def rundetection(output_directory, pdf_path):
"""Detect figures from the pdf at PDF_PATH.
Detect the figures from the pdf located at PDF_PATH and write the
detection results to the directory specified by OUTPUT_DIRECTORY.
"""
# import lazily to speed up response time for returning help text
from deepfigures.extraction import pipeline
figure_extractor = pipeline.FigureExtractionPipeline()
figure_extractor.extract(pdf_path, output_directory)
def test_extract(self):
"""Test extract against a known extraction."""
pdf_path = "/work/tests/data/endtoend/paper.pdf"
figure_extractor = pipeline.FigureExtractionPipeline()
with tempfile.TemporaryDirectory() as tmp_dir:
figure_extraction = figure_extractor.extract(pdf_path, tmp_dir)
test.test_deepfigures_json(
self,
expected_json=
'/work/tests/data/endtoend/_work_tests_data_endtoend_paper.pdf-result.json',
actual_json=figure_extraction.deepfigures_json_path)
"""Detect the figures in a PDF."""
import logging
import os
import click
logger = logging.getLogger(__name__)
from deepfigures.extraction import pipeline
figure_extractor = pipeline.FigureExtractionPipeline()
# @click.command(
# context_settings={
# 'help_option_names': ['-h', '--help']
# })
# @click.argument(
# 'output_directory',
# type=click.Path(file_okay=False))
# @click.argument(
# 'pdf_path',
# type=click.Path(exists=True, dir_okay=False))
def rundetection(output_directory, pdf_path):
"""Detect figures from the pdf at PDF_PATH.
Detect the figures from the pdf located at PDF_PATH and write the
detection results to the directory specified by OUTPUT_DIRECTORY.
"""
print(output_directory, pdf_path)
# import lazily to speed up response time for returning help text