Скачать с ютуб How to Train TensorFlow Lite Object Detection Models Using Google Colab | SSD MobileNet в хорошем качестве

How to Train TensorFlow Lite Object Detection Models Using Google Colab | SSD MobileNet

Let's train, export, and deploy a TensorFlow Lite object detection model on the Raspberry Pi - all through a web browser using Google Colab! We'll walk through a Colab notebook that provides start-to-finish code and instructions for training a custom TFLite model, and then show how to run it on a Raspberry Pi. The notebook uses the TensorFlow Object Detection API to train SSD-MobileNet or EfficientDet models and converts them to TFLite format. Click this link to the Colab notebook to get started: https://colab.research.google.com/git... -- Other Links -- 📸 How to capture and label training data for object detection models:    • How to Capture and Label Training Dat...   🏅 TFLite model comparison article: https://ejtech.io/learn/tflite-object... 🍓 Instructions to set up TFLite on the Raspberry Pi:    • How To Run TensorFlow Lite on Raspber...   💻 Instructions to run TFLite models on Windows: https://github.com/EdjeElectronics/Te... 🐜 How to quantize your TFLite model: Still to come! 📄 TFLite GitHub repository: https://github.com/EdjeElectronics/Te... -- Chapters -- 0:00 Introduction 1:06 Google Colab 1:41 1. Gather Training Images 3:22 2. Install TensorFlow 4:43 3. Upload Images and Prepare Data 8:41 4. Set up Training Configuration 11:20 5. Train Model 13:48 6. Convert Model to TFLite 14:20 7. Test Model 17:50 8. Deploy Model 22:07 9. Quantization 22:30 Conclusion -- Music -- - Blue Wednesday – Japanese Garden - Provided by Lofi Records - Watch:    • Blue Wednesday – Japanese Garden   - Download/Stream: https://fanlink.to/Discovery