$30 off During Our Annual Pro Sale. View Details »
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
ML Kit Introduction (for Android)
Search
Elvis Lin
July 18, 2018
Programming
0
300
ML Kit Introduction (for Android)
Introduce the basic concept of ML Kit and how to use it in Android development
Elvis Lin
July 18, 2018
Tweet
Share
More Decks by Elvis Lin
See All by Elvis Lin
Protect Users' Privacy in iOS 14
elvismetaphor
0
54
Dubugging Tips and Tricks for iOS development
elvismetaphor
0
53
Strategies of Facebook LightSpeed project
elvismetaphor
0
90
Background Execution And WorkManager
elvismetaphor
2
490
作為一個跨平台的 Mobile App 開發者,從入門到放棄!?
elvismetaphor
2
520
Dependency Injection for testability of iOS app
elvismetaphor
1
1.4k
Briefly Introduction of Kotlin coroutines
elvismetaphor
1
310
MotionLayout Brief Introduction
elvismetaphor
1
330
Chapter 10. Pattern Matching with Regular Expressions
elvismetaphor
0
50
Other Decks in Programming
See All in Programming
AI Agent Dojo #4: watsonx Orchestrate ADK体験
oniak3ibm
PRO
0
100
Spinner 軸ズレ現象を調べたらレンダリング深淵に飲まれた #レバテックMeetup
bengo4com
0
130
DevFest Android in Korea 2025 - 개발자 커뮤니티를 통해 얻는 가치
wisemuji
0
170
モデル駆動設計をやってみようワークショップ開催報告(Modeling Forum2025) / model driven design workshop report
haru860
0
280
The Past, Present, and Future of Enterprise Java
ivargrimstad
0
250
生成AI時代を勝ち抜くエンジニア組織マネジメント
coconala_engineer
0
290
「コードは上から下へ読むのが一番」と思った時に、思い出してほしい話
panda728
PRO
39
26k
Cap'n Webについて
yusukebe
0
150
Giselleで作るAI QAアシスタント 〜 Pull Requestレビューに継続的QAを
codenote
0
270
Flutter On-device AI로 완성하는 오프라인 앱, 박제창 @DevFest INCHEON 2025
itsmedreamwalker
1
140
メルカリのリーダビリティチームが取り組む、AI時代のスケーラブルな品質文化
cloverrose
1
320
FluorTracer / RayTracingCamp11
kugimasa
0
250
Featured
See All Featured
Unsuck your backbone
ammeep
671
58k
How Fast Is Fast Enough? [PerfNow 2025]
tammyeverts
3
400
Building AI with AI
inesmontani
PRO
1
570
RailsConf 2023
tenderlove
30
1.3k
Deep Space Network (abreviated)
tonyrice
0
20
Ethics towards AI in product and experience design
skipperchong
1
140
The Power of CSS Pseudo Elements
geoffreycrofte
80
6.1k
Git: the NoSQL Database
bkeepers
PRO
432
66k
The Hidden Cost of Media on the Web [PixelPalooza 2025]
tammyeverts
2
120
How GitHub (no longer) Works
holman
316
140k
I Don’t Have Time: Getting Over the Fear to Launch Your Podcast
jcasabona
34
2.6k
Into the Great Unknown - MozCon
thekraken
40
2.2k
Transcript
ML Kit 使⽤用簡介 Elvis Lin @Android Taipei 2018-07-18
關於我 • Elvis Lin • Android 與 iOS 永遠的初學者 •
Twitter: @elvismetaphor • Blog: https://blog.elvismetaphor.me
不是業配 https://youtu.be/Z-dqGRSsaBs
⼤大綱 • 什什麼是(我理理解的)機器學習 • 移動裝置上實作機器學習應⽤用的限制 • TensorFlow Lite 與 ML
Kit • 範例例
機器學習的應⽤用
機器學習 • 從資料中歸納出有⽤用的規則 • 訓練模型 • 使⽤用模型 • Mobile Application
Engineer 參參與開發主要是在「使⽤用模型」 這個範圍
Data Result (Trained) Model
移動裝置上 實作機器學習應⽤用的限制 • 記憶體有限與儲存空間有限 • 計算能⼒力力不如⼤大型伺服器 • 電池容量量有限
移動裝置上 實作機器學習應⽤用的改良⽅方向 • 記憶體有限與儲存空間有限 —> 減少模型(Model)的體積 • 計算能⼒力力不如⼤大型伺服器 —> 降低演算法的複雜度
• 電池容量量有限 —> 降低演算法的複雜度
Google 推出的解決⽅方案 • TensorFlow Lite • ML Kit
https://www.tensorflow.org/mobile/tflite/
Neural Networks API Metal
ML Kit • Cloud Vision API / Mobile Vision API
• Tensorflow Lite • 整合 Firebase,託管「客製化的模型」
ML Kit Base APIs • Image labeling • Text recognition
(OCR) • Face detection • Barcode scanning • Landmark detection • others……
使⽤用 ML Kit
建立⼀一個 Firebase 專案
建立⼀一個 Android app 下載設定檔 設定好 Package Name 下載 google-service.json
