aiacademy: 深度學習 CNN Kaggle-Image-Classification
超級好玩的兒~ AIA 在 Kaggle 創建的 Pokemon 比賽
Image Classification 總共 15 個地點類別!
練習方向:
- Data preprocessing and data augmentation
- DNN/CNN model construction and hyper-parameter tuning
- Metrics: Accuracy
先看我自己刻的 transfer learning model: mobilenet
- acc: 0.87 多
-
import
import numpy as np import os import keras import matplotlib.pyplot as plt from keras.layers import Dense,GlobalAveragePooling2D, Dropout from keras.applications import MobileNet, MobileNetV2, VGG16, VGG19, Xception from keras.preprocessing import image from keras.applications.mobilenet import preprocess_input from keras.preprocessing.image import ImageDataGenerator from keras.models import Model from keras.optimizers import Adam -
Base_model
base_model = MobileNet( weights='imagenet', include_top=False # 如果是 true 表示要拿這model的classes 來分類 ) -
Build model: Functional Programming
x = base_model.output x = GlobalAveragePooling2D()(x) x = Dense(1024, activation='relu')(x) x = Dense(1024, activation='relu')(x) x = Dense(512, activation='relu')(x) preds = Dense(15, activation='softmax')(x) model = Model(inputs=base_model.input, outputs=preds)-
Base_model 的層數不要 train
- 留下上面的全連結層(Dense)
for layer in model.layers[:-4]: layer.trainable=False for layer in model.layers[-4:]: layer.trainable=True
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model 細節
__________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== input_1 (InputLayer) (None, None, None, 3 0 __________________________________________________________________________________________________ block1_conv1 (Conv2D) (None, None, None, 3 864 input_1[0][0] __________________________________________________________________________________________________ block1_conv1_bn (BatchNormaliza (None, None, None, 3 128 block1_conv1[0][0] __________________________________________________________________________________________________ block1_conv1_act (Activation) (None, None, None, 3 0 block1_conv1_bn[0][0] __________________________________________________________________________________________________ block1_conv2 (Conv2D) (None, None, None, 6 18432 block1_conv1_act[0][0] __________________________________________________________________________________________________ block1_conv2_bn (BatchNormaliza (None, None, None, 6 256 block1_conv2[0][0] __________________________________________________________________________________________________ block1_conv2_act (Activation) (None, None, None, 6 0 block1_conv2_bn[0][0] __________________________________________________________________________________________________ block2_sepconv1 (SeparableConv2 (None, None, None, 1 8768 block1_conv2_act[0][0] __________________________________________________________________________________________________ block2_sepconv1_bn (BatchNormal (None, None, None, 1 512 block2_sepconv1[0][0] __________________________________________________________________________________________________ block2_sepconv2_act (Activation (None, None, None, 1 0 block2_sepconv1_bn[0][0] __________________________________________________________________________________________________ block2_sepconv2 (SeparableConv2 (None, None, None, 1 17536 block2_sepconv2_act[0][0] __________________________________________________________________________________________________ block2_sepconv2_bn (BatchNormal (None, None, None, 1 512 block2_sepconv2[0][0] __________________________________________________________________________________________________ conv2d_1 (Conv2D) (None, None, None, 1 8192 block1_conv2_act[0][0] __________________________________________________________________________________________________ block2_pool (MaxPooling2D) (None, None, None, 1 0 block2_sepconv2_bn[0][0] __________________________________________________________________________________________________ batch_normalization_1 (BatchNor (None, None, None, 1 512 conv2d_1[0][0] __________________________________________________________________________________________________ add_1 (Add) (None, None, None, 1 0 block2_pool[0][0] batch_normalization_1[0][0] __________________________________________________________________________________________________ block3_sepconv1_act (Activation (None, None, None, 1 0 add_1[0][0] __________________________________________________________________________________________________ block3_sepconv1 (SeparableConv2 (None, None, None, 2 33920 block3_sepconv1_act[0][0] __________________________________________________________________________________________________ block3_sepconv1_bn (BatchNormal (None, None, None, 2 1024 block3_sepconv1[0][0] __________________________________________________________________________________________________ block3_sepconv2_act (Activation (None, None, None, 2 0 