from keras.callbacks import EarlyStopping, TensorBoard
from ctpn import CTPN
from ctpn.data_loader import DataLoader
from ctpn.lib.utils import get_session
from custom import LRScheduler, SingleModelCK
import keras.backend as K
if __name__ == '__main__':
import argparse
K.set_session(get_session(0.8))
parser = argparse.ArgumentParser()
parser.add_argument("-ie",
"--initial_epoch",
help="初始迭代数",
default=0,
type=int)
parser.add_argument("--epochs", help="迭代数", default=20, type=int)
parser.add_argument("--gpus", help="gpu的数量", default=1, type=int)
parser.add_argument("--images_dir",
help="图像位置",
default="E:\data\VOCdevkit\VOC2007\JPEGImages")
parser.add_argument("--anno_dir",
help="标注文件位置",
default="E:\data\VOCdevkit\VOC2007\Annotations")
parser.add_argument("--config_file_path",
help="模型配置文件位置",
default="config/ctpn-default.json")
parser.add_argument("--weights_file_path", help="模型初始权重文件位置", default=None)
parser = argparse.ArgumentParser()
parser.add_argument("--image_path", help="图像位置")
parser.add_argument("--dict_file_path",
help="字典文件位置",
default="data/char_std_5990.txt")
parser.add_argument("--config_file_path",
help="模型配置文件位置",
default="config/densent-default.json")
parser.add_argument("--weights_file_path",
help="模型权重文件位置",
default="model/weights-densent-init.hdf5")
args = parser.parse_args()
K.set_session(get_session(0.4))
image_path = args.image_path
dict_file_path = args.dict_file_path # 字典文件位置
weight_path = args.weights_file_path # 权重文件位置
config_path = args.config_file_path # 模型配置文件位置
id_to_char = load_dict(dict_file_path, "UTF-8")
config = DenseNetOCR.load_config(config_path)
config['weight_path'] = weight_path
ocr = DenseNetOCR(**config)
start = datetime.now()
print(ocr.predict(image_path, id_to_char)[0])
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("--image_path", help="图像位置")
parser.add_argument("--dict_file_path", help="字典文件位置", default="data/char_std_5990.txt")
parser.add_argument("--densenet_config_path", help="densenet模型配置文件位置",
default="config/densent-default.json")
parser.add_argument("--ctpn_config_path", help="ctpn模型配置文件位置",
default="config/ctpn-default.json")
parser.add_argument("--ctpn_weight_path", help="ctpn模型权重文件位置",
default="model/weights-ctpnlstm-init.hdf5")
parser.add_argument("--densenet_weight_path", help="densenet模型权重文件位置",
default="model/weights-densent-init.hdf5")
parser.add_argument("--adjust", help="是否对图像进行适当裁剪",
default=True, type=bool)
args = parser.parse_args()
K.set_session(get_session())
app = TextDetectionApp(ctpn_weight_path=args.ctpn_weight_path,
densenet_weight_path=args.densenet_weight_path,
dict_path=args.dict_file_path,
ctpn_config_path=args.ctpn_config_path,
densenet_config_path=args.densenet_config_path)
start_time = datetime.now()
for rect, line in app.detect(args.image_path, args.adjust):
print(line)
print(f"cost {(datetime.now() - start_time).microseconds / 1000}ms")
parser.add_argument("--dict_file_path", help="字典文件位置",
default="/home/sunsheenai/application/data/OCR/char_std_5990.txt")
parser.add_argument("--train_file_path", help="训练文件位置",
default="/home/sunsheenai/application/data/OCR/train.txt")
parser.add_argument("--test_file_path", help="测试文件位置",
default="/home/sunsheenai/application/data/OCR/test.txt")
parser.add_argument("--config_file_path", help="模型配置文件位置",
default="config/densent-default.json")
parser.add_argument("--weights_file_path", help="模型初始权重文件位置",
default=None)
parser.add_argument("--save_weights_file_path", help="保存模型训练权重文件位置",
default=r'model/weights-densent-{epoch:02d}.hdf5')
args = parser.parse_args()
K.set_session(utils.get_session(0.8))
batch_size = args.batch_size
encoding = "UTF-8"
initial_epoch = args.initial_epoch
# 载入模型配置文件
config = DenseNetOCR.load_config(args.config_file_path)
weights_file_path = args.weights_file_path
gpus = args.gpus
config['num_gpu'] = gpus
# 载入初始权重
if weights_file_path is not None:
config["weight_path"] = weights_file_path