/google-cloud-vision-example

Primary LanguagePython

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

This sample demonstrates how to use the Cloud Vision API to do label detection.

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:

  1. When running locally, use the Google Cloud SDK

    gcloud auth application-default login

  2. 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.

  3. 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:

    export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service_account.json

Install Dependencies

  1. Install pip and virtualenv if you do not already have them.

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

    $ virtualenv env
$ source env/bin/activate

  3. Install the dependencies needed to run the samples.

    $ pip install -r requirements.txt

Samples

Label detection

To run this sample:

$ python label.py

usage: label.py [-h] image_file

positional arguments:
  image_file  The image you'd like to label.

optional arguments:
  -h, --help  show this help message and exit