Build a smart IoT device with TensorFlow Lite and Raspberry Pi
summary
Raspberry Pi 2/3/4 or Zero 2 runs TensorFlow Lite (64-bit Pi OS gives ~20% speedup); demo uses YAMNet 521 classes for one‑second audio windows and a half‑second loop to classify live mic input, and EfficientDet‑Lite 70 classes for camera object detection running about 6 fps on Pi (Coral USB accelerator recommended for faster inference). Model Maker trains custom models (dozens of images per class for prototypes, >100 per class for production) and deploys by swapping the .tflite file; install via pip install tflite-model-maker.
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chapters (12)
- 0:00Introduction to AI on Pi
- 1:07Setting up Raspberry Pi
- 2:59Installing required software
- 4:02Audio classification
- 5:25Real-time audio detection
- 7:43Running audio classification
- 8:36Object detection concept
- 9:53Object detection code
- 10:59Live video detection
- 12:18Additional vision tasks
- 13:21Training custom models
- 14:46Deployment and resources
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