#load pipe for data transmittion to the process _plot_image(frame_np_new)ĭef _init_(self, rtsp_url, width, height):

# here, I'm sending fetching the frame currently being handled by bufferless_cameraįrame_nd_orig = mx.nd.array(cv2.cvtColor(frame_np_orig, cv2.COLOR_BGR2RGB)).astype('uint8')įrame_nd_new, frame_np_new = .ansform_test(frame_nd_orig, short=600)įrame_nd_new = frame_nd_new.as_in_context(ctx)Ĭlass_IDs, scores, bboxes = net(frame_nd_new)įrame_np_new = _plot_bbox(frame_np_new, bboxes, scores, class_IDs, thresh=0.8, class_names=net.classes) Net = gcv.model_zoo.get_model('faster_rcnn_resnet50_v1b_coco', pretrained=True, ctx=ctx)Ĭam = bufferless_camera('rtsp://camera_IP_address:port_number', 640, 480) The code I have is something like this: import time Whenever the object detection finishes analyzing a frame, it requests the frame currently being grabbed by the camera_bufferless process. The idea is that I have a process (say, camera_bufferless), parallel to object detection, constantly grabbing frames from the camera. I first tried setting the buffer length by: cap = cv2.VideoCapture('rtsp://camera_IP_address:port_number')

This happens automatically when using a camera connected through USB, but with a RTSP stream the frames are buffered, so after completing the detection on frame 01 the program proceeds to analyze frame 02, which I want to avoid. After the elaboration of frame 01 is completed the detection jumps to the frame currently streamed, which is #06. In the meanwhile, the camera gets other 4 frames, from 02 to 05, which should be ignored. 본 문서는 Ubuntu 환경에서 OpenCV 4.4를 빌드하는 방법에 대하여 설명하는 문서이다.So, basically the program should get the first frame and analyze it.

Pencv python ffmpeg