Comments (8)
@padmareddy21 Generate tfrecords first:)
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No I generated using python tools/write_tfrecords
--dataset_dir PATH/TO/SYNTH90K_DATASET_ROOT_DIR
--save_dir PATH/TO/TFRECORDS_DIR with this command
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@padmareddy21 replace PATH/TO/SYNTH90K_DATASET_ROOT_DIR with your own path
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yes I used my data set's path
python write_tfrecords.py --dataset_dir mnt/ramdisk/max/90kDICT32px --save_dir records_dir
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python train_shadownet.py --dataset_dir tfrecords --char_dict_path data/char_dict/char_dict.json --ord_map_dict_path data/char_dict/ord_map.json
I0813 00:21:33.093167 20187 train_shadownet.py:569] Use single gpu to train the model
Traceback (most recent call last):
File "train_shadownet.py", line 575, in
need_decode=args.decode_outputs
File "train_shadownet.py", line 144, in train_shadownet
flags='train'
File "/home/avenir-dl/Desktop/ocr/CRNN_Tensorflow/tools/data_provider/shadownet_data_feed_pipline.py", line 240, in init
raise ValueError('{:s} not exist, please check again'.format(self._tfrecords_dir))
ValueError: tfrecords/tfrecords not exist, please check again
--dataset_dir tfrecords is the wrong path. It should be the folder dir where the tfrecords was placed.
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tfrecords are generated using this command (python write_tfrecords.py --dataset_dir mnt/ramdisk/max/90kDICT32px --save_dir records_dir) and I am giving same records_dir path exactly
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@padmareddy21 The error log was pretty clear. tfrecords folder was not found. Maybe you can figure it out by yourself:)
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@padmareddy21 mkdir tfrecords inside records_dir and then move all the tfrecord files into tfrecords folder
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