Python Client for Google Cloud Vision¶
The Google Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy to use REST API. It quickly classifies images into thousands of categories (e.g., “sailboat”, “lion”, “Eiffel Tower”), detects individual objects and faces within images, and finds and reads printed words contained within images. You can build metadata on your image catalog, moderate offensive content, or enable new marketing scenarios through image sentiment analysis. Analyze images uploaded in the request or integrate with your image storage on Google Cloud Storage.
Quick Start¶
In order to use this library, you first need to go through the following steps:
Installation¶
Install this library in a virtualenv using pip. virtualenv is a tool to create isolated Python environments. The basic problem it addresses is one of dependencies and versions, and indirectly permissions.
With virtualenv, it’s possible to install this library without needing system install permissions, and without clashing with the installed system dependencies.
Supported Python Versions¶
Python >= 3.5
Deprecated Python Versions¶
Python == 2.7. Python 2.7 support will be removed on January 1, 2020.
Mac/Linux¶
pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install google-cloud-vision
Windows¶
pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install google-cloud-vision
Example Usage¶
from google.cloud import vision
client = vision.ImageAnnotatorClient()
response = client.annotate_image({
'image': {'source': {'image_uri': 'gs://my-test-bucket/image.jpg'}},
'features': [{'type': vision.enums.Feature.Type.FACE_DETECTION}],
})
Next Steps¶
Read the Client Library Documentation for Google Cloud Vision API API to see other available methods on the client.
Read the Product documentation to learn more about the product and see How-to Guides.
Using the Library¶
Annotate an Image¶
You can call the annotate_image() method directly:
>>> from google.cloud import vision
>>> client = vision.ImageAnnotatorClient()
>>> response = client.annotate_image({
... 'image': {'source': {'image_uri': 'gs://my-test-bucket/image.jpg'}},
... 'features': [{'type': vision.enums.Feature.Type.FACE_DETECTION}],
... })
>>> len(response.annotations)
2
>>> for face in response.annotations[0].faces:
... print(face.joy)
Likelihood.VERY_LIKELY
Likelihood.VERY_LIKELY
Likelihood.VERY_LIKELY
>>> for logo in response.annotations[0].logos:
... print(logo.description)
'google'
'github'
Single-feature Shortcuts¶
If you are only requesting a single feature, you may find it easier to ask for it using our direct methods:
>>> from google.cloud import vision
>>> client = vision.ImageAnnotatorClient()
>>> response = client.face_detection({
... 'source': {'image_uri': 'gs://my-test-bucket/image.jpg'},
... })
>>> len(response.annotations)
1
>>> for face in response.annotations[0].faces:
... print(face.joy)
Likelihood.VERY_LIKELY
Likelihood.VERY_LIKELY
Likelihood.VERY_LIKELY
No results found¶
If no results for the detection performed can be extracted from the image, then an empty list is returned. This behavior is similar with all detection types.
Example with logo_detection():
>>> from google.cloud import vision
>>> client = vision.ImageAnnotatorClient()
>>> with open('./image.jpg', 'rb') as image_file:
... content = image_file.read()
>>> response = client.logo_detection({
... 'content': content,
... })
>>> len(response.annotations)
0
API Reference¶
This package includes clients for multiple versions of the Vision
API. By default, you will get v1, the latest stable version.
A new beta release with additional features over the current stable version,
spelled v1p4beta1, is provided to allow you to use these new features.
These are expected to move into the stable release soon; until then, the
usual beta admonishment (changes are possible, etc.) applies.
Previous beta releases v1p3beta1 and v1p2beta1 are provided as well.
An API and type reference is provided for v1p3beta1:
An API and type reference is provided for v1p2beta1:
