You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
454 lines
20 KiB
454 lines
20 KiB
# 导入代码依赖
|
|
import time
|
|
import av
|
|
import os
|
|
import cv2
|
|
import numpy as np
|
|
import threading
|
|
import importlib.util
|
|
import datetime
|
|
from core.DBManager import mDBM,DBManager
|
|
from myutils.MyLogger_logger import LogHandler
|
|
from myutils.ConfigManager import myCongif
|
|
from model.plugins.ModelBase import ModelBase
|
|
|
|
import acl
|
|
from PIL import Image
|
|
|
|
ACL_MEM_MALLOC_HUGE_FIRST = 0
|
|
ACL_MEMCPY_HOST_TO_DEVICE = 1
|
|
ACL_MEMCPY_DEVICE_TO_HOST = 2
|
|
|
|
class VideoCaptureWithFPS:
|
|
'''视频捕获的封装类，是一个通道一个'''
|
|
def __init__(self, source=0):
|
|
self.source = source
|
|
self.cap = cv2.VideoCapture(self.source)
|
|
self.width = None
|
|
self.height = None
|
|
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
|
|
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 = self.cap.get(cv2.CAP_PROP_FPS) + 20 #只是个参考值，休眠时间要比帧率快点，由于read也需要耗时。
|
|
#print(self.fps)
|
|
self.frame = None
|
|
self.running = True
|
|
self.read_lock = threading.Lock()
|
|
self.thread = threading.Thread(target=self.update)
|
|
self.thread.start()
|
|
|
|
def update(self):
|
|
while self.running:
|
|
ret, frame = self.cap.read()
|
|
if not ret:
|
|
continue
|
|
with self.read_lock:
|
|
self.frame = frame
|
|
time.sleep(1.0 / self.fps)
|
|
|
|
def read(self):
|
|
with self.read_lock:
|
|
frame = self.frame
|
|
return frame is not None, frame
|
|
|
|
def release(self):
|
|
self.running = False
|
|
self.thread.join()
|
|
self.cap.release()
|
|
|
|
|
|
class ModelManager:
|
|
def __init__(self):
|
|
self.verify_list = {} #模型的主要数据
|
|
self.bRun = True
|
|
self.logger = LogHandler().get_logger("ModelManager")
|
|
# 本地YOLOv5仓库路径
|
|
self.yolov5_path = myCongif.get_data("yolov5_path")
|
|
self.buflen = myCongif.get_data("buffer_len")
|
|
self.icout_max = myCongif.get_data("RESET_INTERVAL") #跟视频帧序用一个变量
|
|
self.frame_rate = myCongif.get_data("frame_rate")
|
|
self.frame_interval = 1.0 / int(myCongif.get_data("verify_rate"))
|
|
#保存视频相关内容
|
|
self.fourcc = cv2.VideoWriter_fourcc(*'mp4v') # 使用 mp4 编码
|
|
#基于模型运行环境进行相应初始化工作
|
|
if myCongif.get_data("model_platform") == "acl":
|
|
|
|
|
|
def __del__(self):
|
|
self.logger.debug("释放资源")
|
|
|
|
def _init_acl(self):
|
|
'''acl初始化函数'''
|
|
self.device_id = 0
|
|
#step1 初始化
|
|
ret = acl.init()
|
|
|
|
|
|
|
|
def _open_view(self,url,itype): #打开摄像头 0--USB摄像头，1-RTSP,2-海康SDK
|
|
if itype == 0:
|
|
cap = VideoCaptureWithFPS(int(url))
|
|
elif itype == 1:
|
|
cap = VideoCaptureWithFPS(url)
|
|
else:
|
|
raise Exception("视频参数错误！")
|
|
return cap
|
|
|
|
def _import_model(self,model_name,model_path):
|
|
'''根据路径，动态导入模块'''
|
|
if os.path.exists(model_path):
|
|
module_spec = importlib.util.spec_from_file_location(model_name, model_path)
|
|
if module_spec is None:
|
|
self.logger.error(f"{model_path} 加载错误")
|
|
return None
|
|
module = importlib.util.module_from_spec(module_spec)
|
|
