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.

• 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. Clone python-docs-samples and change directory to the sample directory you want to use.

   $ git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git

2. 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.

3. Create a virtualenv. Samples are compatible with Python 3.6+.

   $ virtualenv env
   $ source env/bin/activate

4. Install the dependencies needed to run the samples.

   $ pip install -r requirements.txt

Samples

Detect

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,web-geo,web-geo-uri,crophints,crophints-uri,document,document-uri,ocr-uri,object-localization,object-localization-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 web-geo ./resources/city.jpg
python detect.py faces-uri gs://your-bucket/file.jpg
python detect.py ocr-uri gs://python-docs-samples-tests/HodgeConj.pdf gs://BUCKET_NAME/PREFIX/
python detect.py object-localization ./resources/puppies.jpg
python detect.py object-localization-uri gs://...

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,web-geo,web-geo-uri,crophints,crophints-uri,document,document-uri,ocr-uri,object-localization,object-localization-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.
    web-geo             Detects web annotations given an image, using the
                        geotag metadata in the image to detect web entities.
    web-geo-uri         Detects web annotations given an image in the file
                        located in Google Cloud Storage., using the geotag
                        metadata in the image to detect web entities.
    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.
    ocr-uri             OCR with PDF/TIFF as source files on GCS
    object-localization
                        OCR with PDF/TIFF as source files on GCS
    object-localization-uri
                        OCR with PDF/TIFF as source files on GCS

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

Beta Detect

To run this sample:

$ python beta_snippets.py


usage: beta_snippets.py [-h]
                        {object-localization,object-localization-uri,handwritten-ocr,handwritten-ocr-uri,batch-annotate-files,batch-annotate-files-uri,batch-annotate-images-uri}
                        ...

Google Cloud Vision API Python Beta Snippets

Example Usage:
python beta_snippets.py -h
python beta_snippets.py object-localization INPUT_IMAGE
python beta_snippets.py object-localization-uri gs://...
python beta_snippets.py handwritten-ocr INPUT_IMAGE
python beta_snippets.py handwritten-ocr-uri gs://...
python beta_snippets.py batch-annotate-files INPUT_PDF
python beta_snippets.py batch-annotate-files-uri gs://...
python beta_snippets.py batch-annotate-images-uri gs://... gs://...

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

positional arguments:
  {object-localization,object-localization-uri,handwritten-ocr,handwritten-ocr-uri,batch-annotate-files,batch-annotate-files-uri,batch-annotate-images-uri}
    object-localization
                        Localize objects in the local image. Args: path: The
                        path to the local file.
    object-localization-uri
                        Localize objects in the image on Google Cloud Storage
                        Args: uri: The path to the file in Google Cloud
                        Storage (gs://...)
    handwritten-ocr     Detects handwritten characters in a local image. Args:
                        path: The path to the local file.
    handwritten-ocr-uri
                        Detects handwritten characters in the file located in
                        Google Cloud Storage. Args: uri: The path to the file
                        in Google Cloud Storage (gs://...)
    batch-annotate-files
                        Detects document features in a PDF/TIFF/GIF file.
                        While your PDF file may have several pages, this API
                        can process up to 5 pages only. Args: path: The path
                        to the local file.
    batch-annotate-files-uri
                        Detects document features in a PDF/TIFF/GIF file.
                        While your PDF file may have several pages, this API
                        can process up to 5 pages only. Args: uri: The path to
                        the file in Google Cloud Storage (gs://...)
    batch-annotate-images-uri
                        Batch annotation of images on Google Cloud Storage
                        asynchronously. Args: input_image_uri: The path to the
                        image in Google Cloud Storage (gs://...) output_uri:
                        The path to the output path in Google Cloud Storage
                        (gs://...)

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.