Measure size of objects with image | Computer Vision | Opencv with Python | Pyresearch

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foreign [Music] so let's going on the uh today uh we are getting the one report simple creating one report you copy this link and go to the your terminal and paste also go to the CD in document folder upgrade here we not need to necessary the requirements files just only python and a python platform and opencv Library so you get the result they just run this command I think my name is it will be changed I will update it so I'm also code updated here uh uh code file and two things will be updated one pictures and then one script it is very simple and basic technique of the with computer vision best a lot of people's want to detect the object size so a lot of people cannot be achieved it is very complex so this project provide a script read image best on Dimension reference find object of the dimension uh other objects in a sense the reference must object to left most object that sends in Sample image you can also see the simple image uh in simple image 2.2 centimeters you will let me know here you can see the IM image 2 centimeter by 2 centimeter and second reference object okay so uh I also creating the some Theory I'm gonna need to new file only just read file so you can see the countenator shadow reference drop okay I will also showing you the how to and also just trip by the opencv python command and numpy comma no need necessary a lot of libraries and algorithm technique I will also show you how to algorithm technique will be used how to read the file gray converted into the grayscal object segmentation different object and the computer results so do not worry I will this report will be created will be simply so I have already code so open the file and pictures you can see here the result and here the samples okay so let's move on here the example number two okay I will use this picture second number so first of all you can see the here this is the image size underscore object okay uh sci-fi you can see the numpy CV2 library then you function need to convert in the image uh also going to the red path of the image and uh read image process pre-processing you can get the convert into the grayscale find the counters how much uh count the object okay so the counter left right and keep this comma left right comma counter different object and then you can see the remove counter with a large number enough uh 100 greater than 100 okay refresh the object uh two by two centimeter so you can see the tool by two centimeter of the different object so draw the remaining counter you can see the also remaining Counting so let's move on how to work okay I have clearing all so going to my desktop directory object size I will show you three files one image folder then python file python version you can see that's python version 3.9.19 okay do not be confused and you can see also open CV version oh import sorry import CV2 CV2 dot underscore version 4.6.0 okay so after you see the versions and platform version just run the python size credit score object dot pi so you can get the result uh python 4.1 centimeter 1.8 centimeter thirteen point the height span and you can see the object different object is two by two rectangular object so I hope you understood getting my Royal points uh I hope it is will very be simple I hope you like it please support our channel for more getting information updates any kind of computer confusion you can comment down [Music] foreign
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Channel: Pyresearch
Views: 13,795
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Keywords: Education, Pyresearch, Pyresearch - YouTube, how to Grow, money, facebook app, facebook, how to set goal, mask rcnn, mask r-cnn, faster rcnn, rcnn, video mask rcnn, mask rcnn github, mask rcnn pytorch, mask rcnn tutorial, real time mask rcnn, deep learning, machine learning, mask, r-cnn, mask_rcnn, mask-rcnn, maskrcnn, artificial intelligence, faster_rcnn, computer vision, image recognition, ai, segmentation, object detection, image processing, cnn, Deep Learning, opencv, real time
Id: 4L5jF1Dkfxw
Channel Id: undefined
Length: 6min 18sec (378 seconds)
Published: Thu Jan 05 2023
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