commit

ec/tortmp.py

@@ -0,0 +1,73 @@
+import cv2
+import time
+import subprocess as sp
+import multiprocessing
+
+
+class stream_pusher(object):
+    def __init__(self, rtmp_url=None, raw_frame_q=None):  # 类实例化的时候传入rtmp地址和帧传入队列
+        self.rtmp_url = rtmp_url
+        self.raw_frame_q = raw_frame_q
+
+        fps = 20  # 设置帧速率
+        # 设置分辨率
+        width = 1920  # 宽
+        height = 1080  # 高
+
+        # 设置FFmpeg命令文本
+        self.command = ['ffmpeg',
+                        '-y',
+                        '-f', 'rawvideo',
+                        '-vcodec', 'rawvideo',
+                        '-pix_fmt', 'bgr24',
+                        '-s', "{}x{}".format(width, height),
+                        '-r', str(fps),
+                        '-i', '-',
+                        '-c:v', 'libx264',
+                        '-pix_fmt', 'yuv420p',
+                        '-preset', 'ultrafast',
+                        '-f', 'flv',
+                        self.rtmp_url]
+
+    # 向服务器推送
+    def push_frame(self):
+
+        # 配置向os传递命令的管道
+        p = sp.Popen(self.command, stdin=sp.PIPE)
+
+        while True:
+            if not self.raw_frame_q.empty():  # 如果输入管道不为空
+                # 把帧和相关信息从输入队列中取出
+                frame = self.raw_frame_q.get()
+
+                # 把内容放入管道，放入后有os自己去执行
+                p.stdin.write(frame.tostring())
+            else:
+                time.sleep(0.01)
+
+    # 启动运行
+    def run(self):
+        # 定义一个子进程
+        push_frame_p = multiprocessing.Process(target=self.push_frame, args=())
+        push_frame_p.daemon = True  # 把子进程设置为daemon方式
+        push_frame_p.start()  # 运行子进程
+
+
+if __name__ == '__main__':
+
+    cap = cv2.VideoCapture("rtsp://admin:hk123456@192.168.1.65:554")
+
+    rtmpUrl = "rtmp://127.0.0.1:8554/video"  # 用vcl等直播软件播放时，也用这个地址
+    raw_q = multiprocessing.Queue()  # 定义一个向推流对象传入帧及其他信息的队列
+
+    my_pusher = stream_pusher(rtmp_url=rtmpUrl, raw_frame_q=raw_q)  # 实例化一个对象
+    my_pusher.run()  # 让这个对象在后台推送视频流
+    while True:
+        _, raw_frame = cap.read()
+
+        if not raw_q.full():  # 如果队列没满
+            raw_q.put(raw_frame)  # 送入队列
+        if cv2.waitKey(1) == ord('q'):  # q to quit
+            raise StopIteration
+    cap.release()
+    print('finish')

ec/tortsp copy.py

@@ -0,0 +1,45 @@
+# -*- coding:utf-8 -*-
+# @Time : 2021/11/4 10:17
+# @Author : JulyLi
+# @File : rtsp2.py
+# @Software: PyCharm
+
+import cv2
+
+import sys
+import json
+import subprocess as sp
+import signal
+import numpy as npbool
+#此处换为你自己的地址
+rtsp_url = 'rtsp://192.168.1.182:8554/video'
+cap = cv2.VideoCapture("rtsp://admin:hk123456@192.168.1.65:554")
+# Get video information
+fps = int(cap.get(cv2.CAP_PROP_FPS))
+width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+command = ['ffmpeg',
+               '-y',
+               '-f', 'rawvideo',
+               '-vcodec', 'rawvideo',
+               '-pix_fmt', 'bgr24',
+               '-s', "{}x{}".format(width, height),
+               '-r', str(fps),
+               '-i', '-',
+               '-c:v', 'libx265',
+               '-pix_fmt', 'yuv420p',
+               '-preset', 'ultrafast',
+               '-f', 'rtsp',
+               rtsp_url]
+p = sp.Popen(command, stdin=sp.PIPE)
+
+while (cap.isOpened()):
+    ret, frame = cap.read()
+    if not ret:
+        print("Opening camera is failed")
+        break
+    # frame = 你的图像处理的函数(frame)
+    p.stdin.write(frame.tostring())
+    cv2.imshow('img',frame)
+    if cv2.waitKey(1) == ord('q'):  # q to quit
+                    raise StopIteration

