my chinese blog:https://blog.csdn.net/fanzonghao/article/details/107199538
Dbnet is usually used to detect word, in fact barcode can be detected.
This project also provide word detect model.
model:
follow icdar15 dataset format, x1,y1,x2,y2,x3,y3,x4,y4,label,(x1,y1) is left top,(x2,y2) is right top.
where config/icdar2015_resnet18_FPN_DBhead_polyLR_code_phone.yaml you can change learning rate,train_path and so on.
single gpu train: python train_code_phone.py
multi gpus train:sh multi_gpu_train.sh , nedd notice os.environ['CUDA_VISIBLE_DEVICES'] is match nproc_per_node.
python predict_code_phone.py
First python model_to_onnx.py to get onnx model. Then where onnx_project you can python dbcode_tensorrt_predict.py.
notice:change model path
python train_word_industry_res50.py train teacher(res50) model;
python train_word_industry_res18_kd.py train student(res18)model;
--change you own path in labelme_txt_box.py
python labelme_txt_box.py
pytorch1.5
torchvision0.6
cuda9.0+
tensorrt 7.0
1.word:https://github.com/zonghaofan/dbnet_torch/tree/master/phone_word_model 2.code:https://github.com/zonghaofan/dbnet_torch/tree/master/phone_code_model
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learning rate show
２.some test examples
3.train loss
1. https://github.com/WenmuZhou/DBNet.pytorch
More tensortrt inference.