module_spec.loader.exec_module(module)
|
|
md = getattr(module, "Model")(model_path)
|
|
if not isinstance(md, ModelBase):
|
|
self.logger.error("{} not zf_model".format(md))
|
|
return None
|
|
else:
|
|
self.logger.error("{}文件不存在".format(model_path))
|
|
return None
|
|
return md
|
|
|
|
def getschedule(self,c2m_id,myDBM):
|
|
'''
|
|
根据c2mID 查询该算法的布防时间
|
|
:param c2m_id:
|
|
:return: 以day为行，hour作为列的，布防标识值二维list
|
|
'''
|
|
strsql = f"select day,hour,status from schedule where channel2model_id ={c2m_id} order by hour asc,day asc;"
|
|
datas = myDBM.do_select(strsql)
|
|
onelist = []
|
|
twolist = []
|
|
threelist = []
|
|
fourlist = []
|
|
fivelist = []
|
|
sixlist = []
|
|
sevenlist = []
|
|
if datas:
|
|
for i in range(24):
|
|
onelist.append(datas[i*7 + 0][2])
|
|
twolist.append(datas[i*7 + 1][2])
|
|
threelist.append(datas[i*7 + 2][2])
|
|
fourlist.append(datas[i*7 + 3][2])
|
|
fivelist.append(datas[i*7 + 4][2])
|
|
sixlist.append(datas[i*7 + 5][2])
|
|
sevenlist.append(datas[i*7 + 6][2])
|
|
else:
|
|
self.logger(f"没有数据？{c2m_id}")
|
|
onelist = [1]*24
|
|
twolist = [1]*24
|
|
threelist = [1]*24
|
|
fourlist = [1]*24
|
|
fivelist = [1]*24
|
|
sixlist = [1]*24
|
|
sevenlist = [1]*24
|
|
schedule_list = []
|
|
schedule_list.append(onelist)
|
|
schedule_list.append(twolist)
|
|
schedule_list.append(threelist)
|
|
schedule_list.append(fourlist)
|
|
schedule_list.append(fivelist)
|
|
schedule_list.append(sixlist)
|
|
schedule_list.append(sevenlist)
|
|
return schedule_list
|
|
|
|
def verify(self,frame,myModle_list,myModle_data,channel_id,schedule_list,result_list,isdraw=1):
|
|
'''验证执行主函数，实现遍历通道关联的模型，调用对应模型执行验证，模型文件遍历执行'''
|
|
img = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
|
|
# img = frame.to_ndarray(format="bgr24")
|
|
# 使用 模型 进行目标检测
|
|
i_warn_count = 0 #报警标签
|
|
isverify = False
|
|
for i in range(len(myModle_list)): # 遍历通道关联的算法进行检测，若不控制模型数量，有可能需要考虑多线程执行。
|
|
model = myModle_list[i]
|
|
data = myModle_data[i]
|
|
schedule = schedule_list[i]
|
|
result = result_list[i]
|
|
#验证检测计划，是否在布防时间内
|
|
now = datetime.datetime.now() # 获取当前日期和时间
|
|
weekday = now.weekday() # 获取星期几，星期一是0，星期天是6
|
|
hour = now.hour
|
|
result.pop(0) # 保障结果数组定长 --先把最早的结果推出数组
|
|
if schedule[weekday][hour] == 1: #不在计划则不进行验证，直接返回图片
|
|
# 调用模型，进行检测，model是动态加载的，具体的判断标准由模型内执行 ---- *********
|
|
isverify = True
|
|
detections, bwarn, warntext = model.verify(img, data,isdraw) #****************重要
|
|
# 对识别结果要部要进行处理
|
|
if bwarn: # 整个识别有产生报警
|
|
#根据模型设定的时间和占比判断是否
|
|
# 绘制报警文本
|
|
cv2.putText(img, 'Intruder detected!', (50, (i_warn_count + 1) * 50),
|
|
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
|
|
i_warn_count += 1
|
|
result.append(1) #要验证数组修改，是地址修改吗？
|
|
else: #没有产生报警也需要记录，统一计算占比
|
|
result.append(0)
|
|
else:
|
|
result.append(0)
|
|
if not isverify: #没做处理，直接返回的，需要控制下帧率，太快读取没有意义。
|
|
time.sleep(1.0/self.frame_rate) #给个默认帧率，不超过30帧，---若经过模型计算，CPU下单模型也就12帧这样
|
|
|
|
# 将检测结果图像转换为帧 -- 需要确认前面对img的处理都是累加的。
|
|
