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[DO_NOT_MERGE] Add samples for object localization and handwritten ocr (#1572)
* Add samples for object localization and handwritten ocr * Update to released lib * Update beta_snippets.py
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‎vision/cloud-client/detect/README.rst

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Beta Detect
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+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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.. image:: https://gstatic.com/cloudssh/images/open-btn.png
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:target: https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/GoogleCloudPlatform/python-docs-samples&page=editor&open_in_editor=vision/cloud-client/detect/beta_snippets.py,vision/cloud-client/detect/README.rst
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To run this sample:
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.. code-block:: bash
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$ python beta_snippets.py
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usage: beta_snippets.py [-h]
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{object-localization,object-localization-uri,handwritten-ocr,handwritten-ocr-uri}
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...
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Google Cloud Vision API Python Beta Snippets
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Example Usage:
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python beta_snippets.py -h
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python beta_snippets.py object-localizer INPUT_IMAGE
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python beta_snippets.py object-localizer-uri gs://...
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python beta_snippets.py handwritten-ocr INPUT_IMAGE
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python beta_snippets.py handwritten-ocr-uri gs://...
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For more information, the documentation at
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https://cloud.google.com/vision/docs.
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positional arguments:
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{object-localization,object-localization-uri,handwritten-ocr,handwritten-ocr-uri}
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object-localization
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Localize objects in the local image. Args: path: The
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path to the local file.
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object-localization-uri
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Localize objects in the image on Google Cloud Storage
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Args: uri: The path to the file in Google Cloud
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Storage (gs://...)
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handwritten-ocr Detects handwritten characters in a local image. Args:
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path: The path to the local file.
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handwritten-ocr-uri
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Detects handwritten characters in the file located in
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Google Cloud Storage. Args: uri: The path to the file
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in Google Cloud Storage (gs://...)
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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

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

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- name: Detect
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file: detect.py
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show_help: True
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- name: Beta Detect
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file: beta_snippets.py
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show_help: True
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cloud_client_library: true
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‎vision/cloud-client/detect/beta_snippets.py

