hi,huoyijie，在label的时候，有个地方不太理解，就是这里的后四位，表示的是每一个点和最长边的点的距离吗？ gt[i, j, 3:5] = xy_list[vs[long_edge][ith][0]] - [px, py]

gt[i, j, 5:] = xy_list[vs[long_edge][ith][1]] - [px, py]

这里的xy_list[]记录的是这个4个点，按顺时针顺序存储的

这里的后四位gt[i,j,3:7]存储的表示 [px,py]这个点到这两个长边点的距离吗？为什么要计算这个距离呢？

@huoyijie 您好，谢谢您代码的分享。我遇到一些问题，没找到头绪，想要咨询一下。 首先，我要检测的是自然场景下的文字，所以我对训练数据集进行了更改，使用的是ICDAR 2017的数据集和自己标注的数据集，后面找了一些图片进行测试。发现一些问题，有很多图片出现了有头无尾，有尾无头，无头无尾，以及相邻两行之间交叉，分不开的情况，可是我找不到原因以及怎么改善？可以给我一些建议吗？研三了，比较急，谢谢啦

Hi! I try to train my own datasets with your pre-trained weights. First I set load_weights=True in cfg.py, then an error occurs in advanced_east.py as follow：

Traceback (most recent call last): File "D:/Workspace/Ad_new/advanced_east.py", line 17, in main east_network.load_weights(cfg.saved_model_weights_file_path) File "D:\ProgramData\Anaconda3\envs\gpu\lib\site-packages\tensorflow\python\keras\engine\network.py", line 1391, in load_weights saving.load_weights_from_hdf5_group(f, self.layers) File "D:\ProgramData\Anaconda3\envs\gpu\lib\site-packages\tensorflow\python\keras\engine\saving.py", line 732, in load_weights_from_hdf5_group ' layers.') ValueError: You are trying to load a weight file containing 30 layers into a model with 1 layers.

According to stackoverflow, I rewrite advanced_east.py ：

import os
from tensorflow.python.keras.callbacks import EarlyStopping, ModelCheckpoint
from tensorflow.python.keras.optimizers import Adam
from tensorflow.python.keras.models import load_model
from tensorflow.python.keras.models import model_from_json

import cfg
from network import East
from losses import quad_loss
from data_generator import gen

east = East()
east_network = east.east_network()

if cfg.load_weights and os.path.exists(cfg.saved_model_weights_file_path):
  east_network.load_weights(cfg.saved_model_weights_file_path, by_name=True)
  json_string = east_network.to_json()
  east_network = model_from_json(json_string)

east_network.summary()
east_network.compile(loss=quad_loss, optimizer=Adam(lr=cfg.lr,
                                                    # clipvalue=cfg.clipvalue,
                                                    decay=cfg.decay))

east_network.fit_generator(generator=gen(),
                           steps_per_epoch=cfg.steps_per_epoch,
                           epochs=cfg.epoch_num,
                           validation_data=gen(is_val=True),
                           validation_steps=cfg.validation_steps,
                           verbose=1,
                           # use_multiprocessing=True,
                           initial_epoch=cfg.initial_epoch,
                           callbacks=[
                               EarlyStopping(patience=cfg.patience, verbose=1),
                               ModelCheckpoint(filepath=cfg.model_weights_path,
                                               save_best_only=False,
                                               save_weights_only=True,
                                               verbose=1)])
east_network.save(cfg.saved_model_file_path)
east_network.save_weights(cfg.saved_model_weights_file_path)

After then, my training process started successfully. While I tried to predict images with my trained weights east_model_weights_3T736.h5 in folder saved_model , the error showing up again:

Traceback (most recent call last): File "D:/Workspace/Ad_new/test_img.py", line 163, in main() File "D:/Workspace/Ad_new/test_img.py", line 137, in main east_detect.load_weights("saved_model/east_model_weights_3T736.h5") File "D:\ProgramData\Anaconda3\envs\gpu\lib\site-packages\tensorflow\python\keras\engine\network.py", line 1391, in load_weights saving.load_weights_from_hdf5_group(f, self.layers) File "D:\ProgramData\Anaconda3\envs\gpu\lib\site-packages\tensorflow\python\keras\engine\saving.py", line 732, in load_weights_from_hdf5_group ' layers.') ValueError: You are trying to load a weight file containing 1 layers into a model with 30 layers.

