Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
Firebase ML Kit for iOS Developer
Search
Sponsored
·
SiteGround - Reliable hosting with speed, security, and support you can count on.
→
Kajornsak Peerapathananont
October 07, 2018
Technology
96
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
Firebase ML Kit for iOS Developer
Firebase Dev Day 2018 @Bangkok, Thailand
Kajornsak Peerapathananont
October 07, 2018
More Decks by Kajornsak Peerapathananont
See All by Kajornsak Peerapathananont
Full-Stack Development with FlutterFire
kajornsakp
0
35
How to build native-experience with cross-platform
kajornsakp
0
45
Understanding your Android build
kajornsakp
0
67
iOSDevTH #21
kajornsakp
0
65
What's new in Flutter (Google I/O Extended Bangkok 22)
kajornsakp
0
99
Mobile Design System at scale
kajornsakp
0
160
What's new in Flutter 2020
kajornsakp
0
89
Mobile Machine Learning for All Skill Levels
kajornsakp
0
54
What's new in Flutter 1.9
kajornsakp
0
70
Other Decks in Technology
See All in Technology
Claude in Chrome 入門 / Introduction to Claude in Chrome
cielo1985
0
860
開発投資の期待値を上げるプロダクトロードマップづくり ~プロダクトエンジニアが越境して事業を伸ばす~
kekekenta
1
210
株式会社シーエーシー エンジニア向け会社紹介資料
cac
0
57k
研究開発部の紹介 / Sansan R&D Profile
sansan33
PRO
5
25k
白金鉱業Meetup Vol.25 アウトカムが二値のデータに対するCausal Impact
brainpadpr
0
250
The Knowledge Spine: A Machine-Executable Ontology for Governed Marketing Activation
vananth22
0
110
あるけみー式LTスライド作成術
alchemy1115
2
220
HRC_Frontend_Conference_Fukuoka_2026.pdf
ts020
0
750
Claude Codeを「使うほど育つ」AI秘書にするノウハウ
minorun365
PRO
31
27k
Vibe Coding で作ったプロダクトをどう安全に動かすか / How to Safely Run Products Built with Vibe Coding
glidenote
0
170
30座EKS, 180次升級淬煉的EKS Upgrade Skill 的歷程
eric8230
0
180
AIは推し活である。
kurazuuuuuu
1
570
Featured
See All Featured
The Cost Of JavaScript in 2023
addyosmani
55
10k
Easily Structure & Communicate Ideas using Wireframe
afnizarnur
194
17k
We Have a Design System, Now What?
morganepeng
55
8.3k
Max Prin - Stacking Signals: How International SEO Comes Together (And Falls Apart)
techseoconnect
PRO
0
470
Color Theory Basics | Prateek | Gurzu
gurzu
1
470
Optimizing for Happiness
mojombo
378
71k
Visualization
eitanlees
152
17k
Cheating the UX When There Is Nothing More to Optimize - PixelPioneers
stephaniewalter
287
14k
Designing Experiences People Love
moore
143
24k
技術選定の審美眼(2025年版) / Understanding the Spiral of Technologies 2025 edition
twada
PRO
120
120k
DBのスキルで生き残る技術 - AI時代におけるテーブル設計の勘所
soudai
PRO
68
57k
The Success of Rails: Ensuring Growth for the Next 100 Years
eileencodes
47
8.3k
Transcript
ML Kit for iOS developers Kajornsak Peerapathananont Agoda
Machine Learning
#FirebaseDevDay
Google Lens
Smart Reply
On-device Machine Learning
#FirebaseDevDay Doable, but hard.
