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Mask RCNN Tutorial Training Pothole Segmentation | OpenCV Python | Computer Vision 2020 Part 3
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Mask RCNN Tutorial #3 - Training Mask RCNN for Pothole Segmentation - Dataset & Annotation - We use OpenCV and Python for our final implementation.
Hey guys and welcome back, in the next few videos, I’m going to show you how to build your own pot-hole detector using Mask RCNN. Now Mask RCNN is particularly useful for this application because you are able to quantify the amount of pixels belong the pothole thus allowing you to measure how big and how bad the pothole is. In most countries potholes and sink holes are quite a huge problem and costs each countries more than a billion dollars a year to fix.
Now imagine if you had a scout vehicle or drone that is able to automatically geolocate, these potholes. They would be able to measure them using image data to then determine if the road needs to be fixed or even better to predict when and where the next pot hole will occur.
So in this lecture, we are going to start with downloading the dataset. You also have the option to scrape your pot hole image dataset from google image search just like how we did in the Yolo V3 course. We perform mask rcnn pytorch tutorial in this lecture.
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Geeky Bee AI Pvt Ltd
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Support Augmented Startups on Patreon
Chat to us on Discord
Interact with us on Facebook
Check my latest work on Instagram
Learn Advanced Tutorials on Udemy
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To learn more on Artificial Intelligence, Augmented Reality IoT, Deep Learning FPGAs, Arduinos, PCB Design and Image Processing then check out
Please Like and Subscribe for more videos :)
Hey guys and welcome back, in the next few videos, I’m going to show you how to build your own pot-hole detector using Mask RCNN. Now Mask RCNN is particularly useful for this application because you are able to quantify the amount of pixels belong the pothole thus allowing you to measure how big and how bad the pothole is. In most countries potholes and sink holes are quite a huge problem and costs each countries more than a billion dollars a year to fix.
Now imagine if you had a scout vehicle or drone that is able to automatically geolocate, these potholes. They would be able to measure them using image data to then determine if the road needs to be fixed or even better to predict when and where the next pot hole will occur.
So in this lecture, we are going to start with downloading the dataset. You also have the option to scrape your pot hole image dataset from google image search just like how we did in the Yolo V3 course. We perform mask rcnn pytorch tutorial in this lecture.
--------------------------------------------------------------
Geeky Bee AI Pvt Ltd
------------------------------------------------------------
Support Augmented Startups on Patreon
Chat to us on Discord
Interact with us on Facebook
Check my latest work on Instagram
Learn Advanced Tutorials on Udemy
------------------------------------------------------------
To learn more on Artificial Intelligence, Augmented Reality IoT, Deep Learning FPGAs, Arduinos, PCB Design and Image Processing then check out
Please Like and Subscribe for more videos :)
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