Machine Learning APIs and Algorithmic Rotoscope Work
Algorithmic rotoscope work can make for a creative yet very API-focused project that you can turn into a small business or keep as something to do in your spare time.
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I was playing around with Algorithmia for a story about their business model back in December, when I got sucked into playing with their DeepFilter service, resulting in a four-week long distraction which ultimately became what I am calling my algorithmic rotoscope work. After weeks of playing around, I have a good grasp of what it takes to separate videos into individual images, apply the Algorithmia machine learning filters, and reassemble them as videos. I also have several of my own texture filters created now using the AWS AMI and Algorithmia — you can learn more about algorithmic rotoscope and get details of what I did via the GitHub project updates here.
The project has been a great distraction from what I should be doing. After the election, I just did not feel like doing my regular writing of articles, scheduling of tweets, processing of press releases, and the other things I do on a regular basis. Algorithmic Rotoscope provided a creative yet very API-focused project to take my mind off things during the holidays. It was a concept that I couldn't get out of my head, which is always a sign for me that I should be working on the project. The work was more involved than I anticipated, but after a couple weeks of tinkering, I have the core process for applying filters to videos working well, allowing me to easily apply the algorithmic textures.
Other than just being a distraction, this project has been a great learning experience for me, with several aspects keeping me engaged.
Algorithmia's Image Filters
This is their very cool DeepFilter service, which allows you to apply artistic and stylish filters to your images using their API or CLI, providing over 30 filters you can use right away.
Training Style Transfer Models
With these models, you can fire up an Amazon GPU instance, look through art books, and find interesting pieces that can be used to train the machine learning models so that you can define your own filters.
Applying Filters To Images
I spent hours playing with Algorithmia's filters, applying them to my photo library, experimenting, and playing around with what looks good and what is possible.
Applying Filters To Videos
Applying Algorithmia's and my own filters to videos I have laying around, especially when this is possible when applied to the GB's of drone video I have laying around, is something that is only going to grow.
Why is this an API story? Well, first of all, it uses the Algorithmia API. Also, I have developed the separation of the videos, application of filters to images, and reassembly of the videos as an API. It isn't anything that is production stable, but I've processed thousands of images and many minutes of video and made over 100K API calls to Algorithmia. Next, I am going to write up Algorithmia's business model, using my algorithmic rotoscope work as a hypothetical API-driven business. This will help me think through the economics of building a SaaS or retail API solution on top of Algorithmia.
Beyond being an API story, it has been a lot of fun to engineer and play with. I still have a GPU instance fired up and training filters, and I'm recording more drone and other video footage specifically so that I can apply some of the new filters I've produced. I have no intention of doing it as a business — algorithmic rotoscope is just a side project that I hope will continue to be a creative distraction for me and give me another reason to keep flying drones and get away from the computer when I can. In the end, I am learning a lot about drones, videography, and machine learning. Best of all, it has helped me regain my writing mojo.
Published at DZone with permission of Kin Lane, DZone MVB. See the original article here.
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