This is a pytorch re-implementation of EAST: An Efficient and Accurate Scene Text Detector.
This version will be updated soon, please pay attention to this work. The motivation of this version is to build a easy-training model. This version can automatically update best_model by comparing current hmean and the former. At the same time, we can see evaluation info about every sample easily.
The version is ported from argman/EAST, from Tensorflow to Pytorch
If you have no confidence of the result of our program, you could use submit.zip to submit on website,then you can see result of every image.
right -- green || wrong -- red || miss -- blue
recall/precision/hmean for every test image
This is a pytorch re-implementation of EAST: An Efficient and Accurate Scene Text Detector. The features are summarized blow:
. dataset(you need to prepare for dataset for train and test) suggestions: you could do a soft-link to roottothisprogram/dataset/train/img/*.jpg + -- train ./dataset/train/img/img###.jpg ./dataset/train/gt/img###.txt (you need to change name) + -- test ./data/test/img###.jpg (img only) + -- gt.zip ./result/gt.zip(ICDAR15 gt.zip is avaliable on website
+ In config.py set resume True and set checkpoint path/to/weight/file + I will provide pretrianed weight soon
. check GPUs and CPUs you can use following to check aviliable gpu, this is for train
watch -n 0.1 nvidia-smithen, you will see 2,3 is avaliable, modify config.py gpuids = [0,1], gpu = 2, and modify run.sh - CUDAVISIBLE_DEVICES=2,3
If you want to train the model, you should provide the dataset path in config.py and run
** Note: you should modify run.sh to specify your gpu id
If you have more than one gpu, you can pass gpu ids to gpulist(like gpulist=0,1,2,3) in config.py
** Note: you should change the gt text file of icdar2015's filename to img*.txt instead of gtimg*.txt(or you can change the code in icdar.py), and some extra characters should be removed from the file. See the examples in trainingsamples/**
By default, we set train-eval process into integer. If you want to use eval independently, you can do it by yourself. Any question can contact me.
Here are some test examples on icdar2015, enjoy the beautiful text boxes!