#FirebaseDevDay
#FirebaseDevDay Get Image Image Classification Transform Interpret Get Result
#FirebaseDevDay Transform unsigned char *sourceBaseAddr = (unsigned char *)(CVPixelBufferGetBaseAddress(pixelBuffer)); int
image_height; unsigned char *sourceStartAddr; if (fullHeight <= image_width) { image_height = fullHeight; sourceStartAddr = sourceBaseAddr; } else { image_height = image_width; const int marginY = ((fullHeight - image_width) / 2); sourceStartAddr = (sourceBaseAddr + (marginY * sourceRowBytes)); } const int image_channels = 4; assert(image_channels >= wanted_input_channels); tensorflow::Tensor image_tensor( tensorflow::DT_FLOAT, tensorflow::TensorShape( {1, wanted_input_height, wanted_input_width, wanted_input_channels})); auto image_tensor_mapped = image_tensor.tensor<float, 4>(); tensorflow::uint8 *in = sourceStartAddr; float *out = image_tensor_mapped.data(); for (int y = 0; y < wanted_input_height; ++y) { float *out_row = out + (y * wanted_input_width * wanted_input_channels); for (int x = 0; x < wanted_input_width; ++x) { const int in_x = (y * image_width) / wanted_input_width; const int in_y = (x * image_height) / wanted_input_height; tensorflow::uint8 *in_pixel = in + (in_y * image_width * image_channels) + (in_x * image_channels); float *out_pixel = out_row + (x * wanted_input_channels); for (int c = 0; c < wanted_input_channels; ++c) { out_pixel[c] = (in_pixel[c] - input_mean) / input_std; } } }
#FirebaseDevDay Interpret if (tf_session.get()) { std::vector<tensorflow::Tensor> outputs; tensorflow::Status run_status =
tf_session->Run( {{input_layer_name, image_tensor}}, {output_layer_name}, {}, &outputs); if (!run_status.ok()) { LOG(ERROR) << "Running model failed:" << run_status; } else { tensorflow::Tensor *output = &outputs[0]; auto predictions = output->flat<float>(); NSMutableDictionary *newValues = [NSMutableDictionary dictionary]; for (int index = 0; index < predictions.size(); index += 1) { const float predictionValue = predictions(index); if (predictionValue > 0.05f) { std::string label = labels[index % predictions.size()]; NSString *labelObject = [NSString stringWithUTF8String:label.c_str()]; NSNumber *valueObject = [NSNumber numberWithFloat:predictionValue]; [newValues setObject:valueObject forKey:labelObject]; } } dispatch_async(dispatch_get_main_queue(), ^(void) { [self setPredictionValues:newValues]; }); } }
None
#FirebaseDevDay
#FirebaseDevDay Real-world Common Use Cases
#FirebaseDevDay FIRVisionImage | VisionImage NS_SWIFT_NAME(VisionImage) @interface FIRVisionImage : NSObject @property(nonatomic,
nullable) FIRVisionImageMetadata *metadata; - (instancetype)initWithImage:(UIImage *)image NS_DESIGNATED_INITIALIZER; - (instancetype)initWithBuffer:(CMSampleBufferRef)sampleBuffer NS_DESIGNATED_INITIALIZER; - (instancetype)init NS_UNAVAILABLE; @end
Text Recognition - On-device - On-cloud
#FirebaseDevDay https://firebase.google.com/docs/ml-kit/recognize-text
#FirebaseDevDay FIRVisionText | VisionText NS_SWIFT_NAME(VisionText) @interface FIRVisionText : NSObject @property(nonatomic,
readonly) NSString *text; @property(nonatomic, readonly) NSArray<FIRVisionTextBlock *> *blocks; - (instancetype)init NS_UNAVAILABLE; @end
#FirebaseDevDay On-device Usage let textRecognizer = vision.onDeviceTextRecognizer() textRecognizer.process(visionImage) { (text,
error) in guard let text = text else { return } // do something with your text }
#FirebaseDevDay On-cloud Usage let textRecognizer = vision.cloudTextRecognize() textRecognizer.process(visionImage) { (text,
error) in guard let text = text else { return } // do something with your text }
Image Labeling - On-device (400+ labels) - On-cloud (10,000+ labels)
#FirebaseDevDay https://firebase.google.com/docs/ml-kit/label-images
#FirebaseDevDay FIRVisionLabel | VisionLabel NS_SWIFT_NAME(VisionLabel) @interface FIRVisionLabel : NSObject @property(nonatomic,
readonly) CGRect frame; @property(nonatomic, readonly) float confidence; @property(nonatomic, copy, readonly) NSString *entityID; @property(nonatomic, copy, readonly) NSString *label; @end
#FirebaseDevDay On-device Usage let labelDetector = vision.labelDetector() labelDetector.detect(in: visionImage) {
(labels, error) in guard let error == nill, let labels = labels, !labels.isEmpty else { return } // do something with your labels }
#FirebaseDevDay On-cloud Usage let labelDetector = vision.cloudLabelDetector() labelDetector.detect(in: visionImage) {
(labels, error) in guard let error == nill, let labels = labels, !labels.isEmpty else { return } // do something with your labels }
Face detection - On-device
#FirebaseDevDay
#FirebaseDevDay FIRVisionFace | VisionFace NS_SWIFT_NAME(VisionFace) @interface FIRVisionFace : NSObject @property(nonatomic,
readonly) CGRect frame; @property(nonatomic, readonly) BOOL hasTrackingID; @property(nonatomic, readonly) NSInteger trackingID; @property(nonatomic, readonly) BOOL hasHeadEulerAngleY; @property(nonatomic, readonly) CGFloat headEulerAngleY; @property(nonatomic, readonly) BOOL hasHeadEulerAngleZ; @property(nonatomic, readonly) CGFloat headEulerAngleZ; @property(nonatomic, readonly) BOOL hasSmilingProbability; @property(nonatomic, readonly) CGFloat smilingProbability; @property(nonatomic, readonly) BOOL hasLeftEyeOpenProbability; @property(nonatomic, readonly) CGFloat leftEyeOpenProbability; @property(nonatomic, readonly) BOOL hasRightEyeOpenProbability; @property(nonatomic, readonly) CGFloat rightEyeOpenProbability; - (instancetype)init NS_UNAVAILABLE; - (nullable FIRVisionFaceLandmark *)landmarkOfType:(FIRFaceLandmarkType)type; #ifdef ENABLE_FACE_CONTOUR - (nullable FIRVisionFaceContour *)contourOfType:(FIRFaceContourType)type; #endif // ENABLE_FACE_CONTOUR @end
#FirebaseDevDay On-device Usage let faceDetector = vision.faceDetector() faceDetector.detect(in: visionImage) {
(faces, error) in guard let error == nill, let faces = faces, !faces.isEmpty else { return } // do something with your faces }
#FirebaseDevDay Face Contour?