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#!/usr/bin/env python
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# Copyright 2018 Google LLC
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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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"""
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Google Cloud Vision API Python Beta Snippets
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Example Usage:
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python beta_snippets.py -h
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python beta_snippets.py object-localization INPUT_IMAGE
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python beta_snippets.py object-localization-uri gs://...
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python beta_snippets.py handwritten-ocr INPUT_IMAGE
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python beta_snippets.py handwritten-ocr-uri gs://...
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For more information, the documentation at
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https://cloud.google.com/vision/docs.
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"""
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import argparse
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import io
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# [START vision_localize_objects]
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def localize_objects(path):
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"""Localize objects in the local image.
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Args:
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path: The path to the local file.
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"""
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from google.cloud import vision_v1p3beta1 as vision
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client = vision.ImageAnnotatorClient()
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with open(path, 'rb') as image_file:
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content = image_file.read()
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image = vision.types.Image(content=content)
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objects = client.object_localization(
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image=image).localized_object_annotations
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print('Number of objects found: {}'.format(len(objects)))
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for object_ in objects:
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print('\n{} (confidence: {})'.format(object_.name, object_.score))
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print('Normalized bounding polygon vertices: ')
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for vertex in object_.bounding_poly.normalized_vertices:
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print(' - ({}, {})'.format(vertex.x, vertex.y))
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# [END vision_localize_objects]
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# [START vision_localize_objects_uri]
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def localize_objects_uri(uri):
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"""Localize objects in the image on Google Cloud Storage
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Args:
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uri: The path to the file in Google Cloud Storage (gs://...)
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"""
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from google.cloud import vision_v1p3beta1 as vision
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client = vision.ImageAnnotatorClient()
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image = vision.types.Image()
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image.source.image_uri = uri
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objects = client.object_localization(
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image=image).localized_object_annotations
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print('Number of objects found: {}'.format(len(objects)))
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for object_ in objects:
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print('\n{} (confidence: {})'.format(object_.name, object_.score))
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print('Normalized bounding polygon vertices: ')
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for vertex in object_.bounding_poly.normalized_vertices:
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print(' - ({}, {})'.format(vertex.x, vertex.y))
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# [END vision_localize_objects_uri]
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# [START vision_handwritten_ocr]
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def detect_handwritten_ocr(path):
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"""Detects handwritten characters in a local image.
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Args:
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path: The path to the local file.
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"""
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from google.cloud import vision_v1p3beta1 as vision
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client = vision.ImageAnnotatorClient()
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with io.open(path, 'rb') as image_file:
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content = image_file.read()
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image = vision.types.Image(content=content)
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# Language hint codes for handwritten OCR:
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# en-t-i0-handwrit, mul-Latn-t-i0-handwrit
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# Note: Use only one language hint code per request for handwritten OCR.
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image_context = vision.types.ImageContext(
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language_hints=['en-t-i0-handwrit'])
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response = client.document_text_detection(image=image,
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image_context=image_context)
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print('Full Text: {}'.format(response.full_text_annotation.text))
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for page in response.full_text_annotation.pages:
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for block in page.blocks:
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print('\nBlock confidence: {}\n'.format(block.confidence))
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for paragraph in block.paragraphs:
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print('Paragraph confidence: {}'.format(
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paragraph.confidence))
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for word in paragraph.words:
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word_text = ''.join([
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symbol.text for symbol in word.symbols
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])
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print('Word text: {} (confidence: {})'.format(
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word_text, word.confidence))
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for symbol in word.symbols:
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print('\tSymbol: {} (confidence: {})'.format(
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symbol.text, symbol.confidence))
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# [END vision_handwritten_ocr]
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# [START vision_handwritten_ocr_uri]
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def detect_handwritten_ocr_uri(uri):
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"""Detects handwritten characters in the file located in Google Cloud
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Storage.
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Args:
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uri: The path to the file in Google Cloud Storage (gs://...)
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"""
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from google.cloud import vision_v1p3beta1 as vision
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client = vision.ImageAnnotatorClient()
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image = vision.types.Image()
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image.source.image_uri = uri
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# Language hint codes for handwritten OCR:
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# en-t-i0-handwrit, mul-Latn-t-i0-handwrit
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# Note: Use only one language hint code per request for handwritten OCR.
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image_context = vision.types.ImageContext(
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language_hints=['en-t-i0-handwrit'])
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response = client.document_text_detection(image=image,
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image_context=image_context)
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print('Full Text: {}'.format(response.full_text_annotation.text))
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for page in response.full_text_annotation.pages:
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for block in page.blocks:
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print('\nBlock confidence: {}\n'.format(block.confidence))
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for paragraph in block.paragraphs:
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print('Paragraph confidence: {}'.format(
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paragraph.confidence))
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for word in paragraph.words:
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word_text = ''.join([
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symbol.text for symbol in word.symbols
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])
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print('Word text: {} (confidence: {})'.format(
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word_text, word.confidence))
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for symbol in word.symbols:
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print('\tSymbol: {} (confidence: {})'.format(
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symbol.text, symbol.confidence))
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# [END vision_handwritten_ocr_uri]
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(
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description=__doc__,
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formatter_class=argparse.RawDescriptionHelpFormatter)
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subparsers = parser.add_subparsers(dest='command')
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object_parser = subparsers.add_parser(
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'object-localization', help=localize_objects.__doc__)
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object_parser.add_argument('path')
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object_uri_parser = subparsers.add_parser(
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'object-localization-uri', help=localize_objects_uri.__doc__)
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object_uri_parser.add_argument('uri')
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handwritten_parser = subparsers.add_parser(
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'handwritten-ocr', help=detect_handwritten_ocr.__doc__)
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handwritten_parser.add_argument('path')
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handwritten_uri_parser = subparsers.add_parser(
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'handwritten-ocr-uri', help=detect_handwritten_ocr_uri.__doc__)
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handwritten_uri_parser.add_argument('uri')
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args = parser.parse_args()
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if 'uri' in args.command:
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if 'object-localization-uri' in args.command:
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localize_objects_uri(args.uri)
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elif 'handwritten-ocr-uri' in args.command:
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detect_handwritten_ocr_uri(args.uri)
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else:
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if 'object-localization' in args.command:
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localize_objects(args.path)
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elif 'handwritten-ocr' in args.command:
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detect_handwritten_ocr(args.path)

‎vision/cloud-client/detect/beta_snippets_test.py

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# Copyright 2018 Google LLC 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 beta_snippets
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RESOURCES = os.path.join(os.path.dirname(__file__), 'resources')
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def test_localize_objects(capsys):
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path = os.path.join(RESOURCES, 'puppies.jpg')
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beta_snippets.localize_objects(path)
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out, _ = capsys.readouterr()
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assert 'Dog' in out
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def test_localize_objects_uri(capsys):
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uri = 'gs://cloud-samples-data/vision/puppies.jpg'
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beta_snippets.localize_objects_uri(uri)
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out, _ = capsys.readouterr()
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assert 'Dog' in out
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def test_handwritten_ocr(capsys):
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path = os.path.join(RESOURCES, 'handwritten.jpg')
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beta_snippets.detect_handwritten_ocr(path)
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out, _ = capsys.readouterr()
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assert 'Cloud Vision API' in out
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def test_handwritten_ocr_uri(capsys):
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uri = 'gs://cloud-samples-data/vision/handwritten.jpg'
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beta_snippets.detect_handwritten_ocr_uri(uri)
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out, _ = capsys.readouterr()
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assert 'Cloud Vision API' in out

‎vision/cloud-client/detect/requirements.txt

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google-cloud-vision==0.32.0
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google-cloud-vision==0.33.0
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google-cloud-storage==1.6.0

‎vision/cloud-client/detect/resources/duck_and_truck.jpg

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‎vision/cloud-client/detect/resources/handwritten.jpg

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‎vision/cloud-client/detect/resources/puppies.jpg

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