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オフィスの前にある信号が変わる タイミング教えてくれるWebページ 作ろうとしたよ with ...
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Takayuki Sakai
January 15, 2018
Programming
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1.3k
オフィスの前にある信号が変わる タイミング教えてくれるWebページ 作ろうとしたよ with DeepLearning
2017年末に社内で開かれたハッカソンの発表資料を社外向けに少し修正したものです。
Takayuki Sakai
January 15, 2018
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Transcript
ΦϑΟεͷલʹ͋Δ৴߸͕มΘΔ λΠϛϯάڭ͑ͯ͘ΕΔ Webϖʔδ ࡞ͬͨΑ࡞Ζ͏ͱͨ͠Α Hackday2017 Team4 ञҪ ਸࢸ ※Hackday2017ͱɺ౦ূҰ෦্اۀͷגࣜձࣾϑΝϯίϛϡχέʔγϣϯζࣾͰͷ Ջͳ༨༟ͷ͋Δ࣌ʹߦΘΕͨνʔϜ੍ϋοΧιϯͷ͜ͱͰ͢
Ռ ͜Μͳײ͡
ͳͥ࡞͔ͬͨ - ΦϑΟεͷલͷาߦऀ৴߸ͷͪ࣌ؒ݁ߏ ͍ - ੨ʹͳΔ·Ͱͷ͕͔࣌ؒΕɺ੮Λཱͭ λΠϛϯά͔Δͣ
ΈΜͳϋοϐʔ ؒҧ͍ͳ͍ʂ - ΦϑΟεͷલͷาߦऀ৴߸ͷͪ࣌ؒ݁ߏ ͍ - ੨ʹͳΔ·Ͱͷ͕͔࣌ؒΕɺ੮Λཱͭ λΠϛϯά͔Δͣ
֓ཁ - ৴߸ͷมΘΔपظ༧Ίଌ͓ͬͯ͘ - ͨ·ʹը૾ೝࣝͰ੨ΓସΘΓ λΠϛϯάΛิਖ਼͢Δ
पظཧαʔό पظऔಘ ৴߸ͷ৭ ৴߸ͷपظΛཧ ੨ఆϓϩάϥϜ શମߏ ৴߸ͷը૾ࡱӨ ৴߸ͷ৭Λఆ ϒϥβ ৴߸ͷλΠϛϯάΛදࣔ
৴߸ͷ੨ೝࣝͷ ͨΊʹͬͨ͜ͱ
͜ΜͳΧϝϥͰ
͜Μͳը૾ͷ৴߸ͷ৭Λ
͜͜ʹ͋Δʢ੨ʣ
ఆ͍ͨ͠ʂ
͜͏͍͏ը૾ॲཧͱ͍͑
Deep Learning Ͱ͢ΑͶ…
ཁ݅ - WebΧϝϥͰࡱͬͨը૾Λ͏ - ҎԼېࢭ - खಈͰ৴߸ʹζʔϜ - खಈͰը૾Ճ -
ΧϝϥΛશʹݻఆ͢Δ
·ֶͣशσʔλ࡞Γ ʢ৭Μͳ͔֯ΒࡱΔ,5000ຕʣ ੨ ੨
PythonͷίʔυΛΨʔοͱॻ͍ͯ ʢ200ߦ͘Β͍ʣ … def vgg_std16_model(img_rows, img_cols): model = Sequential() model.add(ZeroPadding2D((1,
1), input_shape=(3, img_rows, img_cols))) model.add(Convolution2D(64, 3, 3, activation='relu')) model.add(ZeroPadding2D((1, 1))) model.add(Convolution2D(64, 3, 3, activation='relu')) model.add(MaxPooling2D((2, 2), strides=(2, 2))) model.add(ZeroPadding2D((1, 1))) model.add(Convolution2D(128, 3, 3, activation='relu'))
ֶशʂ(ŕŦŖƃ ~/hackday/python$ python3 train_and_evaluate.py 4591 train samples Start training........... Train
on 3121 samples, validate on 551 samples 10/3121 [=>..............................] - ETA: 35023s - loss: 0.5735 - acc: 0.6032
Μ…ʁ ~/hackday/python$ python3 train_and_evaluate.py 4591 train samples Start training........... Train
