# EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi

A tutorial showing how to train, convert, and run TensorFlow Lite object detection models on Android devices, the Raspberry Pi, and more!

Repository: https://github.com/EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi
Canonical: https://ross.abutalabs.com/products/tensorflow-lite-object-detection-on-android-and-raspberry-pi
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Last push: 2025-02-13T17:34:28+00:00

## Health v2 (maintenance only)
Score: 35/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 6, release rhythm 35, longevity 100
- inputs: {"age_days": 2538, "days_push": 566, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1592, forks 695 (observed 2026-08-28T04:05:08.808875+00:00)

## What it is
A tutorial repository with Jupyter notebooks teaching how to train, convert, and deploy custom TensorFlow Lite object detection models on edge devices like Android phones and Raspberry Pi. It includes Colab-based training and Python code for running detection on images, video, and webcam feeds.

## Use cases
- train a custom object detection model for raspberry pi
- deploy tensorflow lite model on android
- run real-time object detection on webcam
- convert tensorflow model to tflite format
- learn edge device machine learning
- train object detection model in google colab

## When to choose
- you want a guided, beginner-friendly walkthrough for training and deploying TFLite object detection models
- you target edge devices like Raspberry Pi or Android phones
- you prefer learning via Colab notebooks and video tutorials

## When to avoid
- you need a production-ready inference library rather than a tutorial
- you use frameworks other than TensorFlow (e.g. PyTorch, YOLO)
- you need non-detection tasks like segmentation or classification

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, computer-vision, image-processing
- domain: machine-learning, computer-vision, education, tutorials
- platform: python, cross-platform
- tags: tensorflow-lite, object-detection, raspberry-pi, edge-devices, google-colab, jupyter-notebook, model-training, tutorial, android, linux

## Member repositories
- EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi (main) score 35

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:08.808875+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:54:16.661618+00:00, confidence not recorded.
  - readme: https://github.com/EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi (fetched 2026-08-28T04:05:08.808875+00:00, sha 1d32dc68b506)
- Data as of 2026-08-30T08:39:29.467469+00:00.