Re-implement CVPR2017 paper: "dense captioning with joint inference and visual context" and minor changes in Tensorflow. (mAP 8.296 after 500k iters of training)
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TypeError: a bytes-like object is required, not 'str' #40
hello
when i try to this
$ cd $ROOT/lib
$ python preprocess.py --version [version] --path [raw_data_path] \
--output_dir [dir] --max_words [max_len]$ cd $ROOT/lib ,
i have type error..
split image number: 77398 for split name: train
start loading json files...
10.529908 seconds for loading
train: 0%| | 0/108077 [00:00<?, ?it/s]
Traceback (most recent call last):
File "preprocess.py", line 226, in
process_vg()
File "preprocess.py", line 222, in process_vg
vocab = process_dataset(split_name, vocab=vocab)
File "preprocess.py", line 196, in process_dataset
split_ids=split_image_ids, vocab=vocab)
File "preprocess.py", line 117, in init
obj['phrase_tokens'] = phrase.translate(None, string.punctuation).split()
TypeError: a bytes-like object is required, not 'str'
hello when i try to this $ cd $ROOT/lib $ python preprocess.py --version [version] --path [raw_data_path] \ --output_dir [dir] --max_words [max_len]$ cd $ROOT/lib ,
i have type error..
split image number: 77398 for split name: train start loading json files... 10.529908 seconds for loading train: 0%| | 0/108077 [00:00<?, ?it/s] Traceback (most recent call last): File "preprocess.py", line 226, in
process_vg()
File "preprocess.py", line 222, in process_vg
vocab = process_dataset(split_name, vocab=vocab)
File "preprocess.py", line 196, in process_dataset
split_ids=split_image_ids, vocab=vocab)
File "preprocess.py", line 117, in init
obj['phrase_tokens'] = phrase.translate(None, string.punctuation).split()
TypeError: a bytes-like object is required, not 'str'
how to fix it?