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Crop hints tutorial (#861)
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* Adds crop hints tutorial.

* Uses aspect ratio so that we actually crop.

* Addresses review feedback

* nits

* Restructures samples for CI
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gguuss authored and dpebot committed Mar 20, 2017
1 parent e6a5ff4 commit 959ca2c
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2 changes: 2 additions & 0 deletions vision/cloud-client/crop_hints/.gitignore
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output-crop.jpg
output-hint.jpg
111 changes: 111 additions & 0 deletions vision/cloud-client/crop_hints/README.rst
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.. This file is automatically generated. Do not edit this file directly.
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
gcloud beta auth application-default login
#. 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
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service_account.json
.. _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
$ virtualenv env
$ source env/bin/activate
#. Install the dependencies needed to run the samples.

.. code-block:: bash
$ pip install -r requirements.txt
.. _pip: https://pip.pypa.io/
.. _virtualenv: https://virtualenv.pypa.io/

Samples
-------------------------------------------------------------------------------

Crop Hints Tutorial
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++



To run this sample:

.. code-block:: bash
$ python crop_hints.py
usage: crop_hints.py [-h] image_file mode
positional arguments:
image_file The image you'd like to crop.
mode Set to "crop" or "draw".
optional arguments:
-h, --help show this help message and exit
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 Client Library for Python:
https://googlecloudplatform.github.io/google-cloud-python/
.. browse the source:
https://github.com/GoogleCloudPlatform/google-cloud-python
.. report issues:
https://github.com/GoogleCloudPlatform/google-cloud-python/issues
.. _Google Cloud SDK: https://cloud.google.com/sdk/
22 changes: 22 additions & 0 deletions vision/cloud-client/crop_hints/README.rst.in
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# 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: Crop Hints Tutorial
file: crop_hints.py
show_help: True

cloud_client_library: true
97 changes: 97 additions & 0 deletions vision/cloud-client/crop_hints/crop_hints.py
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#!/usr/bin/env python

# Copyright 2017 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Outputs a cropped image or an image highlighting crop regions on an image.
Examples:
python crop_hints.py resources/cropme.jpg draw
python crop_hints.py resources/cropme.jpg crop
"""
# [START full_tutorial]
# [START imports]
import argparse
import io

from google.cloud import vision
from PIL import Image, ImageDraw
# [END imports]


def get_crop_hint(path):
# [START get_crop_hint]
"""Detect crop hints on a single image and return the first result."""
vision_client = vision.Client()

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

image = vision_client.image(content=content)

# Return bounds for the first crop hint using an aspect ratio of 1.77.
return image.detect_crop_hints({1.77})[0].bounds.vertices
# [END get_crop_hint]


def draw_hint(image_file):
"""Draw a border around the image using the hints in the vector list."""
# [START draw_hint]
vects = get_crop_hint(image_file)

im = Image.open(image_file)
draw = ImageDraw.Draw(im)
draw.line([vects[0].x_coordinate, vects[0].y_coordinate,
vects[1].x_coordinate, vects[1].y_coordinate],
fill='red', width=3)
draw.line([vects[1].x_coordinate, vects[1].y_coordinate,
vects[2].x_coordinate, vects[2].y_coordinate],
fill='red', width=3)
draw.line([vects[2].x_coordinate, vects[2].y_coordinate,
vects[3].x_coordinate, vects[3].y_coordinate],
fill='red', width=3)
draw.line([vects[3].x_coordinate, vects[3].y_coordinate,
vects[0].x_coordinate, vects[0].y_coordinate],
fill='red', width=3)
im.save('output-hint.jpg', 'JPEG')
# [END draw_hint]


def crop_to_hint(image_file):
"""Crop the image using the hints in the vector list."""
# [START crop_to_hint]
vects = get_crop_hint(image_file)

im = Image.open(image_file)
im2 = im.crop((vects[0].x_coordinate, vects[0].y_coordinate,
vects[2].x_coordinate - 1, vects[2].y_coordinate - 1))
im2.save('output-crop.jpg', 'JPEG')
# [END crop_to_hint]


if __name__ == '__main__':
# [START run_crop]
parser = argparse.ArgumentParser()
parser.add_argument('image_file', help='The image you\'d like to crop.')
parser.add_argument('mode', help='Set to "crop" or "draw".')
args = parser.parse_args()

parser = argparse.ArgumentParser()

if args.mode == 'crop':
crop_to_hint(args.image_file)
elif args.mode == 'draw':
draw_hint(args.image_file)
# [END run_crop]
# [END full_tutorial]
37 changes: 37 additions & 0 deletions vision/cloud-client/crop_hints/crop_hints_test.py
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# Copyright 2017 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os

import crop_hints


def test_crop(cloud_config, capsys):
"""Checks the output image for cropping the image is created."""
file_name = os.path.join(
os.path.dirname(__file__),
'resources/cropme.jpg')
crop_hints.crop_to_hint(file_name)
out, _ = capsys.readouterr()
assert os.path.isfile('output-crop.jpg')


def test_draw(cloud_config, capsys):
"""Checks the output image for drawing the crop hint is created."""
file_name = os.path.join(
os.path.dirname(__file__),
'resources/cropme.jpg')
crop_hints.draw_hint(file_name)
out, _ = capsys.readouterr()
assert os.path.isfile('output-hint.jpg')
2 changes: 2 additions & 0 deletions vision/cloud-client/crop_hints/requirements.txt
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google-cloud-vision==0.23.2
pillow==4.0.0
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Expand Up @@ -70,18 +70,6 @@ Install Dependencies
Samples
-------------------------------------------------------------------------------

Quickstart
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++



To run this sample:

.. code-block:: bash
$ python quickstart.py
Detect
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

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22 changes: 22 additions & 0 deletions vision/cloud-client/detect/README.rst.in
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# 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: Detect
file: detect.py
show_help: True

cloud_client_library: true
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Expand Up @@ -356,7 +356,7 @@ def detect_crop_hints(path):
content = image_file.read()
image = vision_client.image(content=content)

hints = image.detect_crop_hints()
hints = image.detect_crop_hints({1.77})

for n, hint in enumerate(hints):
print('\nCrop Hint: {}'.format(n))
Expand All @@ -372,7 +372,7 @@ def detect_crop_hints_uri(uri):
vision_client = vision.Client()
image = vision_client.image(source_uri=uri)

hints = image.detect_crop_hints()
hints = image.detect_crop_hints({1.77})
for n, hint in enumerate(hints):
print('\nCrop Hint: {}'.format(n))

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