Object Tracking Using YOLOv4, Deep SORT, and TensorFlow

Let me know what additions you would like added to the code and if you run into any issues. Cheers :)

Sorry sir, yolov4.weights file has been error

What about same person or car come again, will count new for it

Hello, the Google drive link doesn't work

hey, I would like thank you very much for this video. If you see this comment, could you let me know if there is any way to run this directly from a python script on live video?

@The AI Guy Thank you for your work. I followed your instruction, all works like in your video, but I have nor detections neither tracking. Output avi == input avi, and when I add --info in command line, I can see only FPS, no detection&tracking info.🤔

Question: When I run your notebook it runs well but boxes cant add to the output video!! I have same input and output (without boxes and labels :/)

You have no idea how this video saved me, I cannot thank you enough

Thats very cool, how can i get this to track soccer players on my video? and could it track data? Thx

Hey I am unable to download pre-trained yolov4.weights file. Please help me out link is not working.

Hey, the google drive link has expired for the weights. Is there an updated link anywhere?

Hello
When I open yolo4.weight google drive link, l faced with 404 error, could you fix the link
Thanks!

i folow to your instruction but the video output has no bouding box. can you tell me why?

Thank you for an awesome clear explanation, on object tracking. If I convert the tiny YoloV4 model to tensorflow lite can I use Coral USB accelerator to accelerate the inferencing? I just need a way to make a post process quantized edge tpu .tflite model.

Hey great work with this, can we use this for lidar data aswell?

Hi first of all thank you so much for putting up such a nice video, could you tell if we are interested in tracking only single person instead of all. can we do it?

Nice video
I want to add a congestion measurement to this, do you know how please?

I am not getting any bounding boxes

I am getting errors when I try to run the code (conda env create -f conda-gpu.yml).
ERROR conda.core.link:_execute(730): An error occurred while installing package 'defaults::qt-5.9.7-vc14h73c81de_0'.
Rolling back transaction: done

LinkError: post-link script failed for package defaults::qt-5.9.7-vc14h73c81de_0
location of failed script: C:\Users\User\anaconda3\envs\yolov4-gpu\Scripts\.qt-post-link.bat

Does anyone know how to solve this issue? Thank you

How can i do this with yolov5?

Let's focus on optimizing it, to reach realtime.

thanks for your extremely helpful content , I have a question is there a way to detect only one class using colab ?

Can i execute this code in colab

Great video!
Do you know if there's a way to get the mAP on this model? I can't find the code to save the detections to the file in order to run any mAP algorithms.

Can we do this in google colab?, as my computer doesn't support gpu i am facing difficulty.

How to store those bounding box coordinates to use them as trajectory data? Please explain this also.

How do I create my own custom file. I need to do some down stream task with the tracking ID and bounding boxes.

hope to see additional feature of counting the number of cars within the video and passing through the lane successfully?

Not getting any detection bro... i tried latest tensorflow gpu version i.e. 2.7 and also afew others like 2.5 and 2.3 but getting no bounding box... can you guess what's wrong?

I'm trying to run the object_tracker script, but it get stuck on frame #1 and doesn't move. It seems like a problem with the model conversion to TF.

Can someone guide me in the right direction?

Can I implement it with YOLOv5 with custom classes?

That was very helpful! I know it prints FPS at each frame. Is there an easy way to print the actual frame number from the original video?

If we can track objects then we can also measure speed and such right? How would you go about getting the (x,y) coordinates?

When I try convert the model:

conv_weights = conv_weights.reshape(conv_shape).transpose([2, 3, 1, 0])
ValueError: cannot reshape array of size 4554552 into shape (1024,512,3,3)

What should I do?

Hello I containerized the project, their is one error I created an issue on github

Please do one for YoloR, thank you.

To the guys for whom no bounding boxes appear in the video : create a new environment as he says in the beginning of the video and use this, rather than using one which you might have created earlier for some other purpose. This worked for me.

how to use the code without Cuda or does it specifically have to use Cuda to run the code?

Hey, actually I tried this out and it turned out to be too low FPS while renderring, actually I want to implement this in a real-time moving camera where I will be detecting other vehicles on the road. What might be the solution to this very low FPS that I'm getting? (I tried using tiny weights too, which was very inaccurate, yet not giving too much FPS to be real-time)

Great video, well documented code and sturdy implementation 10/10

Does it work on only lidar data?

Hii, very nice tutorial. I was wondering if you could count the vehicles after tracking them.

Thank you so much for this video. Btw, can I apply this code into raspberry pi with camera installation?

Can you do this for google colab version?

EDIT: Guess what, you clearly used AI to predict my question and you answered it, thank you

Hello all, need help , how may i run this object tracking on webcam in colab. Regards