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Adds document text detection tutorial.
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‎vision/cloud-client/document_text/README.rst‎

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.. This file is automatically generated. Do not edit this file directly.
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Google Cloud Vision API Python Samples
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===============================================================================
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This directory contains samples for Google Cloud Vision API. `Google Cloud Vision API`_ allows developers to easily integrate vision detection features within applications, including image labeling, face and landmark detection, optical character recognition (OCR), and tagging of explicit content
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.. _Google Cloud Vision API: https://cloud.google.com/vision/docs
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Setup
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-------------------------------------------------------------------------------
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Authentication
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++++++++++++++
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Authentication is typically done through `Application Default Credentials`_,
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which means you do not have to change the code to authenticate as long as
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your environment has credentials. You have a few options for setting up
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authentication:
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#. When running locally, use the `Google Cloud SDK`_
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.. code-block:: bash
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gcloud beta auth application-default login
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#. When running on App Engine or Compute Engine, credentials are already
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set-up. However, you may need to configure your Compute Engine instance
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with `additional scopes`_.
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#. You can create a `Service Account key file`_. This file can be used to
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authenticate to Google Cloud Platform services from any environment. To use
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the file, set the ``GOOGLE_APPLICATION_CREDENTIALS`` environment variable to
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the path to the key file, for example:
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.. code-block:: bash
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export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service_account.json
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.. _Application Default Credentials: https://cloud.google.com/docs/authentication#getting_credentials_for_server-centric_flow
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.. _additional scopes: https://cloud.google.com/compute/docs/authentication#using
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.. _Service Account key file: https://developers.google.com/identity/protocols/OAuth2ServiceAccount#creatinganaccount
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Install Dependencies
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++++++++++++++++++++
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#. Install `pip`_ and `virtualenv`_ if you do not already have them.
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#. Create a virtualenv. Samples are compatible with Python 2.7 and 3.4+.
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.. code-block:: bash
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$ virtualenv env
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$ source env/bin/activate
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#. Install the dependencies needed to run the samples.
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.. code-block:: bash
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$ pip install -r requirements.txt
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.. _pip: https://pip.pypa.io/
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.. _virtualenv: https://virtualenv.pypa.io/
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Samples
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-------------------------------------------------------------------------------
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Document Text tutorial
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+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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To run this sample:
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.. code-block:: bash
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$ python doctext.py
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usage: doctext.py [-h] image_file
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positional arguments:
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image_file The image for text detection.
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optional arguments:
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-h, --help show this help message and exit
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The client library
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-------------------------------------------------------------------------------
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This sample uses the `Google Cloud Client Library for Python`_.
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You can read the documentation for more details on API usage and use GitHub
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to `browse the source`_ and `report issues`_.
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.. Google Cloud Client Library for Python:
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https://googlecloudplatform.github.io/google-cloud-python/
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.. browse the source:
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https://github.com/GoogleCloudPlatform/google-cloud-python
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.. report issues:
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https://github.com/GoogleCloudPlatform/google-cloud-python/issues
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.. _Google Cloud SDK: https://cloud.google.com/sdk/

‎vision/cloud-client/document_text/README.rst.in‎

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# This file is used to generate README.rst
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product:
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name: Google Cloud Vision API
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short_name: Cloud Vision API
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url: https://cloud.google.com/vision/docs
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description: >
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`Google Cloud Vision API`_ allows developers to easily integrate vision
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detection features within applications, including image labeling, face and
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landmark detection, optical character recognition (OCR), and tagging of
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explicit content.
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setup:
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- auth
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- install_deps
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samples:
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- name: Document Text tutorial
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file: doctext.py
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show_help: True
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cloud_client_library: true

‎vision/cloud-client/document_text/doctext.py‎

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#!/usr/bin/env python
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# Copyright 2017 Google Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Outlines document text given an image.
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Example:
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python doctext.py resources/cropme.jpg
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"""
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# [START full_tutorial]
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# [START imports]
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import argparse
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from enum import Enum
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import io
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from google.cloud import vision
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from PIL import Image, ImageDraw
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# [END imports]
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class FeatureType(Enum):
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PAGE = 1
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BLOCK = 2
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PARA = 3
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WORD = 4
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SYMBOL = 5
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def draw_boxes(im, blocks, color, width):
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"""Draw a border around the image using the hints in the vector list."""
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# [START draw_blocks]
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draw = ImageDraw.Draw(im)
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for block in blocks:
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draw.line([block.vertices[0].x, block.vertices[0].y,
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block.vertices[1].x, block.vertices[1].y],
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fill=color, width=width)
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draw.line([block.vertices[1].x, block.vertices[1].y,
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block.vertices[2].x, block.vertices[2].y],
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fill=color, width=width)
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draw.line([block.vertices[2].x, block.vertices[2].y,
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block.vertices[3].x, block.vertices[3].y],
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fill=color, width=width)
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draw.line([block.vertices[3].x, block.vertices[3].y,
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block.vertices[0].x, block.vertices[0].y],
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fill=color, width=width)
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return im
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# [END draw_blocks]
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def get_document_bounds(image_file, feature):
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# [START detect_bounds]
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"""Returns document bounds given an image."""
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vision_client = vision.Client()
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bounds = []
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with io.open(image_file, 'rb') as image_file:
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content = image_file.read()
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image = vision_client.image(content=content)
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document = image.detect_full_text()
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for b, page in enumerate(document.pages):
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for bb, block in enumerate(page.blocks):
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for p, paragraph in enumerate(block.paragraphs):
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for w, word in enumerate(paragraph.words):
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for s, symbol in enumerate(word.symbols):
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if (feature == FeatureType.SYMBOL):
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bounds.append(symbol.bounding_box)
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if (feature == FeatureType.WORD):
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bounds.append(word.bounding_box)
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if (feature == FeatureType.PARA):
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bounds.append(paragraph.bounding_box)
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if (feature == FeatureType.BLOCK):
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bounds.append(block.bounding_box)
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if (feature == FeatureType.PAGE):
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bounds.append(block.bounding_box)
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return bounds
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# [END detect_bounds]
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def render_doc_text(filein, fileout):
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# [START render_doc_text]
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im = Image.open(filein)
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bounds = get_document_bounds(filein, FeatureType.PAGE)
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draw_boxes(im, bounds, 'blue', 3)
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bounds = get_document_bounds(filein, FeatureType.PARA)
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draw_boxes(im, bounds, 'green', 2)
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bounds = get_document_bounds(filein, FeatureType.WORD)
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draw_boxes(im, bounds, 'yellow', 1)
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if fileout is not 0:
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im.save(fileout)
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else:
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im.show()
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# [END render_doc_text]
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if __name__ == '__main__':
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# [START run_crop]
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parser = argparse.ArgumentParser()
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parser.add_argument('detect_file', help='The image for text detection.')
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parser.add_argument('-out_file', help='Optional output file', default=0)
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args = parser.parse_args()
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parser = argparse.ArgumentParser()
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render_doc_text(args.detect_file, args.out_file)
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# [END run_crop]
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# [END full_tutorial]

‎vision/cloud-client/document_text/doctext_test.py‎

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# Copyright 2017 Google Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import doctext
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def test_text(cloud_config, capsys):
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"""Checks the output image for drawing the crop hint is created."""
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doctext.render_doc_text('resources/text_menu.jpg', 'output-text.jpg')
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out, _ = capsys.readouterr()
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assert os.path.isfile('output-text.jpg')

‎vision/cloud-client/document_text/requirements.txt‎

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google-cloud-vision==0.23.2
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pillow==4.0.0

‎vision/cloud-client/document_text/resources/text_menu.jpg‎

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