# tucan9389/awesome-ml-demos-with-ios

The challenge projects for Inferencing machine learning models on iOS

Repository: https://github.com/tucan9389/awesome-ml-demos-with-ios
Canonical: https://ross.abutalabs.com/products/awesome-ml-demos-with-ios
Language: Python
License: MIT
License Family: permissive
Topics: ios, machine-learning, coreml, mlkit, tensorflow, tensorflow-lite, demo, awesome, inference
Last push: 2021-03-21T18:31:23+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3025, "days_push": 1991, "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 1291, forks 139 (observed 2026-08-28T04:04:15.558964+00:00)

## What it is
A curated collection of demo and challenge projects for running machine learning model inference on iOS using Core ML, ML Kit, and TensorFlow Lite. It includes baseline projects for image classification, object detection, segmentation, and performance measurement tools.

## Use cases
- learn how to run machine learning models on iOS
- find Core ML demo projects for image classification
- convert TensorFlow models for on-device iOS inference
- benchmark ML model performance on iPhone
- examples of object detection with ML Kit on iOS
- learn semantic segmentation on mobile devices

## When to choose
- you are an iOS developer learning on-device ML inference with Core ML or TensorFlow Lite
- you want reference demo projects for image classification, detection, or segmentation on iOS
- you need example code for model conversion and pre/postprocessing on mobile

## When to avoid
- you need production-ready ML libraries rather than educational demos
- you target Android or cross-platform ML deployment
- you need actively updated examples - the repo's latest release dates to 2021

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, image-processing, computer-vision
- domain: machine-learning, mobile-development, tutorials
- platform: -
- tags: coreml, tensorflow-lite, ml-kit, on-device-inference, awesome-list, demo-projects, ios, swift, mobile

## Member repositories
- tucan9389/awesome-ml-demos-with-ios (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:15.558964+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 2026-08-30T04:54:49.585622+00:00, confidence not recorded.
  - readme: https://github.com/tucan9389/awesome-ml-demos-with-ios (fetched 2026-08-28T04:04:15.558964+00:00, sha 5258d7e3aca6)
- Data as of 2026-08-30T08:39:29.467469+00:00.