You Only Look Once: Unified, Real-Time Object Detection

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This video is about You Only Look Once: Unified, Real-Time Object Detection
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Great show and unbelievable explanation. Thank you for your tremendous effort.

engineer.alqupatimohammed
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love the "toilet" regonition at 11:17😂

ΦιλιπποςΚουμπάρος
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Great presentation: clear, thoughtful and fun!

beteaberra
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you've reduced me a lot of time. Thank you!

quang-namvu
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The video takes me to another dimension hahaha

hamzakholti-ej
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*THAT IT IS AN EXCELENT SOFTWARE FOR USING IN "DASH CAMERAS" FOR CAPTURING AND VIDEO RECORDING PEOPLE AROUND YOUR BELONGINGS OR CAR KEYING YOUR CAR*

zuam
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How it's works at Inference time. I am not able to get it. Each output with give range between -1 to 1. Now how can I bring it BB into original image.? Kindly tell me the mathematics, how to compute it's? This is where I stuck. Help me🙏

sahil-
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how does a grid cell predict a box that is bigger than itself?

alexdalton
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2:30 .... Wow... !
[Edited] 11:50 .... Awe-Inspiring !

crabsynth
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Is it possible to integrate the YOLO algorithm with arduino or raspberry pi using a webcam?

apurbaroy
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sir, where can i get complete code....pls help i am working on this project

sherlockskey
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Thank you for the video.
I did not get "NMS and threshold detections"
could you explain a bit more?

hyunseokjeong
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I just Had one question When we know where the ground-truth centre of the object is why can't we scan just that area or nearby area why do we scan the whole image??

vikrantchoudhary
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When you say "dont adjust the class probabilities or coordinates" if there are no object centered in that grid cell, you mean simply pass on that cell and move to next, right? So you only backpropagate the NN when there is an object centered in that cell. Am I getting it right?

huawei
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2:43 more than 105 % sure that there is a person when there is not.

dominiksulzer
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why they use 2 bounding boxes for 1 cell? For localization 1 bounding box for each cell should be enough or? In OpenCv for example the Object Detection draws only 1 bounding box around an object.

Dennis-nntc
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This new method is going to be the future of object detection... So fast and accurate. Is he running on a windows or linux pc ??

manojguha
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Hey I'm new to the field of Convolutional Neural Network.
I have a presentation in school on YOLO and I need some help.
Can someone please explain how the output of the convolution layer works.
The input to the first convolution network is a 448*448*3 tensor. And it's output is a 224*224*64 tensor on a filter of 7*7.
I understand that the depth is 64 because of 64 different filters (features)
Thank you!

dudeking
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YOLO is so fucking hilarious.. it's a big "fuck you" to all these kind of scientists who see things a bit too seriously. I love these kind of things and it gets me motivated in the science field, given that science for most part is very dry and it easily makes you depressed. Just thinking about the fact that "YOLO" will probably be mentioned in my masters thesis is so good :D 0:01 That picture is top notch.

nano
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103% probability that its a person. Something fishy in your calculation

TheVasanthbuddy