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