A package for google ML_APIs.
ML_APIs enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy to use. 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.
In order to use this library, you first need to go through the following steps:
- Select or create a Cloud Platform project.
- Enable billing for your project.
- Enable the Google Cloud Vision API.
- Setup Authentication.
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.
se7en@bar:~$ pip install virtualenv se7en@bar:~$ virtualenv <your-env> se7en@bar:~$ <your-env>\Scripts\activate (<your-env>)se7en@bar:~$
The easiest way to install the latest stable version of ML_APIs is with pip:
(<your-env>)se7en@bar:~$ pip install ML_APIs
Example Usage Google Vision A.I. on local media file
from ML_APIs.google import vision_ai_local path = <your-image> model = 'logos' credentials = <your-credentials.json> image_classification = vision_ai_local(path, model, credentials) image_classification.logos
Read the Product documentation to learn more about the product and see How-to Guides.
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