Pothole Detection Made Easy: Training a Dataset with YOLOv8

preview_player
Показать описание
#pyresearch

In this video, we had a detailed walkthrough to train the YOLOv8 models on a custom dataset. In the process, we also carried out a small real-world training experiment for pothole detection.

YOLOv8
Object Detection
Custom Dataset
Training
Deep Learning
Computer Vision
Convolutional Neural Networks (CNNs)
Transfer Learning
Data Preparation
Labeling
Model Architecture
Hyperparameter Tuning
Evaluation Metrics
Inference
Detection Accuracy
Tensorboard
PyTorch
OpenCV
Python Programming.

Please let me know your valuable feedback on the video by means of comments. Please like and share the video. Do not forget to subscribe to my channel for more educational videos.

Any type of problem you can comment down.

Want more education? Connect with me here:

Tags:
#ComputerVision #deeplearning #Fine #tune #YOLOv8 #Object #Detection #pothole #detection #PyTorch #Train #YOLOv8 #train #YOLOv8 #on #custom #data #YOLO #yolo #object #detection #YOLOv8 #YOLOv8 #custom #data #YOLOv8 #tutorial #YOLOv8n #YOLOv8s #YOLOv8m #objectdetection #potholes #yolo #yolov8 #computervision #segmentation #customdataset #machinelearning

Related tags:

#Potholedetection
#YOLOv8
#Dataset #training
#Computervision
#Objectdetection
#Road #safety
#Machinelearning
#Artificialintelligence
#Deeplearning
#imageprocessingpython
Convolutional neural networks
Training models
Computer vision applications
Smart transportation
Intelligent transportation systems
Autonomous vehicles
OpenCV
Python
Image annotation
Video processing
Рекомендации по теме
Комментарии
Автор

I have enjoyed learning about training with YOLOv8, for example in "Pothole Detection." However, I am curious about the procedure or technique for retraining a model. Whether I want to include new images to improve detection but do not have the original dataset (the one that originated the first trained model), or simply want to reduce training time.

Another case could be adding a new detection class (for example, crack detection) to the pothole detection model, but avoiding training from scratch and instead starting from the already trained pothole model.

germancruz
Автор

Do you have a tutorial on how to create the bounding box labels of the potholes? Thank you! Great video!!

henryl
Автор

Hi, Thanks for making this video. If you don't mind, where do you get the dataset?

adityaerlanggawibowo
Автор

how can we detect pothole in real time and which is better jetson nano or raspberry pi

balajik
Автор

Bro can you give training results like heap map, f1 score, accuracy

johnwesly
Автор

What preprocessing techniques are used?

AnvithaReddy-ds
Автор

You can do a tutotial explaining the implementation in camera in real time

rpino
Автор

Hi bro i need details of hardware requirements

varunvaru