def main_test():
print('[INFO] 解析配置...')
parser = None
config = None
model_path = None
try:
args, parser = get_test_args()
config = process_config(args.config)
model_path = args.model
except Exception as e:
print('[Exception] 配置无效, %s' % e)
if parser:
parser.print_help()
print ('[Exception] 参考: python main_test.py -c configs/simple_mnist_config.json ' \
'-m simple_mnist.weights.10-0.24.hdf5')
exit(0)
# config = process_config('configs/simple_mnist_config.json')
np.random.seed(47) # 固定随机数
print('[INFO] 加载数据...')
dl = SimpleMnistDL()
test_data = np.expand_dims(dl.get_test_data()[0][0], axis=0)
test_label = np.argmax(dl.get_test_data()[1][0])
print('[INFO] 预测数据...')
# infer = SimpleMnistInfer("simple_mnist.weights.16-0.19.hdf5", config)
infer = SimpleMnistInfer(model_path, config)
infer_label = np.argmax(infer.predict(test_data))
print('[INFO] 真实Label: %s, 预测Label: %s' % (test_label, infer_label))
print('[INFO] 预测完成...')
def main_train():
"""
训练模型
:return:
"""
print '[INFO] 解析配置...'
parser = None
config = None
try:
args, parser = get_train_args()
config = process_config(args.config)
except Exception as e:
print '[Exception] 配置无效, %s' % e
if parser:
parser.print_help()
print '[Exception] 参考: python main_train.py -c configs/simple_mnist_config.json'
exit(0)
# config = process_config('configs/simple_mnist_config.json')
print '[INFO] 加载数据...'
dl = SimpleMnistDL(config=config)
print '[INFO] 构造网络...'
model = SimpleMnistModel(config=config)
print '[INFO] 训练网络...'
trainer = SimpleMnistTrainer(
model=model.model,
data=[dl.get_train_data(), dl.get_test_data()],
config=config)
trainer.train()
print '[INFO] 训练完成...'
def test_main():
print('[INFO] 解析配置...')
config = process_config('configs/simple_mnist_config.json')
print('[INFO] 加载数据...')
dl = SimpleMnistDL()
test_data = np.expand_dims(dl.get_test_data()[0][0], axis=0)
test_label = np.argmax(dl.get_test_data()[1][0])
print('[INFO] 预测数据...')
infer = SimpleMnistInfer("simple_mnist.weights.10-0.21.hdf5", config)
infer_label = np.argmax(infer.predict(test_data))
print('[INFO] 真实Label: %s, 预测Label: %s' % (test_label, infer_label))
print('[INFO] 预测完成...')
def main_train():
"""
训练模型
:return:
"""
print('[INFO] 解析配置...')
parser = None
config = None
# try:
# args, parser = get_train_args()
# config = process_config(args.config)
# except Exception as e:
# print('[Exception] 配置无效, %s' % e)
# if parser:
# parser.print_help()
# print('[Exception] 参考: python main_train.py -c configs/simple_mnist_config.json')
# exit(0)
config = process_config('configs/simple_mnist_config.json')
np.random.seed(47) # 固定随机数
print('[INFO] 加载数据...')
dl = SimpleMnistDL(config=config)
print('[INFO] 构造网络...')
model = SimpleMnistModel(config=config)
print('[INFO] 训练网络...')
trainer = SimpleMnistTrainer(
model=model.model,
data=[dl.get_train_data(), dl.get_test_data()],
config=config)
trainer.train()
print('[INFO] 训练完成...')