How to Build an Object Detection Model with YOLO: Step-by-Step Tutorial
Master YOLO Object Detection: Full Project Walkthrough | YOLO Object Detection Made Easy: Complete Guide| #ailearning #yolo #objectdetection #imagedifference #cnn
Important Link:
[Website Link] : https://simplifyai.in/
[Dataset Link] : https://universe.roboflow.com/polsko-...
[Google Colab Notebook Link] : https://colab.research.google.com/dri...
[GitHub Repository for YOLO] : https://github.com/ultralytics/yolov5...
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Description:
In this video, we’ll walk you through the process of building an object detection project using YOLO. We'll start by downloading the dataset from Roboflow and uploading it to Google Drive. Then, we'll set up and run our Colab notebook to train the YOLO model.
Key Steps Covered:
1. Download Dataset: Visit Roboflow, select a vehicle detection dataset, and download it.
2. Upload to Google Drive: Upload the dataset to your Google Drive and organize it.
3. Set Up Google Colab: Mount Google Drive, install necessary libraries, and set the runtime to GPU.
4. Training the Model: Train the YOLO model using the downloaded dataset.
5. Updating YAML File: Modify the data.yaml file to include exact paths for train, test, and validation sets.
6. Saving and Testing the Model: Save the trained model and test it to see the predictions.
By the end of this tutorial, you'll have a working object detection model trained to detect cars, trucks, traffic signs, and more. This project is simple and easy to follow, making it perfect for beginners.
Links and Resources:
[Dataset Link] : https://universe.roboflow.com/polsko-...
[Google Colab Notebook Link] : https://colab.research.google.com/dri...
[GitHub Repository for YOLO] : https://github.com/ultralytics/yolov5...
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If you have any questions or run into any issues, feel free to leave a comment below. Don't forget to like, share, and subscribe for more tutorials!
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#YOLO #ObjectDetection #MachineLearning #DeepLearning #ComputerVision #AI #ArtificialIntelligence #GoogleColab #Roboflow #YOLOv5
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