#img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) #numpy.ndarray
|
|
if isinstance(img, np.ndarray):
|
|
new_frame = av.VideoFrame.from_ndarray(img, format="rgb24") #AVFrame
|
|
new_frame.pts = None # 添加此行确保有pts属性
|
|
#self.logger.debug("img 是np.darry")
|
|
else:
|
|
#self.logger.error("img不是np.darry")
|
|
new_frame = None
|
|
#处理完的图片后返回-gbr模式 （new_frame 是 rgb)
|
|
img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
|
|
return new_frame,img
|
|
|
|
|
|
def dowork_thread(self,channel_id):
|
|
'''一个通道一个线程，关联的模型在一个线程检测,局部变量都是一个通道独有'''
|
|
channel_data = self.verify_list[channel_id] #一通道一线程 [url,type,True,img_buffer,img,icount]
|
|
|
|
cap = None
|
|
#查询关联的模型 --- 在循环运行前把基础数据都准备好
|
|
myDBM = DBManager()
|
|
myDBM.connect()
|
|
strsql = (f"select t1.model_id,t1.check_area,t1.polygon ,t2.duration_time,t2.proportion,t2.model_path,t1.ID,"
|
|
f"t2.model_name "
|
|
f"from channel2model t1 left join model t2 on t1.model_id = t2.ID where t1.channel_id ={channel_id};")
|
|
myModels = myDBM.do_select(strsql)
|
|
#加载模型 --- 是不是要做个限制，一个视频通道关联算法模块的上限 --- 关联多了一个线程执行耗时较多，造成帧率太低，或者再多线程并发 #？
|
|
|
|
myModle_list = [] #存放模型对象List 一个模型一个
|
|
myModle_data = [] #存放检测参数 一个模型一个
|
|
schedule_list = [] #布防策略 -一个模型一个
|
|
result_list = [] #检测结果记录 -一个模型一个
|
|
proportion_lsit = []#占比设定 -一个模型一个
|
|
warn_save_count = []#没个模型触发报警后，保存录像的最新帧序号 -一个模型一个
|
|
|
|
view_buffer = []
|
|
ibuffer_count = 0
|
|
last_img = None
|
|
|
|
for model in myModels:
|
|
#基于基类实例化模块类
|
|
m = self._import_model("",model[5]) #动态加载模型
|
|
if m:
|
|
myModle_list.append(m)
|
|
myModle_data.append(model)
|
|
#model[6] -- c2m_id --把通道对于模型的 0-周一，6-周日
|
|
schedule_list.append(self.getschedule(model[6],myDBM))
|
|
result = [0 for _ in range(model[3] * myCongif.get_data("verify_rate"))] #初始化时间*验证帧率数量的结果list
|
|
result_list.append(result)
|
|
proportion_lsit.append(model[4])
|
|
warn_save_count.append(0) #保存录像的最新帧初始化为0
|
|
|
|
# if not myModle_list: #没有成功加载的模型原画输出
|
|
# self.logger.info(f"视频通道：{channel_id}，未配置算法模块，结束线程！")
|
|
# return #可以不结束，直接返回未处理画面显示。
|
|
#开始循环检测
|
|
#print(mydata[0],mydata[1],mydata[2],mydata[3]) # url type tag img_buffer
|
|
#[url,type,True,img_buffer]
|
|
iread_count =0
|
|
last_frame_time = time.time()
|
|
#保存视频录像使用 -- 放在循环外面，可以减少点消耗
|
|
FPS = myCongif.get_data("verify_rate") # 视频帧率
|
|
fourcc = cv2.VideoWriter_fourcc(*'mp4v') # 使用 mp4 编码
|
|
while channel_data[2]: #基于tag 作为运行标识。 线程里只是读，住线程更新，最多晚一轮，应该不用线程锁。需验证
|
|
# 需要控制帧率
|
|
current_time = time.time()
|
|
elapsed_time = current_time - last_frame_time
|
|
if elapsed_time < self.frame_interval:
|
|
time.sleep(self.frame_interval - elapsed_time) #若小于间隔时间则休眠
|
|
last_frame_time = time.time()
|
|
#*********取画面*************
|
|
if not cap: #还没连接视频源
|
|
try:
|
|
cap = self._open_view(channel_data[0],channel_data[1])
|
|
iread_count = 0
|
|
except:
|
|
self.logger.error("参数错误，终止线程")
|
|
return
|
|
ret,frame = cap.read()
|
|
if not ret:
|
|
if iread_count > 60:
|
|
self.logger.warning(f"通道-{channel_id}：view disconnected. Reconnecting...")