<root>/build.gradle dependencies { classpath 'com.android.tools.build:gradle:3.1.3' classpath 'com.google.gms:google-services:4.0.2' }
<root>/app/build.gradle dependencies { // ... implementation 'com.google.firebase:firebase-ml-vision:16.0.0' }
掃描 barcode (local) FirebaseVisionImage image = FirebaseVisionImage.fromBitmap(image); FirebaseVisionBarcodeDetectorOptions options =
new FirebaseVisionBarcodeDetectorOptions.Builder() .setBarcodeFormats( FirebaseVisionBarcode.FORMAT_QR_CODE, FirebaseVisionBarcode.FORMAT_AZTEC ) .build(); FirebaseVisionBarcodeDetector detector = FirebaseVision.getInstance() .getVisionBarcodeDetector(options); detector.detectInImage(image) .addOnSuccessListener( new OnSuccessListener<List<FirebaseVisionBarcode>>() { @Override public void onSuccess(List<FirebaseVisionBarcode> barcodes) {} }) .addOnFailureListener(new OnFailureListener() { @Override public void onFailure(@NonNull Exception e) {} });
初始化 Detector FirebaseVisionImage image = FirebaseVisionImage.fromBitmap(image); FirebaseVisionBarcodeDetectorOptions options = new
FirebaseVisionBarcodeDetectorOptions.Builder() .setBarcodeFormats( FirebaseVisionBarcode.FORMAT_QR_CODE, FirebaseVisionBarcode.FORMAT_AZTEC ) .build(); FirebaseVisionBarcodeDetector detector = FirebaseVision .getInstance() .getVisionBarcodeDetector(options);
取得結果 detector.detectInImage(image) .addOnSuccessListener( new OnSuccessListener<List<FirebaseVisionBarcode>>() { @Override public void onSuccess(List<FirebaseVisionBarcode>
barcodes) {} }) .addOnFailureListener(new OnFailureListener() { @Override public void onFailure(@NonNull Exception e) {} });
⽀支援的 barcode 格式 • Code 128 (FORMAT_CODE_128) • Code 39
(FORMAT_CODE_39) • Code 93 (FORMAT_CODE_93) • Codabar (FORMAT_CODABAR) • EAN-13 (FORMAT_EAN_13) • EAN-8 (FORMAT_EAN_8) • ITF (FORMAT_ITF) • UPC-A (FORMAT_UPC_A) • UPC-E (FORMAT_UPC_E) •QR Code (FORMAT_QR_CODE) • PDF417 (FORMAT_PDF417) • Aztec (FORMAT_AZTEC) • Data Matrix (FORMAT_DATA_MATRIX)
辨識⽂文字 (local) FirebaseVisionImage image = FirebaseVisionImage.fromBitmap(selectedImage); FirebaseVisionTextDetector detector = FirebaseVision.getInstance().getVisionTextDetector();
detector.detectInImage(image) .addOnSuccessListener(new OnSuccessListener<FirebaseVisionText>() { @Override public void onSuccess(FirebaseVisionText text) {} }) .addOnFailureListener(new OnFailureListener() { @Override public void onFailure(@NonNull Exception e) {} });
辨識⽂文字 (cloud) FirebaseVisionCloudDetectorOptions options = new FirebaseVisionCloudDetectorOptions.Builder() .setModelType(FirebaseVisionCloudDetectorOptions.LATEST_MODEL) .setMaxResults(15) .build();
FirebaseVisionImage image = FirebaseVisionImage.fromBitmap(selectedImage); FirebaseVisionCloudDocumentTextDetector detector = FirebaseVision.getInstance() .getVisionCloudDocumentTextDetector(options); detector.detectInImage(image) .addOnSuccessListener(new OnSuccessListener<FirebaseVisionCloudText>() { @Override public void onSuccess(FirebaseVisionCloudText text) {} }) .addOnFailureListener(new OnFailureListener() { @Override public void onFailure(@NonNull Exception e) {} });
補充資料 • ML Kit 簡介 (for Android) https://blog.elvismetaphor.me/ml-kit-fundamentals-for- android-6444e2db0fdb •
ML Kit 簡介 (for iOS) https://blog.elvismetaphor.me/ml-kit-fundamentals-for- ios-cb705044e69b
參參考資料 • https://youtu.be/Z-dqGRSsaBs • https://codelabs.developers.google.com/codelabs/mlkit- android/ • https://github.com/firebase/quickstart-android/tree/ master/mlkit
None