Datasets:

datnguyentien204
/

BLIP_ImagesCaptioning

#!/usr/bin/env python
# 
# File Name : ptbtokenizer.py
#
# Description : Do the PTB Tokenization and remove punctuations.
#
# Creation Date : 29-12-2014
# Last Modified : Thu Mar 19 09:53:35 2015
# Authors : Hao Fang <hfang@uw.edu> and Tsung-Yi Lin <tl483@cornell.edu>
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import os
import sys
import subprocess
import tempfile
import itertools

# path to the stanford corenlp jar
STANFORD_CORENLP_3_4_1_JAR = 'stanford-corenlp-3.4.1.jar'

# punctuations to be removed from the sentences
PUNCTUATIONS = ["''", "'", "``", "`", "-LRB-", "-RRB-", "-LCB-", "-RCB-", \
        ".", "?", "!", ",", ":", "-", "--", "...", ";"] 

class PTBTokenizer:
    """Python wrapper of Stanford PTBTokenizer"""

    def tokenize(self, captions_for_image):
        cmd = ['java', '-cp', STANFORD_CORENLP_3_4_1_JAR, \
                'edu.stanford.nlp.process.PTBTokenizer', \
                '-preserveLines', '-lowerCase']

        # ======================================================
        # prepare data for PTB Tokenizer
        # ======================================================
        final_tokenized_captions_for_image = {}
        image_id = [k for k, v in list(captions_for_image.items()) for _ in range(len(v))]
        sentences = '\n'.join([c['caption'].replace('\n', ' ') for k, v in list(captions_for_image.items()) for c in v])

        # ======================================================
        # save sentences to temporary file
        # ======================================================
        path_to_jar_dirname=os.path.dirname(os.path.abspath(__file__))
        tmp_file = tempfile.NamedTemporaryFile(delete=False, dir=path_to_jar_dirname)
        tmp_file.write(sentences.encode('utf-8'))
        tmp_file.close()

        # ======================================================
        # tokenize sentence
        # ======================================================
        cmd.append(os.path.basename(tmp_file.name))
        p_tokenizer = subprocess.Popen(cmd, cwd=path_to_jar_dirname, \
                stdout=subprocess.PIPE)
        token_lines = p_tokenizer.communicate(input=sentences.rstrip())[0]
        lines = token_lines.decode("utf-8").split('\n')
        # remove temp file
        os.remove(tmp_file.name)

        # ======================================================
        # create dictionary for tokenized captions
        # ======================================================
        for k, line in zip(image_id, lines):
            if not k in final_tokenized_captions_for_image:
                final_tokenized_captions_for_image[k] = []
            tokenized_caption = ' '.join([w for w in line.rstrip().split(' ') \
                    if w not in PUNCTUATIONS])
            final_tokenized_captions_for_image[k].append(tokenized_caption)

        return final_tokenized_captions_for_image

	#!/usr/bin/env python
	#
	# File Name : ptbtokenizer.py
	#
	# Description : Do the PTB Tokenization and remove punctuations.
	#
	# Creation Date : 29-12-2014
	# Last Modified : Thu Mar 19 09:53:35 2015
	# Authors : Hao Fang <hfang@uw.edu> and Tsung-Yi Lin <tl483@cornell.edu>
	from __future__ import absolute_import
	from __future__ import division
	from __future__ import print_function

	import os
	import sys
	import subprocess
	import tempfile
	import itertools

	# path to the stanford corenlp jar
	STANFORD_CORENLP_3_4_1_JAR = 'stanford-corenlp-3.4.1.jar'

	# punctuations to be removed from the sentences
	PUNCTUATIONS = ["''", "'", "``", "`", "-LRB-", "-RRB-", "-LCB-", "-RCB-", \
	".", "?", "!", ",", ":", "-", "--", "...", ";"]

	class PTBTokenizer:
	"""Python wrapper of Stanford PTBTokenizer"""

	def tokenize(self, captions_for_image):
	cmd = ['java', '-cp', STANFORD_CORENLP_3_4_1_JAR, \
	'edu.stanford.nlp.process.PTBTokenizer', \
	'-preserveLines', '-lowerCase']

	# ======================================================
	# prepare data for PTB Tokenizer
	# ======================================================
	final_tokenized_captions_for_image = {}
	image_id = [k for k, v in list(captions_for_image.items()) for _ in range(len(v))]
	sentences = '\n'.join([c['caption'].replace('\n', ' ') for k, v in list(captions_for_image.items()) for c in v])

	# ======================================================
	# save sentences to temporary file
	# ======================================================
	path_to_jar_dirname=os.path.dirname(os.path.abspath(__file__))
	tmp_file = tempfile.NamedTemporaryFile(delete=False, dir=path_to_jar_dirname)
	tmp_file.write(sentences.encode('utf-8'))
	tmp_file.close()

	# ======================================================
	# tokenize sentence
	# ======================================================
	cmd.append(os.path.basename(tmp_file.name))
	p_tokenizer = subprocess.Popen(cmd, cwd=path_to_jar_dirname, \
	stdout=subprocess.PIPE)
	token_lines = p_tokenizer.communicate(input=sentences.rstrip())[0]
	lines = token_lines.decode("utf-8").split('\n')
	# remove temp file
	os.remove(tmp_file.name)

	# ======================================================
	# create dictionary for tokenized captions
	# ======================================================
	for k, line in zip(image_id, lines):
	if not k in final_tokenized_captions_for_image:
	final_tokenized_captions_for_image[k] = []
	tokenized_caption = ' '.join([w for w in line.rstrip().split(' ') \
	if w not in PUNCTUATIONS])
	final_tokenized_captions_for_image[k].append(tokenized_caption)

	return final_tokenized_captions_for_image