F0416 21:56:18.036826 12284 concat_layer.cpp:42] Check failed: top_shape[j] == bottom[i]->shape(j) (75 vs. 76) All inputs must have the same shape, except at concat_axis. *** Check failure stack trace: *** Aborted (core dumped)

下载了您的代码,在运行demo.py的时候出现了这样的问题,怎么解决?

CTPN's performance on ICDAR 2013 dataset is F-measure 0.88 (R 0.83, P 0.93), not 0.822 in your paper (table 2 on page 11.) They published test model at https://github.com/tianzhi0549/CTPN (downloadable test model has F 0.86 on ICDAR 2013, which does not include side refinement feature described in the paper.)

CTPN does not handle angled text well, though. Their score on 2015 dataset is quite low.

Thanks for sharing the paper and repository. Wondering where to download your pretrained model file so that we can try with ICDAR 13 and 15 dataset. A pointer to training dataset will be great too.

论文中提到，将ICDAR2015将短边resize到900，ICDAR2013将短边resize到640，这是靠反复实验得到的一个参数吗？或者说有没有什么选择的方法？作者有没有考虑过multi-scale的测试？我换了数据，loss在训练一千次之后，一直到十万次，数值一直是在零点几到二点几之间波动，learning rate已经设置到1*e-5，感觉一直没有收敛，请问作者在之前实验过程中遇到过吗？

i am confused with the sentences below "For each diagonal, select any one corner from last two types and rotate the diagonal until three points (two endpoints and the third one) are collinear, then a quadrilateral proposal determined by those two diagonals will be obtained." how could three conners determine a quadrilateral proposal? while rotating the diagonal, where is the fixed point?

查看了作者读取数据集的函数，发现读取的是四个点八个坐标值，与网上的教程“将ICDAR21015转化为VOC2007”有所区别，那里提及的bndbox是以x,y,w,h,angle的格式制作annotations。我参照作者的代码，将数据集制作为如下格式，不知道与作者用于训练的VOC2007数据集的格式是否有差异？

After run test model on some test images (experiments/scripts/test.sh), got following lines (show 1st 10 lines here):

testimage-001 1.000 69.0 624.3 159.9 624.4 testimage-001 1.000 167.5 624.5 207.0 624.6 testimage-001 1.000 120.6 564.6 172.2 564.7 testimage-001 1.000 64.4 564.7 112.8 564.8 testimage-001 1.000 9.5 624.5 60.9 624.5 testimage-001 1.000 178.0 563.4 224.6 562.2 testimage-001 0.999 348.3 222.6 441.9 222.5 testimage-001 0.999 10.6 443.2 77.4 443.3 testimage-001 0.999 9.6 564.4 56.9 564.4 testimage-001 0.999 9.7 222.7 104.0 222.5 testimage-001 0.999 10.1 504.0 74.1 504.0

How to interpret them? It does not look like a boundbox in standard voc format (i.e. xmin,ymin,xmax,ymax), since y1 and y2 are so close to each other, does not look a valid boundbox.

[723.29144 542.9097 723.29144 552.94037 723.29144 552.94037 723.29144 542.9097 ] [270. nan 723.29144 555.44806 270. nan 723.29144 557.9557 ] [723.29144 560.4634 723.29144 562.97107 723.29144 562.97107 723.29144 560.4634 ]] Traceback (most recent call last): File "./tools/train_net.py", line 112, in max_iters=args.max_iters) File "/home/zq/crpn/tools/../lib/fast_rcnn/train.py", line 162, in train_net model_paths = sw.train_model(max_iters) File "/home/zq/crpn/tools/../lib/fast_rcnn/train.py", line 103, in train_model self.solver.step(1) File "/home/zq/crpn/tools/../lib/rpn/labelmap_layer.py", line 66, in forward x2 = int(round(bbox[2] * spatial_scale)) ValueError: cannot convert float NaN to integer

这样的错误是要删除对应的图片吗,还是修改sort_points中的代码?

