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Train a custom object detection model using your data
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=-ZyFYniGUsw
Learn how to train a custom object detection model for Raspberry Pi to detect less common objects like versions of a logo using your own collection of data. • 00:00 Introduction • 00:49 The 3 steps of training a custom model • 01:24 Step 1: Create a training dataset • 04:01 Step 2: Train a custom model with TensorFlow Lite Model Maker • 09:03 Step 3: Deploy the custom model to Raspberry Pi • 11:08 What’s next • Colab notebook to train a custom object detection model → https://goo.gle/3ocbqmI • Sample app to run the object detection model on Raspberry Pi → https://goo.gle/3GaABw3 • Android figurine dataset → https://goo.gle/31DtXPL • Explaining “average precision” → https://goo.gle/3lBR5p6 • Transfer learning → https://goo.gle/3pBDiAh • Responsible AI → https://goo.gle/2QEEuVV • Choose an object detection model architecture for Raspberry Pi → https://goo.gle/3lDe9DO • Make object detection run faster by using Coral → https://goo.gle/3EuH3xn • Watch all Machine Learning for Raspberry Pi videos → https://goo.gle/ML-raspberrypi • Subscribe to TensorFlow → https://goo.gle/TensorFlow • #TensorFlow #MachineLearning #ML #RaspberryPi #EdgeAI • • product: TensorFlow - TensorFlow Lite, TensorFlow - General; fullname: Khanh LeViet;
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