Object Detection Using YOLO v4 on Custom Dataset | Practical Implementation

Step by step Implementation of YOLO v4.
Dataset Preparation for yolo v4.
Train your custom Yolo v4 Model
Test your Yolo v4 Model

What is YOLO?
YOLO stands for You Only Look Once
YOLO is an algorithm that uses neural networks to provide real-time object detection. This algorithm is popular because of its speed and accuracy. It has been used in various applications to detect traffic signals, people, parking meters, and animals.
With the timeline, it has become faster and better, with its versions named as:
YOLO V1
YOLO V2
YOLO V3
YOLO V4
YOLO V5
YOLO V2 is better than V1 in terms of accuracy and speed.
YOLO V3 is not faster than V2 but is more accurate than V2 and so on.

How the YOLO algorithm works?
YOLO algorithm works using the following three techniques:

1- Residual blocks: image is divided into various grids. Each grid has a dimension of n X n
2- Bounding box regression
3- Intersection Over Union (IOU) : YOLO uses IOU to provide an output box that surrounds the objects perfectly.

#yolov4 #yolo #objectdetection #computervision #deeplearning #ai #artificialintelligence #ml #machinelearning #neuralnetworks #darknet

[vikramreddy]

Most awaited video ...thanks so much mam for the video ...

[CodeWithAarohi]

You can use LabelIMG tool for Annotation. It is easier to annotate images in yolo format with it.

[kevinchinnavadu]

Thank you so much!
Your setup video with 1 line command and this tutorial on training yolo worked perfectly 1st try for me 🎉

I used LabelImg for annotations instead tho.


Best teacher out there for YOLO :)

[darshan]

best explanation on internet on yolo model thank u so much.

[muhammadalisiddique]

Hey Aroshi, I want to thank you.
you saved me in the final year project❤

[utkarshtripathi]

mam, your way of teaching is Exellent, Ossm

[ganeshchalamalasetti]

Thank you very much Aarohi for making up this video. Very useful.

[Nirex_]

Thank you for the amazing tutorial, you left nothing uncovered! I wish I could have subscribed and liked more than once!

[venkatesanr]

Thanks for your efforts and for sharing your knowledge

[servicepeinture]

Thank you Ms aarohi for your efforts <3 <3

[nirmaltiwari]

Excellent tutorial. Can you share the presentation also for reference ?

[nisreenalaas]

Thank you ma'am.. useful video it help me alot, I appreciate your efforts
There are two types of images:
1- One image with one object
2- One image with multiple objects.
In this video you deal with the first type. Is it same for the second type? Or how to train images using yolov4 that contained multiple objects? Please, I need your help

[pallebharath]

Hii mam .We tried as same as your way but at last while prediction imshow it just giving same image as output without any bounding box and prediction class..Can you pls help on this

[DileepJ-jg]

Hi Aarohi, It's an excellent effort to share your knowledge. Nice Video. I was working on the same. I could not able to train my model. I am using windows 10 Operating system. i got this error.: ./darknet: error while loading shared libraries: libcuda.so.1: cannot open shared object file: No such file or directory. Can you please help me to sort out this problem

[NavneetKaur-imub]

Heyyy Mam. Thankyou soo much for this amzing tutorial. I m not able 2 recieve train.txt nd test.txt files by running !python process.py

[danianiazi]

Can you share the presentation will us ? It will help to follow the steps your explaination is wonderful

[namith]

Thanks for the video..Can you pls make a video about model evaluation part(IoU & mAP) for this project or for previous YoloV3 project.

[Pal_Views]

Thank you for the wonderful video.I have a a question... How to get the bounding box coordinate in predicted image ?

[cyd]

Hi Aarohi, is it okay that have an image for laptop called 1.jpg and an image for phone called 1.jpg or is this an issue because both classes images will be combined in the multiple images folder. Should the names of the images not overlap? For example is 1_phone.jpg and 1_laptop.jpg a better way to go? Thank you and great video!

[AyazKhan-huso]

when i run this code in colab it gives me empty file as train.txt having no paths to the images
images_list =
print(images_list)

# Create train.txt file
file = open("data/train.txt", "w")

file.close()