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 starttofinish 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 SSDMobileNet 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/tfliteobject...

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