block3_sepconv1_bn[0][0] __________________________________________________________________________________________________ block3_sepconv2 (SeparableConv2 (None, None, None, 2 67840 block3_sepconv2_act[0][0] __________________________________________________________________________________________________ block3_sepconv2_bn (BatchNormal (None, None, None, 2 1024 block3_sepconv2[0][0] __________________________________________________________________________________________________ conv2d_2 (Conv2D) (None, None, None, 2 32768 add_1[0][0] __________________________________________________________________________________________________ block3_pool (MaxPooling2D) (None, None, None, 2 0 block3_sepconv2_bn[0][0] __________________________________________________________________________________________________ batch_normalization_2 (BatchNor (None, None, None, 2 1024 conv2d_2[0][0] __________________________________________________________________________________________________ add_2 (Add) (None, None, None, 2 0 block3_pool[0][0] batch_normalization_2[0][0] __________________________________________________________________________________________________ block4_sepconv1_act (Activation (None, None, None, 2 0 add_2[0][0] __________________________________________________________________________________________________ block4_sepconv1 (SeparableConv2 (None, None, None, 7 188672 block4_sepconv1_act[0][0] __________________________________________________________________________________________________ block4_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block4_sepconv1[0][0] __________________________________________________________________________________________________ block4_sepconv2_act (Activation (None, None, None, 7 0 block4_sepconv1_bn[0][0] __________________________________________________________________________________________________ block4_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block4_sepconv2_act[0][0] __________________________________________________________________________________________________ block4_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block4_sepconv2[0][0] __________________________________________________________________________________________________ conv2d_3 (Conv2D) (None, None, None, 7 186368 add_2[0][0] __________________________________________________________________________________________________ block4_pool (MaxPooling2D) (None, None, None, 7 0 block4_sepconv2_bn[0][0] __________________________________________________________________________________________________ batch_normalization_3 (BatchNor (None, None, None, 7 2912 conv2d_3[0][0] __________________________________________________________________________________________________ add_3 (Add) (None, None, None, 7 0 block4_pool[0][0] batch_normalization_3[0][0] __________________________________________________________________________________________________ block5_sepconv1_act (Activation (None, None, None, 7 0 add_3[0][0] __________________________________________________________________________________________________ block5_sepconv1 (SeparableConv2 (None, None, None, 7 536536 block5_sepconv1_act[0][0] __________________________________________________________________________________________________ block5_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block5_sepconv1[0][0] __________________________________________________________________________________________________ block5_sepconv2_act (Activation (None, None, None, 7 0 block5_sepconv1_bn[0][0] __________________________________________________________________________________________________ block5_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block5_sepconv2_act[0][0] __________________________________________________________________________________________________ block5_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block5_sepconv2[0][0] __________________________________________________________________________________________________ block5_sepconv3_act (Activation (None, None, None, 7 0 block5_sepconv2_bn[0][0] __________________________________________________________________________________________________ block5_sepconv3 (SeparableConv2 (None, None, None, 7 536536 block5_sepconv3_act[0][0] __________________________________________________________________________________________________ block5_sepconv3_bn (BatchNormal (None, None, None, 7 2912 block5_sepconv3[0][0] __________________________________________________________________________________________________ add_4 (Add) (None, None, None, 7 0 block5_sepconv3_bn[0][0] add_3[0][0] __________________________________________________________________________________________________ block6_sepconv1_act (Activation (None, None, None, 7 0 