打开一个新文件,将其命名为 video_object_detection.py ,并插入以下代码: video_name='12.mkv' prototxt='MobileNetSSD_deploy.prototxt.txt' model_path='MobileNetSSD_deploy.caffemodel' confidence_ta=0.2 #initializethelistofclasslabelsMobileNetSSDwastrainedto #detect,thengenerateasetofboundingboxcolorsforeach...
importorg.opencv.core.Mat;importorg.opencv.core.CvType;importorg.opencv.core.Size;importorg.opencv.core.Rect;importorg.opencv.core.Point;importorg.opencv.core.Scalar;importorg.opencv.imgproc.Imgproc;publicclassVideoObjectRecognition{publicstaticvoidmain(String[]args){// ... [前面的代码]Matframe=n...
我们插入一行: ap.add_argument("-v","--video", required=True, help="path to Caffe video file") 然后在初始化视频流时,修改为: vs =cv2.VideoCapture(args["video"]) 运行命令修改为 python real_time_object_detection.py -p ./MobileNetSSD_deploy.prototxt.txt -m ./MobileNetSSD_deploy.caffemode...
Execute with image or video file: $ example_dnn_object_detection--config=[PATH-TO-DARKNET]/cfg/yolo.cfg--model=[PATH-TO-DARKNET]/yolo.weights--classes=object_detection_classes_pascal_voc.txt--width=416--height=416--scale=0.00392--input=[PATH-TO-IMAGE-OR-VIDEO-FILE]--rgb 参考这个 方法...
AI 研习社按:本文为雷锋字幕组编译的技术博客,原标题 Real-time and video processing object detection using Tensorflow, OpenCV andDocker,作者为 Léo Beaucourt 。 翻译 | 于志鹏 徐普 校对 | 陶玉龙 整理 | 孔令双 在本文中,我将介绍如何在 Docker容器中使用 Tensorflow Object-detectionAPI来执行实时(网络摄...
''' import numpy as np import cv2 cap = cv2.VideoCapture(0) # take first frame of the video ret,frame = cap.read() # setup initial location of window r,h,c,w = 300,200,400,300 # simply hardcoded the values track_window = (c,r,w,h) roi = frame[r:r+h, c:c+w] hsv_roi...
importcv2# Load the cascade classifier detection objectcascade= cv2.CascadeClassifier("haarcascade_eye.xml")# Turn on the web cameravideo_capture= cv2.VideoCapture(0)# Read data from the web camera (get the frame)_, frame = video_capture.read()# Convert t...
在本文中我们将学习如何扩展原有的目标检测项目,使用深度学习和 OpenCV 将应用范围扩展到实时视频流和视频文件中。这个任务会通过VideoStream类来完成。 深度学习目标检测教程:http://www.pyimagesearch.com/2017/09/11/object-detection-with-deep-learning-and-opencv/ ...
本文还展示了如何使用《Building a Real-Time Object Recognition App with Tensorflow and OpenCV》中的原始 Python 脚本执行多进程视频处理。 原文链接:https://towardsdatascience.com/real-time-and-video-processing-object-detection-using-tensorflow-opencv-and-docker-2be1694726e5...
要学习OpenCV的更多知识,可以参考以下教程:loading -video-python-opencv-tutorial 4. 使用 Python 与 OpenCV 进行颜色检测 我们想做的一件事情就是检测并跟踪某种颜色的物体。为此,我们必须理解一点OpenCV是如何翻译颜色的。 关于颜色检测,Henri Dang写了一篇...