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 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') 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 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...')