Train a Custom YOLOv5 Model on Google Colab and Detect Objects In Real Time on Windows | Part 3
🚀Hey everyone and welcome to the final part of the YOLOv5 series!
In this video (Part 3) we'll learn about training a custom YOLOv5 PyTorch model on Google Colab, and using Weights & Biases to understand the training process.
We'll start off by discussing the differences between pre-trained and custom-trained models, and how we can train using the custom dataset that we collected in part 2. Then, we'll use Weights & Biases to determine which of the models we trained is the best one, and deploy that model locally on Windows to perform real-time detection using a custom-trained model.
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Links
📍Google Colab to train a custom YOLOv5: https://wandb.me/train-yolov5
📍 My WandB dashboard from the video: https://wandb.ai/ivangoncharov/custom...
📍Artifacts docs: https://docs.wandb.ai/guides/artifacts
📍 COCO dataset: https://cocodataset.org/#home
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You can watch the whole YOLOv5 Series here:
🚀Part 0 - Overview of the YOLOv5 and W&B integration: • Train and Debug YOLOv5 Models with We... Rocket
🚀Part 1 - Install YOLOv5 on Windows and Google Colab: • Install YOLOv5 to Detect Objects on W... Rocket
🚀Part 2 - Collect & Label a Custom Dataset: • Collect and Label Images to Train a Y... Rocket
🚀Part 3 - Train a Custom YOLOv5 Model to Detect Bus Numbers: • Train a Custom YOLOv5 Model on Google...
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Follow Ivan:
👉 Twitter: / ivangrov
👉 YouTube: / ivangoncharovai
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⏳ Timestamps ⏳
00:00 Intro
00:50 How to think about training a YOLOv5 to detect new classes
03:28 Training a custom YOLOv5 model on Google Colab
08:23 How Weights & Biases helps you understand the training process
12:12 Training a large YOLOv5 model
16:18 Deploying a custom-trained model on Windows
18:28 Outro