ec/tortsp.py

@@ -0,0 +1,109 @@
+# -*- coding:utf-8 -*-
+# @Time : 2021/11/4 10:17
+# @Author : JulyLi
+# @File : rtsp2.py
+# @Software: PyCharm
+
+import cv2
+import gi
+import sys
+import json
+import time
+import signal
+import numpy as np
+
+gi.require_version('Gst', '1.0')
+gi.require_version('GstRtspServer', '1.0')
+from gi.repository import Gst, GstRtspServer, GObject
+
+#cv2.namedWindow('video_realtime_face', cv2.WINDOW_NORMAL)
+
+def to_node(type, message):
+    # convert to json and print (node helper will read from stdout)
+    try:
+        print(json.dumps({type: message}))
+    except Exception:
+        pass
+    # stdout has to be flushed manually to prevent delays in the node helper communication
+    sys.stdout.flush()
+
+to_node("status", "Facerecognition started...")
+
+def shutdown(self, signum):
+    to_node("status", 'Shutdown: Cleaning up camera...')
+    quit()
+
+signal.signal(signal.SIGINT, shutdown)
+
+
+class SensorFactory(GstRtspServer.RTSPMediaFactory):
+    def __init__(self, **properties):
+        super(SensorFactory, self).__init__(**properties)
+        self.cap = cv2.VideoCapture("rtsp://admin:admin123@192.168.2.190:554/sub")
+        # self.cap = cv2.VideoCapture("shmsrc socket-path=/tmp/foo2 ! video/x-raw, format=BGR ,width=1920,height=1080,framerate=30/1 ! videoconvert ! video/x-raw, format=BGR ! appsink")
+        #self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
+        #self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
+        self.number_frames = 0
+        self.fps = 30.0
+        self.duration = 1 / self.fps * Gst.SECOND  # duration of a frame in nanoseconds
+        self.launch_string = 'appsrc name=source is-live=true block=true format=GST_FORMAT_TIME ' \
+                             'caps=video/x-raw,format=BGR,width=1920,height=1080,framerate=30/1 ' \
+                             '! videoconvert ! video/x-raw,format=I420 ' \
+                             '! x264enc speed-preset=ultrafast tune=zerolatency threads=4 ' \
+                             '! rtph264pay config-interval=1 name=pay0 pt=96'
+
+    def on_need_data(self, src, lenght):
+        if self.cap.isOpened():
+            ret, frame = self.cap.read()
+            if ret:
+                #cv2.imshow("video_realtime_face", frame)
+                #if cv2.waitKey(1) & 0xFF == ord('q'):
+                #    return
+                data = frame.tostring()
+                buf = Gst.Buffer.new_allocate(None, len(data), None)
+                buf.fill(0, data)
+                buf.duration = self.duration
+                timestamp = self.number_frames * self.duration
+                buf.pts = buf.dts = int(timestamp)
+                buf.offset = timestamp
+                self.number_frames += 1
+                retval = src.emit('push-buffer', buf)
+                print('pushed buffer, frame {}, duration {} ns, durations {} s'.format(self.number_frames,
+                                                                                       self.duration,
+                                                                                       self.duration / Gst.SECOND))
+                if retval != Gst.FlowReturn.OK:
+                    print(retval)
+
+    def do_create_element(self, url):
+        return Gst.parse_launch(self.launch_string)
+
+    def do_configure(self, rtsp_media):
+        self.number_frames = 0
+        appsrc = rtsp_media.get_element().get_child_by_name('source')
+        appsrc.connect('need-data', self.on_need_data)
+
+
+class GstServer(GstRtspServer.RTSPServer):
+    def __init__(self, **properties):
+        super(GstServer, self).__init__(**properties)
+        self.factory = SensorFactory()
+        self.factory.set_shared(True)
+        self.get_mount_points().add_factory("/test", self.factory)
+        self.attach(None)
+
+
+def run():
+    GObject.threads_init()
+    Gst.init(None)
+
+    server = GstServer()
+    rtsp_port_num = 8554
+    print("\n *** DeepStream: Launched RTSP Streaming at rtsp://localhost:%d/test ***\n\n" % rtsp_port_num)
+    loop = GObject.MainLoop()
+    loop.run()
+
+
+
+if __name__ == "__main__":
+    run()
+

main.py

@@ -271,5 +271,7 @@ if __name__ == '__main__':
     args.img_size = check_img_size(args.img_size)
     print(args)
 
-    with torch.no_grad():
+    with torch.no_grad(): 
+        print(torch.__version__)  #注意是双下划线
+        
         detect(args)