This is a wonderful explainer, thanks much for doing this 🙏 just getting to know more about YOLO and everything about object detection. Have been in a rabbit hole & watching multiple videos but no other video explains as succinctly as this one.
@sagnikroy64053 жыл бұрын
Thanks, sir. Your content helped a lot. Everybody just codes and moves on, but nobody tells how it happens. Thank You
@totally_insane81402 жыл бұрын
Very lucid explanation and easy to understand. Learned a lot from this video alone, thanks and keep it coming
@mohammadyahya782 жыл бұрын
The best explanation on YOLO so far. Thank you.
@conOC3 жыл бұрын
Simple, clear and instructible. Perfect to introduce to YOLO. SO GOOD
@rashibhardwaj506 Жыл бұрын
Amazing video. Thank you for explaining everything in just one video😃
@chidanandchidu5154 Жыл бұрын
Sir👏, your teaching is just😚
@tanmaythaker29052 жыл бұрын
Perfect and Crisp Explanation!
@rodghani Жыл бұрын
simple and clear easy to comprehend
@jaysoni78123 жыл бұрын
Amazing explanation with enough time thanks for saving my time
@anandks3642 ай бұрын
Excellent brother🎉
@sagarlekhak70992 ай бұрын
Great Explanation
@wcottee5 ай бұрын
I missed something...for training and testing we have images plus bounding boxes in our inputs. But the final model input is image only. How is this handled?
@priyathirumalainambi3 жыл бұрын
Thanks balaji. You taught really well. Pls upload more videos. will be more useful
@venupunna99403 жыл бұрын
really good simplification of yolo part1 ..... Thankyou
@departmentofbasicsciencesc569310 ай бұрын
very nicely explained thank you.
@harshdevmurari0072 жыл бұрын
nice explaination..........really good........
@srinivasand6174 жыл бұрын
Thanks much balaji. This will help me in my project preparations!
@BalajiSrinivasan254 жыл бұрын
Thank you 😊
@punithpuni9272 жыл бұрын
Sir I have a doubt please help me, you told that: 1) Output layer consists of both classification(pc, c1, c2, ...) and bounding box values(bx, by, bh, bw) i.e, its a regression. 2) At 2:45 you told that for ouput layer softmax activation is applied, but how can a softmax activation be applied on bounding box values which is regression. 3) Ok let me assume that as the width and height values of Image and grid will be between 0 and 1 their may be a chance of using softmax, because softmax activation output will be between 0 and 1, but Iam not sure about this. But at 17:05 you told that in some cases in output layer bounding box width and height can be more than 1, but softmax which is applied to output layer can give values between 0 and 1, then how can bounding box width and height get the value more than 1. 4) Softmax when used in output layer it will consider bounding box values also as classes, so how can softmax be used in output layer. Can you please solve my confusion.
@praveenreddy17673 жыл бұрын
I have doubt could you please clear this...Suppose consider 3 X3 Grid (grid1,2,3,4,5,6) and consider a image ie car is spread over 2 grids (5th and 6th grids ) For Grid 5th, Yolo through CNN operation identifies image and its bounding box and vector cordinates are predicted covering two (5th and 6th) grid cells . Now for 6th grid also same operation will be applied . So now after whole grids operation does.5th and 6th grid predictions combined through NMS and IOU to single prediction where image is exactly PRESENT ? Is my understanding correct?
@qaisjoker8306 Жыл бұрын
Thank you so much. You are a legend!.
@021bethineedilakshmideepak44 жыл бұрын
@Balaji Srinivasan, Sir you explained exactly like Andrew ng in a detailed manner. Happy to come to know about your channel
@prathmeshdeval8773 Жыл бұрын
Great explanation!
