ML Kit Vision Quickstart Sample App

Introduction

This ML Kit Vision iOS Quickstart app demonstrates how to use and integrate various vision based ML Kit features into your app.

Feature List

Features that are included in this demo app:

Object Detection - Detect, track, and classify objects in real time and static images
Custom Object Detection (Birds) - Detect, track, and classify birds with a custom TensorFlow Lite model
Face Detection - Detect faces in real time and static images
Text Recognition - Recognize text in real time and static images
Barcode Scanning - Scan barcodes in real time and static images
Image Labeling - Label images in real time and static images
Custom Image Labeling (Birds) - Label images of birds with a custom TensorFlow Lite model
Pose Detection - Detect the position of the human body in real time.
Selfie Segmentation - Segment people from the background in real time.

Getting Started

Run the sample code on your iOS device or simulator
Try extending the code to add new features and functionality

How to use the app

This app supports two usage scenarios: Live Camera mode and Static Image mode.

Static Image Scenario

When the app is first opened, you will begin in Static Image mode. Use the carousel to select a specific API and hit “detect” to exercise the API on the preloaded images. In order to add your own images from the camera roll, select the camera roll icon on the top of the screen.

Live Camera Scenario

This mode uses the camera preview as input instead of static images. In order to enter this mode, select the video camera icon in the top right corner of the screen.

Support

Stack Overflow

License

Copyright 2020 Google, Inc.

Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.