How to Train YOLO v7 on a Custom Dataset for Structural Damage Detection in Critical Infrastructure скачать в хорошем качестве

How to Train YOLO v7 on a Custom Dataset for Structural Damage Detection in Critical Infrastructure

Join the co-founder and CEO of Abud AI, in this comprehensive tutorial on training YOLOv7, the cutting-edge object detection model, to identify damages in critical infrastructures. Discover how to use Abud AI platform for dataset uploading, model training, and deployment, with specific focus on detecting cracks and rebar exposures using drones. 🚀 Sign up for a free Abud AI account today and start innovating in AI! #YOLOv7 #AI #MachineLearning #ObjectDetection #DroneTechnology #Infrastructure Chapters: 00:00 Introduction to Abud AI and YOLOv7 00:37 Signing Up for Abud AI 01:04 Choosing the Right YOLOv7 Model 01:27 Uploading and Examining the Dataset 03:24 Dataset Labeling Tutorial 05:35 Training the YOLOv7 Model 07:01 Model Training Metrics and Adjustments 08:36 Deploying the Trained Model 09:53 Testing the Model in Playground 10:55 Conclusion and Practical Applications Links and Resources: 🥳 [Sign up now for free](https://abud.ai/ref/yt:zy714VQA_OY/home) 💬 [Join our discord server](  / discord  ) 📱 [Join our WhatsApp group](https://chat.whatsapp.com/CzlqpwU9rID...) 💾 [Download the structural damage dataset](https://drive.google.com/file/d/1vcWj...) 📚 [Read our official docs to learn how to use the Abud API in your software](https://docs.abud.ai/deployment#use-y...) ⚡️ [Clone the Easy YOLOv7 repo to run it locally without internet](https://github.com/abud-ai/easy-yolov7) Thanks for watching! Don't forget to like, subscribe, and share your thoughts in the comments. Stay tuned for more AI insights and tutorials.