@krishnendudutta14654 жыл бұрын
Thnx balaji. Your content is awesome
@BalajiSrinivasan254 жыл бұрын
Thank you
3 жыл бұрын
Nice introduction, thank you
@jeffreyeiyike122 Жыл бұрын
please i want to know which tensor or vector of the images saved. all I see is the bounding box and classification and probability
@nikeshmali8506 Жыл бұрын
thanks for this explaintion
@kalidasuangadi40523 жыл бұрын
1. how anchor boxes are placed(initially). 2. what is the value of ground truth at the time of inferencing
@durgeshmishra9449 Жыл бұрын
Anchor boxes are defined by us by giving the y value as ground truth while training. During the inference time you don't have the ground truth right.
@jayeshbagul39613 жыл бұрын
Excelent it really benifical for me Thank you for your guidance
@manojkpr79344 жыл бұрын
Very well explained👌
@aashishrana93562 жыл бұрын
well explained , thank you much
@kollaanantraj36902 жыл бұрын
very well explained
@mehul4mak2 жыл бұрын
If y output only detect one object at a time then how come we can have multiple object detected in single frame at a time?
@nitinvedwal57862 жыл бұрын
is it for training or identification
@aiswaryajustin27283 жыл бұрын
Thanks for sharing ❤️
@lakshaydulani3 жыл бұрын
great work
@waqarmurtaza16114 жыл бұрын
WELL EXPLAINED...
@rohankishor30003 жыл бұрын
How program decides that how many Anchor boxes should be present for that particular image ?
@bruhm0ment7672 жыл бұрын
multiple anchor boxes are predicted for every object, YOLOv2 uses NMS (non maximal suppression through IoU (Intersection over Union)) and the Pc values to reduce down to a single anchor box for every object
@sikendrakumar90093 жыл бұрын
its is an awesome video and u explained everything quite well. plz make a list of videos about opencv and neural network working.
@DeepakSaini-sg3pq4 жыл бұрын
Great explanation thank you 😊 #Subscribed
@kishorejuniordeveloper43614 жыл бұрын
HI SIR , Excellent Explanation
@BalajiSrinivasan254 жыл бұрын
Thank you 😊
@kishorejuniordeveloper43614 жыл бұрын
@@BalajiSrinivasan25 Are You From TAMILNADU ...Sir???
@mazharmumbaiwala92442 жыл бұрын
any resources to the newer or better methods to solve the limitations of anchor boxes? what if my image has 100 instances of different objects to be detected, can someone point a link or mention them
@apurbaroy84113 жыл бұрын
Is it possible to integrate the YOLO algorithm with arduino or raspberry pi using a webcam?
@PraveenKumar-zf6ks4 жыл бұрын
Hi Balaji, could you pls upload RCNN and its types. Masked RCNN also?
@BalajiSrinivasan254 жыл бұрын
Sure, will upload them in a few days. Thanks for the suggestion 😊
@roobanrajr88663 жыл бұрын
Bro today yenaku interview coding test iruku ....object detection model built pana solirukanga help pana mudiyum ma ?I have one two day to complete the code
@lavanyaramesh12414 жыл бұрын
Must thank you bro❤️
@Ggghvujhjihhhhh7 ай бұрын
Can someone develop project for my business using YOLO.
@Vros_vlog6 ай бұрын
glad to do for you!
@riyazbagban91902 жыл бұрын
Bro I like this explanation but I have doubts How bh bw bx by will be calculated Means who is responsible to calculate And how bunch of images get bounding boxes for training
@abinashpegu8663 Жыл бұрын
Those training data are manually generated by data labellers.
@karthifairhawn98254 жыл бұрын
Nanba I'm new subscriber hope you are tamil
@robinson98223 жыл бұрын
Bro can you make aa face mask detection and social distancing using yolo
@thirumalaisurya45873 жыл бұрын
Bro code not working arguments error came
@devakinandan2326 күн бұрын
0:27
@priyanayak2000 Жыл бұрын
Code run agilla bro ..
@codevalley95118 ай бұрын
thanks
@zalakthakker68463 жыл бұрын
are able to share me slide?
@tejabolla4 жыл бұрын
usage: yolo.py [-h] -i IMAGE [-c CONFIDENCE] [-t THRESHOLD] yolo.py: error: the following arguments are required: -i/--image i am getting above error ,please help ji