on 3121 samples, validate on 551 samples 10/3121 [=>..............................] - ETA: 35023s - loss: 0.5735 - acc: 0.6032
Γ࣌ؒ35023s ≒ 10࣌ؒ ~/hackday/python$ python3 train_and_evaluate.py 4591 train samples Start
training........... Train on 3121 samples, validate on 551 samples 10/3121 [=>..............................] - ETA: 35023s - loss: 0.5735 - acc: 0.6032
ʮऴΘΒͳ͍… Ͳ͏͢Ε…ʯ
ʁʮCPU͕ΒΕͨΑ͏ͩͳ…ʯ
ʮ͋ɺ͋ͳͨ…ʂʂʯ
ʮGPU͞Μʂʯ
ͬͯ͜ͱͰGPUͰ࠶ֶशʂ(ŕŦŖƃ ※AWSͷGPUΠϯελϯε͍·ͨ͠ ~/hackday/python$ python3 train_and_evaluate.py Using gpu device 0: Tesla
M60 (CNMeM is disabled, cuDNN 4007) 4591 train samples Start training........... Train on 3121 samples, validate on 551 samples 10/3121 [=>..............................] - ETA: 2714s - loss: 0.5735 - acc: 0.6032
1࣌ؒҎͰऴΘΔʂ ~/hackday/python$ python3 train_and_evaluate.py Using gpu device 0: Tesla M60
(CNMeM is disabled, cuDNN 4007) 4591 train samples Start training........... Train on 3121 samples, validate on 551 samples 10/3121 [=>..............................] - ETA: 2714s - loss: 0.5735 - acc: 0.6032
1࣌ؒޙ…
ʮ͓ɺֶशऴΘͬͯΔ…ʯ 3121/3121 [==============================] - 0s - loss: 0.0051 - acc:
1.0000 - val_loss: 0.0085 - val_acc: 1.0000
ʮਫ਼… 100%ʂʁʯ 3121/3121 [==============================] - 0s - loss: 0.0051 -
acc: 1.0000 - val_loss: 0.0085 - val_acc: 1.0000
ʮਫ਼… 100%ʂʁʯ ʮ͜ͷউෛΖͨͰʂʯ 3121/3121 [==============================] - 0s - loss: 0.0051
- acc: 1.0000 - val_loss: 0.0085 - val_acc: 1.0000
1ऴྃ
2
ʮͯ͞ϦΞϧλΠϜʹࡱͬ ͨ৴߸ͷ৭Λ༧ଌ͢Δ͔…ʯ
PCʮ੨ʂʯ ʮਖ਼ղʂʯ
PCʮʂʯ ʮ͍͢͝ʂʯ
PCʮʂʯ ʮ͋Ε…ʁʯ
PCʮ੨ʂʯ ʮΜΜΜ...ʁʯ
ʮ͍ͭ͜͠…ʯ
ʮԣஅาಓͷ্ʹਓ͕͍Δ͔Ͳ ͏͔Ͱஅ͕ͯ͠Δʂʂʂʯ
Deep Learningମೝࣝೳྗ͕ ߴ͗ͯ͢ɺਓؒͰࢥ͍͔ͭͳ͍Α͏ ͳϧʔϧΛউखʹ࡞ͬͯ͠·͏ͷͰ͢ɻ
ʮͰ͜Ε͕ࡱͬͨσʔλ ʹภΓ͕͚͋ͬͨͩ…ʯ
ʮҎԼͷΑ͏ͳը૾Λͨ͘͞Μ ࡱͬͯ࠶ֶशʂʯ - ͚ͩͲͬͯΔਓ͕͍Δࣸਅ - ੨͚ͩͲ୭ͬͯͳ͍ࣸਅ
࠶ֶशޙ…
PCʮʂʯ ʮΑ͠Α͠ʯ
PCʮ੨ʂʯ ʮ͓ʁʯ
ʮ͍ͭ͜…ʯ
ʮࠓ͜͜Λं͕ͬͯΔ͔ Ͳ͏͔Ͱఆ͕ͯ͠Δʂʯ
ҎԼ͍ͨͪͬ͜͝ʢഊʣ
݁Ռ - ࠷ऴతʹ·͊·͊ͳਫ਼ʹͳͬͨ ʢϦΞϧλΠϜը૾Ͱ90%͘Β͍ʁʣ - ͰɺࠓճͷతͷͨΊʹਫ਼ෆ - ภΓͷͳֶ͍शσʔλΛͬͱͨ͘͞Μ ࡱΕΕղܾ͢Δͣ
ݸਓతײ - Deep Learning͍͢͝ - GPU͍͢͝ - ྑֶ͍शσʔλΛ࡞ΔͷΉ͍ͣ