Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Firebase ML Kit for iOS Developer
Search
Kajornsak Peerapathananont
October 07, 2018
Technology
89
0
Share
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
18
How to build native-experience with cross-platform
kajornsakp
0
22
Understanding your Android build
kajornsakp
0
49
iOSDevTH #21
kajornsakp
0
62
What's new in Flutter (Google I/O Extended Bangkok 22)
kajornsakp
0
92
Mobile Design System at scale
kajornsakp
0
150
What's new in Flutter 2020
kajornsakp
0
84
Mobile Machine Learning for All Skill Levels
kajornsakp
0
49
What's new in Flutter 1.9
kajornsakp
0
65
Other Decks in Technology
See All in Technology
AI-DLCを活用した高品質・安全なAI駆動開発実践 / AI Driven Development with AI-DLC
yoshidashingo
0
110
Spring AI × MCP 入門〜AIエージェントへのツール公開、境界設計から始める最小構成 〜
yuyamiyamoto
0
210
oracle-to-databricks-migration-with-llm-and-dbt
casek
1
430
「気づいたら仕事が終わっている」バクラクAIエージェント本番運用の裏側 / layerx-bakuraku-aie2026
yuya4
18
9.1k
Mastering Ruby Box
tagomoris
3
140
Claude Codeを組織で使いこなす— サーバサイドAIエージェント運用の実践知
techtekt
PRO
0
190
Oracle AI Database@AWS:サービス概要のご紹介
oracle4engineer
PRO
4
2.8k
React、まだ楽しくて草
uhyo
7
3.9k
ポスター発表&デモと総括 / Poster Presentations & Demonstrations and Summary
ks91
PRO
0
190
AIを「創る」と「使う」の循環 — HRテックが実践するリアルなAI組織実装
taketo957
0
1.1k
地元にいないローカルオーガナイザーの立ち回り
uvb_76
1
450
個人の発見を、組織の知恵に 〜生成AI活用を"探索"から"組織の仕組み"へ〜
kintotechdev
2
830
Featured
See All Featured
The Impact of AI in SEO - AI Overviews June 2024 Edition
aleyda
5
1.1k
Context Engineering - Making Every Token Count
addyosmani
9
930
Test your architecture with Archunit
thirion
1
2.3k
The SEO Collaboration Effect
kristinabergwall1
1
470
StorybookのUI Testing Handbookを読んだ
zakiyama
31
6.8k
Site-Speed That Sticks
csswizardry
13
1.2k
How to train your dragon (web standard)
notwaldorf
97
6.7k
Embracing the Ebb and Flow
colly
88
5.1k
The Myth of the Modular Monolith - Day 2 Keynote - Rails World 2024
eileencodes
28
3.5k
How to make the Groovebox
asonas
2
2.2k
What the history of the web can teach us about the future of AI
inesmontani
PRO
1
600
SEO for Brand Visibility & Recognition
aleyda
0
4.6k
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