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Shinichi Goto
June 30, 2017
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Core ML / Vision Frameworkを使ってできること / What can we achieve using Core ML and Vision framework
2017/06/30 WWDC - Developer's Living #lifull_wwdc
Shinichi Goto
June 30, 2017
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Transcript
Core ML / Vision Framework ΛͬͯͰ͖Δ͜ͱ ɹ 2017/06/30 WWDC -
Developer's Living @ LIFULL shingt (Shinichi Goto)
shingt (Shinichi Goto) GitHub: @shingt Twi5er: @_shingt 2
Core ML Vision Framework 3
4
Outline • Core MLͷ֓ཁ • Vision Frameworkͷ֓ཁ • Ͱ͖Δ͜ͱ /
ࣄྫհ 5
Core ML 6
ML (Machine Learning) 7
8
9
10
Core ML • ֶशࡁͷModelΛར༻ͯ͠ͷਪʹಛԽ • Core ML model format (**.mlmodel)
• Xcode͕Swi6ͷΠϯλʔϑΣΠεΛࣗಈੜ • αϯϓϧϞσϧApple͕ެ։ • Accerelate / Metal্ʹࡌ͓ͬͯΓϋΠύϑΥʔϚϯε • coremltools 11
ɹ let animalModel = AnimalModel() if let prediction = try?
animalModel.prediction(animalImage: image) { return prediction.animalType } 12
ɹ let animalModel = AnimalModel() if let prediction = try?
animalModel.prediction(animalImage: image) { return prediction.animalType } 13
ɹ let animalModel = AnimalModel() if let prediction = try?
animalModel.prediction(animalImage: image) { return prediction.animalType } 14
ɹ let animalModel = AnimalModel() if let prediction = try?
animalModel.prediction(animalImage: image) { return prediction.animalType } 15
coremltools • "iOS্Ͱѻ͏ͨΊͷModelΛͲ͏༻ҙ͢Δ͔" ͷղܾࡦ • ओཁͳػցֶशπʔϧͷֶशࡁModelΛCore ML༻ͷModelม • Keras,
Caffe, scikit-learn, etc. 16
17
6/28ʹKeras 2.0αϙʔτʢൃද࣌1.2.2ͷΈͩͬͨʣ h"ps:/ /forums.developer.apple.com/thread/81196 18
Vision Framework 19
Vision Framework • Core ML্ʹࡌͬͨը૾ೝࣝɾମݕग़ͳͲͷը૾ղੳ༻ͷϑϨʔϜϫʔΫ • Detec,on • Face, Face
landmarks, Rectangle, Barcode, Text, Horizon • طଘͷͷਫ਼্ʢDeep Learningͷ׆༻ʣ • Tracking • Image Registra,on • Core MLͱͷΈ߹Θͤ 20
21
Tracking • ը૾ʢಈըʣதͷମͷ • إͷTrackingCIDetectorͰՄೳͩͬͨ • ҙͷରʹରͯ͠ͷTracking͕Մೳʹ • VisionͰͷݕग़݁Ռ •
ҙͷྖҬࢦఆ 22
23
Demo (Rectangle Detec,on + Tracking) h"ps:/ /github.com/shingt/VisionTrackerSample 24
զʑCV/MLͷΤΩεύʔτͰ͋Δඞཁͳ͍ ʢͱɺAppleηογϣϯதʹݴ͍ͬͯΔʣ 25
Կ͕Ͱ͖Δͷ͔ʁ ʢΞϓϦέʔγϣϯΤϯδχΞͱͯ͠ͷࢹ͔Βʣ 26
27
28
ࣄྫհ 29
ମݕग़ 30
31
YOLO • YOLO (You only look once) • ߴͳ͜ͱ͕ಛͷମݕग़༻ͷ χϡʔϥϧωοτϫʔΫ
• h1ps:/ /www.youtube.com/watch? v=VOC3huqHrss • ͜ΕҰൠతͳYOLO 32
• iOSࣄྫ • YOLO: Core ML versus MPSNNGraph • Core
MLΛ༻͍ͯiOS্ͰYOLOΛಈ࡞ • Tiny YOLOʢެ։͞Ε͍ͯΔModelʣΛར༻ 33
34
ը૾ੜ 35
Goodfellow, Ian J.; Pouget-Abadie, Jean; Mirza, Mehdi; Xu, Bing; Warde-Farley,
David; Ozair, Sherjil; Courville, Aaron; Bengio, Yoshua. GeneraIve Adversarial Networks. arXiv:1406.2661, 2014. 36
Alec Radford, Luke Metz, and Soumith Chintala. Unsupervised representa>on learning
with deep convolu>onal genera>ve adversarial networks. arXiv preprint arXiv:1511.06434, 2015. 37
• GAN (Genera+ve Adversarial Nets) • ֶशσʔλͱࣅͨσʔλΛੜ͢ΔϞσϧͷҰछ • iOSࣄྫ •
Crea+ve AI on the iPhone: Genera+ve Adversarial Networks (GAN) with Apple's CoreML Tools • MNISTΛσʔληοτͱͯ͠ɺCore MLΛ༻͍ͯiOS্Ͱࣈ ʢʹࣅͨʣը૾Λੜ 38
39
Summary • Core ML / Vision Framework • iOS্Ͱͷը૾ղੳٕज़ͷར༻ϋʔυϧ͕Լ •
ͱ͍͑ࣝ͋Δఔඞཁʢͱײͨ͡ʣ • Ͱ͖Δ͜ͱ • ը૾ೝࣝ / τϥοΩϯά / ମݕग़ / ը૾ੜ / etc. • Follow @mhollemans 40
ࢀߟηογϣϯ • Introducing Core ML • Core ML in depth
• Vision Framework: Building on Core ML 41
ࢀߟࢿྉ • iOS 11: Machine Learning for everyone • Google’s
MobileNets on the iPhone • YOLO: Core ML versus MPSNNGraph • CreaAve AI on the iPhone: GeneraAve Adversarial Networks (GAN) with Apple's CoreML Tools - Zedge • Why Core ML will not work for your app (most likely) • θϩ͔Β࡞ΔDeep Learning 42
Thanks! 43
ʢิʣͰ͖ͳ͍͜ͱ / ੍ͳͲ • ֶशෆՄ • αϙʔτ͍ͯ͠ΔػցֶशϑϨʔϜϫʔΫʹ͍ͭͯɺಛఆͷόʔδϣϯʹറΒΕΔʢগͳ͘ͱ ݱঢ়ʣ • Kerasͷ2.0αϙʔτೖͬͨ͠ɺࠓޙ͍͛ͯ͘ͷ͔
• ModelͷαΠζ͕େ͖͗͢Δ • RegressionͱClassifica5onͷΈʢ☓ ΫϥελϦϯάɺϥϯΩϯάֶशɺetc.ʣ • ϥϯλΠϜͰϢʔβͷೖྗɾߦಈΛModelʹөͤ͞Δ͜ͱͰ͖ͳ͍ • etc. 44