add_4[0][0] __________________________________________________________________________________________________ block6_sepconv1 (SeparableConv2 (None, None, None, 7 536536 block6_sepconv1_act[0][0] __________________________________________________________________________________________________ block6_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block6_sepconv1[0][0] __________________________________________________________________________________________________ block6_sepconv2_act (Activation (None, None, None, 7 0 block6_sepconv1_bn[0][0] __________________________________________________________________________________________________ block6_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block6_sepconv2_act[0][0] __________________________________________________________________________________________________ block6_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block6_sepconv2[0][0] __________________________________________________________________________________________________ block6_sepconv3_act (Activation (None, None, None, 7 0 block6_sepconv2_bn[0][0] __________________________________________________________________________________________________ block6_sepconv3 (SeparableConv2 (None, None, None, 7 536536 block6_sepconv3_act[0][0] __________________________________________________________________________________________________ block6_sepconv3_bn (BatchNormal (None, None, None, 7 2912 block6_sepconv3[0][0] __________________________________________________________________________________________________ add_5 (Add) (None, None, None, 7 0 block6_sepconv3_bn[0][0] add_4[0][0] __________________________________________________________________________________________________ block7_sepconv1_act (Activation (None, None, None, 7 0 add_5[0][0] __________________________________________________________________________________________________ block7_sepconv1 (SeparableConv2 (None, None, None, 7 536536 block7_sepconv1_act[0][0] __________________________________________________________________________________________________ block7_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block7_sepconv1[0][0] __________________________________________________________________________________________________ block7_sepconv2_act (Activation (None, None, None, 7 0 block7_sepconv1_bn[0][0] __________________________________________________________________________________________________ block7_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block7_sepconv2_act[0][0] __________________________________________________________________________________________________ block7_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block7_sepconv2[0][0] __________________________________________________________________________________________________ block7_sepconv3_act (Activation (None, None, None, 7 0 block7_sepconv2_bn[0][0] __________________________________________________________________________________________________ block7_sepconv3 (SeparableConv2 (None, None, None, 7 536536 block7_sepconv3_act[0][0] __________________________________________________________________________________________________ block7_sepconv3_bn (BatchNormal (None, None, None, 7 2912 block7_sepconv3[0][0] __________________________________________________________________________________________________ add_6 (Add) (None, None, None, 7 0 block7_sepconv3_bn[0][0] add_5[0][0] __________________________________________________________________________________________________ block8_sepconv1_act (Activation (None, None, None, 7 0 add_6[0][0] __________________________________________________________________________________________________ block8_sepconv1 (SeparableConv2 (None, None, None, 7 536536 block8_sepconv1_act[0][0] __________________________________________________________________________________________________ block8_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block8_sepconv1[0][0] __________________________________________________________________________________________________ block8_sepconv2_act (Activation (None, None, None, 7 0 block8_sepconv1_bn[0][0] __________________________________________________________________________________________________ block8_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block8_sepconv2_act[0][0] __________________________________________________________________________________________________ block8_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block8_sepconv2[0][0] __________________________________________________________________________________________________ block8_sepconv3_act (Activation (None, None, None, 7 0 block8_sepconv2_bn[0][0] __________________________________________________________________________________________________ block8_sepconv3 (SeparableConv2 (None, None, None, 7 