All posts by James Sutton

Train a Machine to Turn Documents into Keywords, via Document Classification

Figuring out the meaning of a document was once a very hard problem for computers to solve… even for humans, understanding the complexity of natural language can be tricky!

Fortunately, there are some great tools that can help address those concerns. The Document Classifier turns your existing documents and associated keywords into a model which can be used to predict the most appropriate keywords for new blocks of text. Read More…

Introduction to Video Tag Sequencing

Video Metadata Extraction

Sifting through unlabelled videos can be difficult and time-consuming. Even for the most seasoned analyst, fatigue leads to mistakes. Whether you’re trying to detect anomalies in mission-critical infrastructure — or you just want to find all of the segments in your vacation videos that contain ducks — we have a microservice that can help reduce the workload.

What is the Video Tag Sequencer? How does it work?

The VideoTagSequencer is an algorithm takes the time series point data generated from VideoMetadataExtraction and converts it into an index of detected labels and sequences contained in the video. In a nutshell, it takes frame-by-frame results, and converts them into a list of time ranges at which each result occurs. Read More…

Deep Dive into Parallelized Video Processing

Where it all began

At Algorithmia, one of our driving goals is to enable all developers to stand on the shoulders of the algorithmic giants. Like Lego our users can construct amazing devices and tools by utilizing our algorithmic building blocks like FaceDetection or Smart Image Downloader.

As a platform, Algorithmia is unique in that we’re able to scale to meet any volume of concurrent algorithm requests, meaning that even though your algorithm might be making 10,000 API requests to a particular image processing algorithm, it won’t influence the experience of other users quality of service.

One of the earliest projects I worked on at Algorithmia was to construct a video processing pipeline which would leverage our existing image processing algorithms as building blocks. The project was designed to improve the reach of our image processing algorithms by automatically enabling them to become video processing algorithms.

After the first couple of weeks the first Interface and process flow was starting to come together and by using ffmpeg we were able to easily split videos into frames and concatenate them back into any video format we wanted. However, it quickly became apparent how fragile this initial process flow was, and how difficult it was to use for an end user. Read More…