I0423 10:43:13.650262 4174 net.cpp:242] This network produces output loss_rpn_bl I0423 10:43:13.650265 4174 net.cpp:242] This network produces output loss_rpn_br I0423 10:43:13.650269 4174 net.cpp:242] This network produces output loss_rpn_tl I0423 10:43:13.650272 4174 net.cpp:242] This network produces output loss_rpn_tr I0423 10:43:13.650315 4174 net.cpp:255] Network initialization done. I0423 10:43:13.650451 4174 solver.cpp:56] Solver scaffolding done. Loading pretrained model weights from Model/pretrain.caffemodel HDF5-DIAG: Error detected in HDF5 (1.10.1) thread 139667392706304: #000: H5F.c line 408 in H5Fis_hdf5(): unable open file major: File accessibilty minor: Not an HDF5 file #001: H5Fint.c line 532 in H5F__is_hdf5(): unable to open file major: Low-level I/O minor: Unable to initialize object #002: H5FD.c line 809 in H5FD_open(): open failed major: Virtual File Layer minor: Unable to initialize object #003: H5FDsec2.c line 346 in H5FD_sec2_open(): unable to open file: name = 'Model/pretrain.caffemodel', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0 major: File accessibilty minor: Unable to open file HDF5-DIAG: Error detected in HDF5 (1.10.1) thread 139667392706304: #000: H5F.c line 586 in H5Fopen(): unable to open file major: File accessibilty minor: Unable to open file #001: H5Fint.c line 1236 in H5F_open(): unable to open file: time = Mon Apr 23 10:43:13 2018 , name = 'Model/pretrain.caffemodel', tent_flags = 0 major: File accessibilty minor: Unable to open file #002: H5FD.c line 809 in H5FD_open(): open failed major: Virtual File Layer minor: Unable to initialize object #003: H5FDsec2.c line 346 in H5FD_sec2_open(): unable to open file: name = 'Model/pretrain.caffemodel', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0 major: File accessibilty minor: Unable to open file F0423 10:43:13.652704 4174 net.cpp:791] Check failed: file_hid >= 0 (-1 vs. 0) Couldn't open Model/pretrain.caffemodel *** Check failure stack trace: *** ./experiments/scripts/train.sh: line 55: 4174 Aborted (core dumped) ./tools/train_net.py --gpu 0 --solver models/${NET}/solver.pt --weights ${WEIGHTS} --imdb ${TRAIN_IMDB} --iters ${ITERS} --cfg models/${NET}/config.yml ${EXTRA_ARGS}

作者你好,这是什么错误?怎么解决

Hello @xhzdeng, I am trying to run your code. But when I run cd $CRPN_ROOT/caffe-fast-rcnn make -j8 && make pycaffe I got the following error Makefile:6: *** Makefile.config not found. See Makefile.config.example.. Stop.

Should I download more files?

some infomation,

• ./tools/test_net.py --gpu 0 --def models/vgg16/test.pt --net /home/deep3/work/crpn/models/vgg16/test.caffemodel --imdb voc_2007_test --cfg models/vgg16/config.yml Called with args: Namespace(caffemodel='/home/deep3/work/crpn/models/vgg16/test.caffemodel', cfg_file='models/vgg16/config.yml', comp_mode=False, gpu_id=0, imdb_name='voc_2007_test', max_per_image=100, prototxt='models/vgg16/test.pt', set_cfgs=None, vis=False, wait=True)

AP for text = 0.0459 Mean AP = 0.0459 Mean REC = 0.1231 Mean PREC = 0.1032

what's wrong? thanks

Hello, @xhzdeng I am trying to get F-measure for ICDAR2015 test subset. I change TEST.SCALES to 840 in config.yaml and save detentions to txt from lib/fast_rcnn/test.py just after the line 316 to be able to run ICDAR eval tool. For the provided test.caffemodel I am getting is only 0.8357763975155279.