Google Cloud Vision API Python Samples

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

.. _Google Cloud Vision API: https://cloud.google.com/vision/docs

Setup

Authentication

Authentication is typically done through `Application Default Credentials`_,

which means you do not have to change the code to authenticate as long as

your environment has credentials. You have a few options for setting up

authentication:

#. When running locally, use the `Google Cloud SDK`_

.. code-block:: bash

#. When running on App Engine or Compute Engine, credentials are already

set-up. However, you may need to configure your Compute Engine instance

with `additional scopes`_.

#. You can create a `Service Account key file`_. This file can be used to

authenticate to Google Cloud Platform services from any environment. To use

the file, set the ``GOOGLE_APPLICATION_CREDENTIALS`` environment variable to

the path to the key file, for example:

.. code-block:: bash

.. _Application Default Credentials: https://cloud.google.com/docs/authentication#getting_credentials_for_server-centric_flow

.. _additional scopes: https://cloud.google.com/compute/docs/authentication#using

.. _Service Account key file: https://developers.google.com/identity/protocols/OAuth2ServiceAccount#creatinganaccount

Install Dependencies

#. Install `pip`_ and `virtualenv`_ if you do not already have them.

#. Create a virtualenv. Samples are compatible with Python 2.7 and 3.4+.

.. code-block:: bash

#. Install the dependencies needed to run the samples.

.. code-block:: bash

.. _pip: https://pip.pypa.io/

.. _virtualenv: https://virtualenv.pypa.io/

Samples

Web

To run this sample:

.. code-block:: bash

The client library

This sample uses the `Google Cloud Client Library for Python`_.

You can read the documentation for more details on API usage and use GitHub

to `browse the source`_ and `report issues`_.

.. _Google Cloud SDK: https://cloud.google.com/sdk/

# This file is used to generate README.rst

product:

name: Google Cloud Vision API

short_name: Cloud Vision API

url: https://cloud.google.com/vision/docs

description: >

`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

setup:

- auth

- install_deps

samples:

- name: Web

file: web_detect.py

show_help: True

cloud_client_library: true

import argparse

import io

from google.cloud import vision

def annotate(path):

"""Returns web annotations given the path to an image."""

# [START get_annotations]

image = None

vision_client = vision.Client()

if path.startswith('http') or path.startswith('gs:'):

image = vision_client.image(source_uri=path)

else:

with io.open(path, 'rb') as image_file:

content = image_file.read()

image = vision_client.image(content=content)

return image.detect_web()

# [END get_annotations]

def report(annotations):

"""Prints detected features in the provided web annotations."""

# [START print_annotations]

if annotations.pages_with_matching_images:

print('\n{} Pages with matching images retrieved')

for page in annotations.pages_with_matching_images:

print('Score : {}'.format(page.score))

print('Url : {}'.format(page.url))

if annotations.full_matching_images:

print ('\n{} Full Matches found: '.format(

len(annotations.full_matching_images)))

for image in annotations.full_matching_images:

print('Score: {}'.format(image.score))

print('Url : {}'.format(image.url))

if annotations.partial_matching_images:

print ('\n{} Partial Matches found: '.format(

len(annotations.partial_matching_images)))

for image in annotations.partial_matching_images:

print('Score: {}'.format(image.score))

print('Url : {}'.format(image.url))

if annotations.web_entities:

print ('\n{} Web entities found: '.format(

len(annotations.web_entities)))

for entity in annotations.web_entities:

print('Score : {}'.format(entity.score))

print('Description: {}'.format(entity.description))

# [END print_annotations]

if __name__ == '__main__':

# [START run_web]

parser = argparse.ArgumentParser(

description=__doc__,

formatter_class=argparse.RawDescriptionHelpFormatter)

path_help = str('The image to detect, can be web URI, '

'Google Cloud Storage, or path to local file.')

parser.add_argument('image_url', help=path_help)

args = parser.parse_args()

report(annotate(args.image_url))

# [END run_web]

import web_detect

def test_detect_file(cloud_config, capsys):

file_name = ('../detect/resources/landmark.jpg')

web_detect.report(web_detect.annotate(file_name))

out, _ = capsys.readouterr()

assert 'Description: Palace of Fine Arts Theatre' in out

def test_detect_web_gsuri(cloud_config, capsys):

file_name = ('gs://{}/vision/landmark.jpg'.format(

cloud_config.storage_bucket))

web_detect.report(web_detect.annotate(file_name))

out, _ = capsys.readouterr()

assert 'Description: Palace of Fine Arts Theatre' in out

def test_detect_web_http(cloud_config, capsys):

web_detect.report(web_detect.annotate('https://goo.gl/X4qcB6'))

out, _ = capsys.readouterr()

assert 'https://cloud.google.com/vision/' in out