MaxML
MaxML
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HOW YOLO V3 WORKS?
In this video I will focus on how Yolo algorithms(mainly yolov3) work.
So what is happening between feeding the image to the network and getting the detections.
I will also share with you the tool that I created that is an interactive notebook,
that allows you to explore this alogrithm on your own.
Link to the repository:
github.com/MaxMLgh/YOLO_tutorial
Table of context:
0:00 Intro and installation
3:11 How back-bone feature extractor works
11:30 From feature maps to detection
23:47 How does YOLO picks the right detections
31:13 Tips for better detection
37:49 Which implementation of YOLO to use
Переглядів: 21 627

Відео

FIRST GAME STEERED WITH GESTURES!!! YOU CAN PLAY IT TOO!!!
Переглядів 3823 роки тому
In this video I will show you the game that I created that is STEERED WITH GESTURES ONLY. If you have a camera and python=3.6 or higher YOU CAN PLAY IT TOO. The installation is super easy. Link to github repository: github.com/MaxMLgh/Space_game_gesture_steering The game is made in python library pygame and it uses the newest technology form google MEDIAPIPE. It uses deep neural network with ot...
Central limit theorem (part 3): Graphical interpretation for standard deviation of sample means
Переглядів 1253 роки тому
Easy to understand visual explanation of formula for standard deviation of sample means. Link to correlation and covariance tutorial: ua-cam.com/video/VTWq4YUs93Y/v-deo.html Link to previous video - CENTRAL LIMIT THEOREM: proof of formula for standard deviation of sample means: ua-cam.com/video/ZolDtJv9c0o/v-deo.html Link to previous video - CENTRAL LIMIT THEOREM: simple visual explanation ua-c...
Central Limit theorem (part 2): Proof of formula for standard deviation of sample means
Переглядів 1573 роки тому
Easy to understand explanation of formula for standard deviation of sample means. Link to correlation and covariance tutorial: ua-cam.com/video/VTWq4YUs93Y/v-deo.html Link to previous video CENTRAL LIMIT THEOREM: simple visual explanation Link to next video - GRAPHICAL PROOF of standard deviation of sample means: pass Link to online python notebook: pass (click on the link, then 'runtime' - 'ru...
CENTRAL LIMIT THEOREM: simple visual explanation
Переглядів 4303 роки тому
Easy to understand visual step by step explanation of the Central limit theorem. One of the most important concepts in statistics. It explains why we so often see normal distribution in nature. Link to correlation and covariance tutorial: ua-cam.com/video/VTWq4YUs93Y/v-deo.html Link to next video - standard deviation of sample means: pass Link to online python notebook: pass (click on the link,...
CORRELATION AND COVARIANCE: SIMPLE VISUAL EXPLANATION OF USEFUL COEFFICIENT IN STATISTICS, ML, AI
Переглядів 9233 роки тому
Easy to understand visual step by step explanation of Correlation (linear, Pearson coefficient) and Covariance. Tools very often used in math, statistics, machine, learning and artificial intelligence. Interactive graphs I used in a video: colab.research.google.com/drive/1KAWv3kmP9T8zeBM9adrN6QlFrNrj0254?usp=sharing Timestamps: 0:00 - Intro and test tool 1:16 - Basic idea and visual estimation ...

КОМЕНТАРІ

  • @vishnu9134
    @vishnu9134 4 місяці тому

    ❤❤❤

  • @soriven5794
    @soriven5794 10 місяців тому

    Квадратик видео... Oh, squared!

  • @nemonovich
    @nemonovich Рік тому

    Thanks a lot! One of the best explanation ❤

  • @aeaxao9973
    @aeaxao9973 Рік тому

    Great explained! Thanks

  • @xl0xl0xl0
    @xl0xl0xl0 Рік тому

    Excellent explanation. I really like your style and the level you picked.

  • @mengwenwang7592
    @mengwenwang7592 Рік тому

    I got you! really good video to understand the formula!

  • @vipingautam9501
    @vipingautam9501 Рік тому

    at 12:06 you mentioned 255( 3 predictions 4+1+80). Could you explain a bit how did you get these 3 predictions after performing convolution over your feature maps..

  • @Dayisa29
    @Dayisa29 Рік тому

    Oh this Video helped me a lot to understand, Thanks!!!

  • @shabbirahammed4596
    @shabbirahammed4596 2 роки тому

    so nice...

  • @cvbasics
    @cvbasics 2 роки тому

    Hey Nice video. Really informative. You have not added the paint image to the GitHub repository. Please add

  • @Ip_man22
    @Ip_man22 2 роки тому

    Awesome!

  • @venkatpr
    @venkatpr 2 роки тому

    Super man.... Waiting more videos like this

  • @ytohustler
    @ytohustler 3 роки тому

    awesome explanation. really appreciated.

  • @luiscao7241
    @luiscao7241 3 роки тому

    Thanks

  • @RRP3168
    @RRP3168 3 роки тому

    You are awesome! Very well explained!

  • @hazemabolholl705
    @hazemabolholl705 3 роки тому

    Thank you for a wonderful video! I have an equation here in the last convolutional for the detection layer you have 1*1*18 how does it come? thank you

  • @arielherold
    @arielherold 3 роки тому

    Great. Just there is no comparison of V3 vs. V4... still, very good!

  • @cristiancorches74
    @cristiancorches74 3 роки тому

    So much good stuff in this video, it's just amazing. Thank you a lot! :D

  • @zubairsk1624
    @zubairsk1624 3 роки тому

    Hello man i hope you are okay im asking Is there any way to increase the accuracy of yolo v4 maybe we add more layers or something else?

  • @hoangtung8464
    @hoangtung8464 3 роки тому

    thanks you so much! This was really helpful

  • @harikrishnasamy1551
    @harikrishnasamy1551 3 роки тому

    I'm a beginner in object detection, this is really helped me lot....expecting more for people detection and gender identification

  • @ranam
    @ranam 3 роки тому

    amazing friend have never seen an tutorial like this i am very greedy now to copy this tutorial to my channel you have given me the wisdom of yolo so i am just admiring it . copying is an shame full act so i will surely subscribe and tell my subscriber to follow this cool guy on UA-cam you are awesome i am so excited thank you for this wonderful tutorial

  • @skaayth8366
    @skaayth8366 3 роки тому

    Amazing, mostly all the videos are just yolo in 5 minutes. But this was really helpful for me , thanks a lot.

  • @KarolMajek
    @KarolMajek 3 роки тому

    Nice tutorial!

  • @manandoshi7640
    @manandoshi7640 3 роки тому

    Nicely explained

  • @leszekalbrzykowski64
    @leszekalbrzykowski64 3 роки тому

    Good job Max!

  • @annalewkowicz9030
    @annalewkowicz9030 3 роки тому

    My average error was 0.25. Amazing video, keep up your work!

  • @TheKuba1122
    @TheKuba1122 4 роки тому

    Superb! Wating for more!

  • @morewind
    @morewind 4 роки тому

    keep future topics narrow. dig in to the basics

  • @cybfreak
    @cybfreak 4 роки тому

    Good job, really interesting and helpful. Hope to see more.