Here's what I don't quite get: why does the GPU differentiation matter to me as a user of your API? I get that you're faster than doing it myself using something like ImageMagick, but are you faster than the other image processing APIs out there because of this? If so, that's what I think you should be touting. If not, whether the images are being processed by GPUs or trained giraffes is not that important to me as a consumer of the API, but I could be way off-base.
With Metal Performance Shaders we have absolute control over pixels and direct access to the underlying hardware. For us that means we can rapidly test and deploy new CoreML models and also the ability to quickly respond to any feature-request.
So this was my point in bringing it up: "We're faster than the other APIs out there" is a much more direct benefit to communicate to me as an API user than "We use GPUs, which makes us fast, faster than the competition, who don't use GPUs". The latter version has me making assumptions and eventually getting to a conclusion that matters to me; why not take me there immediately?
The thing is, as a non-expert in this area, I don't even fully understand whether the real performance bottleneck in such an API is the latency of uploading the image and downloading the result, or the computational processing of the image. So if using GPUs cuts the overall request time by 70%, that's great! If it only affects the round-trip time by 5%, then it's not a huge deal to me. As the domain expert, I'm relying on Pixaven's marketing to educate me on this.
Congrats on launching, great work!
Pixaven is an image processing API that runs entirely on Mac Pros (cylindrical, 2nd gen) that we host ourselves in a Tier-3 data center in Frankfurt, Germany. The goal was to build a service that would enable developers to process huge amounts of images at blazing speed with a simple to use API. Since pixels nowadays belong to graphic cards all heavy processing takes place on the GPUs [1].
We wrote our image rendering engine from scratch and can rapidly deploy custom solutions that revolve around pixel manipulation, computer vision and machine learning.
Pixaven API currently supports:
- Resizing and scaling (with multiple modes) - Cropping (with multiple modes) - Face detection - Watermarking - Masking - Filtering (such as blurring, colour isolation, duotone, etc.) - Manual adjustments (such as brightness, contrast, exposure, etc.) - Automatic enhancements - External storage to AWS, GCP, Azure, IBM, DO and Rackspace
While Pixaven works like a standard API and can push processed images to object storage of choice, we also offer Storage and Delivery addon and can distribute visual content over a global 65+ Tbps content delivery network.
Developers can integrate the API right away with production-ready integration libraries for Node, Go, PHP, Java, Ruby and Python.
We also implemented some additional features around the Pixaven Account such as 2FA and SSO, team management, access control and detailed activity logs.
We'd love to get some feedback and I'm here to answer any questions
[1]: https://www.pixaven.com/about