I wanted to use the same solution and code as follow：

  east = East()
  east_detect = east.east_network()
  east_detect.load_weights("saved_model/east_model_weights_3T736.h5", by_name=True)
  json_string = east_detect.to_json()
  east_detect = model_from_json(json_string)

Here occurs new error：

File "D:/Workspace/Ad_new/test_img.py", line 163, in main() File "D:/Workspace/Ad_new/test_img.py", line 130, in main east_detect.load_weights("saved_model/east_model_weights_3T736.h5", by_name=True) File "D:\ProgramData\Anaconda3\envs\gpu\lib\site-packages\tensorflow\python\keras\engine\network.py", line 1389, in load_weights saving.load_weights_from_hdf5_group_by_name(f, self.layers) File "D:\ProgramData\Anaconda3\envs\gpu\lib\site-packages\tensorflow\python\keras\engine\saving.py", line 810, in load_weights_from_hdf5_group_by_name K.batch_set_value(weight_value_tuples) File "D:\ProgramData\Anaconda3\envs\gpu\lib\site-packages\tensorflow\python\keras\backend.py", line 2711, in batch_set_value assign_op = x.assign(assign_placeholder) File "D:\ProgramData\Anaconda3\envs\gpu\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 945, in assign self._shape.assert_is_compatible_with(value_tensor.shape) File "D:\ProgramData\Anaconda3\envs\gpu\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 847, in assert_is_compatible_with raise ValueError("Shapes %s and %s are incompatible" % (self, other)) ValueError: Shapes (128,) and (1024,) are incompatible

Am I using a wrong way loading or saving weights? And is there anyone else facing the same problem?

when I use the file ‘east_model_weights_2T736.h5’, Error comes up. ValueError: You are trying to load a weight file containing 58 layers into a model with 30 layers. It seems the weight file does not match.

I want to test the pre-train model the environment : ubuntu16.04 python2.7 tensorflow==1.5.0

I put my test image in the demo,here is my command --python predict.py -p demo/1.jpg

but i got error:

please help me

头尾按照属于第一个poly进行标记，但是初始map为0, 属于head-side的ith=0，属于tail-side的ith=1，no-side的ith=-1，如此标记的话，head-side与non-side的值都为0，这部分可视化出来会发现只有tail没有head，在训练过程中head的损失计算会出现错误。这里作者认为如何

the code resize the image to max 736 pixel wide before processing the detection, this makes the text in the image (larger than 1000 pixel wide) too small to detect, and leads to inaccuracy.

if I change the resize process, i got resource exhausted error. do you have any ideas how to solve this?

Downloading data from https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5

8192/58889256 [..............................] - ETA: 38:30

24576/58889256 [..............................] - ETA: 47:25 40960/58889256 [..............................] - ETA: 39:50 57344/58889256 [..............................] - ETA: 39:34Traceback (most recent call last):

i do not know how to solve it????

File "/home/louj1/pywork/AEAST/data_generator.py", line 37, in gen y[i] = np.load(gt_file) ValueError: could not broadcast input array from shape (21,4,2) into shape (64,64,7)

Hi I am trying to run the training and am getting the following error:

 File "D:\AdvancedEAST\data_generator.py", line 33, in gen
    img

ValueError: could not broadcast input array from shape (720,1280,3) into shape (736,736,3)

Did you ever get such an error? Any suggestions? My data includes just a few images for merely initiating the training loop.

The tree structure of the files used for training is displayed below:

Respected moderator I would venture to ask, this Advanced EAST did not see the training entrance, it is estimated that many people like me are looking for. Thank you.

使用作者提供的模型，同时使用tensorflow中的模型优化包对模型进行裁剪，但是出现如下错误： prune_low_magnitude can only prune an object of the following types: tf.keras.models.Sequential, tf.keras functional model, tf.keras.layers.Layer, list of tf.keras.layers.Layer. You passed an object of type: Model.

你的检测结果是好的吗，为什么我的检测结果很差，可以邮件交流吗？[email protected]

我的检测很好，看你的场景吧，[email protected]

_Originally posted by @yahuuu in https://github.com/huoyijie/AdvancedEAST/issues/114#issuecomment-659986151 我的检测效果也很差，用的就是他给的数据集，，，请教一下[email protected] _