|
|
cap.release()
|
|
cap = None
|
|
time.sleep(myCongif.get_data("cap_sleep_time"))
|
|
else:
|
|
iread_count += 1
|
|
time.sleep(1.0/20) #20帧只是作为个默认参考值，一般验证帧率都比这个慢
|
|
continue #没读到画面继续
|
|
iread_count = 0 #重置下视频帧计算
|
|
|
|
#执行图片推理 -- 如何没有模型或不在工作时间，返回的是原画，要不要控制下帧率？ -- 在verify中做了sleep
|
|
new_frame,img = self.verify(frame,myModle_list,myModle_data,channel_id,schedule_list,result_list)
|
|
|
|
#分析图片放入内存中
|
|
channel_data[3].append(img)
|
|
channel_data[5] += 1 #帧序列加一
|
|
#print(self.verify_list[channel_id][5])
|
|
if channel_data[5] > self.icout_max:
|
|
channel_data = 0
|
|
if len(channel_data[3]) > self.buflen: # 保持缓冲区大小---缓冲区可以用来保持录像
|
|
channel_data[3].pop(0)
|
|
#self.logger.debug("drop one frame!")
|
|
channel_data[4] = new_frame #一直更新最新帧
|
|
|
|
#验证result_list -是否触发报警要求
|
|
for i in range(len(result_list)):
|
|
result = result_list[i]
|
|
proportion = proportion_lsit[i]
|
|
|
|
count_one = float(sum(result)) #1,0 把1累加的和就是1的数量
|
|
ratio_of_ones = count_one / len(result)
|
|
#self.logger.debug(result)
|
|
if ratio_of_ones >= proportion: #触发报警
|
|
model_name = myModle_data[i][7]
|
|
w_s_count = warn_save_count[i]
|
|
buffer_count = channel_data[5]
|
|
self.save_warn(model_name,w_s_count,buffer_count,channel_data[3],cap.width,cap.height,
|
|
channel_id,myDBM,FPS,fourcc)
|
|
self.send_warn()
|
|
#更新帧序列号
|
|
warn_save_count[i] = buffer_count
|
|
#结果记录要清空
|
|
for i in range(len(result)):
|
|
result[i] = 0
|
|
|
|
# end_time = time.time() # 结束时间
|
|
# print(f"Processing time: {end_time - start_time} seconds")
|
|
# 本地显示---测试使用
|
|
# cv2.imshow('Frame', img)
|
|
# if cv2.waitKey(1) & 0xFF == ord('q'):
|
|
# break
|
|
#结束线程
|
|
cap.release()
|
|
cv2.destroyAllWindows()
|
|
|
|
def save_warn(self,model_name,w_s_count,buffer_count,buffer,width,height,channnel_id,myDBM,FPS,fourcc):
|
|
'''
|
|
保存报警信息
|
|
:param model_name: 模型名称，如人员入侵
|
|
:param w_s_count: 报警已存储的最新帧序列
|
|
:param buffer_count: 当前视频缓冲区的最新帧序列
|
|
:param buffer: 视频缓存区
|
|
:param width: 视频画面的width
|
|
:param height: 视频画面的height
|
|
:param channnel_id: 视频通道ID
|
|
:return: ret 数据库操作记录
|
|
'''
|
|
now = datetime.datetime.now() # 获取当前日期和时间
|
|
current_time_str = now.strftime("%Y-%m-%d_%H-%M-%S")
|
|
filename = f"{channnel_id}_{current_time_str}"
|
|
#保存视频
|
|
video_writer = cv2.VideoWriter(f"model/warn/{filename}.mp4", fourcc, FPS, (width, height))
|
|
if not video_writer.isOpened():
|
|
print(f"Failed to open video writer for model/warn/{filename}.mp4")
|
|
return False
|
|
ilen = len(buffer)
|
|
istart = 0;
|
|
iend = ilen
|
|
if buffer_count < w_s_count or (buffer_count-w_s_count) > ilen: #buffer_count重置过
|
|
#buffer区，都保存为视频
|
|
istart = 0
|
|
else:#只取差异的缓冲区大小
|
|
istart = ilen - (buffer_count-w_s_count)
|
|
for i in range(istart,iend):
|
|
video_writer.write(buffer[i])
|
|
video_writer.release()
|
|
#保存图片
