeError("视频源打开失败")
failure_count = 0
self.bok = True
while self.running:
#subprocess-udp 拉流
#raw_frame = ffmpeg_process.stdout.read(640 * 480 * 3)
if self.cap.grab():
current_time = time.time()
if current_time - last_frame_time > frame_interval:
last_frame_time = current_time
ret, frame = self.cap.retrieve()
if ret:
# resized_frame = cv2.resize(frame, (int(self.width / 2), int(self.height / 2)))
#self.frame_queue.myappend(frame)
with self.read_lock:
self.frame = frame
failure_count = 0 # 重置计数
else:
failure_count += 1
time.sleep(0.1) # 休眠一段时间后重试
if failure_count >= reconnect_attempts:
with self.read_lock:
self.frame = None
raise RuntimeError("无法读取视频帧")
continue
#正常结束,关闭进程,释放资源
#ffmpeg_process.terminate()
self.cap.release()
self.bok = False
except Exception as e:
print(f"发生异常:{e}")
#ffmpeg_process.terminate()
self.cap.release()
self.bok = False
print(f"{self.source}视频流,将于{sleep_time}秒后重连!")
# 分段休眠,检测 self.running
total_sleep = 0
while total_sleep < sleep_time:
if not self.running:
return
time.sleep(2)
total_sleep += 2
def read(self):
with self.read_lock:
frame = self.frame.copy() if self.frame is not None else None
if frame is not None:
return True, frame
else:
return False, None
# if not self.frame_queue.empty():
# try:
# frame = self.frame_queue.get(timeout=0.05)
# except queue.Empty:
# #print("cap-frame None")
# return False, None
# else:
# #print("cap-frame None")
# return False, None
# ret = False
# frame = None
# if self.bok: #连接状态再读取
# frame = self.frame_queue.mypopleft()
# if frame is not None:
# ret = True
# else:
# print("____读取cap帧为空,采集速度过慢___")
# return ret, frame
def release(self):
self.running = False
self.thread.join()
self.cap.release()