536536 block8_sepconv3_act[0][0] __________________________________________________________________________________________________ block8_sepconv3_bn (BatchNormal (None, None, None, 7 2912 block8_sepconv3[0][0] __________________________________________________________________________________________________ add_7 (Add) (None, None, None, 7 0 block8_sepconv3_bn[0][0] add_6[0][0] __________________________________________________________________________________________________ block9_sepconv1_act (Activation (None, None, None, 7 0 add_7[0][0] __________________________________________________________________________________________________ block9_sepconv1 (SeparableConv2 (None, None, None, 7 536536 block9_sepconv1_act[0][0] __________________________________________________________________________________________________ block9_sepconv1_bn (BatchNormal (None, None, None, 7 2912 block9_sepconv1[0][0] __________________________________________________________________________________________________ block9_sepconv2_act (Activation (None, None, None, 7 0 block9_sepconv1_bn[0][0] __________________________________________________________________________________________________ block9_sepconv2 (SeparableConv2 (None, None, None, 7 536536 block9_sepconv2_act[0][0] __________________________________________________________________________________________________ block9_sepconv2_bn (BatchNormal (None, None, None, 7 2912 block9_sepconv2[0][0] __________________________________________________________________________________________________ block9_sepconv3_act (Activation (None, None, None, 7 0 block9_sepconv2_bn[0][0] __________________________________________________________________________________________________ block9_sepconv3 (SeparableConv2 (None, None, None, 7 536536 block9_sepconv3_act[0][0] __________________________________________________________________________________________________ block9_sepconv3_bn (BatchNormal (None, None, None, 7 2912 block9_sepconv3[0][0] __________________________________________________________________________________________________ add_8 (Add) (None, None, None, 7 0 block9_sepconv3_bn[0][0] add_7[0][0] __________________________________________________________________________________________________ block10_sepconv1_act (Activatio (None, None, None, 7 0 add_8[0][0] __________________________________________________________________________________________________ block10_sepconv1 (SeparableConv (None, None, None, 7 536536 block10_sepconv1_act[0][0] __________________________________________________________________________________________________ block10_sepconv1_bn (BatchNorma (None, None, None, 7 2912 block10_sepconv1[0][0] __________________________________________________________________________________________________ block10_sepconv2_act (Activatio (None, None, None, 7 0 block10_sepconv1_bn[0][0] __________________________________________________________________________________________________ block10_sepconv2 (SeparableConv (None, None, None, 7 536536 block10_sepconv2_act[0][0] __________________________________________________________________________________________________ block10_sepconv2_bn (BatchNorma (None, None, None, 7 2912 block10_sepconv2[0][0] __________________________________________________________________________________________________ block10_sepconv3_act (Activatio (None, None, None, 7 0 block10_sepconv2_bn[0][0] __________________________________________________________________________________________________ block10_sepconv3 (SeparableConv (None, None, None, 7 536536 block10_sepconv3_act[0][0] __________________________________________________________________________________________________ block10_sepconv3_bn (BatchNorma (None, None, None, 7 2912 block10_sepconv3[0][0] __________________________________________________________________________________________________ add_9 (Add) (None, None, None, 7 0 block10_sepconv3_bn[0][0] add_8[0][0] __________________________________________________________________________________________________ block11_sepconv1_act (Activatio (None, None, None, 7 0 add_9[0][0] __________________________________________________________________________________________________ block11_sepconv1 (SeparableConv (None, None, None, 7 536536 block11_sepconv1_act[0][0] __________________________________________________________________________________________________ block11_sepconv1_bn (BatchNorma (None, None, None, 7 2912 block11_sepconv1[0][0] __________________________________________________________________________________________________ block11_sepconv2_act (Activatio (None, None, None, 7 0 block11_sepconv1_bn[0][0] __________________________________________________________________________________________________ block11_sepconv2 (SeparableConv (None, None, None, 7 536536 block11_sepconv2_act[0][0] __________________________________________________________________________________________________ block11_sepconv2_bn (BatchNorma (None, None, None, 7 2912 block11_sepconv2[0][0] __________________________________________________________________________________________________ block11_sepconv3_act (Activatio (None, None, None, 7 0 block11_sepconv2_bn[0][0] __________________________________________________________________________________________________ block11_sepconv3 (SeparableConv (None, None, None, 7 536536 block11_sepconv3_act[0][0] __________________________________________________________________________________________________ block11_sepconv3_bn (BatchNorma (None, None, None, 7 2912 block11_sepconv3[0][0] __________________________________________________________________________________________________ add_10 (Add) (None, None, None, 7 0 block11_sepconv3_bn[0][0] add_9[0][0] __________________________________________________________________________________________________ block12_sepconv1_act (Activatio (None, None, None, 7 0 add_10[0][0] __________________________________________________________________________________________________ block12_sepconv1 (SeparableConv (None, None, None, 7 536536 block12_sepconv1_act[0][0] __________________________________________________________________________________________________ block12_sepconv1_bn (BatchNorma (None, None, None, 7 2912 block12_sepconv1[0][0] __________________________________________________________________________________________________ block12_sepconv2_act (Activatio (None, None, None, 7 0 block12_sepconv1_bn[0][0] __________________________________________________________________________________________________ block12_sepconv2 (SeparableConv (None, None, None, 7 536536 block12_sepconv2_act[0][0] __________________________________________________________________________________________________ block12_sepconv2_bn (BatchNorma (None, None, None, 7 2912 block12_sepconv2[0][0] __________________________________________________________________________________________________ block12_sepconv3_act (Activatio (None, None, None, 7 0 block12_sepconv2_bn[0][0] __________________________________________________________________________________________________ block12_sepconv3 (SeparableConv (None, None, None, 7 536536 block12_sepconv3_act[0][0] __________________________________________________________________________________________________ block12_sepconv3_bn (BatchNorma (None, None, None, 7 2912 block12_sepconv3[0][0] __________________________________________________________________________________________________ add_11 (Add) (None, None, None, 7 0 block12_sepconv3_bn[0][0] add_10[0][0] __________________________________________________________________________________________________ block13_sepconv1_act (Activatio (None, None, None, 7 0 add_11[0][0] __________________________________________________________________________________________________ block13_sepconv1 (SeparableConv (None, None, None, 7 536536 block13_sepconv1_act[0][0] __________________________________________________________________________________________________ block13_sepconv1_bn (BatchNorma (None, None, None, 7 2912 block13_sepconv1[0][0] __________________________________________________________________________________________________ block13_sepconv2_act (Activatio (None, None, None, 7 0 block13_sepconv1_bn[0][0] __________________________________________________________________________________________________ block13_sepconv2 (SeparableConv (None, None, None, 1 752024 block13_sepconv2_act[0][0] __________________________________________________________________________________________________ block13_sepconv2_bn (BatchNorma (None, None, None, 1 4096 block13_sepconv2[0][0] __________________________________________________________________________________________________ conv2d_4 (Conv2D) (None, None, None, 1 745472 add_11[0][0] __________________________________________________________________________________________________ block13_pool (MaxPooling2D) (None, None, None, 1 0 block13_sepconv2_bn[0][0] __________________________________________________________________________________________________ batch_normalization_4 (BatchNor (None, None, None, 1 4096 conv2d_4[0][0] __________________________________________________________________________________________________ add_12 (Add) (None, None, None, 1 0 block13_pool[0][0] batch_normalization_4[0][0] __________________________________________________________________________________________________ block14_sepconv1 (SeparableConv (None, None, None, 1 1582080 add_12[0][0] __________________________________________________________________________________________________ block14_sepconv1_bn (BatchNorma (None, None, None, 1 6144 block14_sepconv1[0][0] __________________________________________________________________________________________________ block14_sepconv1_act (Activatio (None, None, None, 1 0 block14_sepconv1_bn[0][0] __________________________________________________________________________________________________ block14_sepconv2 (SeparableConv (None, None, None, 2 3159552 block14_sepconv1_act[0][0] __________________________________________________________________________________________________ block14_sepconv2_bn (BatchNorma (None, None, None, 2 8192 block14_sepconv2[0][0] __________________________________________________________________________________________________ block14_sepconv2_act (Activatio (None, None, None, 2 0 block14_sepconv2_bn[0][0] __________________________________________________________________________________________________ global_average_pooling2d_1 (Glo (None, 2048) 0 block14_sepconv2_act[0][0] __________________________________________________________________________________________________ dense_1 (Dense) (None, 1024) 2098176 global_average_pooling2d_1[0][0] __________________________________________________________________________________________________ dense_2 (Dense) (None, 1024) 1049600 dense_1[0][0] __________________________________________________________________________________________________ dense_3 (Dense) (None, 512) 524800 dense_2[0][0] __________________________________________________________________________________________________ dense_4 (Dense) (None, 15) 7695 dense_3[0][0] ================================================================================================== Total params: 24,541,751 Trainable params: 3,680,271 Non-trainable params: 20,861,480 __________________________________________________________________________________________________ -
懶人拆資料方法 (ImageDataGenerator)
target_size = (224, 224) batch_size = 32- 當training set 和 valid set 都在同一個資料夾的時候
train_datagen = ImageDataGenerator(preprocessing_function=preprocess_input, validation_split=0.1)- train image gen
train_image_gen = train_datagen.flow_from_directory('train', target_size=target_size, batch_size=batch_size, class_mode='categorical', classes={ 'kitchen' : 0, 'street' : 1, 'industrial' : 2, 'insidecity' : 3, 'forest' : 4, 'livingroom' : 5, 'opencountry' : 6, 'PARoffice' : 7, 'mountain' : 8, 'CALsuburb' : 9, 'coast' : 10, 'store' : 11, 'bedroom' : 12, 'tallbuilding' : 13, 'highway' :14 }, subset='training')- valid image gen
valid_image_gen = train_datagen.flow_from_directory('train', target_size=target_size, batch_size=batch_size, class_mode='categorical', classes={ 'kitchen' : 0, 'street' : 1, 'industrial' : 2, 'insidecity' : 3, 'forest' : 4, 'livingroom' : 5, 'opencountry' : 6, 'PARoffice' : 7, 'mountain' : 8, 'CALsuburb' : 9, 'coast' : 10, 'store' : 11, 'bedroom' : 12, 'tallbuilding' : 13, 'highway' :14 }, subset='validation') -
Complie Train 一發!
- Compile
model.compile(loss='categorical_crossentropy', optimizer='RMSprop', metrics=['accuracy'])- callBack
from keras.callbacks import EarlyStopping, ModelCheckpoint, ReduceLROnPlateau import os checkpoint = ModelCheckpoint('kaggle-image-classification.hdf5', monitor='val_acc', save_best_only=True, mode='auto', verbose=1) earlystop = EarlyStopping(monitor='val_acc', mode='min', patience=20, verbose=1) reduce_lr = ReduceLROnPlateau(monitor='val_acc', factor=0.2,patience=5, min_lr=0.001)- Train
model_history = model.fit_generator(train_image_gen, epochs=40, steps_per_epoch=(train_image_gen.samples//batch_size), validation_data=valid_image_gen, validation_steps=(valid_image_gen.samples//batch_size), callbacks=[ checkpoint, earlystop, reduce_lr ]) -
Test, Predict
- Load hdf5
from keras.models import load_model hdf5_model = load_model('kaggle-image-classification.hdf5')- Load Test Data
import os from keras.preprocessing import image as k_image import re import numpy as np r_image = re.compile(r'.*\.(jpg|png|gif)$') test_image = [] test_image_id = [] for file in os.listdir('./testset/'): img = k_image.load_img(os.path.join('./testset/{}'.format(file)), target_size=target_size) img = k_image.img_to_array(img) test_image.append(img) test_image_id.append(file.split('.')[0])- image preprocessing
test_train = np.array(test_image) test_train_id = np.array(test_image_id) test_train = test_train * 1./255- Predict
ans = hdf5_model.predict(test_train) result = np.argmax(ans,axis=1) # 因為用 Modle 建 model- CSV
result = result.reshape((-1, 1)) test_train_id = test_train_id.reshape((-1, 1)) import csv with open('result_transfer_learning.csv', 'a') as a_writer: for i in range(len(result)): result_r = csv.writer(a_writer, lineterminator='\n') result_r.writerow([test_image_id[i], str(result[i]).lstrip('[').rstrip(']')])