|
|
ret = cv2.imwrite(f"model/warn/{filename}.png",buffer[-1])
|
|
if not ret:
|
|
print("保存图片失败")
|
|
return False
|
|
#保存数据库
|
|
strsql = (f"INSERT INTO warn (model_name ,video_path ,img_path ,creat_time,channel_id ) "
|
|
f"Values ('{model_name}','model/warn/{filename}.mp4','model/warn/{filename}.png',"
|
|
f"'{current_time_str}','{channnel_id}');")
|
|
ret = myDBM.do_sql(strsql)
|
|
return ret
|
|
|
|
|
|
def send_warn(self):
|
|
'''发送报警信息'''
|
|
pass
|
|
|
|
def save_frame_to_video(self):
|
|
'''把缓冲区中的画面保存为录像'''
|
|
pass
|
|
|
|
def start_work(self,channel_id=0):
|
|
'''算法模型是在后台根据画面实时分析的
|
|
1.布防开关需要触发通道关闭和开启
|
|
2.布防策略的调整也需要关闭和重启工作
|
|
'''
|
|
if channel_id ==0:
|
|
strsql = "select id,ulr,type from channel where is_work = 1;" #执行所有通道
|
|
else:
|
|
strsql = f"select id,ulr,type from channel where is_work = 1 and id = {channel_id};" #单通道启动检测线程
|
|
datas = mDBM.do_select(strsql)
|
|
for data in datas:
|
|
img_buffer = []
|
|
img = None
|
|
icout = 0 #跟img_buffer对应，记录进入缓冲区的帧序列号
|
|
run_data = [data[1],data[2],True,img_buffer,img,icout]
|
|
self.verify_list[data[0]] = run_data #需要验证重复情况#?
|
|
th_chn = threading.Thread(target=self.dowork_thread, args=(data[0],)) #一个视频通道一个线程，线程句柄暂时部保留
|
|
th_chn.start()
|
|
|
|
|
|
def stop_work(self,channel_id=0):
|
|
'''停止工作线程，0-停止所有，非0停止对应通道ID的线程'''
|
|
if channel_id ==0: #所有线程停止
|
|
for data in self.verify_list:
|
|
data[2] = False
|
|
del data[3]
|
|
time.sleep(2)
|
|
self.verify_list.clear()
|
|
else:
|
|
data = self.verify_list[channel_id]
|
|
data[2] = False
|
|
del data[3]
|
|
time.sleep(1)
|
|
del self.verify_list[channel_id]
|
|
|
|
#print(f"Current working directory (ModelManager.py): {os.getcwd()}")
|
|
mMM = ModelManager()
|
|
def test():
|
|
buffer = [np.zeros((480, 640, 3), dtype=np.uint8) for _ in range(60)] # 示例帧列表
|
|
FRAME_WIDTH = 640 # 根据你的图像尺寸设置
|
|
FRAME_HEIGHT = 480 # 根据你的图像尺寸设置
|
|
FPS = myCongif.get_data("verify_rate") # 你的视频帧率
|
|
fourcc = cv2.VideoWriter_fourcc(*'mp4v') # 使用 mp4 编码
|
|
now = datetime.datetime.now() # 获取当前日期和时间
|
|
current_time_str = now.strftime("%Y-%m-%d_%H-%M-%S")
|
|
filename = f"{2}_{current_time_str}.mp4"
|
|
#filename = "saved_video.mp4"
|
|
print(filename)
|
|
# 保存视频
|
|
video_writer = cv2.VideoWriter(filename, fourcc, FPS, (FRAME_WIDTH, FRAME_HEIGHT))
|
|
if not video_writer.isOpened():
|
|
print(f"Failed to open video writer for filename")
|
|
return False
|
|
for frame in buffer:
|
|
video_writer.write(frame)
|
|
video_writer.release()
|
|
# 保存图片
|
|
ret = cv2.imwrite("saved_frame.jpg", buffer[-1])
|
|
if ret:
|
|
print("保存图片成功")
|
|
else:
|
|
print("保存图片失败")
|
|
return False
|
|
|
|
if __name__ == "__main__":
|
|
#mMM.start_work()
|
|
# model = ModelManager()._import_model("", "../model/plugins/RYRQ/RYRQ_Model_ACL.py")
|
|
# model.testRun()
|
|
test()
|
|
|
|
|
|
|
|
|