from tensorflow import keras
logdir = "./folder" + datetime.now().strftime("%Y%m%d-%H%M%S")
tensorboard_callback = keras.callbacks.TensorBoard(log_dir=logdir)
from get_image_generator import train_generator, validation_generator, test_generator
from model import model
from meta_parameters import EPOCHS, STEPS_PER_EPOCH, VALIDATION_STEPS, BATCH_SIZE
model.fit_generator(
train_generator,
steps_per_epoch=STEPS_PER_EPOCH,
epochs=EPOCHS,
validation_data=validation_generator,
validation_steps=VALIDATION_STEPS,
use_multiprocessing=True,
callbacks=[tensorboard_callback],
)
model.save_weights('my_model_weights.h5')
print("evaluate", model.metrics_names)
print(model.evaluate_generator(
test_generator,
use_multiprocessing=True,
))
model.count_params()
model.summary()
#TODO numbe of parameters
# https://stackoverflow.com/questions/35792278/how-to-find-number-of-parameters-of-a-keras-model
from model import model, preprocess_input, smodel
from keras.optimizers import SGD
from keras.callbacks import ReduceLROnPlateau
from generator import Generator
import json
if __name__ == '__main__':
model = smodel()
opt = SGD(lr=0.01, momentum=0.9)
model.compile(optimizer=opt,
loss='categorical_crossentropy',
metrics=['acc'])
print(model.summary())
model.load_weights('weights/classifier.h5')
listsss = json.load(open('list_withbndbx.json', 'r'))
train_gen = Generator(
listsss[:7211],
'/home/palm/PycharmProjects/DATA/Tanisorn/imgCarResize/',
preprocess_function=preprocess_input)
test_gen = Generator(
listsss[7211:],
'/home/palm/PycharmProjects/DATA/Tanisorn/imgCarResize/',
preprocess_function=preprocess_input)
reduce_lr_01 = ReduceLROnPlateau(monitor='val_1st_acc',
factor=0.2,
patience=5,
min_lr=0,
mode='max')
reduce_lr_02 = ReduceLROnPlateau(monitor='val_2nd_acc',
factor=0.2,