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README.rst

Google Cloud Vision API Python Samples

https://gstatic.com/cloudssh/images/open-btn.png

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.

  • See the migration guide for information about migrating to Python client library v0.25.1.

Setup

Authentication

This sample requires you to have authentication setup. Refer to the Authentication Getting Started Guide for instructions on setting up credentials for applications.

Install Dependencies

  1. Install pip and virtualenv if you do not already have them. You may want to refer to the Python Development Environment Setup Guide for Google Cloud Platform for instructions.
  1. Create a virtualenv. Samples are compatible with Python 2.7 and 3.4+.

    $ virtualenv env
    $ source env/bin/activate
  2. Install the dependencies needed to run the samples.

    $ pip install -r requirements.txt

Samples

Detect

https://gstatic.com/cloudssh/images/open-btn.png

To run this sample:

$ python detect.py

usage: detect.py [-h]
                 {faces,faces-uri,labels,labels-uri,landmarks,landmarks-uri,text,text-uri,logos,logos-uri,safe-search,safe-search-uri,properties,properties-uri,web,web-uri,crophints,crophints-uri,document,document-uri}
                 ...

This application demonstrates how to perform basic operations with the
Google Cloud Vision API.

Example Usage:
python detect.py text ./resources/wakeupcat.jpg
python detect.py labels ./resources/landmark.jpg
python detect.py web ./resources/landmark.jpg
python detect.py web-uri http://wheresgus.com/dog.JPG
python detect.py faces-uri gs://your-bucket/file.jpg

For more information, the documentation at
https://cloud.google.com/vision/docs.

positional arguments:
  {faces,faces-uri,labels,labels-uri,landmarks,landmarks-uri,text,text-uri,logos,logos-uri,safe-search,safe-search-uri,properties,properties-uri,web,web-uri,crophints,crophints-uri,document,document-uri}
    faces               Detects faces in an image.
    faces-uri           Detects faces in the file located in Google Cloud
                        Storage or the web.
    labels              Detects labels in the file.
    labels-uri          Detects labels in the file located in Google Cloud
                        Storage or on the Web.
    landmarks           Detects landmarks in the file.
    landmarks-uri       Detects landmarks in the file located in Google Cloud
                        Storage or on the Web.
    text                Detects text in the file.
    text-uri            Detects text in the file located in Google Cloud
                        Storage or on the Web.
    logos               Detects logos in the file.
    logos-uri           Detects logos in the file located in Google Cloud
                        Storage or on the Web.
    safe-search         Detects unsafe features in the file.
    safe-search-uri     Detects unsafe features in the file located in Google
                        Cloud Storage or on the Web.
    properties          Detects image properties in the file.
    properties-uri      Detects image properties in the file located in Google
                        Cloud Storage or on the Web.
    web                 Detects web annotations given an image.
    web-uri             Detects web annotations in the file located in Google
                        Cloud Storage.
    crophints           Detects crop hints in an image.
    crophints-uri       Detects crop hints in the file located in Google Cloud
                        Storage.
    document            Detects document features in an image.
    document-uri        Detects document features in the file located in
                        Google Cloud Storage.

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.