video-tracking

How to detect an object real time and track it automatically, instead of user having to draw a bounding box around the object to be tracked?

由 倾然丶 夕夏残阳落幕 提交于 2021-02-19 07:37:26
问题 I have the following code where the user can press p to pause the video, draw a bounding box around the object to be tracked, and then press Enter (carriage return) to track that object in the video feed: import cv2 import sys major_ver, minor_ver, subminor_ver = cv2.__version__.split('.') if __name__ == '__main__' : # Set up tracker. tracker_types = ['BOOSTING', 'MIL','KCF', 'TLD', 'MEDIANFLOW', 'GOTURN', 'MOSSE', 'CSRT'] tracker_type = tracker_types[1] if int(minor_ver) < 3: tracker = cv2

Occlusion with camshift

由 自作多情 提交于 2021-02-19 07:26:50
问题 I am working on object tracking by camshift algorithm. For the time being I am using the inbuilt opencv code wherein I have trouble dealing with occlusion. hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV) mask = cv2.inRange(hsv, np.array((0., 60., 32.)), np.array((180., 255., 255.))) prob = cv2.calcBackProject([hsv], [0], self.hist, [0, 180], 1) cv2.imshow('prob_0',prob) prob &= mask cv2.imshow('prob',prob) term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 ) track_box,

Occlusion with camshift

由 馋奶兔 提交于 2021-02-19 07:24:30
问题 I am working on object tracking by camshift algorithm. For the time being I am using the inbuilt opencv code wherein I have trouble dealing with occlusion. hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV) mask = cv2.inRange(hsv, np.array((0., 60., 32.)), np.array((180., 255., 255.))) prob = cv2.calcBackProject([hsv], [0], self.hist, [0, 180], 1) cv2.imshow('prob_0',prob) prob &= mask cv2.imshow('prob',prob) term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 ) track_box,

Simple OpenCV project - detecting and tracking a tennis ball

由 生来就可爱ヽ(ⅴ＜●) 提交于 2019-12-19 04:08:28
问题 I have a project where I need to use OpenCV to detect an object (Tennis Ball) on a webcam, and for bonus credit, track it when I roll it across the table. I haven't had much luck finding info on this, since I'm using OpenCV 2.4, C++, and a lot of information is in the older OpenCV version. I've read a lot of about different ways to do it, but I just don't know how to implement it into my code. Any help would be appreciated, especially on how to integrate a detection/tracking function into my

Unable to run Tracking on Open CV 3.4.1 on Python 3.6.6

由 …衆ロ難τιáo~ 提交于 2019-12-12 13:51:01
问题 I tried running tracking using open CV on python 3.6.6, but it shows: AttributeError: module 'cv2' has no attribute 'TrackerKCF_create' I also tried the python 2.7 API, but the same result: AttributeError: module 'cv2' has no attribute 'Tracker_create' The Open CV version is 3.4.1. Any idea how to resolve this? Thanks in advance. Edit: The problem is different to the one asked here. I tried this but it wasn't working for me. However, I solved it and I have given a solution below. 回答1: The

Color tracking using EMGUcv

由 ￣綄美尐妖づ 提交于 2019-12-10 09:45:59
问题 I am trying to make an colored object tracker which uses a binary image and blob detector to follow the target sort of like this: https://www.youtube.com/watch?v=9qky6g8NRmI . However I can not figure out how the ThresholdBinary() method work and if it is even the right one. Here is a relevant bit of the code: cam._SmoothGaussian(3); blobDetector.Update(cam); Image<Bgr,byte> binaryImage = cam.ThresholdBinary(new Bgr(145,0,145),new Bgr(0,0,0)); Image<Gray,byte> binaryImageGray = binaryImage

Color tracking using EMGUcv

由 烂漫一生 提交于 2019-12-06 02:54:50
I am trying to make an colored object tracker which uses a binary image and blob detector to follow the target sort of like this: https://www.youtube.com/watch?v=9qky6g8NRmI . However I can not figure out how the ThresholdBinary() method work and if it is even the right one. Here is a relevant bit of the code: cam._SmoothGaussian(3); blobDetector.Update(cam); Image<Bgr,byte> binaryImage = cam.ThresholdBinary(new Bgr(145,0,145),new Bgr(0,0,0)); Image<Gray,byte> binaryImageGray = binaryImage.Conver<Gray,byte>(); blobTracker.Process(cam, binaryImageGray); foreach (MCvBlob blob in blobTracker) {
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