Landmark recognition - On-cloud
#FirebaseDevDay
#FirebaseDevDay FIRVisionCloudLandmark | VisionCloudLandmark NS_SWIFT_NAME(VisionCloudLandmark) @interface FIRVisionCloudLandmark : NSObject @property(nonatomic,
copy, readonly, nullable) NSString *entityId; @property(nonatomic, copy, readonly, nullable) NSString *landmark; @property(nonatomic, readonly, nullable) NSNumber *confidence; @property(nonatomic, readonly) CGRect frame; @property(nonatomic, readonly, nullable) NSArray<FIRVisionLatitudeLongitude *> *locations; - (instancetype)init NS_UNAVAILABLE; @end
#FirebaseDevDay On-cloud Usage let landmarkDetector = vision.cloudLandmarkDetector() landmarkDetector.detect(in: visionImage) {
(landmarks, error) in guard let error == nill, let landmarks = landmarks, !landmarks.isEmpty else { return } // do something with your landmarks }
Barcode scanning - On-device
#FirebaseDevDay https://firebase.google.com/docs/ml-kit/label-images
#FirebaseDevDay FIRVisionBarcode | VisionBarcode NS_SWIFT_NAME(VisionBarcode) @interface FIRVisionBarcode : NSObject @property(nonatomic,
readonly) CGRect frame; @property(nonatomic, readonly, nullable) NSString *rawValue; @property(nonatomic, readonly, nullable) NSString *displayValue; @property(nonatomic, readonly) FIRVisionBarcodeFormat format; @property(nonatomic, readonly, nullable) NSArray<NSValue *> *cornerPoints; @property(nonatomic, readonly) FIRVisionBarcodeValueType valueType; @property(nonatomic, readonly, nullable) FIRVisionBarcodeEmail *email; @property(nonatomic, readonly, nullable) FIRVisionBarcodePhone *phone; @property(nonatomic, readonly, nullable) FIRVisionBarcodeSMS *sms; @property(nonatomic, readonly, nullable) FIRVisionBarcodeURLBookmark *URL; @property(nonatomic, readonly, nullable) FIRVisionBarcodeWiFi *wifi; @property(nonatomic, readonly, nullable) FIRVisionBarcodeGeoPoint *geoPoint; @property(nonatomic, readonly, nullable) FIRVisionBarcodeContactInfo *contactInfo; @property(nonatomic, readonly, nullable) FIRVisionBarcodeCalendarEvent *calendarEvent; @property(nonatomic, readonly, nullable) FIRVisionBarcodeDriverLicense *driverLicense; - (instancetype)init NS_UNAVAILABLE; @end
#FirebaseDevDay FIRVisionBarcodeCalendarEvent | VisionBarcodeCalendarEvent NS_SWIFT_NAME(VisionBarcodeCalendarEvent) @interface FIRVisionBarcodeCalendarEvent : NSObject @property(nonatomic,
readonly, nullable) NSString *eventDescription; @property(nonatomic, readonly, nullable) NSString *location; @property(nonatomic, readonly, nullable) NSString *organizer; @property(nonatomic, readonly, nullable) NSString *status; @property(nonatomic, readonly, nullable) NSString *summary; @property(nonatomic, readonly, nullable) NSDate *start; @property(nonatomic, readonly, nullable) NSDate *end; - (instancetype)init NS_UNAVAILABLE; @end
#FirebaseDevDay On-device Usage let barcodeDetector = vision.barcodeDetector() barcodeDetector.detect(in: visionImage) {
(barcodes, error) in guard let error == nill, let barcodes = barcodes, !barcodes.isEmpty else { return } // do something with your barcodes }
Custom model - Tensorflow Lite
#FirebaseDevDay let conditions = ModelDownloadConditions(isWiFiRequired: true, canDownloadInBackground: true) let cloudModelSource
= CloudModelSource( modelName: "my_cloud_model", enableModelUpdates: true, initialConditions: conditions, updateConditions: conditions ) let registrationSuccessful = ModelManager.modelManager().register(cloudModelSource)
Demo
Thank You! #FirebaseDevDay Helpful resources fb.com/FirebaseThailand fb.com/groups/FirebaseDevTH medium.com/FirebaseThailand Kajornsak Peerapathananont