Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your
tasks on an array of workers while following the specified dependencies. Rich command line utilities make
performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines
running in production, monitor progress, and troubleshoot issues when needed.
OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning S\w library.
OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of
machine perception in the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses
to utilize and modify the code.The library has more than 2500 optimized algorithms, which includes comprehensive
set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be
used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements,
track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images
together to produce a high resolution image of an entire scene, find similar images from an image database,
remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers
to overlay it with augmented reality, etc. OpenCV has more than 47 thousand people of user community and
estimated number of downloads exceeding 14 million. The library is used extensively in companies, research
groups and by governmental bodies.
Along with well-established companies like Google, Yahoo, Microsoft, Intel, IBM, Sony, Honda, Toyota that employ
the library, there are many startups such as Applied Minds, VideoSurf, and Zeitera, that make extensive use of
OpenCV. OpenCV’s deployed uses span the range from stitching streetview images together, detecting intrusions
in surveillance video in Israel, monitoring mine equipment in China, helping robots navigate and pick up objects
at Willow Garage, detection of swimming pool drowning accidents in Europe, running interactive art in Spain and
New York, checking runways for debris in Turkey, inspecting labels on products in factories around the world on
to rapid face detection in Japan.
# You Can Also Use RESTful APIs To Scrape Twitter Data( Just Make Edit In TwitterStream.py )
# The standard (free) Twitter APIs consist of REST APIs and Streaming APIs.
The enterprise (paid subscription) APIs include filtered firehose, historical search and engagement
APIs for deeper data analytics, listening and other enterprise business applications. The premium
(pay as you go) APIs consist of reliable and affordable versions of enterprise APIs, allowing your
business to grow with your usage. Additionally, there are some families of APIs (such as the Ads API)
which require applications to be whitelisted in order to make use of them.
# The API aims to be a RESTful resource
With the exception of the Streaming API and Account Activity webhooks, the Twitter API endpoints
attempt to conform to the design principles of Representational State Transfer (REST). Twitter
APIs use the JSON data format for responses (and in some cases, for requests).
# The API is HTTP-based (over SSL)
Methods to retrieve data from the Twitter API require a GET request. Methods that submit, change or
destroy data require a POST. A DELETE request is also accepted for methods that destroy data. API
methods that require a particular HTTP method will return an error if not invoked using the correct
style. HTTP Response Codes are meaningful.